Nordic Social Attitudes in a European Perspective

Nordic Social Attitudes in a European Perspective

Nordic Social Attitudes in a European Perspective Edited by

Heikki Ervasti Professor of Social Policy, University of Turku, Finland

Torben Fridberg Senior Researcher, SFI – The Danish National Centre for Social Research, Denmark

Mikael Hjerm Associate Professor of Sociology, Umeå University, Sweden and

Kristen Ringdal Professor of Sociology, Norwegian University of Science and Technology, Norway

Edward Elgar Cheltenham, UK • Northampton, MA, USA

© Heikki Ervasti, Torben Fridberg, Mikael Hjerm and Kristen Ringdal 2008 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library Library of Congress Control Number: 2008932883

ISBN 978 1 84720 931 3 (cased) Printed and bound in Great Britain by MPG Books Ltd, Bodmin, Cornwall

Contents vii ix xi

List of contributors Foreword by Roger Jowell Acknowledgements 1 The Nordic model Heikki Ervasti, Torben Fridberg, Mikael Hjerm, Olli Kangas and Kristen Ringdal

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2 The welfare state, poverty and social exclusion Torben Fridberg and Olli Kangas

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3 Health and happiness Terje Andreas Eikemo, Arne Mastekaasa and Kristen Ringdal

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4 Social capital Torben Fridberg and Olli Kangas

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5 Who should decide? A comparative analysis of multilevel governance in Europe Linda Berg and Mikael Hjerm

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6 Political activism Frode Berglund, Øyvin Kleven and Kristen Ringdal

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7 Trust in political institutions Ola Listhaug and Kristen Ringdal

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8 Disagreement about the division of work among couples in Europe: the role of gender ideology and labour involvement Mikael Nordenmark 9 Non-standard employment and job quality Heikki Ervasti

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10 Attitudes towards immigrants Heikki Ervasti, Torben Fridberg and Mikael Hjerm

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11 Economic morality Kristen Ringdal

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12 The meaning and implications of religiosity Heikki Ervasti

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13 Conclusions: Nordic uniqueness, reality or myth? Heikki Ervasti, Torben Fridberg, Mikael Hjerm and Kristen Ringdal

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Appendix: data source and statistical methods Mikael Hjerm and Kristen Ringdal

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Index

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Contributors Linda Berg is a doctor in political science from Gothenburg University. During 2007–2008 she is a visiting fellow (postdoc) to the Institute of Governance, University of Edinburgh. Her main research focus is on how individuals feel attached to different territorial levels in society, and how that influences their political (especially welfare) attitudes. Frode Berglund is a senior researcher at the Norwegian Institute for Urban and Regional Studies. He is a political scientist, and most of his research is related to political behaviour in different forms. In English, he has published articles on party identification and political behaviour among older citizens, and he contributed to the book The European Voter edited by Jaques Thomassen. His latest article is on political recruitment among young citizens. Terje Andreas Eikemo works as a researcher at SINTEF Health Research, Trondheim and as a research fellow at the Department of Sociology and Political Science at the Norwegian University of Science and Technology (NTNU), Trondheim. His fields of interest are related to research into political and social changes in Eastern Europe (he has been a trainee at the royal Norwegian Embassy in Prague), the welfare state, and public health. Heikki Ervasti is Professor of Social Policy at the Department of Social Policy, University of Turku, Finland. He is currently the Finnish National Coordinator for the European Social Survey. His main research interests include comparative analyses on labour markets and unemployment, and social, political and economic attitudes. Torben Fridberg has been a researcher at SFI – The Danish National Centre for Social Research – since 1976. He is the Danish national coordinator for the European Social Survey. His main research interest includes topics around the welfare state. Mikael Hjerm is an associate professor in the Department of Sociology at Umeå University, Sweden. His research focuses mainly on attitudes of nationalism, racism and questions of integration in different institutional contexts. He is currently interested in how national identities relate to perceptions of the welfare state. Hjerm is the national coordinator for the European Social Survey in Sweden. vii

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Olli Kangas is a professor and head of the research department at the Social Insurance Institution of Finland (KELA). He has published extensively on comparative welfare state and social policy issues. Øyvin Kleven is a senior advisor at the Division for Data Collection Methods, Statistics Norway. He has a masters in political science from the University of Oslo, and was the project leader for the team that carried out the fieldwork in the European Social Survey in Norway. He has published several papers and articles on political participation and non-sampling errors in survey research. Ola Listhaug is Professor of Political Science at The Norwegian University of Science and Technology, Trondheim. He is also a research group leader at the Centre for the Study of Civil War, PRIO, director (since 1982) of the Norwegian Values Study, and member of the European Values Study Executive Committee. He has published extensively in political science journals. Arne Mastekaasa is professor of Sociology at University of Oslo, Department of Sociology and Human Geography. His research falls into several sociological subfields like social stratification, job attitudes, labour markets, and mental health, and he has published more than 40 articles in international journals. Current projects include studies of the impact of education and social origins on labour market success and job mobility, and job motivation among professional employees. Mikael Nordenmark is a Professor in the Department of Health Sciences, Mid-Sweden University. His main research interests are relationships among labour market situation, family life, gender and well-being. He has been a research fellow at the Swedish Collegium for Advanced Study in the Social Sciences (SCASSS) in Uppsala, Sweden, and at the Center for Advanced Study in the Behavioral Sciences (CASBS) in Stanford, USA. Kristen Ringdal is Professor of Sociology in the Department of Sociology and Political Science, the Norwegian University of Science and Technology, Trondheim. He is the Norwegian National Coordinator for the European Social Survey, and is an elected member of the Royal Norwegian Society of Sciences and Letters. He has published articles in a broad range of journals.

Foreword Having been closely involved in the development and design of the European Social Survey (ESS) from the start, I am delighted by the convincing evidence in this book that our painstaking work is yielding such important findings. When the ESS started its life in 2001, a great deal was expected of it. Learning from the experience of other pioneering cross-national studies, such as the Eurobarometers, the European Value Surveys and the International Social Survey Programme, it was designed to produce high quality evidence about how citizens of over 20 nations in Europe see themselves, one another and their collective world. To pursue that goal effectively, however, we had to devise a bulletproof means of achieving the same or closely equivalent data within every participating country. In the absence of such close equivalence, comparisons between countries would be spurious. So the defining characteristic of the ESS is conformity to a meticulous common specification that applies both to its methods and to its content. The outcome, we believe, is a cross-national dataset of unusual quality and reliability. The findings in this book are based on the first two rounds of the ESS (2001/2002 and 2003/2004). Twenty-two countries participated in Round 1 and 26 in Round 2, and it is good to see that this book makes use of data from virtually all those countries. Also impressive is the multidisciplinary nature of the book, including contributions from authors with backgrounds in political science, sociology and social policy. The Nordic countries are particularly interesting in a cross-national context. Not only are their survey standards among the highest in Europe, but they historically embody a unique model of social democracy that may at once cause and be caused by certain attitudes and values. They are also perhaps the closest approximation in Europe to a group of countries that might be expected to share broadly similar characteristics and cultures. The analyses in this book reveal whether these images are justified. Or do the Nordic countries actually differ as much from one another as from other European countries? Or do within-country differences effectively outweigh between-country differences? Several books and articles based on ESS data have already appeared. Some focus on particular topics. Others examine European attitudes and ix

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values from the perspective of a single country. This book is the first to cover such a wide range of topics and be produced by authors from a cluster of neighbouring countries. It is an especially welcome and interesting work of scholarship. Roger Jowell City University London Principal Investigator, ESS

Acknowledgements We, the editors of this book are all National Coordinators of the European Social Survey. This book could not have been accomplished without the support from our funding organizations: the Danish Social Science Research Council, the Academy of Finland, the Research Council of Norway, the Swedish Council for Working Life and Social Research (FAS), the Swedish Research Council (VR) and Riksbankens Jubileumsfond (RJ). We want to acknowledge valuable advice from Ola Listhaug for the first draft of the introductory chapter. We also owe many thanks to SFI – the Danish National Centre for Social Research for generously hosting our editorial meetings in Copenhagen over a period of more than two years. Finally, this study would have been impossible without the cooperation of the thousands of respondents across Europe, and the ESS staff who planned and fielded the surveys.

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The Nordic model Heikki Ervasti, Torben Fridberg, Mikael Hjerm, Olli Kangas and Kristen Ringdal

INTRODUCTION The ambition of this book is to describe the Nordic countries in a European context by means of the European Social Surveys of 2002 and 2004. In this chapter we present the context of our analysis, namely the institutional and historical characteristics of the Nordic countries. We also discuss the many challenges that the institutional settings of the Nordic countries are facing. The point of departure for all the chapters in this book is the idea that institutions affect attitudes and behaviour. Institutions may loosely be defined as the ‘formal rules of the game’. Institutions are systems of rules and procedures that are embodied in, for example, social insurance systems, electoral systems, or family law. Institutions affect behaviour in that they modify and set the structure for possible actions. For instance, it is impossible to be on paid parental leave if such an institutional arrangement does not exist. Institutions also promote or discourage certain behaviour in relation to the issue of costs. For example, the existence of daycare facilities reduces the cost for women to work and, thus, enhances female labour participation. It is not only the case that institutions affect behaviour that will, in turn, affect attitudes and perceptions in an indirect way, but they will also affect them more directly. Svallfors (2007) accounts for three ways in which institutions affect attitudes. First, institutions affect the visibility of social phenomena. For instance, the class differences in attitudes are greater in countries that have higher levels of redistribution or, in other words, in countries where redistribution is more institutionalized. Second, institutions affect what is considered possible. For example, a greater percentage of people in countries that have limited childcare facilities think that women should stay at home and take care of their children. Third, institutions embody and create norms about what is fair and just. For instance, people in the USA think that a just difference in salaries between a CEO and a worker is much higher than do Scandinavians. 1

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Nevertheless, institutions do not determine attitudes and behaviour; they only make certain attitudes and behaviour more or less likely. Birth rates are higher in countries that provide generous childcare benefits, daycare facilities, parental leave, and so on. The latter does, of course, not mean that there is a deterministic relationship between where an individual lives and the number of children that she will have. Moreover, the relationship between institutions and behaviour is reciprocal. Institutions do structure attitudes and behaviour, but existing attitudes also help to create, sustain and modify existing institutions. For example, institutions can be changed much more easily if there is attitudinal support for a specific change than if no such support exists. The idea behind this approach is to expect that diversity among countries in the main institutions, such as politics, work relations, the welfare state and the family, produces differences in attitudes among people across countries. The institutional differences in Europe have deep historical roots that translate into differences among the countries in behaviour as well as in the values and attitudes of individuals in those countries. Different institutional settings can be bundled together into regimes. In particular, welfare state researchers have discussed widely the division of the socio-political systems in different countries into a limited number of regimes or models. Similarly, gender researchers have grouped countries according to gender-related policies and immigration researchers according to immigration and integration policies. Also in this book, the point of departure is the idea that the Nordic countries share a Nordic regime or model of society. However, we adopt a wider perspective in regime thinking than specialists in narrow fields of research have usually done. Our picture of the Nordic model consists of a large range of issues. We argue that the exceptional nature of the institutional settings of the Nordic model is mirrored in most fields of social life; it is reflected in the attitudes, values and behaviour of individuals in issues ranging from the welfare state and social capital to economic morality, immigration attitudes, family roles and religiosity, not to mention political attitudes and behaviour. The next step is therefore to locate the main institutions that may distinguish the Nordic countries from the rest of Europe. The Nordic, or the Scandinavian, model is a well-known concept in popular media as well as in scientific literature. It is easy to find resemblances between the countries, although no one can deny that certain differences also exist. Any description of the Nordic model needs to make certain common features of the individual Nordic countries visible as well as downplaying certain differences between the countries. Therefore, we start by outlining a number of common structural and historical features that the Nordic societies share historically. We also track the new challenges that are often claimed

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to create pressure to change the Nordic societies fundamentally. This chapter concludes with a short presentation of the empirical chapters in the book.

POLITICAL AND STRUCTURAL CHARACTERISTICS OF NORDIC SOCIETIES The Nordic countries are all small and relatively culturally homogeneous. They are also all relatively rich countries with strong public sectors and have a culture of cooperative institutions that merge private and public interests. The three most unique features are the following: (1) exceptionally egalitarian and democratic political traditions, (2) the welfare state and (3) labour market politics and work relations. We begin with a description of the political background of the Nordic model, which is also described in terms of Scandinavian exceptionality, and continue with the other two pillars of the Nordic model: the welfare state and labour market relations. Scandinavian Exceptionality in Politics The Nordic countries are small states at the northern periphery of Europe. According to Katzenstein’s (1985) theory, small states are by necessity more open to the international economy than larger states. Their small size makes the Nordic states vulnerable to external changes, which exert pressure to solve internal conflicts. The openness and vulnerability favour national consensus through corporatist solutions. Conflicts are solved by informal political bargaining among relatively centralized interest groups and the state bureaucracies in policy networks. This permanent cooperation between major private and public actors allows for flexible adaptation to international economic changes, where compensation for the costs of adaptation has relied heavily on state intervention and public investments. Let us look at the historical background of the Nordic model. In contrast to many other developing and poor countries, the state in Scandinavia was strong enough not to be a mere vehicle for particular groups; the state was able to make its own plans and decisions that aided the promotion of the collective or national good instead of merely promoting group-specific interests (Alestalo and Kuhnle 1987). Traditionally, the local municipality, or parish, was responsible for tax collection, delivering help to the poor and for other basic public goods. In order to cover the costs of these tasks, municipalities and parishes could collect and keep a certain percentage of tax revenues for their own disposal, whereas the rest was sent to the central

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government. Moreover, within certain limits the municipalities could decide on their own activities and municipal tax rates. Before 1900, the Scandinavian countries had established a functioning local level democracy that was combined with and coordinated by the central government. The local character of decision making safeguarded the legitimacy of the public sector. The possibility of the grassroots participating in the municipal decision making created and fortified a general feeling of inclusion and belongingness in the Nordic societies. Municipalities took care of everyday issues close to common people – in Central European countries people were taken care of by non-governmental organizations (NGOs) – and consequently, the match between the public sector and civil society became blurred. One indication of the latter is that in Scandinavia ‘state’ is often used synonymously with ‘society’, and the state is not perceived as such a hostile and alien force to the individual as it is in many other countries. Another important factor that gave a special flavour to the Nordic societies was the independent peasantry. In the Nordic hemisphere the peasants themselves owned their fields. Nordic agriculture was individualized, so to speak (Alestalo and Kuhnle 1987). The independent peasantry with rather strong formal rights constituted the nucleus of the Nordic democratic tradition. The peasantry voiced their opinion through the municipal decisionmaking process and they also had collective representation at the central government level in the meetings of estates. The independent peasantry could regard the state as an impartial and even benevolent agent and a counter-balancing force vis-à-vis the urban bourgeoisie. The same goes for social democracy. When the Nordic social democrats chose to support parliamentary reformism instead of radical revolutionism in the 1930s, the state became a vehicle also for the growing industrial working class to promote class interests (Esping-Andersen 1985). Thus, the ‘societal’ and democratic views of the state have long historical roots in the Nordic hemisphere. This long line of history may be of importance in discussions of present-day relationships between the state and the individual, political trust and beliefs in government. As the independent peasantry formed its own distinct social class with political representation, the Nordic class structure came to be tripolar, instead of bipolar like in most other countries. This class structure was more or less directly mirrored in the political sphere. In addition to the left and right wing parties, relatively strong agrarian (later centre) parties were important political forces that conditioned early Nordic policy-making. The historical features explained above make it rather easy to understand the development of the Nordic welfare state. As noted, local democracy fostered the increasing role of the public sector in social issues. The origi-

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nal political character of the Nordic countries also left obvious traces in the welfare state. The political representation of the rural population could not be neglected when the first measures of social policy were planned. Therefore, the Scandinavians began to legislate national insurance, which covered the whole population rather than workers’ insurance, which was limited to the industrial working class as in many Central European countries, or for the poor as in the Anglo-Saxon countries (Baldwin 1990; Kangas and Palme 2005). The agrarian parties in the middle divided the homogeneity of the non-socialist block and made it easier for social democrats to pursue their politics. As argued by Francis Castles (1979), the social democratic hegemony in Scandinavia is not only based on the strength of the left but also on the weakness of the right. As a consequence of these structural and political factors, social insurance schemes in the Nordic countries came to be universal; that is, the whole population or almost all became the target of social policy. Indeed, in comparative terms, the present-day Nordic social transfer system is characterized by nearly universal coverage and high income loss compensations. However, the income-related part of the transfer system is not necessarily better than in the Central European countries, which in many cases, guarantee higher replacement rates but for a smaller group of recipients (see e.g. Kangas and Palme 2005). Therefore, social policy was harnessed to provide something that in the present-day social science vocabulary is called bridging social capital and this is expressed in the very names of the major welfare schemes: people’s insurance, people’s school and so on. When it comes to the legitimacy of social policy, these universal schemes are extremely popular (Ervasti and Kangas 1995). The institutional set-ups of social policy programmes unify and divide people and social groups, creating strong and weak ties (Granovetter 1973) or – if you like – bridging and bonding social capital (Putnam 2000). The Nordic Welfare State Esping-Andersen claimed in his seminal book The Three Worlds of Welfare Capitalism (1990) that it was possible to classify countries according to the roles of the state, the market and the family in providing welfare for its citizens. The Nordic countries share an emphasis on universal programmes and a consequential high degree of decommodification; that is, a reduced level of market reliance among their citizens. This implies that welfare state programmes cover all citizens and that there is a large redistribution of resources between citizens via the state. This can be compared to the liberal welfare states that have implemented means tested programmes and modest

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universal transfers. The corporatist countries rely on the family to provide social assistance and the state only steps in as a last safety net when the family fails to provide the necessary means. Decommodification is lower than in the Nordic countries, but higher than in the liberal ones. Since the publication of Esping-Andersen’s book, a great deal of printing ink and paper has been used to verify or disprove the existence of welfare state models. A number of writers have argued in favour of four or five welfare regimes, whereas historically oriented scholars argue that there are as many models as there are nation states (see Arts and Gelissen 2002 for an overview). However, most authors agree that the Nordic model of the welfare state stands out from the other welfare state models quite clearly, although certain variations between the Nordic countries undoubtedly exist. There is substantial disagreement over the dimensions on which the classifications should be based. The majority of studies use a mixed approach; that is, they combine causal factors (social democracy, Catholicism, etc.), institutional indicators (e.g. generosity and universality of income transfer programmes, financial structure) with outcome variables (income inequality, poverty, unemployment, labour force participation rates). In all these dimensions the Nordic countries display a family resemblance. In the following we briefly discuss a number of the dimensions used in previous analyses to depict the Nordic welfare state model. We look at the welfare state institutions and a number of central outcome indicators. Despite its strong emphasis on collective welfare and the role of the state, the Scandinavian welfare model is predominantly individualistic in its character. The schemes are targeted at the individual and the family situation does not play a large role, whereas in other countries male breadwinner bonuses are tied into the benefits, and therefore depend on the spouse and the number of children to be provided for. The same goes for taxation. As a rule, taxation in the Nordic countries is more or less individual, and family-related tax deductions, which play an important role in Central Europe, have been either totally abolished as in Finland and Sweden or they have been circumscribed as in Denmark and Norway. Needless to say, the taxation system has especially important ramifications for work incentives for mothers and thereby for the breadwinner model that various countries display. In addition to tax and income transfer systems, the production of various care services plays a crucial role in the formation of breadwinnership and the family–work life nexus. Here social services in general and childcare services in particular are of importance. In all the Nordic countries the building up of childcare facilities has been on the political

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agenda since the 1970s. This is directly reflected in the comparatively high labour force participation of women1 and also in the fact that the Nordic countries display almost the same rather high fertility rates (around 1.7 in all Nordic countries). The labour force participation rates and the fertility rates indicate that it is possible to unify high labour force participation with rather high fertility rates – a dilemma that is unsolved in many southern European and post-socialist countries. Comparative studies (e.g. Fritzell and Ritakallio 2004) have shown that one of the best safeguards against poverty in all OECD countries is to have a dual-earner household. Through its promotion of the dual wage earner model, the Nordic model has reduced the risk of poverty. In addition, the high social transfer safety net effectively alleviates poverty. Consequently, poverty rates and social inequalities are low in the Nordic countries. Relative poverty rates in 2002, which are based on the OECD definition of poverty (having less than 50 per cent of median equivalence disposable income), were 4 to 6 per cent for the Nordic countries. The corresponding figures were markedly higher for Central European countries (France 7.0 per cent, Germany 9.8 per cent, the UK 11.5 per cent) and much higher in the USA (17.1 per cent). When it comes to child poverty the OECD average of 12.2 per cent is three times higher than the figures for the Nordic countries (2.4–3.5 per cent). As stated above, one trait of the Nordic model is the strong involvement of local governments in the production of social services. The emphasis of social services is so strong that a number of scholars regard the public service provision as the most important trade mark of the Nordic model. Public service provision is even thought of as more important than the universality in income transfer schemes. Sometimes the Nordic welfare state is labelled a ‘public service state’ (Lehto et al. 1999) where the public sector (mostly municipalities) has the responsibility for organizing health services, various services for the elderly and childcare. One consequence of this emphasis is related to female labour force participation rates. A number of critical voices have advocated that the intense focus on public service provision weakens the possibilities for private and various collective- and civil-society based activities, and thus undermines the basis for the formation of social capital and non-statutory social bonds. All the Nordic countries spend more on services than most of the other OECD countries, and with the exception of Sweden, they spend less on private transfers and services than the other countries do. There seems to be a trade-off between public and private spending: the larger the public budget, the smaller the private spending and vice versa. This crowding-out phenomenon is visible in other areas of activities as well. The presentation above might be considered to be a Candidean view

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of the Nordic model: it is the best of all possible worlds and the Scandinavian collectivistic view of the individual and the state acts as a panacea for all possible social evils. However, it is possible to interpret the situation quite differently. Through the equalization of incomes with the aid of lavish welfare benefits and heavy taxes, the welfare state creates work disincentives and kills individual initiatives, which, in turn, hampers economic growth, promotes the development of the black economy and, in the longer run, this ‘passion for equality’, is also detrimental to the poor. Furthermore, the strong public involvement in all spheres of life eats up individual possibilities and responsibilities. Control and patronage are more often attached to the welfare state. The system world hollows-out the life world, as Habermas puts it, or the state eats up individual liberty, as Hayek argues. It has been emphasized in the collectivist camp that social security is, like political and civil rights, an entitlement that belongs to all citizens more or less automatically. In the liberal view, social obligations instead of social rights are at the forefront. People have to toil in order to get something, entitlements are not automatic. Obligations go before rights, work before welfare. The difference between the emphasis on social rights and the emphasis on social responsibilities can be seen in, for example, a comparison of the debates on social security in various political camps and welfare state regimes. The liberally oriented have emphasized for a long time that the welfare system is not the answer to people’s problems. In order to lift people out of poverty and welfare dependency, they have to help themselves and not merely rely on public benefits. In line with this, participation in paid labour, training programmes or various courses that prepare people for social participation have been set as conditions for obtaining benefits. Thus, welfare is obtained though more active personal and individual efforts. What precisely is welfare, then? Following Erik Allardt (1975), we can talk about three components of welfare: living standard (having), self-realization (being) and communality (loving). The standard of living has to do with satisfying one’s material needs; self-realization and communality have to do with the social side of people. Welfare is the outcome of a combination of these factors. The task of social policy is to create optimal circumstances for the realization of welfare. The responsibility of the state to its citizens is, in the spirit of collectivism, most consequential in the sphere of satisfying material needs, although by guaranteeing the prerequisites for individual self-realization, such as an opportunity for education, the state’s role is also important. However, in the spirit of the liberal approach, communality in human relations is clearly a matter to be left to the individuals themselves.

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The Nordic Model of Work Relations The Nordic model of work relations comprises a labour market policy, collective wage setting, a model of cooperation at the firm level and a model of leadership. Full employment and economic security for the unemployed have been central political goals in all Nordic countries since World War II. Since the 1960s, the active labour market policies of the Nordic governments have sought to re-train people for other jobs, and to assist them financially when relocating to expanding parts of the economy. Huber and Stephens (2001) claim that the comprehensive labour market mobilization of the Nordic countries is actually the ultimate feature of the Nordic model and, indeed, these factors have kept unemployment rates relatively low in the Nordic countries with certain exceptions during certain periods. Although the labour markets in the Nordic countries are heavily regulated, their flexibility is at the level of the more liberal market economies. The keyword that best describes the spirit of the Nordic labour markets is ‘cooperation’, both at the national level and at the firm level. At the national level cooperation is manifested in centrally negotiated compromises between employers’ associations and the trade unions. In the middle of the 1930s, after the great depression, a shift could be observed from conflict towards cooperation between the trade unions and the employers with the adoption of corporatist mechanisms for conflict resolution. In Sweden the ‘Saltsjöbaden agreement’ in 1938 marked an important turning point. The high level of unionization and a similarly high level of organization among employers helped to bring about the next step, centralized bargaining, which became institutionalized in the 1950s. A similar system of wage negotiations developed in the other Nordic countries too. The strength of the social democratic parties in the Nordic countries was essential for the compromise between labour unions and employers’ associations. Ideologically, the compromise was built on social democratic principles, and an active state could help by guaranteeing economic security through welfare state policies. There are several key elements in the Nordic compromise between the trade unions and the employers’ associations. The first one is the principle of wage solidarity. Centrally negotiated wage settlements resulted in a compressed wage structure that is still reflected in the low levels of income inequality in the Nordic countries compared with other European countries. A second element is the security from unemployment given by socially responsible employers as a reward for restraint in wage negotiations. A third element is economic security for all, which is guaranteed through generous state unemployment and sickness insurance schemes. Cooperation at the firm and workplace level is a central aspect of the

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Nordic model. The Scandinavian model of cooperation at the firm level has two aspects: a socio-technical approach to develop the work situation, and the participation of workers in the management of the firm (Reve 1994). In the socio-technical approach the firm is seen as a system within which the relations between people and technology are central. The idea was that the work organization should be shaped by criteria for job design that satisfied both psychological aspects as well as the demands of technology and production systems (Karlsen and Munkeby 1998). In the 1960s researchers, led by Einar Thorsrud, showed that managers had little impact on the feelings of alienation on the shop floor and, therefore, proposed to give the workers more autonomy in the work process in order to increase their motivation. The insights of their field experiments in participatory work redesign were diffused to Sweden later in the decade. The most famous example is the Volvo model of the work group. A natural next phase was the involvement of the workers in the management of the firms. The agenda was to develop democracy at the workplace through formalized collective worker participation. The goal of this was to promote organizational learning and to increase autonomy and flexibility. A concrete result was the institutionalization of economic democracy through changes in relevant laws. This secured the workers formal representation on the boards of firms in the private sector. The participation of the employees through their organizations in the management of the firm had three advantages. It would give the workers influence, strengthen their identification with the interests of the firm, and it would reduce the level of conflicts. As the work relations that have developed in the Nordic countries are special, one may wonder if there is a Nordic way of management or leadership. A recent study states that there is (Schramm et al. 2004). The Scandinavian style of leadership is informal and consensus-oriented with an emphasis on equality and restraint in the use of power. Managers have to sell their ideas internally in the firms rather than taking unilateral decisions. The Scandinavian model of management, according to this study, has great potential for innovation by working in groups and sharing knowledge for a common purpose. This model may release the creativity within organizations to a greater degree than other types of leadership, which is important for success in the future knowledge-based economy.

IS THE NORDIC MODEL WANING? The description of the essence of the Nordic model may give an unduly static impression, whereas in reality the Nordic societies have continuously

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changed to adapt to new challenges. At present we can identify several trends that may erode the Nordic model of society, or at least reshape it. A vertical shift in the decision-making structure is the first factor. The rapid emergence of supranational political entities like the EU, which supersede the nation as the primary source of political power, undermine the state’s possibilities for nation-specific decision making and may invoke harmonization across countries. Parliamentary politics may be perceived to be increasingly irrelevant to voters, partly because minority governments tend to make elections inconsequential for the composition of the government, and partly because power has been transferred to institutions that are outside voter sanctions. The second factor is an ongoing horizontal shift in the decision-making structure. This includes the formation of new political, grassroots, crosscountry allegiances; the increasing power of multinational corporations; the formation of elite organizations and so on. One of the consequences is a decline in corporatism. The trade unions and the employers’ organizations still meet to negotiate wages, but the wage negotiations have been decentralized and take place at the industry and work place levels. The result is increased wage inequalities that have challenged the solidarity principle in the Nordic model. The number of corporative institutions has been reduced, and the old corporative structure is made increasingly irrelevant as public enterprises are transformed into market-oriented businesses. As Østerud (2005) observes, professional information managers and lobbyists, who attempt to influence decision makers, and the media, are gradually replacing the corporative channels. The mass media is an increasingly important institution that is clearly immune to voter control. The countries are also increasingly subjected to international laws that national law has to accommodate. Since the 1980s there has been a general reform trend in Europe to make the state slimmer and more efficient in response to the problem of government overload. The major trends in public administration have been the privatization and market orientation of public enterprises, and the outsourcing of public services to private companies. It is thought that public administration will become more efficient and more ‘customer oriented’ through the application of the ideas of New Public Management. This programme is inspired by neo-liberalist ideas that adopt principles from private firms in the public sector. Corporations may credibly threaten to move production and headquarters to low-cost countries. State control of the private sector is weakening through deregulation. The third factor is a change in patterns of stratification where individuals have become increasingly dependent on market forces for their life chances. Breen (1997) calls this process ‘recommodification’. Regardless of the universality of this process, it is clear that not all groups of individuals

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in all countries are ‘recommodified’ to the same extent. Both the wage system and egalitarianism are under pressure from market ideology, which is advanced by a growing middle class that wants more wage differentiation. Compared with other European countries, the Nordic democratic systems still fare well but Østerud (2005) observes disturbing developments: the democratic chain of command from voter to government is disintegrating. Turnout at elections and participation in popular movements have declined. The link between social class and voting has been weakened in the Nordic countries as part of a general trend in all Western societies (Evans 1999). A major cause of the decline in class voting is a change in the occupational structure as the service industries are replacing the manufacturing industries. The latter change has weakened the traditional working class and may gradually erode the basis for social democratic hegemony in the Nordic countries. The increasing diversity within the nation-states is the fourth factor that can affect the Nordic societies and particularly the universal welfare state. According to Rokkan (1970), class-based political parties encounter increasing problems in post-industrial society as their traditional base in the electorate is dwindling. Increasing pluralism may undermine and diminish the ‘vast majority’ favouring a universal welfare state (Anderson 2002). An important argument is that a universal welfare state is only possible in tiny nations where populations are small and homogeneous, in terms of religion, culture and ethnicity (Alesina and Glaser 2004). The Scandinavian countries fulfilled these criteria, whereas the situation in the USA was totally different: a huge heterogeneous population where social ties at the national level were much looser than in the Nordic hemisphere. Consequently, comprehensive welfare measures are missing. Therefore, following this strand of reasoning it may be argued that because of the cultural diversity following increasing immigration, Scandinavian universalism will lose one of its most crucial cornerstones. A central feature of the Nordic system has been the relatively smooth inclusion of the lower classes into society and the political order. Today, this is challenged by the difficulties of integrating an increasing number of non-Western immigrants into society. These immigrants may form a new underprivileged class but they are divided along ethnic lines with few possibilities of becoming a popular movement. Related to this issue is the problem of the ageing population where a decreasing labour force is expected to support a growing elderly population. This is an equation that threatens to hamper the relatively generous transfer systems. Thus, external and internal forces threaten to erode the Nordic model, or at least diminish the liberty of action for national governments and institutions. The Nordic welfare states are, in spite of recent changes, still more extensive than in other European countries. The combination of coordi-

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nated market economies, decommodification and active labour market policies still results in lower income dispersion, less poverty, smaller class differences and less marginalization among the Nordic countries compared with other countries. This does not imply that changes have not taken place. For example, the classical striving for low levels of unemployment has been abandoned, central wage negotiations diminish in importance, and the welfare states have become somewhat less universal. A major factor that may determine the future of the welfare state is whether the model invokes creativity and innovation so that the Nordic countries may be able to thrive in global competition. Such creativity and adaptation to a new reality includes a functional restructuring of the pension systems to suit the situation of an increasing elderly population, and to support high rates of fertility. Yet, an important part of creative solutions includes the need for cost containment and the simultaneous maintenance of solidarity among all people around the welfare state (Pierson 2001a). We do not make any predictions concerning the future of the Nordic model and the survival of the welfare state, but the answer lies in the adaptability of the institutions to new situations and how the Nordic countries fare in global competition.

THE NORDIC COUNTRIES AND GLOBAL COMPETITION One favourite critique of the Nordic model is that government bureaucracy and intervention in the economy hamper private enterprise. In addition, it is alleged that the security provided in the Nordic welfare states creates a tax burden and outprices the Nordic labour costs in global markets. All this should also undermine the motives for innovation and individual initiative. If this type of critique were valid we would predict a bleak future for the Nordic countries. Seen from the Nordic perspective, an efficient and well-developed public sector may be decisive for the competitiveness of the nation. The welfare state is a social capital that may lay the foundation for progress. The competitive advantage of a stable political and economic system may easily be overlooked. Indeed, recent experiences of the Nordic countries show that it is not impossible to combine a comparatively large public sector and an encompassing welfare state with high competitiveness (see Andersen 2007). So far, the conclusion is that the Nordic model has been surprisingly successful in the world markets. In general there is very little empirical support for the claims that the European welfare states are vanishing in favour of common market solutions (Castles 2004; Huber and Stephens 2001;

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Pierson 2001b). In spite of external and internal pressure, there is little support for the convergence in policy regimes across countries. Or as Pierson (2001b, p. 4) claims: ‘whatever the effects of globalization might be, these are intensely mediated by domestic arrangements, and thus convergence in national social policy structures is not expected’.

Therefore, if institutional responses vary across countries it is expected that people’s attitudes and behaviour will vary accordingly. Recently, the European Union has also started to look to the Nordic model. Politicians and researchers have observed that the economic growth in the Nordic countries has exceeded that of the core countries in the European Union (Schubert and Martens 2005). A recent analysis of economic growth in Europe and the United States indicates that high levels of taxation may not impede employment and economic growth (Dhont and Heylen 2004). According to this study, the main reasons for the low employment and growth levels in the core countries of the euro area are high structural transfers from the state in combination with a lack of sufficient productive government expenditures. Social and economic indicators seem to support the Nordic model as a success story rather than a failure, both in terms of standards of quality of life and economic competitiveness. We will focus on six indicators that cover most of the countries of the world. The first one is the Quality of Life Index developed by The Economist (2005), which combines subjective lifesatisfaction surveys with more objective standard of living indicators. The nine indicators cover subjective life satisfaction, health, political freedom and stability, stability of the family, gender equality, job security, community life and climate. All the Nordic countries are among the 12 with the highest rank. Ireland tops the list with Norway in third position and Finland has the lowest rank among the Nordic countries at 12. The Human Development Index is published annually by the United Nations Development Program (UNDP). The HDI is a composite standard of living index based on life expectancy, education and GDP per capita. Norway and Sweden top the list for 2004 with Iceland ranked 7, Finland 13 and Denmark 17 (UNDP, 2004). Finally, let us look at some economic indicators. The Global Competitiveness Index is published by the World Economic Forum (2005). Finland is found at the top followed by the United States with Sweden and Denmark ranked third and fourth respectively. All the Nordic countries are found among the top ten countries in this assessment of global competitiveness. The Ease of Doing Business Index is published annually by the

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World Bank (2007). The Nordic countries do less well on this index than on competitiveness, but they are all found among the top 15 in the list. At the top we find New Zealand, Singapore and the United States, with Denmark ranked fifth. Sustainable development is important for the preservation of the natural environment. AccountAbility in the UK and the Copenhagen Centre have developed an index of the responsible competitiveness of nations, which is essential to achieve sustainable development in the age of globalization. All the Nordic countries are found among the top six countries on this index, which is topped by Sweden (AccountAbility 2007, p. 143). The Corruption Perception Index (CPI) published by Transparency International ends the list of indicators. The CPI is based on surveys that reflect the perception of business people and country analysts, both resident and non-resident. Again, Finland is found at the top followed by Iceland, New Zealand and Denmark. All the Nordic countries are found among the eight least corrupt countries in the world as measured by the CPI (Transparency International 2006).

PLAN OF THE BOOK Above we have discussed the basic characteristics of Nordic societies. As already noted, we adopt a wide perspective in the Nordic model. Our argument is that as a reflection of the institutional characteristics, surprisingly many features in people’s values, attitudes and behaviour distinguish the Nordic societies from the rest of the European countries. In the following chapters we present empirical analyses in which we compare the various dimensions of people’s values in the Nordic societies to other European countries. Our analyses cover four broad themes: living conditions and the welfare state, politics, family and work, and ethical issues and values. Chapters 2 to 4 deal with living conditions and the welfare state in the Nordic countries. Chapter 2 concentrates on social exclusion and inclusion, which is a core area of social policies. In the recent debate, it has been claimed that social risks are becoming increasingly sporadic in their distribution so that traditional social policies can no longer efficiently guarantee social inclusion. The question posed by Fridberg and Kangas is whether or not the traditional structural factors, like class, labour market position and socio-economic background still serve to explain the phenomenon of social exclusion. Are the traditional lines of inequality disappearing and being supplemented by new cleavages that are less related to the traditional socioeconomic factors? Or is it the case that the old cleavages continue to exist?

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Another big issue is what this will mean for the traditional Nordic welfare state, which has mainly concentrated on traditional socio-economic cleavages between citizens. The welfare state generates material well-being. However, it is often suggested that material living conditions have only a weak correlation to subjective measures of well-being. In principle this could mean that even though the welfare state may improve the material conditions of citizens, it may be incapable of guaranteeing the subjective well-being of individuals. In other words, it may well be possible that, despite their huge investments in the welfare state, the Nordic countries are not the happiest nations in Europe. In Chapter 3 Eikemo, Mastekaasa and Ringdal focus on the determination of subjective health and happiness in Europe. The main question posed concerns differences in levels of subjective well-being. Do the Nordic countries differ from the rest of the European countries in levels of happiness and subjective health, and how may we account for the differences among the countries? Chapter 4 concentrates on social capital. Recently, the importance and the widely ranging positive implications of social capital have been acknowledged by social scientists of all kinds. Social capital promotes economic efficiency and growth, democratic virtue and civic engagement as well as individual health and well-being. Against certain earlier allegations, recent empirical evidence suggests that the comprehensive Nordic type of welfare state tends to generate rather than squeeze out social capital. In Chapter 4, Fridberg and Kangas set out to find more detailed reasons for the fact that the Nordic countries score highest on most of the indicators that are usually used for social capital. They search especially for an association between various forms of social policies and social capital: to what extent is it possible to speak of a specific Nordic orientation in social capital and what are the factors that account for it? The next three chapters relate to the political system in the Nordic countries. In Chapter 5, Berg and Hjerm analyse public perceptions and preferences concerning the level of decision making. As noted above, shifts in decision-making structures are among the major forces currently reshaping the Nordic as well as other European societies. Berg and Hjerm ask if institutional contexts can be discerned in people’s views in relation to which political entity they think should be responsible for various political decisions. They conclude that people’s preferred level of decision making differs across countries and that there are differences within the Nordic countries linked to the country’s relation to Europe. Trying to explain why people in certain countries prefer European level decision making, Berg and Hjerm show that institutional differences and political articulation matter whereas self-interest does not.

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From the level of decision making, we turn to political activism in Chapter 6. Berglund, Kleven and Ringdal distinguish between conventional political activism, mainly channelled through political parties, and unconventional issue-oriented and sometimes elite-challenging political actions. The authors start by discussing whether the declines in election turnout and in party membership are signs of a democratic crisis or whether political participation simply is expressed through other channels than the ballot. Central to the empirical analysis of conventional and unconventional political activism is a country classification based on democratic traditions. The authors contend that political activism of both types will be higher in countries with a long history of democracy, such as the Nordic countries, and low in the new democracies of southern Europe, and especially so in the Eastern European countries. In Chapter 7, Listhaug and Ringdal shift the focus to political trust. More specifically, they distinguish between three dimensions of political trust: trust in the electoral system, trust in the legal system and trust in the European Parliament. They describe detailed country variations with a special focus on the Nordic countries and use summary measures of the three dimensions of political trust in an analysis of cross-national variations in political trust. Their empirical analysis is based on a model where political trust is explained by a combination of individual and country characteristics. The former include the perceived political distance between the voter and the government, and performance evaluations. The country characteristics include a classification of the countries according to welfare regimes. The themes of Chapters 8 and 9 come closer to the everyday life of people in the Nordic countries as compared with other parts of Europe. Nordenmark’s analysis in Chapter 8 is related to the gender aspects of the different European regimes. As often suggested in prior research, the ‘family-friendly’ policies in the Nordic countries make it possible for women to participate in paid labour outside the home. However, it may still be the case that having paid employment on top of family obligations creates more demands than one can handle, which are, in turn, reflected in increasing within-family conflicts. Nordenmark focuses on family conditions, gender role attitudes, levels of satisfaction with the division of labour and, finally, the experience of work–family conflict in the various European clusters of countries. The crucial issue is, whether or not the Nordic model of family and gender roles dissolves conflicts between spouses. The other component of everyday life, work, is analysed in more detail in Chapter 9. As noted above, the structures of work life constitute one of the basic pillars of the Nordic model. In Chapter 9, Ervasti analyses the effects of the emergence of non-standard work arrangements on job

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quality. As often noted, work life is undergoing a process of accelerated change as various sorts of non-standard work, like temporary, fixed-term and part-time work become increasingly common. On the one hand, it is often concluded that flexibilization of the European and especially the Nordic labour markets is the only possible way to economic success and high levels of employment, but on the other hand, it is often feared that non-standard work in itself will generate a massive degradation in employees’ working conditions. In this chapter Ervasti examines whether there is a clear association between non-standard work and working conditions and if this association varies in accordance with labour market regime in Europe. The remaining three chapters concentrate on moral and ethical issues. The aim of these chapters is to find out whether the Nordic countries form a separate unit in Europe in relation to underlying values and not only in terms of social structures. Moreover, these chapters aim to examine whether or not the recent trends in structural development and values are likely to impact moral and ethical issues so that the Nordic countries become more or less similar to the other European countries. Chapter 10 focuses on attitudes towards immigrants. As noted above, the traditional cultural homogeneity in the Nordic countries may soon be lost as a consequence of immigration, which may, in turn, strongly question the collectivist foundations of the Nordic countries. According to recent criticism, the Nordic welfare states are not very well suited to receive immigrants. In Chapter 10 Ervasti, Fridberg and Hjerm examine whether there are crossnational differences in attitudes towards immigrants that can be explained by differences in societal macro-level conditions. In Chapter 11, the focus shifts to economic morality. Recently, several economic scandals have been exposed by the media in the Nordic countries. Ringdal examines if there is evidence for the traditional assumptions about especially high standards of economic morality in the Nordic countries. The chapter has a wide scope and covers cross-national differences in the following themes: economic trust, economic morality, consumer victimization, and unethical and illegal economic behaviour. The final multilevel analysis focuses on consumer victimization, having been asked for a bribe, and the frequency of minor or serious economic offences. The final empirical chapter, Chapter 12, concerns religiosity. Traditionally, the Nordic countries constitute the largest mono-confessional Protestant area in Europe. Another peculiar characteristic of the Nordic countries is that the church has a less salient role in society at large. Recently, both secularization and the emergence of non-traditional forms of religiosity have been said to contest the traditional religious settings. In Chapter 12, Ervasti sets out to test these allegations empirically. Are people in the Nordic coun-

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tries still more secular than other European nations? How much does religiosity influence the lives of individuals in the Nordic countries? In the concluding chapter we summarize the findings and discuss whether the Nordic uniqueness has its roots in reality or whether it is a myth.

NOTE 1. However, in Finland labour force participation of women with children under the age of three is much lower than in other Nordic countries. This is caused by the popularity of the so-called home care allowance payable to parents of children under three years of age who choose to take care of their own children or, more randomly, take them into private daycare. Home care is, by far, the most popular way of caring for small children in Finland (Rantalaiho 2008; Ervasti 1995). In contrast, labour force participation rates among those women whose youngest child is older than six years of age matches the Swedish ones.

REFERENCES AccountAbility (2007), The State of Responsible Competitiveness 2007, London: AccountAbility. Alesina, Alberto and Edward L. Glaser (2004), Fighting Poverty in the US and Europe: A World of Difference, Oxford: Oxford University Press. Alestalo, Matti and Stein Kuhnle (1987), ‘The Scandinavian route: Economic, social, and political developments in Denmark, Finland, Norway, and Sweden’, in Robert Erikson, Erik J. Hansen, Stein Ringen and Hannu Uusitalo (eds), The Scandinavian Model: Welfare States and Welfare Research, Armonk, NY: M.E. Sharpe. Allardt, Erik (1975), Att ha, att Älska, att Vara: Om Välfärd i Norden, Lund: Argos. Andersen, Jørgen Goul (2007), ‘The Danish welfare state as “politics for markets”: Combining equality and competitiveness in a global economy’, New Political Economy, 12 (1), 71–8. Anderson, James (2002), ‘Introduction’, in James Anderson (ed.), Transnational Democracy. Political Spaces and Border Crossings, London: Routledge, pp. 1–5. Arts,Wilhelmus A. and J. Gelissen (2002), ‘Three worlds of welfare capitalism or more? A state-of-the-art report’, Journal of European Social Policy, 12 (2), 137–58. Baldwin, Peter (1990), The Politics of Social Solidarity: Class Bases of the European Welfare State, 1875–1975, Cambridge: Cambridge University Press. Breen, Richard (1997), ‘Risk, recommodification and stratification’, Sociology, 31 (3), 473–89. Castles, Francis G. (1979), Democratic Politics and Policy Outcomes, Milton Keynes: Open University Press. Castles, Francis G. (1993), Families of Nations: Patterns of Public Policy in Western Democracies, Dartmouth: Aldershot. Castles, Francis G. (2004), The Future of the Welfare State. Crisis Myths and Crisis Realities, Oxford: Oxford University Press.

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Dhont, Tine and F. Heylen (2004), ‘Fiscal policy, employment and growth: Why is continental Europe lagging behind?’, Gent, Faculty of Economics and Business Administration, working paper. The Economist (2005), The Economist Intelligence Unit’s Quality-of-Life Index, www.economist.com/media/pdf/QUALITY_OF_LIFE.pdf. Ervasti, Heikki (1995), ‘Bringing the family back in? Attitudes towards the role of the family in caring for the elderly and children’, Yearbook of Population Research in Finland, 32, 80–95. Ervasti, Heikki and O. Kangas (1995), ‘Class bases of universal social-policy – pension policy attitudes in Finland 1993’, European Journal of Political Research, 27 (3), 347–67. Esping-Andersen, Gösta (1985), Politics Against Markets: The Social Democratic Road to Power, Princeton, NJ: Princeton University Press. Esping-Andersen, Gösta (1990), The Three Worlds of Welfare Capitalism, Cambridge: Polity Press. Evans, Geoffrey (1999), The End of Class Politics? Class Voting in Comparative Context, Oxford: Oxford University Press. Fritzell, Johan and V. Ritakallio. (2004), ‘The new social patterning of poverty in Europe: Cross-national and cross-temporal changes’, subreport to Report on Study of the Implications of Demographic Trends on the Formations and Development of Human Capital, Stockholm: The Institute for Futures Studies. Granovetter, Mark S. (1973), ‘Strength of weak ties’, American Journal of Sociology, 78 (6), 1360–80. Huber, Evelyn and Stephens, John D. (2001), Development and Crisis of the Welfare State: Parties and Policies in Global Markets, Chicago: University of Chicago Press. Kangas, Olli and Joakim Palme (2005), Social Policy and Economic Development in the Nordic Countries, Basingstoke: Palgrave Macmillan. Karlsen, Jan I. and I. Munkeby (1998), ‘Den norske samarbeidsmodellen’, in Tore Nilssen (ed.), Mot et Bedre Arbeidsliv, Bergen: Fagbokforlaget. Katzenstein, Peter J. (1985), Small States in World Markets: Industrial Policy in Europe, Ithaca, NY: Cornell University Press. Lehto, Juhani, N. Moss and T. Rostgaard (1999), ‘Universal public care and health care services?’, in Hannu Uusitalo (ed.), Nordic Social Policy. Changing Welfare States, London: Routledge. Østerud, Øyvind (2005), ‘Introduction: The peculiarities of Norway’, West European Politics, 28 (4), 705–20. Pierson, Paul (2001a), ‘Coping with permanent austerity: Welfare state restructuring in affluent democracies’, in Paul Pierson (ed.), The New Politics of the Welfare State, Oxford: Oxford University Press, pp. 410–56. Pierson, Paul (2001b), The New Politics of the Welfare State, Oxford: Oxford University Press. Putnam, Robert D. (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Rantalaiho, Minna (2008), ‘Kvoter, fleksibilitet og valgfrihet: om de indre spenninger i nordisk familiepolitikk’, in Solveig Bergman (ed.), Familjepolitiska ordninger i Norden – olika modeller och deras konsekvenser för jämstäldhet mellan könen. Tema Nord -serien, Köpenhamn: Nordiska Ministerrådet (forthcoming). Reve, Torger (1994), ‘Scandinavian management – from competitive advantage to competitive disadvantage’, Tidsskrift for Samfunnsforskning, 35 (4), 568–82.

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Rokkan, Stein (1970), Citizens, Elections, Parties: Approaches to the Comparative Study of the Processes of Development, Oslo: Universitetsforlaget. Schramm Nielsen, Jette, K.H. Sivesind and P. Lawrence (2004), Management in Scandinavia Culture, Context and Change, Cheltenham; UK and Northampton, MA, USA: Edward Elgar. Schubert, Carlos B. and H. Martens (2005), ‘The Nordic model: A recipe for European success?’, European Policy Centre paper. Svallfors, Stefan (ed.) (2007), The Political Sociology of the Welfare State. Institutions, Social Cleavages and Orientations, Oxford: Oxford University Press. Transparency International (2006), Corruption Perception Index 2006, www.transparency.org/policy_research/surveys_indices/cpi/2006. UNDP (2004), Human Development Report 2004: Cultural Liberty in Today’s Diverse World, New York: UNDP. World Bank (2007), Ease of Doing Business Rank, www.doingbusiness.org/ economyrankings/. World Economic Forum (2005), Annual Report 2005/6, www.weforum.org/ pdf/AnnualReport/2006/.

2.

The welfare state, poverty and social exclusion Torben Fridberg and Olli Kangas

INTRODUCTION Combating poverty is one of the most important tasks of the welfare state – perhaps its most fundamental task. Previous comparative research has shown that different social policy models, or more broadly welfare state regimes, substantially differ in their ability to alleviate poverty (www.lisproject.org/basictables; Atkinson 1998; Andreß 1998; Fritzell and Ritakallio 2004; Whelan and Maître 2005; Kangas and Ritakallio 2007). The welfare regimes not only differ from each other in their capacities to combat poverty, but also in the definition of poverty and the tasks of the welfare state in relation to social problems (Esping-Andersen 1990). The conceptual construction of the tasks for the welfare state is deeply rooted in different understandings of the proper relationships between the state and the individual. With some simplification we can divide these views into collectivistic and individualistic views. The collectivist picture of human nature, which has been the driving force in the leftist welfare discourse, can be derived from the Aristotelian interpretation of man and society. According to Aristotle (1991, p. 10), an individual who is not engaged in a community is comparable to either a god or a beast. A person between these two extremes is a social creature who, even as an individual, exists only in relation to others. Thus, individual welfare is also socially determined: poverty is defined socially, and social relationships are an essential source of well-being. Robinson needs his Friday. The idea of the relativity of poverty and the social character of needs runs through Western social philosophy and continues, for example, in the classical writings of Adam Smith. In his Wealth of Nations (1981, pp. 869–70 [originally published in 1776]) Smith wrote: ‘By necessity I understand, not only the commodities which are indispensably necessary for the support of life, but whatever the custom of the country renders it indecent for creditable people, even of the lowest order, to be without.’ The main stream of poverty research has followed this strand of think22

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ing and has defined poverty contextually, always in relation to the standards in the particular society where the individual is living (Townsend 1979; Gordon and Townsend 2000). Or, as Stein Ringen (1987a, p. 152) succinctly puts it: To be poor is to be deprived in way of life. People need a certain standard in their life in order to avoid exclusion, and in order to be able to participate in and be accepted into normal activities in one’s society. Necessities are determined by social requirements.

Thus, poverty equals lack of resources and that lack leads to an inability to participate in the normal way of life of the surrounding society. Although the very idea of linking human welfare and the command over resources was presented by a Briton, Richard Titmuss in the 1950s (see Titmuss 1974), it attained its strongest footing in Scandinavia and became an inspiration for the Nordic level of living surveys (see e.g. Allardt 1975 and 1993; Ringen 1987b; Erikson 1993; Erikson and Uusitalo 1987; Erikson and Åberg 1987). The crucial issue was that the approach was not only limited to economic scarcity but it continued to emphasize that there are also other important aspects that must be taken into consideration when analysing well-being and the lack of well-being. The approach was crystallized by Sten Johansson (1970, 1979). For Johansson human well-being can be measured and evaluated through nine components: health, employment, economic resources, knowledge and education, social integration, housing and neighbourhood, security of life and property, recreation and culture, and political resources. Johansson’s conceptual map laid the basis for successive Swedish level of living surveys. These surveys were later replicated in some forms and with some modifications in all the Nordic countries; for example, in his comparative Finnish project Erik Allardt shifted focus from resources to the level of need-satisfaction described by the catch-words having, loving and being (Allardt 1975 and 1993). Despite differences in emphasis, the underpinning theme in the Nordic approach is the very wide concept of welfare that always includes the quality of life aspect. The approach has some conceptual linkages to the Senian interpretation of individuals’ capabilities to fulfil their own potential (e.g. Sen 1992 and 1993). According to this brand of social philosophy, when debating on poverty we have much more than the elimination of monetary hardship at stake. Non-poverty does not only mean that we have enough money to make ends meet, but also means that we have the ability to function; that is, we know how to make conscious life choices that we are capable of realizing. The other extreme strand of thinking is tied to more individualistic (or liberalistic) concepts of the relationships between the (welfare) state and

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the individual. According to this approach, which is perhaps the most prominent in American political discourse, individual freedom is set into focus and dictates the subsequent role of the state, the limits for state actions and the concept of poverty. In this approach, which has its root in the ideas presented by classical liberalists, the state is seen to exercise its jurisdiction through coercion that is offensive to people’s autonomy (Kymlicka 2002). For example, the government levies taxes, which cut into people’s personal resources and limit their possibilities to choose. The welfare state is always seen as coercive, partial and patronizing. Liberty begins where the state ends; liberty is only realizable in the private sphere, not in the area of public policy (Hayek 1960; Nozick 1979). In order to maximize liberty, and hence to enhance individual well-being, the activities and tasks of the state should be limited to the minimum: they should only guarantee the basic security needed for subsistence. That is the only way in which individual welfare can be maximized. Whereas the definition of poverty is as wide as possible in the collectivistic Nordic approach, the liberalistic tradition concentrates more on the monetary side of poverty as indicated by trials to define absolute poverty lines in this or that society. In sum, the liberalistic and collectivist views differ in terms of how widely or narrowly the concept of need is defined. The former emphasizes minimal needs; the latter presupposes a much wider definition. In emphasizing a guaranteed minimum level of subsistence (and delimiting the state responsibility to provide that), the liberal social policy approach operates through a concept of absolute poverty: there exists some clearly definable minimum that must be guaranteed to all by social policy. Quite naturally, these conceptual differences lead to divergent views on the role of statutory social policy in creating equality and removing poverty. In liberal social policy, the main attention is on ameliorating poverty, whereas numerous goals of equality are more central in the collectivist view. As poverty is seen as relative and equality is set as the main objective, the domain of social policy necessarily becomes large. The concept of relative poverty keeps social policy evolving, and the elimination of poverty can be compared to shooting at a perpetually moving target. It is necessary to consider over and over again where the limits of public measures are and where the limits of responsibility have to be drawn. Conceptually, one can be socially excluded without being poor, for example because of ethnic discrimination, but in most cases the poor are socially excluded and the elimination of the latter link has been the main idea in the encompassing Nordic ‘cradle to grave’ welfare state. Through the use of European Social Survey (ESS) data this chapter tries to illuminate the links between social policy models, or welfare state regimes reflecting the philosophical lines of demarcation discussed above.

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25

Unfortunately, the ESS is not an especially handy tool for dealing with poverty issues because of its too general measurement of income. However, there are a number of dimensions that give us seemingly good proxies to analyse some of the dimensions defined by Sten Johansson. We are mainly interested in such living condition indicators as health status, difficulties to make ends meet, frequency of social contacts and safety in the local area where the respondent is living. We look at the incidence of these problems among some population groups that have been regarded as vulnerable in previous studies (e.g. Fritzell and Ritakallio 2004). As stated above, our approach is by no means an exhaustive list of important level of living components – such important resources as political participation and cultural activities are left outside of our analyses – but nevertheless the categories we use are sufficiently plentiful and accurate to give a proxy of poverty and social exclusion issues in those countries that have partaken in the ESS. We first depict the extension of welfare efforts in those countries that are included in the first round of the ESS. We look at the level and extension of legislated social rights in different countries and thereafter analyse the level of social spending. The main emphasis is on the analysis of the incidence of poverty in different countries. We try to mimic the Nordic approach and look at a relatively wide array of welfare components, but follow the individualistic tradition and focus mainly on the lower ends of distributions in order to see to what extent citizens in different welfare state models are exposed to various forms of poverty and exclusion. In that sense we combine the classical Nordic welfare approach with more limited poverty studies.

THE EXTENSION OF THE WELFARE STATE The Scandinavian welfare state has been renowned for its ability to reduce income inequalities and provide the poor with a decent livelihood. One important reason behind the good outcomes in the Nordic countries is linked to the specific social policy model applied. In principle, provisions are universal and more or less generous. The former dimension means that social benefits in Scandinavia are for all: they are neither targeted solely for some specific vulnerable groups selected through means-testing, nor are they provisions for members of selected privileged strata entitled to exclusive occupational welfare. Therefore, in the ideal Nordic model, all population categories, the rich and the poor, the working class as well as the populous middle class, and the few rich, are covered by the very same welfare programmes, which is seen as a solid guarantee for high popular support for the welfare state (Korpi and Palme 1998; Kangas and Palme 2005). Ideally, as everybody contributes and everybody benefits there is no

26

Nordic social attitudes in a European perspective

wedge between the well-off payers and the worse-off beneficiaries; there is no room for ‘welfare backlash’ (Korpi 1980). Everybody loves the welfare state, as the Swedish sociologist Stefan Svallfors (1989) somewhat exaggeratedly expressed it. Therefore, the paying well-offs are more willing to finance better benefits also for the poor, and consequently, a kind of Rawlsian social justice principle is fulfilled: good income-related benefits guarantee a rather high level of basic security as in basic pensions, social assistance and so on (Nelson 2003). The Scandinavian inclination towards universalism is already clearly visible in the construction of the post World War II welfare state, as displayed in Figure 2.1.1 Unfortunately, we do not have data for all the European countries that are included in our sample later in our empirical poverty analyses, but the scatter plot of 18 OECD countries provides an excellent clarification of some elements of Nordic exceptionalism and development over the last 50 years. When it comes to the generosity of benefits, the Nordic welfare states are not necessarily the most generous ones among the Western welfare states. For example in many Central and Southern European countries provisions are much higher in terms of compensation for loss of income, but the scope of insurance is limited (see e.g. Palme 1990; Ferrera 1999; Scruggs and Allan 2006). What is unique for the Scandinavian model is the combination of these dimensions. The model is generous and universal, whereas in Central Europe benefits might be more generous but not that universal, while in the liberal or Anglo-American model they are neither universal nor generous (Kvist 2007). These patterns were perhaps more pronounced in the 1950s, but some of the basic traits are still visible in the 2000s. An alternative way to look at the public responsibility for the well-being of citizens is to look at the size of the total public sector and the amount of money that the state’s social obligations take from the total gross national product. These measures are displayed in the left-hand panel in Figure 2.2. Of the Nordic block Sweden and Denmark are the leading countries both on total public spending and public social spending, whereas Finland and Norway are placed closer to the European mean. One important aspect in combating poverty is the level of last resort social benefits in relation to average income. The lower scatter-plot in Figure 2.2 visualizes the relation between the relative level of social spending and the generosity of national social assistance schemes (OECD 2004, pp. 30–32; and OECD 2006). The former is supposed to be an effective proactive mean, or safety-net, to prevent individuals from falling into poverty. The latter, for its part, tries to lift the poor above the poverty line and whether this venture is successful or not depends very much on the level of last resort payments. Here the generosity of social assistance is measured by the ratio between assistance paid to a family with two

27

The welfare state, poverty and social exclusion 1950 80

60

NL BE NZ

50 JP

40

AU

DK

SE

CH FR NO

0

10

20

UK

US

FI

20

IE

IT

30

AT

DE

G

Generosity

70

30

40 50 60 70 Universalism

80

90 100

R 2 = 0.017

2000 80 70

Generosity

NO

AT DE

SE BE CH NL FI DK IT FR

JP

60 AU NZ

50

US

IE

UK

40 30 20

0 7

0

10

20

30

40 50 60 Universalism

70

80

90 100

R 2 = 0.1906

Note: AT  Austria; AU  Australia; BE  Belgium; CH  Switzerland; DE  Germany; DK  Denmark; FI  Finland; FR  France; IE  Ireland; IT  Italy; JP  Japan; NL  Netherlands; NO  Norway; NZ  New Zealand; SE  Sweden; UK  United Kingdom; US  USA.

Figure 2.1 Generosity and universality of social insurance in 18 OECD countries, 1950 and 2000 adults and two children and the average income level in the country. As the graph depicts, high social spending is a necessary but not sufficient cause for lavish assistance payments. Of the high social spenders, Denmark and Belgium show the highest compensation levels for last resort benefits, whereas benefits are lower in the other high-spending countries. Finland, Norway and Sweden are lagging behind the high Danish levels. In principle, we could use an array of other indicators to depict whether there are traits that indicate Nordic peculiarity or not.

28

Nordic social attitudes in a European perspective

Social spending, % of GDP

30

DK SE

FR DE BE

CH

FI

25

NO LU

20

UK

AT GR

IT

CZ

NL PT HU PL

ES SI

15 IE

R 2 = 0.5078

10 30

35

40

45

50

55

60

Social assistance (2 adult and 2 children) / GDP per capita. %

Total public spending, % of GDP

90 DK

80 70 BE

60

PL NL

50

UK

ES

40

LU

IE

FI IT AT NO

SE FR

30 HU

20 10

DE

CH

10

15

20

R 2 = 0.1584

25

30

35

Social spending, % of GDP

Note: AT  Austria; BE  Belgium; CH  Switzerland; CZ  Czech Republic; DE  Germany; DK  Denmark; ES  Spain; FI  Finland; FR  France; GR  Greece; HU  Hungary; IE  Ireland; IT  Italy; LU  Luxembourg; NL  Netherlands; NO  Norway; PL  Poland; PT  Portugal; SE  Sweden; SI  Slovenia; UK  United Kingdom.

Figure 2.2 Total public spending, social spending and the level of social assistance (annual benefits paid for a family with two children divided by the GDP per capita) in 2002

However, on the basis of this cursory analysis the main point is already more or less clear. The Scandinavian countries are not necessarily at the top on all the welfare state indicators, but they are, on average, very well placed in comparison with other countries.

The welfare state, poverty and social exclusion

29

POVERTY AND SOCIAL EXCLUSION Because of space limitations and data availability problems we concentrate in the subsequent analyses on four dimensions of well-being: economic resources, health, social relations and safety (insecurity) of the area where the respondent is living. Three of these variables are compounded by collapsing a number of ESS questions together. The experience of economic hardship varies between 2 (no economic problems) and the maximum value of 8 (big economic problems), whereas the frequency of social contacts varies from 2 (lowest level of contacts) to 12 (the highest sociability), and the sickness index goes from 2 (good health) to 10 (bad health). The fourth index, ‘feel unsafe’, is based on a single ESS question: ‘How safe do you feel – or would you feel – walking alone in this area after dark?’ The responses varied from 1 (very safe) to 4 (very unsafe). A more detailed description of the composition of the variables is given in the Appendix. For most indicators Denmark is on top or very close to the top and we often find the post-socialist countries at the other end of the continuum. Also the Mediterranean countries are grouped in the lower end of the four indices. As can be seen in Table 2.1, the Nordic countries are often grouped somewhat closely with each other, and as a rule, Finland is lagging behind her Scandinavian neighbours. The clearest break against the Nordic – or perhaps more correctly, the Scandinavian – clustering is the health status of the population where the performance of the Nordics is more or less mediocre. The Anglo-Saxon regime is also dispersed: Ireland is in the lead and the UK is lagging far behind. As many as 26 per cent of the Nordic respondents say that they are hampered in their daily activities by some longstanding illness or disability (C8). Only in Eastern Europe is the share higher (31 per cent) while it is about 10 per cent lower in the other three regimes. The other health-related question (C7) was more subjective and dealt with self-related health status: ‘How is your health in general?’ Now the Nordics perform somewhat better in comparison to the other Europeans. About 5 per cent of the Nordic, Continental and Anglo-Saxon respondents regard their health as bad or very bad, whereas self-rated health is worst in Southern and Eastern Europe (9 per cent and 14 per cent, respectively). This more subjective question also displays rather a wide dispersion between the Nordic countries; however, in spite of this, the rankings are very much the same as shown in the compound index in Table 2.1. In fact, previous studies have shown that perceived health and more ‘objective’ morbidity measures yield similar results in cross-national comparisons and respondents’ self-rated health has been evaluated to ‘a valid and reliable health indicator’ (Lundberg and Lahelma 2001, p. 53; see Chapter 3 in this volume).

30

3.13 3.30 3.38 3.43 3.46 3.48 3.54 3.55 3.55 3.65 3.69 3.71 3.72 3.80 3.87 3.91 4.01 4.14 4.28 4.30 4.49

Sickness

Denmark Sweden Norway Luxembourg United Kingdom Netherlands Ireland Switzerland Italy Finland Austria Germany Belgium Spain Czech Republic Slovenia Portugal Poland Greece Hungary France

Country

2.79 3.16 3.28 3.50 3.55 3.69 3.74 3.88 3.90 3.91 3.98 4.03 4.09 4.43 4.85 4.85 4.96 4.97 5.32 5.32 no data

Hardship

Norway Portugal Denmark Sweden France Netherlands Switzerland Spain Finland Austria United Kingdom Ireland Luxembourg Belgium Germany Slovenia Italy Czech Republic Poland Greece Hungary

Country

8.67 8.31 8.30 8.26 8.14 8.08 8.01 7.96 7.91 7.89 7.86 7.82 7.81 7.77 7.64 7.24 7.21 7.02 6.87 6.79 6.25

Social relations

Denmark Austria Norway Finland Sweden Switzerland Slovenia Luxembourg Netherlands Belgium France Italy Spain Germany Ireland Portugal Greece Poland Hungary United Kingdom Czech Republic

Country

Living condition variables: mean scores, population aged 15 (ESS 2002/03)

Ireland Switzerland Austria Denmark Greece Belgium Luxembourg Italy Norway United Kingdom Netherlands Sweden Spain France Portugal Finland Germany Poland Czech Republic Slovenia Hungary

Country

Table 2.1

1.62 1.63 1.65 1.77 1.81 1.82 1.82 1.95 2.04 2.05 2.09 2.09 2.10 2.11 2.13 2.16 2.18 2.19 2.26 2.30 2.32

Feel unsafe walking in local area alone after dark

The welfare state, poverty and social exclusion

31

As one could anticipate on the basis of Figures 2.1 and 2.2, the prevalence of various forms of economic hardship is less frequent in the Scandinavian model of the welfare state. Our ‘hardship’ indicator is based on two separate questions regarding the respondent’s economic situation. The first one (question F32) is ‘If for some reason you were in serious financial difficulties and had to borrow money to make ends meet, how difficult or easy would that be?’ (1  very difficult . . . 5  very easy). Not surprisingly, the greatest difficulties in obtaining extra money if suddenly needed are among the post-socialist countries. As many as 61 per cent of the respondents say that they found it either very difficult or difficult to get loans. Also the Southern Europeans (54 per cent) have difficulties in covering their acute financial needs via loans, while the Central Europeans, Anglo-Saxons, and the Northerners have much less of a problem in borrowing money (38 per cent, 29 per cent and 22 per cent, respectively). The same pattern emerges if we look at the other variable (question F31) in the ‘hardship’ indicator: ‘How do you feel about your household’s income’. Thirty-six per cent of the Eastern and Southern European respondents, some 15 per cent of the Central Europeans and Anglo Saxons and fewer than 10 per cent of Nordics find it difficult or very difficult to live on their present income (see Table 2.1). Common national prejudice depicts the Northerners as sulky, lonely, not that talkative, emotionless people living in their remote cold countries in contrast to verbal, social and sunny Southern Europeans full of emotions and with close informal ties. Funnily enough, ESS data do not support such stereotypes and, in fact, the Northerners seem to be much more social than Europeans on average. Despite this dark stereotypic reputation, 45 per cent of the Northerners meet socially with friends and relatives (question C2) on a daily basis or several times a week, whereas only 6 per cent meet less than once a month. The corresponding figures for the other regimes are as follows: 38 per cent and 12 per cent for Central Europe, 49 per cent and 11 per cent for Anglo-Saxons, 37 per cent and 28 per cent for Southern Europe, 29 per cent and 32 per cent for the postsocialist regime. Neither do data on personal relationships fit in the common picture of the ‘emotionless’ Scandinavians. In fact, in all other regimes the lack of close and intimate relationships is more common: in the Nordic cluster 14 per cent of respondents said that they do not have any close friend to talk to (C3). For example, in the Southern and Eastern European countries the figure is 4 per cent higher and the other welfare clusters fall in between (see Table 2.1). In the traditional Scandinavian level of living studies one important welfare component is personal safety (Erikson and Uusitalo 1987). The ESS question (C6): ‘How safe do you – or would you – feel walking alone

32

Nordic social attitudes in a European perspective

in this area after dark?’ tries to capture the respondents’ general feelings on safety in their neighbourhood. In Chapter 4 on social capital and voluntary work, the Nordic countries are classified as high-trust societies. The Nordic people trust in each other and this mutual trustworthiness seems to be mirrored in feelings of being safe, which is our fourth level of living indicator. The answering alternatives varied from 1, ‘very safe’ to 4, ‘very unsafe’. The national means displayed in Table 2.1 show low ‘unsafe’ values for Austria and the Nordic countries, whereas the UK, which usually performs well along other indicators, is characterized by rather a high level of fear to walk outside after dark. The figures show that 13 per cent of Scandinavians feel unsafe or very unsafe, whereas the ratio is 20 per cent for Continental Europe, 23 per cent for the Anglo-Saxon block, 27 per cent for Southern Europe, and 26 per cent for the post-socialist regime (Table 2.1). The data presented in Table 2.1 does not say that much about the substance of poverty and social exclusion in Europe. The national means hide important information on the amplitude of social problems in some groups that are usually exposed to poverty. Therefore, in Table 2.2 we provide a short summary of the share of the population that is exposed to social problems (those who are sick, immigrants, the unemployed, people without educational qualifications, single parents, the aged and those living on social benefits) and those who suffer from some social problems like poverty and the lack of social relations and safety. In order to make the presentation more understandable and easier to interpret we used dichotomous variables instead of scales. The scales are used again in the next section using multilevel models. Thus, our dichotomous categories2 in Table 2.2 cover to some extent the ‘usual suspects’ of exposed groups (e.g. Alcock 1993; Fritzell and Ritakallio 2004; Whelan and Maître 2005) and the list of level of living components discussed above. Needless to say, these measures are merely poor proxies for the original dimensions used in proper level of living surveys. The proportion of the unemployed, immigrants, the elderly, single parents, those with low educational attainments and people living on social benefits are background indicators that are commonly utilized in macrolevel, cross-national poverty studies. As such, these variables do not pertain directly to poverty or social exclusion; they just give some hints as to the size of those groups that are usually the most exposed to poverty and that are the most likely to suffer from social problems. From the social exclusion point of view incidences of ill-health, poverty, feeling unsafe and lack of social relations are more interesting. When it comes to the prevalence of illhealth among different welfare state regimes, the Southern European block seems to perform quite well and the largest amount of health problems are

33

Sick

Low educated

Note:

*** p  .001.

Nordic 25.9 13.2 Continental 21.3 10.4 Anglo-Saxon 19.0 11.2 Southern 18.7 39.7 Eastern 30.4 17.8 X2 455.6*** 3118.9***

Welfare regime 6.5 12.4 8.3 6.4 3.9 574.6***

7.3 7.0 7.9 7.6 11.6 141.3***

Immigrant Unemployed 9.4 15.7 13.9 34.7 63.9 2682.1***

Poor

Unsafe

17.1 12.8 15.8 19.5 16.5 32.8 20.2 28.0 17.9 26.2 67.7*** 901.9***

Aged

6.9 7.6 8.0 10.9 10.6 126.5***

No friends

3.6 4.6 4.7 5.0 7.5 127.7***

Single parent

Table 2.2 The size of vulnerable groups (% of total population) in different welfare regimes in Europe, 2002

25.2 24.7 26.3 26.3 30.9 90.7***

On social benefit

34

Nordic social attitudes in a European perspective

found among the post-socialist countries. Given the high amount spent on social transfers and services, the Nordic performance is not that impressive, and the Nordic welfare state is much better and much more effective in combating monetary poverty than improving the health status of residents. Differences between the welfare state regimes are the widest for monetary poverty. In the Nordic hemisphere less than one-tenth of the population have problems living on their current income, whereas the proportion is almost two-thirds in Eastern Europe. The other groups of countries fall in between these extremes. One important issue attached to social exclusion is the concentration of social problems in certain vulnerable groups. The more the strong components of social exclusion are concentrated among the same vulnerable groups, the more severe is the degree of social exclusion. The prevalence of suffering from the various welfare problems (loneliness, poverty, sickness and insecurity) in weak population groups (those with low educational attainment, poor, aged, sick, immigrants, unemployed, single parents and those living on social assistance) can be simply calculated by cross-tabulating the dimensions of exclusion and population groups. Then one can study which particular group suffers most in each regime in relation to this or that problem. This analysis provides an idea of policy areas that are not working within a regime type. In the same vein, one can also compare the five welfare regimes and try to figure out which regimes are performing well or badly in various policy dimensions, or one can combine these two approaches. On average, suffering from loneliness is, in all vulnerable groups and in all regimes, lower than other forms of suffering. The highest loneliness percentage is found among the Eastern European aged and single parents (18.7 per cent and 19.5 per cent, respectively) and in most regimes the prevalence of loneliness is the largest among the elderly (varying from 14.2 per cent in Scandinavia to 18.7 per cent in Eastern Europe). In addition to the Eastern Europeans, single parents in the Anglo-Saxon (20.8 per cent) and Southern European (17.8 per cent) clusters feel lonely. Among all vulnerable categories the Scandinavians suffer the least through the lack of friends. Economic problems (suffering from poverty) are common in all regimes among the unemployed but the variation between the Nordic group (25.5 per cent of the unemployed have economic problems) and the post-socialist regime, where as many as 62 per cent of the unemployed have economic problems, is huge. In the UK and Ireland those who are lonely also suffer from economic hardship (40 per cent). In the Southern and Eastern European regimes all the vulnerable groups are hit by very high levels (30 to 60 per cent) of economic hardship and not that surprisingly, they have the most severe problems coping with their current income.

The welfare state, poverty and social exclusion

35

Sickness is a very common nuisance for all the vulnerable population groups (except immigrants). Also in the Nordic countries the prevalence of health problems is wide, and the unemployed (53.4 per cent), the elderly and those living on social benefits especially suffer from some infirmity. In fact, it seems to be that the Nordic unemployed have the most health problems after the Eastern European elderly (64 per cent). However, it is also good to keep in mind that the level of unemployment is the lowest in Scandinavia, which can mean that the Nordic unemployed are a more selected group ( sick) than the unemployed in countries with higher unemployment levels. In all welfare state regimes the aged have the strongest feelings of being insecure. The fear factor is highest in the UK and Ireland where as many as 42 per cent of the aged are scared, whereas the lowest proportion (22 per cent) is found in the Nordic hemisphere. All in all, the general level of insecurity seems to be the highest in the English-speaking countries. In Southern and Eastern Europe, insecurity goes hand in hand with health problems, lack of money and lack of close social relationships, whereas the concentration of these problems is the least severe in Scandinavia.

INDIVIDUAL AND MACRO-LEVEL DETERMINANTS OF SOCIAL EXCLUSION The bivariate inspections presented above do not say a great deal about the additive impacts of various background variables. In line with the other chapters in this volume we also perform multilevel modelling in order to control for a number of intervening factors. Results from such analyses are presented in summary Tables 2.3 and 2.4. The first multivariate table (Table 2.3) presents summary statistics of the explanatory power of four models explaining sickness, economic hardship, lack of social relations, and feeling unsafe. In the case of sickness the first proper model (M1), which includes six individual level control variables, explains 12 per cent of the between-country and 20 per cent of the withincountry variation. The result indicates that cross-national differences observed in sickness are not a result of demographic differences. Models 2 and 3 reveal some interesting features. The inclusion of two country level variables (i.e. the level of social spending and GDP per capita) increases the explanatory power of the model. However, the introduction of the welfare state classification contributed to a great improvement in the variance explained: it led to an increase of 42 percentage points, from 27 per cent to 69 per cent. However, as Table 2.4 indicates, social spending is not significantly linked to the health status of the population, and the prosperity

36

Table 2.3

Nordic social attitudes in a European perspective

Variance components from multilevel regression analyses

Sickness Su Se Explained Su Explained Se Interclass correlation 2 Log likelihood Economic hardship Su Se Explained Su Explained Se Interclass correlation 2 Log likelihood Social relations Su Se Explained Su Explained Se Interclass correlation 2 Log likelihood Feel unsafe Su Se Explained Su Explained Se Interclass correlation 2 Log likelihood

Model 0

Model 1

Model 2

Model 3

0.1282 3.2129

0.1123 2.5673 0.124025 0.20094

0.09379 2.5673 0.268409 0.20094

0.03975 2.5673 0.689938 0.20094

146814.2

146822.3

146799.0

0.4235 1.9453 0.219499 0.108642

0.1494 1.9453 0.724659 0.108642

0.1335 1.9453 0.753962 0.108642

123961.4

123952.4

123940

0.3546 3.7184 0.00482 0.089788

0.2503 3.7184 0.290734 0.089788

0.1641 3.7184 0.534996 0.089788

158732.7

158735.5

158717.0

0.04138 0.5267 0.21241 0.121728

0.03042 0.5267 0.421013 0.121728

0.02057 0.5267 0.608489 0.121728

84892.6

84900.5

84886.7

0.038371 159109.4 0.5426 2.1824

0.199119 130595.4 0.3529 4.0852

0.079516 165816.6 0.05254 0.5997

0.080553 91925.4

Notes: Su: between-country variance; Se: within-country variance; Explained: proportion of the variance in the null model explained by models 1–3. All variance components are statistically significant at the .05 level. Model 0: only intercept; Model 1: M0  control variables; Model 2: M1  GDP and PSE; Model 3: M1  country classification; ESS 1R 2002: 21 countries.

of the country is only weakly significantly linked. Neither is the difference between the different country groups and the Nordic group significant, except for the difference between the Eastern European group and the Nordic group of countries. When it comes to economic hardship, as indicated by the Su and Se

37

The welfare state, poverty and social exclusion

Table 2.4

Multilevel analyses: fixed regression coefficients from model 3

Description

Sickness B

Regression constant Age in years Age in years squared Gender, 1  male, 0  female Years of full time education In paid work or education Born in country Single with children 1  big city – 5  countryside

4.2196 0.0177 0.0001 0.0612

Economic hardship B

p

Social relations B

p

Feel unsafe B

p

*** 5.9242 *** 10.1338 *** 2.7343 *** 0.0072 *** 0.0889 *** 0.0076 ** 0.0001 *** 0.0007 *** 0.0001 *** 0.1271 *** 0.0844 *** 0.3798

p *** *** *** ***

0.0550 *** 0.0844 ***

0.0445 *** 0.0152 ***

0.6873 *** 0.5992 ***

0.1200 *** 0.0795 ***

0.0741 * 0.4158 *** 0.2615 *** 0.0014 0.1833 *** 0.7338 *** 0.1454 * 0.0374 0.0215 ** 0.0189 ** 0.0323 *** 0.1312 ***

Country level variables Public social 0.0041 expenditure pct of GDP 2001 GDP per capita PPP 0.0225 * US$ 1999 Country classification Continental (AT, BE, 0.0880 CH, DE, FR, LU, NL) Anglo-Saxon (IE, 0.2845 GB) Southern (ES, GR, 0.2450 IT, PT) Eastern (CZ, HU, 0.5409 ** PL, SI) Nordic (DK, FI, NO, 0 SE) (reference category)

0.0411

0.0218

0.0287

0.0649 ***

0.0914 **

0.0564

0.4840

0.3638

0.2234 *

0.3145

0.4108

0.5066 ***

1.0553 *** 0.6078 *

0.3218 **

1.5662 *** 1.4118 ***

0.4047 ***

0

0

0

Notes: Coefficients for country level variables PSE01 and GDP99 from model 2. * p  05; ** p  .01; *** p  .001.

38

Nordic social attitudes in a European perspective

variances explained in Table 2.3, the individual level factors explain differences between countries (explained Su variance 22 per cent) better than differences within countries (explained Se variance 10 per cent; see ‘Economic hardship’ in Table 2.3). This is mainly a result of the difference in the levels of educational attainment. As seen in the table, social spending and GDP per capita are important explanatory factors for country differences in the prevalence of economic problems: the explained Su variance increases to 72 per cent. In this case, the inclusion of the welfare state regime does not improve the model very much, and only the differences between the groups of Southern and Eastern European countries and the Nordic countries are significant when the individual level variables are controlled for (Table 2.4). As seen in Table 2.4, the overall prosperity of the country is very important and statistically more significant than social spending. Analyses of differences in social relations, or more specifically in the lack of them, show that individual level characteristics, although statistically significant (Table 2.4), do not contribute at all to explaining the observed differences displayed earlier in Table 2.1. The introduction of the macro-level country variables does contribute to an explanation of the between-country variance (Table 2.3), but only GDP per capita is of statistical importance (Table 2.4). The regime impact is bigger and the variance explained increases to 53 per cent. Yet again, only the differences between the groups of Southern and Eastern European countries and the Nordic countries are significant when the individual level variables are controlled for. The general feeling of being safe was the factor around which all the Nordic countries clustered most tightly together in Table 2.1. Furthermore, as indicated in Table 2.4, the differences are significant between the Nordic regime and all the other four country groups. Interestingly, the level of social security spending, which only had a minor impact on the other welfare components, seems to have some importance in feeling safe. Actually, 27 per cent of the rich Anglo-Saxons, that is, those who are very easily living on their income, feel unsafe, while the corresponding figure is one-third of that in the Nordic countries. Thus, social policy is not only an insurance against social insecurities, but it seems to safeguard against physical insecurity as well, indicating that the welfare state is not only for the poor and it is not only a device to help the poor but it benefits society at large.

DISCUSSION The ultimate aim of the welfare state is to abolish or at least relieve poverty. However, the eradication of poverty is in fact the least common denominator of the different political camps debating on the proper role and

The welfare state, poverty and social exclusion

39

scope of the state’s activities. It is possible to reach political agreement on the proposition that unfortunate people must be helped, but beyond that, views differ strongly over how far the public domain is to be extended. These political underpinnings form the basis for the different welfare state regimes used to classify countries. In some welfare states, notably so in the liberal or Anglo-Saxon regime, the guarantee of a minimum is regarded as the maximum that the welfare state should provide, whereas the supporters of the social democratic/Scandinavian welfare model assume that much more than a minimum security can be – and in fact, must be – achieved: minimum support is the minimum a welfare state should provide. This latter approach is mirrored in the traditional Scandinavian level of living approach or the Senian (Sen 1992, p. 40) interpretation of capabilities and quality of life. In this chapter we have tried vaguely to mimic the wider welfare approach by looking at a number of welfare/illfare indicators and the prevalence of various social problems among some vulnerable groups. In Figure 2.3 we have visualized and summarized our findings on the relationships between welfare components and vulnerable groups. The lines pertain to the share of people in specific vulnerable groups (those with low educational attainments, the sick, immigrants, etc.). The thicker the line, the greater the proportion in the group in question that suffers from the social ill in question. This very simple graph provides a snapshot of where welfare problems in different welfare state regimes lie, and an insight into the amplitude and the relationships between the problems. When it comes to the Nordic regime, the prevailing social policy model has been comparatively successful in combating the traditional, or narrowly defined, poverty. Neither is insecurity, nor the lack of social contacts a larger problem in Scandinavia than in the other regimes. This said, one must however point out that the relationships between poverty, in terms of lack of money and other ill-fare components, also in Scandinavia are significantly linked to traditional background variables; that is, also the Scandinavian poor and unemployed and so on tend to suffer from ill-health and other related problems more than non-poor Scandinavians. In other words, the mechanism is rather similar, but the amplitude of the poverty problem is smaller in Scandinavia. In that sense the Scandinavian welfare state has managed rather well. However, when it comes to improving people’s health, the Nordic model has not done much better than the other regimes and the vulnerable groups in Scandinavia often suffer from ill-health precisely in the same way as in the other regimes. In Continental Europe the vulnerable groups face – in addition to illhealth – also monetary hardship and to some extent insecurity. The same

40

Nordic social attitudes in a European perspective

Nordic regime SICKNESS

SOCIAL RELATIONS Poorly educated Sick Poor Unemployed Aged Unsafe No friends Immigrants

POVERTY

INSECURITY

Continental regime SICKNESS

SOCIAL RELATIONS Poorly educated Sick Poor Unemployed Aged Unsafe No friends Immigrants

POVERTY

INSECURITY

Note: The lines between social problems and vulnerable groups indicate how large is the share (%) of people in those groups that suffer from the social problems in question. Lines are only drawn if the percentage of suffering people exceed 20 per cent (in the case of social relations 15%). The thickness of the lines indicates the strength of the connection.

Figure 2.3 Relationships between welfare components and vulnerable population groups

pattern emerges from the Anglo-Saxon countries, although feelings of insecurity are much more common than in Continental Europe. When moving on to the Southern European regime, traditional poverty comes more and more to the fore, and in the Eastern European cluster, where monetary poverty, sickness and insecurity, and to a lesser extent also problems in social relations, plague the vulnerable people. The rather dark

The welfare state, poverty and social exclusion

41

Anglo-Saxon regime SICKNESS

SOCIAL RELATIONS Poorly educated Sick Poor Unemployed Aged Unsafe No friends Immigrants

POVERTY

INSECURITY

Southern European regime SICKNESS

SOCIAL RELATIONS Poorly educated Sick Poor Unemployed Aged Unsafe No friends Immigrants

POVERTY

INSECURITY

Eastern European regime SICKNESS

SOCIAL RELATIONS Poorly educated Sick Poor Unemployed Aged Unsafe No friends Immigrants

POVERTY Figure 2.3 (continued)

INSECURITY

42

Nordic social attitudes in a European perspective

picture of the poverty situation in the Eastern area is in contrast to those very low poverty figures that we can derive from the Luxembourg Income Study (www.lisproject.org/keyfigures/povertytable.htm; e.g. LIS 2007). Poverty rates, say, for Denmark and Hungary are almost the same, and the Czech Republic performs even better than Denmark, which is a result that goes against our own (in Table 2.1). The discrepancy accentuates the ever-present problem between subjective survey-based measurements that are based on how people feel (as in ESS) and objective register-based and income distribution-based measurements. However, the results are not as incommensurable as they would seem at first sight. What the LIS describes is a rather equal income distribution, both in Scandinavia and the post-socialist countries, which leads to relatively low poverty rates in both cases. As the average income level is much lower in Eastern Europe, people have problems coping on their incomes and show high levels of dissatisfaction. Thus, people in post-socialist countries are (still) equally poor, whereas in Scandinavia they are equally rich, which yields these diametrical results in ‘subjective’ and ‘objective’ measurements. Furthermore, it may be that in the European area people are comparing their level of living with other Europeans more and more, which undermines the purely nation-based poverty measures (see, for example, Kangas and Ritakallio 2007). In the recent influential theoretical social debate (e.g. Beck 1992) it has been emphasized that traditional factors that explain being underprivileged, such as class and labour market position, have lost their meaning. Social risks are considered to be more and more randomly distributed. This ‘democratization’ and diffusion of risks means that it is no longer possible to solve problems by using traditional social policy methods. Our results do not support this kind of view in every respect. ‘Traditional’ background variables, such as socio-economic position, labour market position, education and childhood home, still explain the majority of the variation in poverty risks. Neither does the theory hold true regarding ‘traditional’ social insurance, as it has managed very well to prevent poverty. Pension security and other forms of social insurance are good examples of this. At least in Scandinavia and Continental countries the applied pension policies have produced low poverty rates. What is also evident on the basis of our multilevel analyses is that differences in the individual level characteristics cannot properly explain cross-national differences in welfare. Various institutional factors are much more powerful explanatory factors. What is further evident on the basis of multivariate analyses is that there is still a strong correlation between welfare/ill-fare components within each welfare regime and, as stated above, the Scandinavian social policy model has managed to reduce the

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amplitude of social problems among the citizenry, which is a great achievement without doubt. However, the model has not managed to abolish the negative ties altogether. When it comes to the impact of the two macro-level country variables, GDP per capita was, not that surprisingly, an important explanatory factor in perceived economic hardships. This result also sheds light on the discrepancy between results from objective vs. subjective poverty measurements. Somewhat surprisingly, social spending levels are not that strongly related to welfare outcomes. There are a number of explanations for these contraintuitive results. For example, in the case of health neither GDP nor social spending significantly impacts on health status. One possible reason for this is that the association or causality between GDP and health is curvilinear; that is, there is decreasing marginal utility after a certain level of income. The same applies to the level of social spending. The initial investment in social policy leads to greater output, and after a certain level of spending the extra spending does not contribute that much to health. Finally, it may also be that the Nordic way of producing and delivering health care is not as effectively transformed into good health as it usually is supposed to be. Except for health, the regime impact from the Scandinavian welfare state is highly significant in all the welfare components studied. The regime is a kind of catch-all variable that captures numbers of unobserved factors as income distribution, gender equality, women’s labour force participation and so on. Interestingly enough, there is a positive impact from social spending and the Nordic welfare state on feeling safe, which indicates that social policy is not only an insurance against social insecurities, but it seems to safeguard against physical insecurity as well. Therefore, the welfare state is not only for the poor and it is not only a device to help the destitute, but through helping the poor it also benefits society at large, even the rich. The overall starting point in this chapter was on those historical and socio-philosophical arguments that have fermented political debates on the proper role of the welfare state. Our results indicate that the encompassing – or collectivized – Scandinavian welfare state fares very well in comparison with the other welfare state models in almost all dimensions of well-being. The poverty rates are the lowest and the liberal fears that the state will eat up and hollow-out private initiatives and social ties is not substantiated. On the contrary, the Scandinavian experience indicates that the state– individual relationship is not necessarily ‘either–or’ but can also be a ‘both–and’ relationship. Instead of suffocating an individual’s own potentiality, the encompassing welfare state through provision of resources to master one’s life also enhances individual freedom and life satisfaction. Interestingly, the European Union, which initiated thinking in terms of

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national action programmes (NAPs) to combat poverty, is gradually undermining the much wider Nordic concept of the task for the welfare state. The EU tries to launch special and targeted poverty programmes, whereas, in the traditional Nordic policy discourse, universal social policy programmes fortified by free education, active labour market policies and so on were seen as the best remedies against poverty. What remains to be seen is the kind of consequences that the possible shift in policy orientation may have in the Nordic hemisphere.

NOTES 1. Indicators used in the figure pertain to mean values of old-age pensions, sickness, work accident, and unemployment insurance programmes. Universality is a mean for coverage of those schemes (insured/total population in pensions (%), and insurance/total labour force for other insurance programmes (%)). Generosity is a mean replacement level for the four schemes expressed as a ratio between net benefit and net wage at the average income level. The interpretation of the indicators is straightforward: 0 per cent universality indicates that nobody is insured under any programme and 100 per cent indicates that the total population at risk is covered. Consequently, 0 per cent generosity refers to a situation where there are no benefits at all available in any of the four schemes, whereas the maximum value of 100 per cent pertains to full compensation in all the schemes (net benefit  net income). Data for these measures are derived from the SCIP data base housed at the Swedish Institute for Social Research, University of Stockholm (see e.g. Korpi and Palme 1998). 2. The vulnerable groups on which we focus are the sick (1 for those who are hampered by health problems; 0 for others in question C8), poor (1 for those who find it difficult or very difficult to cope with their present income; 0 for others in question F31), the lonely (1 for those who have no friends, 0 for the others in question C3), immigrants (1 for those who were not born in the country in question, 0 for inborn in question C20), unemployed (1 for those classified as unemployed in question F8, 0 for the others), aged (1 for those 65 years of age, 0 for the others), poorly educated (1 for those whose educational attainment level is less than 2 in question F6, 0 for the others) and the unsafe (1 for those respondents who feel either unsafe or very unsafe, 0 for the others in question C6).

REFERENCES Alcock, Pete (1993), Understanding Poverty, Basingstoke: Macmillan. Allardt, Erik (1975), Att ha, att Älska att Vara. Om välfärd i Norden, Lund: Argos. Allardt, Erik (1993), ‘Having, loving and being: An alternative to the Swedish model of welfare research’, in Martha Nussbaum and Amartya Sen (eds), The Quality of Life, Oxford: Clarendon Press, pp. 88–94. Andreß, Hans-Jürgen (ed.) (1998), Empirical Poverty Research in a Comparative Perspective, Aldershot: Ashgate. Aristotle (1991), The Nicomachean Ethics, Oxford: Oxford University Press. Atkinson, Anthony (1998), Poverty in Europe, Oxford: Blackwell. Beck, Ulrich (1992), Risk Society: Towards a New Modernity, London: Sage.

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Erikson, Robert (1993), ‘Descriptions of inequality: The Swedish approach to welfare research’, in Martha Nussbaum and Amartya Sen (eds), The Quality of Life, Oxford: Clarendon Press, pp. 67–83. Erikson, Robert and Rune Åberg (eds) (1987), Welfare in Transition, Oxford: Clarendon Press. Erikson, Robert and H. Uusitalo (1987), ‘The Scandinavian approach to welfare research’, in Robert Erikson, and Erik-Jørgen Hansen, Stein Ringen and Hannu Uusitalo (eds), The Scandinavian Model: Welfare State and Welfare Research, Armonk, NY: M.E. Sharpe, pp. 177–93. Esping-Andersen, Gøsta (1990), Three Worlds of Welfare Capitalism, Cambridge: Polity Press. Ferrera, Maurizio (1996), ‘The southern European model of welfare in social Europe’, Journal of European Social Policy, 10 (1), 17–37. Fritzell, Johan and Veli-Matti Ritakallio (2004), ‘Societal shifts and the changed patterns of poverty’, Luxembourg Income Study, Working Paper No. 393, Syracuse, NY: Maxwell School of Citizenship and Public Affairs. Gordon, David and Peter Townsend (eds) (2000), Breadline Europe. The Measurement of Poverty, Bristol: Policy Press. Hayek, Friedrich (1960), The Constitution of Liberty, London: Routledge. Johansson, Sten (1970), Om Levnadsnivå Undersökningen, Stockholm: Allmänna förlaget. Johansson, Sten (1979), Mot en Teori om Social Rapportering, Stockholm: Institutet för social forskning. Kangas, Olli and Joakim Palme (eds) (2005), Social Policy and Economic Development in the Nordic Countries, Basingstoke: Palgrave. Kangas, Olli and V.-M. Ritakallio (2007), ‘Relative to what? Cross-national picture of European poverty measured by regional, national and European standards’, European Societies, 9 (2), 119–45. Korpi, Walter (1980), ‘Social policy and distributional conflict in the capitalist democracies: a preliminary comparative framework’, Western European Politics, 3, 291–316. Korpi, Walter and J. Palme (1998), ‘The paradox of redistribution and strategies of equality’, American Sociological Review, 63 (October), 661–87. Kvist, Jon (2007), ‘Fuzzy set ideal type analysis’, Journal of Business Research, 69 (5) 474–81. Kymlicka, Will (2002), Contemporary Political Philosophy, Oxford: Oxford University Press. Lundberg, Olle and E. Lahelma (2001), ‘Nordic health inequalities in the European context’, in Mikko Kautto, Johan Fritzell, Bjørn Hvinden, Jon Kvist and Hannu Uusitalo (eds), Nordic Welfare States in the European Context, London: Routledge, pp. 42–65. Luxembourg Income Studies (2007), www.lisproject.org/basictables, accessed 2 January 2007. Nelson, Kenneth (2003), Fighting Poverty: Comparative Studies on Social Insurance, Means-tested Benefits and Income Distribution, Edsbruk: Akademitryck. Nozick, Robert (1979), Anarchy, State and Utopia, Oxford: Blackwell. OECD (2004), Benefits and Wages OECD Indicators, Paris: OECD. OECD (2006), Employment Outlook No. 80, Paris: OECD. Palme, Joakim (1990), Pension Rights in Welfare Capitalism, Edsbruk: Akademitryck.

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Ringen, Stein (1987a), The Possibility of Politics, Oxford: Clarendon Press. Ringen, Stein (1987b), ‘Poverty in the welfare state’, in Robert Erikson, ErikJørgen Hansen, Stein Ringen and Hannu Uusitalo (eds), The Scandinavian Model: Welfare State and Welfare Research, Armonk, NY: M.E. Sharpe, pp. 122–38. Scruggs, Lyle and J. Allan (2006), ‘Welfare state decommodification in 18 OECD countries: A replication and revision’, Journal of European Social Policy, 16 (1), 55–72. Sen, Amartya (1992), Inequality Re-examined, Oxford: Oxford University Press. Sen, Amartya (1993), ‘Capability and well being’, in Martha Nussbaum and Amartya Sen (eds), The Quality of Life, Oxford: Clarendon Press, pp. 30–53. Smith, Adam (1981) [1776], Inquiry into the Nature and Causes of the Wealth of Nations, Indianapolis: Liberty Classics. Svallfors, Stefan (1989), Vem Älskar Välfärdssstaten?, Lund: Arkiv. Titmuss, Richard (1974), Social Policy, London: Allen & Unwin. Townsend, Peter (1979), Poverty in the United Kingdom. A Survey of Household Resources and Standards of Living, Harmondsworth: Penguin Books. Whelan, Christopher and B. Maître (2005), ‘Vulnerability and multiple deprivation perspectives on economic exclusion in Europe: A latent class analysis’, European Societies, 7 (3), 423–50.

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APPENDIX The construction of additive well-being indices was carried out as follows. ‘Social relations’ is based on a battery of two questions that were added together: ‘How often do you meet socially with friends, relatives or work colleagues?’ (1  never . . . 7  every day) and ‘Compared to other people of your age, how often would you say you take part in social activities?’ (1  much less . . . 5 much more). The minimum value of 2 indicates a low frequency of contacts, whereas the maximum value 12 pertains to frequent contacts. ‘Sickness’ or health status collapses a self-rated health status: ‘How is your health in general?’ (1  very good . . . 5  very bad) and ‘Are you hampered in daily activities by any longstanding illness or disability?’ (1  yes a lot, 2  yes to some extent, 3  no). The latter scale was recoded so that the original answer ‘yes a lot’ was given the value of 5, the ‘yes to some extent’ was given the value of 3 and ‘no’ was given the value of 1. This recoded variable was then added to the self-evaluated health. The compound variable ‘Sickness’ goes from 2 to 10 and the higher the value, the worse the health status. Finally, in order to attain an evaluation of the respondent’s economic situation (Hardship) we added a question: ‘If for some reason you were in serious financial difficulties and had to borrow money to make ends meet, how difficult or easy would that be?’ (1  very difficult . . . 5  very easy) and ‘How do you feel about your household income?’ (1  living comfortably . . . 4  very difficult). The values of the previous question were reversed and the two response alternatives (‘very easy’ and ‘easy’) were merged into the value of 1. As a result the economic hardship indicator varies from 2 (easy life) to 8 (economic problems).

3.

Health and happiness Terje Andreas Eikemo, Arne Mastekaasa and Kristen Ringdal

INTRODUCTION The study of general health and happiness has been thought of as different fields; the first mainly located within public health, and the second within the field of quality of life. Given the closeness of the concepts, the lack of links in the research literature between studies of general health and happiness may come as a surprise. In this chapter we consider health and happiness to be related but separate concepts. We do not, however, attempt to disentangle the nature of their relationship. We keep an open mind as to whether happiness is promoting health or whether health rather leads to happiness, or whether happiness is best seen as a component of health. A common conclusion in quality of life research is that subjective wellbeing is only very weakly related to material living conditions (for reviews, see Arthaud-Day and Near 2005; Diener and Biswas-Diener 2002). Indeed, early findings of such weak relationships in the pioneering quality of life studies of the 1970s (in particular, Campbell et al. 1976; Andrews and Withey 1976) have led to a proliferation of theoretical interpretations, which mostly focus on various kinds of social comparison and adaptation effects. Whereas the weak effects of material living conditions are commonly emphasized in quality of life research, the situation is quite different in research on health, including subjectively assessed health. In this field, income, social class and other indicators of material living conditions are generally considered to be very important determinants. In a comprehensive analysis of the relationship between socio-economic indicators and self-assessed health in ten European countries, the research group, which includes some of the most prominent researchers in this field in Europe, concludes: ‘The persistence of large health inequalities stresses that these inequalities are deeply rooted in the social stratification systems of modern societies’ (Kunst et al. 2005). Against this background of very different views on the importance of material living conditions for health and happiness, a recent study by 48

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Subramanian et al. (2005) is highly interesting. They performed parallel analyses of happiness and self-assessed health in the United States and found that these variables were equally strongly related to income and education. In addition, they found that happiness was much more strongly related to marital status than health. In this chapter we extend Subramanian et al.’s model by adding country characteristics. We need to look more systematically at expectations of social differences in happiness and health. We may distinguish between inequalities between groups formed by demographic variables, socio-economic positions, and social support. Demographic inequalities are captured by age and gender. Socio-economic position includes social class, status, and material living standard, including income (Bartley 2004). Our measure of social class is based on the Erikson and Goldthorpe (1992) class schema, which builds mainly on employment relations and work conditions. It has been used extensively in sociological stratification research and also in studies of health inequalities. Social status in sociological terms is clearly different from social class in that it implies a hierarchical ranking of individuals in terms of prestige or reputation (Bartley 2004). In our study education and social class, after the effect of income is removed, may be seen as measures of different life styles. Higher education and a privileged social class are definitely associated with high status and with healthy life styles. Standard of living may be related to health and happiness in two ways. At the macro level, we may describe countries by their living standard measured by the gross domestic product (GDP) per capita or similar measures. At the individual level we may use individual or household income. To be able to distinguish between those two effects, we use a relative household income measured in quartiles within each country. Social support is regarded as beneficial to people’s well-being (Pinquart and Sorensen, 2000). A study of nearly 3000 elderly Americans showed how participation in social activities such as bingo, bowling or going to church was as important as regular exercise for the maintenance of good health (Glass et al. 1999). The notion of strong and weak ties, as developed by Granovetter (1973), is relevant to this issue, because it refers to the quality and quantity of social relationships. Whereas strong ties make reference to close personal bonds between two people in a social network (that is, between relatives or close friends), the strength of weak ties is that they usually connect socially dissimilar people and provide access to diverse sources of social support. According to studies on the relationship between social support and psychological and physiological well-being, the effects of social support appear to make individuals healthier, live longer, feel better and cope with difficulties resulting from chronic diseases and acute difficulties (Cassel 1976; Cobb 1976). Let us close the introduction by summarizing the expectations of the

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relationship between our explanatory variables and the two outcomes: poor health and unhappiness in line with the findings of Subramanian et al. (2005). With regard to the individual level, we expect that increasing age is accompanied by poorer health and more unhappiness. Furthermore, we expect no sex differences in poor health but men may be expected to show more unhappiness than women. From previous research (Subramanian et al. 2005; Diener et al. 1993) we expect social position variables such as education, social class and household income to be more strongly associated with health than happiness. Marital status is our main indicator of source of social support (strong ties) for the individual. Therefore, we expect that married persons will report poor health and unhappiness less frequently than never married, divorced or widowed persons. We also expect marital status to be more strongly associated with unhappiness than with poor health. We also take advantage of another measure of social support, which we define as frequency of meetings with relatives, friends and colleagues, and which refers to weaker ties. Here, we expect better health and happiness among those who meet other people every day, compared with people meeting friends, relatives and colleagues less frequently. We may distinguish between two separate sources of between-country differences in poor health and unhappiness. First, compositional effects may explain some of the observed differences. Compositional effects stem from unequal distributions among the countries on individual level variables such as years of education and social class. Second, between-country differences may be explained by macro characteristics of the countries. We expect the wealth of the country to be negatively related to poor health and unhappiness. For poor health in particular, a positive relationship may in part be a result of higher spending on health in more affluent countries. We include both the GDP per capita and the total country expenditure on health per capita. Perhaps the salient differences between the countries for our outcome variables will be captured by the Human Development Index (HDI) published by UNDP. The HDI is based on three sub-dimensions: life expectancy at birth, education and literacy, and GDP. As the countries cluster on country characteristics, it may be that a country classification will cover the major part of the between-country variation in poor health and unhappiness. This is a third way to explore country differences. Ours is built on a classification of the European countries by welfare regimes and expanded by a category for Eastern Europe (Arts and Gelissen 2002). We expect the Nordic welfare states, with perhaps the most comprehensive welfare and healthcare benefits, to cluster with low values on both poor health and unhappiness, whereas the East European countries will show high values.

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It is more difficult to make predictions for the remaining three categories: the Anglo-Saxon, the Continental, and the Southern European countries. Finally, we expect poor health and unhappiness to be positively correlated and strongly so at the country level, which would parallel the findings in Subramanian et al. (2005) for the USA. To sum up, this chapter aims to show how the European countries rank on general health and happiness. Furthermore, do we observe the same type of social inequalities and are social inequalities of different importance for general health and happiness? Can the observed between-country differences in health and happiness be explained by compositional effects or by country level characteristics?

METHODS The main results are based on a multilevel analysis of pooled data from the ESS 2002 and 2004, which covered 25 countries. In this section, the multilevel model and the variables to be used in the statistical analysis are described. Our analysis is based on a multivariate multilevel model for binary responses.1 The first level consists of the two outcomes, poor health and unhappiness, nested within the individuals. It is the presence of these two outcome variables that makes the model multivariate. The individuals constitute the second level and they are nested within countries, the third level of the model as shown in Figure 3.1. In this figure the net number of respondents for the first country, Austria, is 3886, and the last country, Ukraine has 1760 respondents. Ukraine did not participate in the 2002 survey and this explains the low number of respondents for the multilevel analysis. The multivariate multilevel model enables us to analyse the outcomes of health and happiness simultaneously. This model also estimates the correlation between health and happiness both at the individual and at the country level, and with and without control variables. The Indicators of Health and Happiness Our measure of general self-reported health is based on this question: ‘How is your health in general? Would you say it is . . . very good, good, fair, bad, or very bad?’ We consider people to have poor health if they answered ‘bad’ or ‘very bad’. Our second outcome variable, unhappiness, is based on the following question: ‘Taking all things together, how happy would you say you are? Please use this card’. The card shows a scale from 0, ‘extremely unhappy’ to 10, ‘extremely happy’. We define people as unhappy if they

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Nordic social attitudes in a European perspective

Level 3: Countries

Level 2: Individuals

Level 1: Outcomes PH

1

1

....

UH PH

.......

3886

25

1

UH

PH

....

1760

UH PH

UH

Source: Adapted from Subramanian et al. (2005), p. 665.

Figure 3.1 Multivariate multilevel model of poor health (PH) and unhappiness (UH) score 0 to 5 on this question. Therefore each of our outcome variables distinguishes between two states with poor health or unhappiness scored as 1, and the remaining response categories scored as 0. Validity and Comparability of the Subjective Measures of Health and Happiness It is important to be aware of the methodological challenges related to studies that compare outcomes of self-reported health and happiness between countries. Is subjective health a valid measure of health, and do responses to a question about happiness reflect how people really feel about their lives? If so, are the measures really comparable across countries? The sociology of health is based on the assumption that self-reported health is partly determined by people’s own socio-cultural perception of what good or poor health should be. Consequently, some health researchers do not fully rely on the subjective measures as valid indicators of health. However, a growing number of studies have shown that subjective measures of health are strongly correlated with harder health measures, such as death. Idler and Benyamini (1997) examined 27 longitudinal studies of representative community samples that investigated this relationship, and their findings were impressively consistent. Global self-reported health was found to be an independent predictor of mortality in nearly all of the studies, despite the inclusion of numerous specific health status indicators and other relevant covariates known to predict mortality. A study from Europe showed that poor self-rated health is a strong predictor of mortality in Finland, and the association was only partly explained by medical history, cardiovascular

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disease risk factors, and education (Heistaro et al. 2001). Undoubtably, these findings support the validity of subjective measures of health. In contrast to health, happiness or well-being is by definition a subjective phenomenon. Nevertheless, it is necessary to distinguish between the concrete survey responses and feelings or evaluations that presumably exist independent of whether an individual is actually questioned about these matters or not. There are indications that subjective well-being measures may be somewhat vulnerable to question order effects, question wording, the time frames given in the questions, and so forth (Schwarz and Strack 1991). Nevertheless, reasonable levels of convergence have been found between reported happiness and similar global well-being measures on the one hand and various other measures like spouse reports and other informant reports (see Diener et al. 1999). The possibility of considerable response biases cannot, however, be entirely ignored. The second challenge is comparability between countries. An important strength of this study is that all the questions used are collected from the same survey, with the same questions asked within the same period of time. Therefore, many sources of artificial variability among countries have been eliminated. More fundamental problems of cross-cultural comparability may nevertheless remain. Even though a great number of studies make use of selfrated health in comparative research, there are few data on its comparability across cultures. Measuring the comparability itself and adjusting for possible differences may also be difficult. One promising suggestion may be to map responses to various questions on the same health domain to a common comparable scale. In line with this, anchoring vignettes can provide a bridge between data collected using different instruments for measuring health status (Salomon et al. 2004). Results from a Finnish study that compared cultural differences in self-rated health in Finland and Italy, suggest that selfrated health is a useful summary of physical health, but may be sensitive to the cultural environment (Jylhä et al. 1998). Similar results on cultural variations are reported in the subjective well-being literature (Diener et al. 2003). Individual Level Explanatory Variables In our analysis, five explanatory variables that describe people’s socioeconomic status have been applied. These are education, occupational class, income, marital status and social network. Education was measured in years of full-time education completed. We use a three-category version of the Erikson and Goldthorpe (1993) class schema: ‘Workers’ (classes IVa to VIIb), ‘Routine non-manual’ (class III), and the ‘Service class’ (class I and II, the reference category for social class). An additional category covers persons with no present or former job registered in the interviews. Income

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Nordic social attitudes in a European perspective

was measured by annual household income divided into four equally sized groups (quartiles) for each country. In this way, we were able to measure relative income levels and keep them distinct from between-country levels in prosperity. The fourth income quartile was set as a reference category. The objective income measure may not tap the actual economic burdens on the household. Therefore, it is quite possible that a subjective question on income insufficiency would be a better indicator of economic hardship. In order to tap this we used a question about feelings concerning the ability of the household income to make ends meet. The response categories ‘living comfortably’ or ‘coping on present income’ were scored as 0 and ‘difficult’ or ‘very difficult on present income’ were scored as 1. Social support is measured by marital status and an indicator of social network. Marital status was constructed from two separate variables: the first variable concerns ‘legal marital status’ and the second one asks whether the person is ‘living with a partner’ or not. By combining these two variables, we were able to construct the following four dummy variables: never married, widowed, divorced/separated and married/partner (reference category). Social network was measured by the frequency of meetings with friends, relatives or colleagues.2 The response categories ‘never’, ‘less than once a month’ and ‘once a month’ were scored as 1, whereas the categories ‘several times a month’, ‘once a week’, ‘several times a week’, and ‘every day’ were scored as 0. Country Level Variables The country level variables were collected from the web pages of WHO (www.who.org) and UNDP (www.hdr.undp.org). The first variable is the natural logarithm of the population size for each country, which adjusts for the rather large population size differences in Europe. The second country level variable is the GDP per capita in 1000 US dollars for 2002. Further, we included total health expenditures per capita (public and private) in 1000s of international dollars in 2003.3 As an alternative to these rather specific variables, we also included the Human Development Index. Finally, the country classification based on welfare regimes was represented by a set of dummy variables for the country categories, with the Nordic countries as the reference category.

RESULTS In this section we present the results of the empirical analysis. In the first section we describe the differences between the 25 countries in poor health

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Health and happiness

Table 3.1 Self-reported poor health and unhappiness: age adjusted country percentages (ESS 2002 and 2004 combined) Poor health (%) Ukraine Hungary Poland Estonia Slovakia Portugal Slovenia Czech Republic Spain Germany Luxembourg France United Kingdom Norway Greece Italy Denmark Sweden Netherlands Iceland Belgium Finland Austria Switzerland Ireland N

Unhappy (%) 18.7 14.7 11.3 10.1 9.9 9.9 9.0 8.1 7.4 6.8 6.6 5.2 4.9 4.5 4.0 3.7 3.5 3.3 3.2 3.0 3.0 3.0 2.8 1.9 1.6 76692

Ukraine Hungary Estonia Poland Italy Slovakia Greece Czech Republic Portugal Germany Slovenia United Kingdom Austria France Spain Luxembourg Ireland Belgium Sweden Netherlands Finland Norway Switzerland Denmark Iceland N

29.3 17.7 17.3 16.8 14.8 14.7 12.9 11.2 9.8 8.9 8.0 7.3 6.6 6.2 5.9 5.5 4.1 3.5 3.5 3.0 3.0 3.0 2.4 1.8 1.0 76412

and unhappiness. In the second section the results from a multilevel analysis with both individual and country level variables are presented. Cross-country Differences in Poor Health and Unhappiness Table 3.1 shows the mean age-adjusted country percentages for having poor health and being unhappy. The Nordic countries are printed in bold and they are found at the bottom or rather at the ‘good’ end of the list, with poor health percentages ranging from a level of 4.5 per cent in Norway to less than 3 per cent in Finland. The countries with the lowest score on poor health are Ireland (1.6 %), Switzerland (1.9 %) and Austria (2.8 %). At the

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Nordic social attitudes in a European perspective

30

% UNHAPPY

UA

25

20

EE IT

15

PL

HU

SK

GR

CZ

10

PT DE SI GB

AT

FR

SE

5

LU

ES

BE

IE CH

F I NL

NO

% POOR HEALTH

DK I S

0 0

5

10

15

20

key: Nordic:

Anglo-Saxon:

Southern:

Eastern

Continental:

Note: AT Austria; BE Belgium; CH Switzerland; CZ Czech Republic; DE Germany; DKDenmark; EE Estonia; ES Spain; FI  Finland; FR France; GB United Kingdom; GR Greece; HU  Hungary; IE Ireland; IS  Iceland; IT Italy; LU Luxembourg; NL  Netherlands; NO  Norway; PL Poland; PT  Portugal; SE  Sweden; SISlovenia; SK  Slovakia; UA Ukraine.

Figure 3.2 Self-reported poor health (x-axis) and unhappiness (y-axis) in European countries by type of welfare system: age adjusted country percentages (ESS 2002 and 2004 combined) other end of the scale we find mainly East European countries: Ukraine, Hungary, Poland and Estonia, that all record percentages of poor health that exceed 10 per cent. In the distribution of unhappiness, the Nordic countries fare even better. Iceland (1%) and Denmark (1.8%) are the two countries with the lowest percentage of unhappy persons. At the other end of the scale we find mostly the same countries as for poor health, however, Italy and Greece are found higher on the list for unhappiness than on the list for poor health. In summary, both lists are topped by poor Eastern European countries, with the rich countries in Western Europe at the bottom end, and the rankings on the two dimensions are roughly equal. The country pattern is even easier to see in Figure 3.2, which displays the data from Table 3.1 in a graph.

Health and happiness

57

In addition, the location of each country in the country classification is marked. The figure reveals a pattern in which East European countries are clustered to the upper right, whereas most West European countries cluster in the lower right corner, and with the South European countries somewhat in the middle. Within the cluster of the West European countries, the small rich countries, which include all the Nordic ones, have the best location with very low scores on both poor health and unhappiness. The unfavourable location of Ukraine at the upper right corner shows that they far exceed all other countries in morbidity as measured by self-reported poor health and unhappiness. Finally, the graph indicates the presence of a close, almost linear relationship between unhappiness and poor health at the country level. We will return to this aspect in the multilevel analysis. A Multivariate Multilevel Analysis of Poor Health and Unhappiness Table 3.2 provides an overview of the individual level (within-country) and country level variation in poor health and unhappiness, and the correlations between the two outcomes at the individual and the country level for five different models. Model 1 contains only the basic demographic variables age and sex. The main purpose of this model is to split the variance in the two outcome variables into within- and between-country components. These variance components are compared with the corresponding quantities in the remaining models to calculate the explained variance at the two levels. Model 1 shows that there is more variation between countries in unhappiness (0.735) than in poor health (0.412). The intra-class correlation (ICC) is a standardized measure of the proportion of variance in the dependent variables that is a result of variation among the countries. The ICC of poor health, which is calculated as the ratio of the random country variance (i.e. in the intercept) to the total variance (ICC0.412 / 0.412 3.29), is 0.111, and the ICC of unhappiness is 0.183. Therefore roughly 11 per cent of the variation in poor health and 18 per cent of the variation in unhappiness are a result of differences among the countries. The corresponding between-country variance component in model 2 is corrected for all individual level variables. The ICCs dropped to 0.077 for poor health and to 0.114 for unhappiness. In other words, about a third of the between-country variations in poor health may have their explanation in compositional effects. For unhappiness the compositional effect of the individual level variables explains even more of the between-country variation. In model 3 the detailed country level variables are added: GDP per capita, total health expenditure per capita, and the natural logarithm of the country population. This increases the explained percentages of the

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Nordic social attitudes in a European perspective

Table 3.2 Variance components from a multilevel regression analysis of poor health and unhappiness in Europe (N 72870)a Model 1 Model 2 Model 3 Model 4 Model 5 Poor general health Individual level variance (Se)b Between-country variance (Su) Explained between-country variance Intra-class correlationc Unhappiness Individual level variance (Se) b Between-country variance (Su) Explained between-country variance Intra-class correlation (ICC)c

3.289 .412 .000

3.289 .276 .330

3.289 .147 .643

3.289 .200 .515

3.289 .196 .524

.111

.077

.043

.057

.056

3.289 .735 .000

3.289 .422 .426

3.289 .175 .762

3.289 .146 .801

3.289 .233 .683

.183

.114

.051

.043

.066

.121 .704

.122 .373

.121 .556

Correlations between poor health and unhappiness at: Individual level .168 .122 Country level .820 .608

Notes: a Model 1: age and sex, Model 2: full individual model, Model 3: M2 country variables  HDI, Model 4: M2 HDI, Model 5: M2  country classification. b Individual level variance set to 2 / 3  3.29. c The intra-class correlation (ICC) shows the proportion of the total variance in the outcome variables that is a result of differences between the countries.

between-country variations in poor health and unhappiness to 64 and 76 per cent, respectively. Model 4 and model 5 are alternatives to model 3 and substitute the country level explanatory variables with only the HDI in model 4 and the country classification in model 5. For poor health, none of the alternative models surpass model 3 in explanatory power, but for unhappiness, models 4 and 5 do very well. The zero order correlations between the outcomes of poor health and unhappiness are 0.20 and 0.83 at the individual level and the country level, respectively. Although these correlations fall in the following models, they stay positive. This relationship shows that persons who report poor health also tend to report being unhappy. The much stronger country level correlation is consistent with Subramanian et al. (2005). The detailed results for models 3–5 are presented in Table 3.3. The bulk of the table shows the results for model 3, because the coefficients for the individual level variables are almost identical in the three models. The last lines in the table shows the result when the country characteristics in

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Health and happiness

Table 3.3 A multilevel analysis of poor health and unhappiness in Europe, regression coefficients from model 3, plus additional coefficients for the country level variables in models 4–5 (N72870)a Variables

Poor health OR

Unhappy OR

Regression constant (intercept) Age centred (age  mean age) Age centred, squared Female Years of full-time education Social class (EGP) No registered class Manual workers Routine non-manual Service class (reference category) Household income in quartiles No income or unknown Quartile 1 Quartile 2 Quartile 3 Quartile 4 (reference category) Household income is insufficient Marital status in four categories Single Divorced Widowed Married (reference category) Weak social support

.079* 1.054 *** .999 *** 1.180 *** .924 ***

.059 ** 1.011 *** .999 *** .931 ** .962 ***

1.143 * 1.139 ** .899 * 1.000

1.120 * 1.228 *** 1.138 *** 1.000

.973 1.155 ** .958 .737 *** 1.000 2.550 ***

1.197 *** 1.205 *** 1.000 .826 *** 1.000 2.846 ***

1.191 *** 1.319 *** 1.480 *** 1.000 1.633 ***

2.306 *** 2.434 *** 2.106 *** 1.000 1.939 ***

Natural log of population size Gross domestic product per capita Total health expenditure per capita Human development index*100b Country classificationc Eastern Europe (CZ, EE, HU, PL, SI, SK, UA) Southern Europe (ES, GR, IT, PT) Anglo-Saxon countries (IE, GB) Continental countries (AT, BE, CH, DE, FR, LU, NL) Nordic (DK, FI, IS, NO, SE) (reference category)

1.024 1.015 .703 * .993 ***

1.121 1.021 .510 *** .987 ***

1.854** .835 1.064

4.015 *** 1.949 ** 2.210 ***

.739

1.626

1.000

1.000

Notes: a OR: odds ratio, exp(B), the exponential of the regression coefficients in the log odds (logit) scale. The statistical significance of the regression coefficients is indicated by asterisks: * p .05, ** p.01, *** p .001. b Coefficients for HDI from model 4. c Coefficients for country classification from model 5. c AT Austria; BEBelgium; CH  Switzerland; CZ  Czech Republic; DE Germany; DK  Denmark; EE  Estonia; ES Spain; FI Finland; FR  France; GBUnited Kingdom; GR  Greece; HU Hungary; IE Ireland; IS Iceland; IT Italy; LU Luxembourg; NL Netherlands; NO Norway; PL Poland; PT Portugal; SE Sweden; SI Slovenia; SK Slovakia; UA  Ukraine.

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model 3 are all replaced by the Human Development Index (HDI) in model 4, and by the country classification in model 5. All the explanatory individual level variables are assumed to have the same effect across countries, whereas the intercepts are allowed to vary among the countries. Starting with the basic demographic variables, there is a significant curvilinear association between age and poor health, and between age and unhappiness. Not surprisingly, age has a stronger effect on health compared to happiness (ORPH 1.05 vs. ORUH 1.01). Furthermore, the table shows that women more often report poor health than men (ORPH 1.18), but seem to be happier (ORUH 0.93). Years of education are negatively related to poor health and unhappiness; that is, people with low education have higher odds of being unhealthy and unhappy than more educated people. Social class position is also crucial for people’s health and happiness in Europe. People belonging to the service class seem to have better chances of staying happy and healthy compared to members of the working classes (ORPH 1.14, ORUH 1.23). However, the routine non-manual class actually does somewhat better in terms of health than the service class, whereas the expected advantage of the latter class shows up in happiness. Two sets of variables were introduced to explain differences in health and happiness by income. Our results suggest that the subjective feeling of the income being insufficient (ORPH 2.55, ORUH 2.85) is by far a stronger predictor than reported household income. The results for the latter are mostly weak and unsystematic. What about the effects of social support? Table 3.3 shows that marital status is a very strong predictor of unhappiness. Married people are far happier compared to those never married (ORUH 2.31), the divorced (ORUH  2.43) and the widowed (ORUH 2.11). It may come as a surprise for some that the never married have a higher odds ratio of being unhappy than divorced and widowed people. However, the situation for never married persons appears better with regard to the subjective feeling of health. Married people feel healthier than the never married (ORPH 1.19), the divorced (ORPH 1.32) and the widowed people (ORPH 1.48). In sum, some health differences may be explained by variation in marital status, but happiness is even more closely related to the marital status of Europeans. The last explanatory variable at the individual level is the social network variable. Table 3.3 shows that persons with a weak social network have significantly higher odds of having poor health (ORPH 1.63) and of being unhappy (ORUH 1.94). The last three variables in model 3 are the country characteristics. Neither population size nor GDP per capita seem to have any effect on poor health and unhappiness. However, total health expenditure per capita has

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strong effects on both outcome variables. In countries that are the top spenders, the odds on having poor health are about 70 per cent lower than in the countries with the lowest health expenditures per capita; for unhappiness the effect is even stronger. In model 4, the Human Development Index shows very strong relationships with both poor health and unhappiness. To illustrate this, the odds of having poor health in a country with a maximum HDI score is 71 per cent lower than in a country with a minimum HDI score; for unhappiness the odds are 90 per cent lower. In model 5, the country classification constitutes an alternative way of explaining the variation between the countries. Inhabitants in the Nordic countries (the reference category) are healthier than people living in Eastern Europe (ORPH 1.85). The odds ratios of Continental (ORPH  0.74) and Southern countries (ORPH 0.84) are below 1.0, which indicates that people in these countries are even healthier than people in the Nordic countries when all individual level variables are taken into account. The country classification seems to be even more relevant as an explanation of the differences in unhappiness among nations. People in the Southern European countries (ORPH 1.95), the Anglo-Saxon (ORPH 2.21) and the Eastern European countries (ORPH 4.02) report that they are unhappy more often than people in the Nordic countries. The latter figure indicates that the odds of unhappiness being reported are four times higher in the East European countries than in the Nordic countries. There is, however, no significant difference in happiness between people who live in the Nordic and the Continental countries.

DISCUSSION In this chapter we have presented European evidence on the relationship between socio-economic inequalities in poor health and unhappiness at the individual level. The main findings are the following: poor health and unhappiness are related to both demographic and socio-economic indicators in Europe. Men felt healthier than women, but were less happy. Having a low level of education, belonging to a lower social class, feeling that one’s income is insufficient, not being married, and lacking a strong social network, were all positively and significantly related to poor health and unhappiness. With the exception of age and social class position, all individual factors were more strongly related to unhappiness than to poor health. Marital status seemed to be a very strong determinant of unhappiness. Let us now take a closer look at the findings with respect to the aggregate level. The national outcomes concerning poor health seem to be

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closely related to those of unhappiness. This may be illustrated by the correlation between the dependent variables. The country level correlation between self-reported general poor health and self-rated unhappiness in the full individual model was 0.61, whereas the individual level correlation of the two variables was found to be 0.12. The same measures were 0.76 and 0.16 between American communities and individuals in the study of Subramanian et al. (2005). This may indicate that health and happiness, after controlling for demographic and socio-economic factors, are more closely related to each other within American communities than across European countries. It should not surprise anyone that communities within the same country are more uniform than different European countries, but this could also indicate that there is more cultural variation in Europe when it comes to defining subjective health and happiness. Let us now conclude by answering our three main research questions. The rich and mostly small countries of Western Europe, which includes the Nordic ones, enjoy the most favourable positions on both health and happiness. Furthermore, the inequalities in general health and happiness largely confirm earlier research that people with higher socio-economic status and good social support are in better health and happier than others. Finally, our study indicates that about a third of the between-country differences in poor health and unhappiness may be explained by compositional effects and about another third may be explained by the country level characteristics.

NOTES 1. Regarding the estimation procedure, a second order PQL (penalized quasi-likelihood) procedure was applied for all models using MLwiN (see the Appendix for more detailed information about multilevel models). 2. The exact question wording is: ‘Using this card, how often do you meet socially with friends, relatives or work colleagues?’ 3. Both these variables take into account country differences in the relative purchasing power by using purchasing power parities (PPP).

REFERENCES Andrews, F.M. and S.B. Withey (1976), Social Indicators of Well-being, New York: Plenum Press. Arthaud-Day, M.L. and J.P. Near (2005), ‘The wealth of nations and the happiness of nations: Why “accounting” matters’, Social Indicators Research, 74 (3), 511–48.

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Arts, W. and J. Gelissen (2002), ‘Three worlds of welfare capitalism or more? A state-of-the-art report’, Journal of European Social Policy, 12 (2), 137–58. Bartley, M. (2004), Health Inequality: An Introduction to Theories, Concepts and Methods, Cambridge: Polity Press. Campbell, A., P.E. Converse and W.L. Rodgers (1976), The Quality of American Life: Perceptions, Evaluations, and Satisfactions, New York: Russell Sage Foundation. Cassel, J. (1976), ‘Contribution of social-environment to host-resistance’, 4th Wade Hampton Frost Lecture, American Journal of Epidemiology, 104 (2), 107–23. Cobb, S. (1976), ‘Social support as a moderator of life stress’, Psychosomatic Medicine, 38 (5), 300–314. Diener, E. and R. Biswas-Diener (2002), ‘Will money increase subjective wellbeing?’, Social Indicators Research, 57 (2), 119–69. Diener, E., S. Oishi and R.E. Lucas (2003), ‘Personality, culture, and subjective wellbeing: Emotional and cognitive evaluations of life’, Annual Review of Psychology, 54, 403–25. Diener, E., E. Sandvik, L. Seidlitz and M. Diener (1993), ‘The relationship between income and subjective well-being – relative or absolute’, ‘Social Indicators Research, 28 (3), 195–223. Diener, E., E.M. Suh, R.E. Lucas and H.L. Smith (1999), ‘Subjective well-being: Three decades of progress’, Psychological Bulletin, 125 (2), 276–302. Erikson, R. and J.H. Goldthorpe (1992), The Constant Flux, Oxford: Clarendon Press. Glass, T.A., C. Mendes de Leon, R.A. Marottoli and L.F. Berkman (1999), ‘Population based study of social and productive activities as predictors of survival among elderly Americans’, British Medical Journal, 319 (7217), 478–483. Granovetter, M. (1973), ‘Strength of weak ties’, American Journal of Sociology, 78 (6), 1360–80. Heistaro, S., P. Jousilahti, E. Lahelma, E. Vartiainen and P. Puska (2001), ‘Self rated health and mortality: A long term prospective study in eastern Finland’, Journal of Epidemiology and Community Health, 55 (4), 227–32. Idler, E.L. and Y. Benyamini (1997), ‘Self-rated health and mortality: A review of twenty-seven community studies’, Journal of Health and Social Behavior, 38 (1), 21–37. Jylhä, M., J.M. Guralnik, L. Ferrucci, J. Jokela and E. Heikkinen (1998), ‘Is selfrated health comparable across cultures and genders?’, Journals of Gerontology Series B – Psychological Sciences and Social Sciences, 53 (3), S144–S152. Kunst, A.E., V. Bos, E. Lahelma, M. Bartley, I. Lissau, E. Regidor et al. (2005), ‘Trends in socioeconomic inequalities in self-assessed health in 10 European countries’, International Journal of Epidemiology, 34 (2), 295–305. Mackenbach, J. (2005), Health Inequalities: Europe in Profile, An independent, expert report commissioned by, and published under the auspices of, UK Presidency of the EU. Pinquart, M. and S. Sorensen (2000), ‘Influences of socioeconomic status, social network, and competence on subjective well-being in later life: A meta-analysis’, Psychology and Aging, 15 (2), 187–224. Salomon, J.A., A. Tandon and C.J.L. Murray (2004), ‘Comparability of self rated health: Cross sectional multi-country survey using anchoring vignettes’, British Medical Journal, 328 (7434), 258–61. Schwarz, N. and F. Strack (1991), ‘Evaluating one’s life: A judgment model of

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subjective well-being’, in F. Strack, M. Argyle and N. Schwarz (eds), Subjective Well-being: An Interdisciplinary Perspective, Oxford: Pergamon Press, pp. 27–48. Subramanian, S.V., D. Kim and I. Kawachi (2005), ‘Covariation in the socioeconomic determinants of self rated health and happiness: A multivariate multilevel analysis of individuals and communities in the USA’, Journal of Epidemiology and Community Health, 59 (8), 664–9.

4.

Social capital Torben Fridberg and Olli Kangas

INTRODUCTION It is argued that each scientific generation invents the wheel anew. The debate revolving around the concept of social capital is not an exception to this rule. According to Robert Putnam (2000, p. 19), the concept of social capital has been invented at least six times during the last decennium. The core of the concept was already sketched in the first usage of the term. In 1916 West Virginian rural educator L.J. Hanifan defined social capital to pertain to good will, fellowship, sympathy and social intercourse among the individuals and families who make up a social unit . . . The individual is helpless socially, if left to himself . . . If he comes into contact with his neighbor, and they with other neighbors, there will be an accumulation of social capital, which may immediately satisfy his social needs and which may bear a social potentiality sufficient to the substantial improvement of living conditions in the whole community. (quoted from Putnam 2000, p. 19)

Since Hanifan’s writings a large amount of printing ink has been used to debate the real meaning of social capital and what the concept is good for. The importance of social capital for economic development and democracy has become widely acknowledged by social scientists of all kinds. Economists, sociologists and political scientists have all taken an interest in this concept, but not that many new ideas have been added since then. The quotation includes all the central elements that have been used in subsequent academic debates. First, there is an emphasis on social networks that will enhance life satisfaction for persons involved in those networks. Second, there are spill-over effects, or ‘externalities’ that positively affect the whole community. The first aspect relates to the role of social capital as an asset or a set of resources created by the social fabrics that the individual is a part of (Coleman 1990, p. 302). Like other forms of capital, social capital also facilitates the achievement of certain goals that would be unattainable without it. This is what French sociologist Pierre Bourdieu emphasized when he developed his ideas concerning different forms of capital. For Bourdieu (1988), social capital was ‘resources which are linked to possession 65

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of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition – or in other words, to membership in a group’. The membership of voluntary associations and the fabrics of social relationships produced by that membership have been seen to be the most important cornerstones of social capital (Putnam 2000). If the first aspect deals with the benefits individuals attain from their social networks, the second aspect concentrates on the aggregate community level. The spill-over effect means that those societies that are rich in social capital perform in many respects better and more efficiently than societies with lower levels of social capital. However, a number of qualifications suffice. Social capital and social ties can be used in malevolent ways that are detrimental for the functioning of the whole society. In the opening paragraphs of his Bowling Alone Robert Putnam (2000, p. 22) makes an important distinction that forms the overarching theme for the project proposed here. According to Putnam, there are two dimensions of social capital: bridging or inclusive and bonding or exclusive social capital (see Granovetter’s, 1973, ‘weak’ and ‘strong’ ties). The bridging form of social capital generates broader identities and brings larger sections of society together by unifying them by weak ties, whereas bonding social capital pertains to specific, group-based solidarity. The bonding form of social capital generates strong ties. However, because of its intra-group solidarity, it may create strong out-group antagonism. Therefore, there is a danger that excluding social capital turns out to be antisocial and detrimental for society as a whole. The notion has important ramifications for social policy making. In this chapter we compare the levels of social capital in European countries with a special emphasis on the effects of the various types of welfare states and social policies. Social policy is not only a distributional issue: who gets what and how much. The institutional set-ups of social policy programmes unify and divide people and social groups. Throughout its history social policy has had bridging and bonding functions. In some countries, such as the Nordic countries, the emphasis has been on the bridging side: the basic principle has been universalism expressed in people’s insurance. When it comes to the legitimacy of social policy, the universal schemes are extremely popular (e.g. Svallfors 1997; Ervasti and Kangas 1995; Kangas 1997). In many other countries (and especially so in Central Europe, Asia and Africa) the schemes have been based on membership of a certain occupational group or category of people. These schemes have relied on bonding social capital and, consequently, they have created strong intra-group interests. A rapid glance over the initial phase of European social policy illuminates the point. The early social insurance funds were often an organizational part of the activities of the emerging labour movement: the funds promoted the recruitment of new members for the trade unions.

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67

Thus, the sickness benefit system, which was based on the activity of unions, contributed to the formation of the working class and strengthened class solidarity among the workers (see e.g. Ritter 1986, pp. 71–82). Similarly, the so-called Ghent unemployment insurance system, which was run by trade unions, was decisive for the evolution of strong labour unions in Denmark, Finland and Sweden (Rothstein 1998). In some countries, and notably so in the Anglo-Saxon world, means testing has conditioned the eligibility. Here the formation of social bonds has been more diffuse and because of the fuzziness of the client groups no interest formation takes place among the clients. As a rule, the overall legitimacy of means-tested schemes is low (see e.g. Korpi 1980; Kangas 1995). Therefore, means testing creates neither bridging nor bonding social capital. Our starting point is that by forcing people together the institutional structure of social policy creates possibilities for social networks, which, in turn, increases trust and reciprocity (Szreter 2002). Thus, these structural factors are essential for creating and maintaining the legitimacy of social institutions. Moreover, they are crucial for collective actors and collective actions to build up, defend and reform the schemes. This leads us to the question of trust, which is an additional element of social capital theories. Memberships of various networks create and fortify norms of reciprocity. Whether the reciprocity is expanded to the aggregate level – to generalized trust in people and society at large – depends on the degree of bridging and bonding social capital and the balance between them (see Putnam 2000, p. 23; Cook 2001; Olson 1965). On the basis of the reasoning above, we can draw up some tentative hypotheses to test in the empirical part of our chapter. First, as engagement in voluntary organizations is seen as a major part of social capital, we first look at the prevalence of various social networks in different European societies. Here we have two competing hypotheses. On the one hand it has been argued that the comprehensive Scandinavian type of welfare state tends to squeeze out the importance of social networks: associations and families and friends. The powerful from-cradle-to-grave welfare state takes care of everything and individuals are lulled into believing that the state does everything. The custodial state penetrates into the intimate lives of individuals and eats up and hollows out their private projects. Private social ties are replaced by public ties. On a more concrete level this means that when the realm of state responsibility is wide there is no room or need for voluntary associations. In the light of this kind of theorizing we could expect that the membership of voluntary associations would be lower in the Scandinavian type big welfare states (H1). A number of empirical studies have presented results that fortify this kind of reasoning and conclude that ‘people living in social-democratic welfare state regimes, with their

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tendency to collectivize care, have the lowest level of social capital as compared to other regimes’ (Scheepers et al. 2002, p. 204). On the other hand, based on the old Aristotelian (or republican) idea of the state being more of a platform for individual actions than a suppressive force, we could expect that large, universal welfare states would enhance higher degrees of civil activism. This is precisely what Simon Szreter (2002, p. 613) argues in his criticism of Putnam: ‘social capital far from being an alternative to the state and to government activity, is symbiotically related to it’. Indeed, some previous studies (e.g. Rothstein 1998; Kumlin and Rothstein 2005; Larsen 2007) seem to provide some qualified support for this argument. The Scandinavian countries score highly on most of the indicators used for social capital. Given the high degree of universalism in the Nordic welfare states we can suppose that the level of bridging social capital and consequently the level of generalized trust would be higher in the Nordic hemisphere than in countries that build their social policy systems on a narrower group membership, which is based on meanstesting. Thus, our hypothesis (H2) is that the generalized form of social trust is higher in Scandinavia than in other countries. The concept of social capital is a multidimensional concept, and the dimensions do not necessarily correlate well with each other. Therefore, it is not easy to operate with aggregated measures of social capital, but the dimensions should be analysed separately. In this study we focus solely on the engagement with voluntary organizations and social trust. As in the other chapters in this volume, we look at the issue from a Nordic viewpoint in order to see how the Scandinavian countries are positioned in relation to voluntary organizations and generalized trust in comparison with other European countries.

DATA ON SOCIAL CAPITAL AND METHODS APPLIED In accordance with the literature, we would expect the Nordic countries to score highly on all the indicators, and expect the Nordic countries to be very much alike on these dimensions. The aim of the chapter is, first, to see if this is the case and, second, to approach the puzzle, which still seems to be why this is the situation. Is it because of the individual level characteristics like education, labour market affiliation, family, basic value orientations and religious sentiments, or are national differences to be explained by country level variables like the wealth of the countries or the level of social security welfare state provisions. Therefore, both individual level and country level variables are included in the analyses.

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69

In the European Social Survey (ESS) there are a number of questions that are directly related to various aspects of social capital. In the first wave of ESS from 2002 there are batteries on voluntary work and civil society indicators. The first battery refers to membership in voluntary associations during the last 12 months. The exact forms of the questions were as follows: R1 E1–E12: For each of the voluntary organizations I will now mention, please use this card to tell me whether any of these things apply to you now or in the last 12 months, and, if so, which.

For each organization the respondent was asked to say if he or she (1) was a member, (2) participated in activities, (3) donated money, (4) did voluntary work, and (5) had personal friends in the organization. On the basis of that information it is possible not only to evaluate the membership rates in voluntary associations, but also to depict the activity rates. There are three questions that usually have been used as proxies for generalized trust: 1. 2. 3.

Most people can be trusted, or you can’t be too careful. Most people try to take advantage of you, or try to be fair. Most of the time people are helpful, or are mostly looking out for themselves.

The respondent could react on these arguments on a scale varying from 0 to 10, the lowest value representing a lack of trust and the highest value indicating the highest level of generalized trust. For space reasons we collapse these three variables into one single indicator of trust. This is warranted as in our factor analyses the three variables produced one factor with relatively high factor loadings (.835, .849, and .790, respectively) and the Cronbach’s alpha was satisfactorily high (.76), which indicates that the three variables represent the same underlying dimension of trust. We include the national means separately for the three variables in Table 4.5 below just to show how countries or groups of countries differ from each other. However, we do not present separate multivariate analyses for them but operate on the merged ‘generalized trust’ indicator.

MEMBERSHIP OF ASSOCIATIONS AND VOLUNTARY WORK In Table 4.1 we first depict country-wise percentages of people who are members of voluntary organizations, and means for the number of organizations the respondents are attached to. As can be seen in the table,

70

92 90 84 84

78 76 75

71 71 70

Luxembourg Finland Austria

Belgium Germany United Kingdom

Member of some voluntary organization

Denmark Sweden Netherlands Norway

Country

Belgium Germany United Kingdom

Austria Luxembourg Ireland

Sweden Denmark Norway Netherlands

Country

1.6 1.6 1.6

2.1 1.9 1.6

2.5 2.5 2.4 2.2

Member in number of categories. Mean

Germany Belgium United Kingdom France Slovenia Ireland

Norway Sweden Netherlands Denmark

Country

19 19 16

26 23 23

37 35 29 28

Voluntary work in some voluntary organization

Ireland Slovenia Belgium

Netherlands Sweden Norway United Kingdom Austria Germany Denmark

Country

Table 4.1 Activities in voluntary organizations: percentage of population aged 15, 2002/03

32 32 26

38 34 34

44 44 41 40

Donated money to some voluntary organization

71

68 55 52 50 36 35 29 27 25 21

Finland Israel France Slovenia Spain Italy Portugal Hungary Greece Poland

1.6 1.2 1.0 0.9 0.7 0.6 0.5 0.4 0.4 0.3

Luxembourg Austria Finland Hungary Israel Spain Greece Portugal Italy Poland

15 14 12 9 8 7 6 6 5 5

France Finland Luxembourg Portugal Spain Israel Italy Poland Greece Hungary

23 19 19 16 15 13 12 12 9 6

Source:

ESS 2002/3.

Note: Activities within the last 12 months were asked for in 12 categories of voluntary organizations: sports clubs, cultural or hobby org., trade union, business or professional org., consumer/automobile humanitarian or human rights, environment or peace, religious/church, science or education, social clubs, other. Comparable data are missing from Switzerland and the Czech Republic.

Ireland Israel Slovenia France Spain Italy Portugal Hungary Greece Poland

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the activities of the population in voluntary organizations show a difference between Northern Europe versus Southern Europe and postcommunist countries. The largest proportions of the population who have been members of some voluntary organization within the last 12 months, are found in Denmark, Sweden, Norway and The Netherlands followed by Luxembourg, Finland and Austria. The smallest proportions are found in Spain, Italy, Portugal, Hungary, Greece and Poland. Almost the same pattern appears when you look at the mean number of different categories of voluntary organizations where respondents are members. Again Sweden, Denmark, Norway and The Netherlands are at the top followed by Austria and Luxembourg. Here Finland is to be found in the middle group. Once more we find Poland, Greece, Hungary, Portugal, Italy and Spain with the smallest mean number of membership categories. In all the four Nordic countries the highest proportions of memberships are in trade unions. This contributes to a high mean number of categories of memberships, but for most it is a rather passive membership. It is one thing just to be a member of various organizations and another to actively contribute in the functions of associations. In order to map the degree of activity people have in their organizations, separate columns for organizational activity rates in terms of voluntary work done and money donated are constructed. When it comes to the proportion of the population doing voluntary work for some of the organizations, the largest proportions are to be found in Norway and Sweden, followed by The Netherlands, Denmark and Germany. Finland is to be found in the lower end of this ranking. The smallest proportions doing voluntary work are found in Poland, Italy, Portugal and Greece. The largest proportions doing voluntary work do it in sports clubs. This is the case for most countries – only at different levels. In Norway it was 18 per cent of the population, in Sweden 17 per cent, in Denmark 13 per cent and in Finland only 4 per cent. In addition voluntary organizations that aim at cultural and hobby activities attract high proportions doing voluntary work in Norway, Sweden and Denmark. Actually, the proportions within each of the categories of voluntary organizations are very much alike in these three countries, but leave Finland as an outsider, where the population is less inclined to work for voluntary organizations. Rather a similar pattern emerges if we look at the proportion of people donating money to voluntary organizations. As far as this question is concerned, The Netherlands and Sweden top the league, closely followed by Norway and the United Kingdom. Denmark and Finland are lagging behind their Nordic neighbours. Even in this dimension the Southern European and post-socialist countries show the lowest degrees of involvement, whereas the Central European countries fall in-between.

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MULTILEVEL ANALYSES OF ACTIVITIES AROUND VOLUNTARY ORGANIZATIONS In order to analyse the relative merit of individual level aspects vis-à-vis welfare state impacts on the results presented above, we carry out a number of multivariate analyses. We are mainly interested in the distinctiveness of different welfare regimes as defined in Table 4.4 and 4.5 (‘country classifications’), a number of country specific variables (the size of population – small countries we expected to display more social capital – and the degree of human development – we suppose that the higher the index value is, the higher the degree of social capital) and the role played by a selection of individual level variables such as age, gender, living with children, educational attainment, labour market status and hours employed. In order to map the impact of attitudes, variables pertaining to opinions were included in the analyses. The dependent variables are (1) membership in some voluntary organization within the last 12 months, (2) number of the 12 categories of voluntary organizations of which the respondents have a membership, (3) voluntary work in some voluntary organization, and (4) have donated money to some voluntary organization within the last 12 months. The multilevel analyses are presented in Table 4.2, which shows the variance components in four models for each of the four dependent variables. Model 0 has no explanatory variables, but splits the variance in the dependent variables into the within-country component (Se) and the betweencountry component (Su). These components are also the basis for the calculation of the intra-class correlation, which shows the variance in the dependent variables that are attributed to between-country variation. This proportion is 0.24 and 0.22 for the membership variables, but only 0.07 for voluntary work and 0.08 for donated money to some voluntary organization. The two variance components in model 0 may also be seen as estimates of the maximum amount of variation that our model can explain at the individual level and at country level. The amount of variance at the two levels explained by each model is also to be found in Table 4.2. Model 0, the baseline, explains nothing by definition. Model 1 adds the demographic and socio-demographic controls: age, age squared, gender, live with children at home, years of education, in paid work and normal working hours. These variables explain some of the variance at country level. They actually explain between 19 per cent of the within-country variance in voluntary work and 27 per cent of the within-country variance in donated money to a voluntary organization. The socio-demographic variables explain less of the within-country variance. However, for the number of memberships only 9 per cent of the within country variance is explained in this model.

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Table 4.2 Variance components from multilevel regression analyses of voluntary work in Europe Model 0

Model 1

Member of a voluntary organization Su 0.0582 0.04682 Se 0.1849 0.1733 Explained Su 0.195533 Explained Se 0.062737 Interclass correlation 0.239408 2 Log likelihood 42052.3 39015.1

Model 2

Model 3

Model 4

0.04437 0.1658 0.237629 0.103299

0.01258 0.1658 0.783849 0.103299

0.008745 0.1658 0.849742 0.103299

36369.3

36349.3

36351.2

Number of memberships in different categories of voluntary organizations Su 0.5784 0.4339 0.4143 0.1367 0.108 Se 2.0831 1.8951 1.7902 1.7902 1.7902 Explained Su 0.249827 0.283714 0.763658 0.813278 Explained Se 0.09025 0.140608 0.140608 0.140608 Interclass correlation 0.217321  2 Log likelihood 130345.5 124549.1 118883.4 118861.4 118860.2 Voluntary work for voluntary organization Su 0.01013 0.008209 Se 0.1368 0.1361 Explained Su 0.189635 Explained Se 0.005117 Interclass correlation 0.068944  2 Log likelihood 31052 30361.4 Donated money to voluntary organization Su 0.01552 0.01134 Se 0.181 0.1762 Explained Su 0.26933 Explained Se 0.026519 Interclass correlation 0.078974  2 Log likelihood 41247 39596.3

0.009157 0.1333 0.096051 0.025585

0.006894 0.1333 0.319447 0.025585

0.00518 0.1333 0.488648 0.025585

28764.5

28763.3

28767.4

0.01131 0.1737 0.271263 0.040331

0.007719 0.1737 0.502642 0.040331

0.007869 0.1737 0.492977 0.040331

37961.6

37958.4

37966.5

Notes: Su: between-country variance; Se: within-country variance; Explained: proportion of the variance in the null model explained by models 1–4. All variance components are statistically significant at the .01 level. Model 0: only intercept; Model 1: M0  demographic variables; Model 2: M1  attitudinal variables; Model 3: M2  country variables; Model 4: M2  country classification; ESS1 2002: 19 countries.

In model 2, the remaining individual level explanatory variables are added. They include the expressions for an attitudinal or normative background for activities concerning voluntary organizations. These are religiousness, interest in politics, important to be active in voluntary

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organizations and trust in most people. The variables only explain a little more than the socio-demographic variables at both individual and country level. Most is added to an explanation of the number of memberships. In this model 14 per cent of the within-country variance in number of memberships is explained and 28 per cent of the between-country variance. For voluntary work we observe that the explained variance actually turns negative. This may happen in maximum likelihood estimation if the variance component is small at the outset. Therefore, we only conclude that the individual level attitudinal variables explain nothing of the between-country variation in the voluntary work. In model 3, the two macro-variables Human Development Index 1999 and the natural logarithm of the population size 1999 are introduced. They increase the amount of explained between-country variation to 78 per cent for membership, 76 per cent for the number of memberships, 32 per cent for voluntary work and 50 per cent for donating money to a voluntary organization. Model 4 is an alternative to model 3. Here the two macro-variables are replaced by the country classification. For the two membership expressions the country classification does a little better in terms of explanatory power than the macro-variables in model 3. For voluntary work, however, the country classification model explains about 49 per cent of the betweencountry variance as compared to 32 per cent by model 3. For donating money the two macro models perform about equally well explaining about 50 per cent of the between-country variance. The results for model 3 are the basis for Tables 4.3 and 4.4. The results for the country classification from model 4 are presented as an additional section at the bottom of the tables. Tables 4.3 and 4.4 present the fixed regression coefficients for the four analyses of dependent variables. The results for model 3 are listed in the tables. The results for the country classification from model 4 are presented as an additional section at the bottom of the tables. For the individual variables the coefficients are almost identical in the two models. Membership, number of memberships, voluntary work and donating money all show a curvilinear relationship to age, with the age groups in the middle being most active in relation to voluntary organizations. For voluntary work the proportion peaks for the age groups between 40 and 59. Men show higher levels than women on all the activities except donating money. Furthermore, persons with children under 18 years of age living at home show higher levels of this kind of social capital than persons without children. The degree of social capital seems to increase with years of education completed, but the effect is not very strong. When it comes to the number of memberships of different categories of voluntary organizations, the results show that these are

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Table 4.3 Multilevel analyses of membership in voluntary organizations: fixed regression coefficients from model 3 Description

Member of a voluntary organization B

p

Number of memberships in different categories B

p

Regression constant 3.560 Age in years 0.004 Age in years squared 0.000 Gender, 1  male, 0  female 0.062 Living with children at home below 18 years 0.000 Years of full time education 0.013 In paid work last 7 days 0.087 Total hours normally worked in main job/week 0.000

0.001 11.712 0.000 0.032 0.000 0.000 0.000 0.186 0.949 0.062 0.000 0.068 0.000 0.260 0.736 0.000

0.001 0.000 0.000 0.000 0.001 0.000 0.000 0.554

How religious are you, 0  not at all How interested in politics, 1  very interested Important to be active in volunt. org., 0  unimportant Most people can be trusted/can’t be too careful

0.005 0.047 0.024

0.000 0.000 0.000

0.000 0.000 0.000

Natural logarithm of total population 1999 Human development index 1999 Country classification Continental (AT, BE, DE, FR, LU, NL) Nordic (DK, FI, NO, SE) Anglo-Saxon (IE, GB) Southern (ES, GR, IT, PT) Eastern (HU, PL, SI) – (reference category)

0.031 0.197 0.098

0.010

0.000

0.036

0.000

0.046 4.959

0.033 0.000

0.147 14.596

0.038 0.000

0.335 0.457 0.308 0.012 0.000

0.000 0.000 0.002 0.865

1.028 1.443 0.868 0.063 0.000

0.000 0.000 0.010 0.805

Note: Coefficients for country classification from model 4.

higher among persons in work than among persons out of work, but slight effects of being in work are found for all the voluntary organization variables. In addition, for the attitudinal variables there are systematic impacts on activities concerning voluntary organizations. We find a slight increase in voluntary activities with religiousness, but a negative effect of political interest except for being a member. The highest coefficients are found for the attitude that it is important to be active in voluntary work. However, as expected, social trust has a positive effect. Finally, the two last sections in Tables 4.4 and 4.5 show the results for the country level variables in models 3 and 4. As expected, population size is

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Table 4.4 Multilevel analyses of voluntary work in voluntary organizations, and donated money: fixed regression coefficients from model 3 Description

Voluntary work in a voluntary organization B

p

Donated money to a voluntary organization B

p

Regression constant 1.577 Age in years 0.003 Age in years squared 0.000 Gender, 1  male, 0  female 0.029 Living with children at home below 18 years 0.013 Years of full time education 0.006 In paid work last 7 days 0.015 Total hours normally worked in main job/week 0.000

0.019 1.905 0.000 0.002 0.000 0.000 0.000 0.016 0.008 0.007 0.000 0.013 0.003 0.047 0.546 0.000

0.009 0.001 0.260 0.001 0.019 0.000 0.000 0.000

How religious are you, 0  not at all 0.008 How interested in politics, 1  very interested 0.026 Important to be active in volunt. org., 0.022 0  unimportant Most people can be trusted/can’t be too careful 0.007

0.000 0.000 0.000

0.000 0.000 0.000

0.000

0.010

0.000

0.001 1.641

0.952 0.013

0.001 1.994

0.956 0.006

0.076 0.135 0.059 0.065 0.000

0.155 0.116 0.025 0.129 0.380 0.156 0.256 0.028 0.000

0.082 0.075 0.071 0.681

Natural logarithm of total population 1999 Human development index 1999 Country classification: Continental (AT, BE, DE, FR, LU, NL) Nordic (DK, FI, NO, SE) Anglo-Saxon (IE, GB) Southern (ES, GR, IT, PT) Eastern (HU, PL, SI) – (reference category)

0.011 0.043 0.014

Note: Coefficients for country classification from model 4.

negatively related to all the activities. As a rule, the activity rates are higher in smaller states. The Human Development Index (HDI) is positively related to all the activities and all are statistically significant. The strongest relationship is with the number of memberships. It is somewhat difficult to interpret the meaning of the HDI for social capital, but a number of tentative thoughts can be drawn. As GDP per capita is one of the most important dimensions included in the HDI, one can speculate that in rich countries citizens have more economic resources at their disposal. Therefore, they can be involved in various voluntary activities and financially contribute to their membership organizations.

78

Denmark Norway Finland Sweden Netherlands Switzerland Ireland Luxembourg Austria United Kingdom Spain Israel Belgium Germany Italy France Czech Republic Portugal Hungary Slovenia Poland Greece

Country

6.99 6.60 6.46 6.09 5.71 5.64 5.47 5.18 5.13 5.05 4.89 4.89 4.81 4.67 4.52 4.48 4.29 4.16 4.08 3.98 3.69 3.63

Denmark Norway Finland Sweden Switzerland Netherlands Ireland Germany Austria Belgium France United Kingdom Luxembourg Israel Portugal Spain Czech Republic Slovenia Hungary Italy Poland Greece

Most people Country can be trusted 7.33 6.98 6.88 6.66 6.20 6.19 6.00 5.77 5.62 5.61 5.61 5.56 5.50 5.36 5.27 5.23 5.11 4.68 4.64 4.59 4.53 3.69 Denmark Sweden Norway Ireland Finland United Kingdom Switzerland Netherlands Austria Germany Luxembourg Israel Belgium Spain France Slovenia Hungary Italy Czech Republic Portugal Poland Greece

Most Country people try to be fair

Table 4.5 Social trust: mean scores, population aged 15, 2002/03

6.12 6.01 6.01 5.95 5.68 5.41 5.32 5.26 5.19 4.85 4.54 4.51 4.44 4.40 4.37 4.24 4.16 4.07 3.95 3.91 3.16 3.01

Denmark Norway Finland Sweden Ireland Switzerland Netherlands United Kingdom Austria Germany Luxembourg Belgium Israel Spain France Czech Republic Portugal Italy Slovenia Hungary Poland Greece

People Country mostly try to be helpful

6.81 6.53 6.34 6.25 5.80 5.72 5.72 5.34 5.31 5.10 5.06 4.96 4.92 4.84 4.81 4.48 4.43 4.40 4.31 4.30 3.81 3.45

Generalized trust (average)

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The country classification in the last section presents more detailed results on differences among groups of countries. The reference category for the country classification is the East European countries. With the exception of the group of South European countries, all other coefficients are positive. The coefficient is only positive for the southern group of countries in relation to the number of memberships. This indicates that controlling for all the individual level variables, the South European countries show the lowest level of engagement with voluntary organizations. The Nordic countries score highest on membership, number of memberships and voluntary work, with the Continental and Anglo-Saxon countries somewhat below. However, when it comes to donating money to voluntary organizations the Anglo-Saxon countries are on top, with the Nordic group second.

GENERALIZED TRUST In his influential book, Trust, Francis Fukuyama (1995, p. 7) argues that ‘a nation’s well-being, as well as its ability to compete, is conditioned by a single, pervasive cultural characteristic: the level of trust inherent in society’. A number of later studies have indicated that there is indeed a relationship between trust and economic growth (Knack and Keefer 1997; Whiteley 2000). Be it as it may, with the relationship of trust in society and the nation’s competitiveness and economic performance, Fukuyama’s argument indicates that trust may have important ramifications for economic performance. Furthermore, similar results have been received at a more mundane individual level on the beneficial relationship between trust and personal well-being/happiness (Inglehart 1990; Brehm and Rahn 1997), between trust and health (Hyyppä and Mäki 2001) and trust and possibilities of being employed (Barbieri 2003). As trust seems to bifurcate into various dimensions, it is warranted to take a short look at the levels of trust in different societies. The analyses of consequences fall beyond the scope of this chapter and we concentrate solely on cross-national differences and determinants of generalized trust. When it comes to the various aspects of trust (Table 4.5) the story is very much the same as for voluntary activities. The Nordic countries display the highest degrees of trust in all dimensions and now the Nordic cluster is more homogeneous than it was previously; that is, Finland, which deviated to some extent from its Scandinavian neighbours when it came to voluntary organizations, is for all indicators a member of the Scandinavian group that forms a rather distinct cluster. Again, the Southern European countries, and notably so Greece and Italy, together with post-communist countries (Hungary, Poland and Slovenia) get the lowest scores. The

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Percentage doing voluntary work for voluntary organizations

40 NO SE 30

NL

DE BE 20

SI

DK

UK

FR LU

AT

IE FI

10 GR 0 3.00

PL

3.50

4.00

PT HU IT

IL ES

4.50

5.00

R 2 = 0.5228 5.50

6.00

6.50

7.00

Generalized social trust ESS 2002/03

Note: AT  Austria; BE  Belgium; DE  Germany; DK  Denmark; ES  Spain; FI  Finland; FR  France; GR  Greece; HU  Hungary; IE  Ireland; IL  Israel; IT  Italy; LU  Luxembourg; NL  Netherlands; NO  Norway; PL  Poland; PT  Portugal; SE  Sweden; SI  Slovenia; UK  United Kingdom.

Figure 4.1

Percentage doing voluntary work and social trust (mean)

Central European countries fall once more somewhere in between these two extreme clusters. There is quite a strong correlation (r  .52) between generalized trust and the previously discussed indicators of voluntary associations as shown in Figure 4.1. The most deviant case is Finland, which displays very high trust levels, but a medium-to-low degree of involvement in working for voluntary organizations. The omission of this deviant case would increase the correlation to as high as .65. Therefore, the two dimensions that have usually been linked to social capital fall nicely together and even though they are conceptually different they go firmly hand in hand. As can be seen in Table 4.6 (model 0) the intra-class correlation indicates that the degree of between-country variation is .20. This result is about the same as for the membership variables, but much higher than for working in and donating money to voluntary organizations as displayed previously in Table 4.2. In model 1 we have added demographic variables into the equation and they seem to explain some 10 per cent of the between-country variance, whereas the within-country impact is weaker (3 per cent). The picture is not much changed if the attitudinal dimension is included in model 2. The inclusion of macro-level variables (HDI and the size of the population)

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Table 4.6 Variance components from multilevel regression analyses of social trust

Social trust Su Se Explained Su Explained Se Interclass correlation  2 Log likelihood

Model 0

Model 1

Model 2

Model 3

Model 4

0.7872 3.2461

0.7082 3.1638 0.100356 0.025354

0.705 3.0916 0.104421 0.047596

0.3625 3.0915 0.539507 0.047626

0.1389 3.0915 0.823552 0.047626

163300.6

158254.4

158236.6

158219.8

0.195175 167530.6

Notes: Su: between-country variance; Se: within-country variance; Explained: proportion of the variance in the null model explained by models 1–4. All variance components are statistically significant at the .01 level. Model 0: only intercept; Model 1: M0  demographic variables; Model 2: M1  attitudinal variables; Model 3: M2  country variables; Model 4: M2  country classification; ESS 1R 2002: 21 countries.

considerably improves the accuracy of the model: the explained betweencountry variance increases to 54 per cent. Finally, the replacement of country level macro-variables by welfare regimes raises the explained between-country variation to as high as 82 per cent, which is about the same as with voluntary organizations in Table 4.2. Table 4.7 presents a more nuanced picture of the relative importance of single individual variables in explaining variability in generalized social trust. Age displays a curvilinear pattern; the youngest age groups have the lowest trust levels and the middle-aged the highest. As a rule, women trust more than men and there is an accumulation of educational capital and social capital; those with the highest educational attainments procuring the highest degrees of trust. There is also a significant association between employment and trust. All attitudinal variables are statistically highly significant, and interestingly enough, the appetite for politics seems to decrease beliefs in trustworthiness. The size of the population does not play a significant role whereas the other country level variable is significant: the higher the HDI, the higher the generalized trust. Finally, only the Nordic welfare state positively deviates from the reference category of the Eastern European low-trust group, which suggests that the degree of belonging to a certain type of welfare model does affect the creation of various forms of social capital.

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Table 4.7 Multilevel analyses of social trust: fixed regression coefficients from model 4 Description

Social trust B

p

Regression constant Age in years Age in years squared Gender, 1  male, 0  female Living with children at home below 18 years Years of full time education In paid work last 7 days Total hours normally worked in main job /week

4.630 0.030 0.000 0.083 0.036 0.052 0.145 0.003

0.000 0.000 0.000 0.000 0.099 0.000 0.000 0.000

How religious are you, 0  not at all How interested in politics, 1  very interested Important to be active in volunt. org., 0  unimportant

0.023 0.158 0.048

0.000 0.000 0.000

Natural logarithm of total population 1999 Human development index 1999

0.127 4.959

0.239 0.000

Country classification: Continental (AT, BE, DE, FR, LU, NL) Nordic (DK, FI, NO, SE) Anglo-Saxon (IE, GB) Southern (ES, GR, IT, PT) Eastern (HU, PL, SI) – (reference category)

0.550 1.778 0.867 0.305 0.373

0.188 0.001 0.077 0.478 0.387

Note: Coefficients for country level variables Lnpop 99 and HD199 from model 3.

DISCUSSION The main purpose of this chapter has been to examine country differences in the levels of various forms of social capital, or more specifically, the degrees of engagement in voluntary organizations and social trust. The focus has been on the Nordic countries. To what extent if any can we speak of a specific Nordic orientation when it comes to the levels of social capital? In addition to that descriptive task, an attempt has been made to find important variables for the within-country differences. One method of finding the answers has been to carry out a multilevel statistical analysis where the individuals constitute the level 1 and the countries level 2. We have seen that Denmark, Norway and Sweden score especially high with regard to relations with voluntary organizations. Thus, there indeed is

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some Scandinavianness in high membership rates. The Scandinavians are not only passively members but also actively contribute to their membership organizations by giving both their time and their money for the common good. When it comes to the other aspect of social capital, generalized trust, the Nordic group is more homogeneous as Finns, who because of a higher degree of passiveness in their organizations, deviated from the three Scandinavian countries, display the very same high level of trust as the other Northerners. In order to control for a number of possible intervening factors, we conducted multivariate analyses to avoid drawing spurious conclusions. It may be that country differences are partly a result of compositional effects and partly of the macro-characteristics of the countries. Our multilevel analysis clearly shows that the socio-demographic controls can only explain a limited part of the between-country variation. Furthermore, the attitudinal explanatory variables can explain some of the between-country variation. The addition of the country classification into the conventional welfare state regimes showed the net differences between the country categories. After controlling for all individual level variables, the betweencountry differences are smaller than the gross ones, but the basic pattern remains with the Nordic countries highest and the South European countries at the other end of the scale. In order to evaluate the contribution of some important macrocharacteristics of countries we added the Human Development Index and the size of the population into the model. The inclusion of these characteristics explained much of the between-country differences in all the four aspects. The Human Development Index is especially related to all the activities in relation to voluntary organizations. Countries that score high on the HDI show high engagement with voluntary organizations and trust. The rich have possibilities for various hobbies and they trust each other. The individual characteristics that act as the main predictors of membership and voluntary work are being a male in paid work. Interest in politics is also important. Political interest is positively related to being a member of a voluntary organization, but negatively related to being a member of more of the different kinds of organizations, and negatively to voluntary work and donation of money to a voluntary organization. There seems to be a ‘virtuous circle’ between the universal welfare state and social capital. Bridging social policy and bonding organizational memberships seem to go hand in hand with trustworthiness. Of course, on the basis of our cross-sectional study it is not possible to draw strong conclusions on causality between the qualitative and quantitative aspects of the welfare state and the degree of social capital, or on the relationships between different aspects of social capital. Which generates what effect?

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However, at least one thing is clear: on the basis of these findings it is very hard to substantiate arguments on the detrimental effects of the generous and encompassing welfare states on non-governmental activities. On the contrary, it seems that there is a positive connection between all these factors.

REFERENCES Barbieri, Paolo (2003), ‘Social capital and self-employment’, International Sociology, 18 (4), 681–701. Bourdieu, Pierre (1989), Distinction: A Social Critique of the Judgement of Taste, Cambridge, MA: Harvard University Press. Brehm, John and W. Rahn (1997), ‘Individual level evidence for the causes and consequences of social capital’, American Journal of Political Science, 41 (3), 999–1023. Coleman, James (1990), Foundation of Social Theory, Cambridge, MA: Harvard University Press. Cook, Karen (ed.) (2001), Trust in Society, New York: Russell Sage Foundation. Ervasti, Heikki and O. Kangas (1995), ‘Class-bases of universal social policy’, European Journal of Political Research, 27 (3), 347–67. Fukuyama, Francis (1995), Trust: The Social Virtues and the Creation of Prosperity, Harmondsworth: Penguin Books. Granovetter, Mark (1973), ‘The strength of weak ties’, American Journal of Sociology, 78 (6), 1360–80. Hyyppä, Markku and J. Mäki (2001), ‘Individual level relationship between social capita and self-related health in a bi-lingual community’, Preventive Medicine, 32 (1), 148–55. Inglehart, Ronald (1990), Culture Shifts in Advanced Industrial Society, Princeton, NJ: Princeton University Press. Kangas, Olli (1995), ‘Attitudes on means-tested social benefits in Finland’, Acta Sociologica, 38 (4), 299–310. Kangas, Olli (1997), ‘Self-interest and the common good: The impact of norms, selfishness and context in social policy opinion’, Journal of Socio-Economics, 26 (5), 475–94. Knack, Stephen and P. Keefer (1997), ‘Does social capital have an economic payoff? A cross-country investigation’, Quarterly Journal of Economics, 112 (4), 1251–88. Korpi, Walter (1980), ‘Social policy and distributional conflict in the capitalist democracies’, West European Politics, 3, 294–316. Kumlin, Staffan and B. Rothstein (2005), ‘Making and breaking social capital: The impact of welfare state institutions’, Comparative Political Studies, 38 (4), 339–65. Larsen, Christian A. (2007), ‘How welfare regimes generate and erode social capital: The impact of underclass phenomena’, Comparative Politics, 40 (1), 83–102. Olson, Mancur (1965), The Logic of Collective Action. Public Goods and the Theory of Groups, Cambridge: Cambridge University Press.

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Putnam, Robert (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Ritter, Gerhard A. (1986), Social Welfare in Germany and Britain, Leamington Spa, UK and New York: Berg. Rothstein, Bo (1998), Just Institutions Matter: The Moral and Political Logic of the Universal Welfare State, Cambridge: Cambridge University Press. Scheepers, Peer, T. Grotenhuis and J. Gelissen (2002), ‘Welfare states and dimensions of social capital’, European Societies, 4 (2), 185–207. Svallfors, Stefan (1997), ‘Worlds of welfare and attitudes to redistribution: A comparison of eight Western nations’, European Sociological Review, 13 (3), 283–304. Szreter, Simon (2002), ‘The state of social capital: Bringing back in power, politics, and history’, Theory and Society, 31 (5), 573–621. Whiteley, Paul (2000), ‘Economic growth and social capital’, Political Studies, 48 (3), 443–66.

5.

Who should decide? A comparative analysis of multilevel governance in Europe Linda Berg and Mikael Hjerm

INTRODUCTION The Nordic countries are all small countries that have a history of seeking national political solutions despite the fact that they rely on internationalization for survival in the economic market. In spite of this commonality and historical interdependence, the relationship between the Nordic countries and Europe has come to be signified by difference. Denmark has been a member of the EU for more than 30 years and Finland and Sweden joined in 1995, whereas Norway is still not a member. Moreover, Finland is the only country that has implemented the euro. The Nordic countries may have different histories in relation to European integration but they have one thing in common; citizens of the Nordic countries have always embraced the idea of closing in on Europe as a means of enhancing economic performance while tending to refute the idea of deeper integration (Olesen 2000; Oscarsson and Holmberg 2004; Siune and Svensson 2002). People in the Nordic countries tend to be somewhat chauvinistic about their Nordic model as they find it superior to other European political solutions. The struggle to keep the Nordic model intact in the face of growing external pressures at different points in time has demanded different responses to the push for European integration. The question is whether the variation in political responses to Europe has affected the Nordic people’s views on European integration. During the last decades we have seen the formation of new or more influential political levels above and beneath the level of the nation state (e.g. the European Union and new subnational regions). However, the distribution of power between political institutions at these levels does not correspond to a federal political system, nor is it traditional intergovernmental cooperation. According to research within the field of multilevel governance, the power and position of the states has been challenged by 86

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three main developmental trends (Pierre and Peters 2000). First, there is a notion about a power shift upwards. Because of the globalization of the economy, communications and politics, contacts across borders have become more important and have contributed to an increase in interaction between the economical and political life of states (Anderson 2003; Goldmann 1994; Held 1991). As a consequence, the traditional strong separation between domestic and international politics has become less meaningful both practically and academically (Aldecoa and Keating 1999). Second, power has shifted downwards to regional and local political levels, which is a trend that has been especially noticeable in Europe over the last 15 years (Keating and Hughes 2003; Newman 2000). Devolution of several policy areas and particularly within the field of public service, has been a common feature in most European countries, as well as the creation of new and more independent subnational regions (Loughlin et al. 1999). Third, there is a shift of power outwards, from public to private interests. The privatization of former public tasks was a pan-European phenomenon during the 1990s. At local and regional levels the combination of privatization and devolution has led to new forms of subnational governance, such as private–public partnerships (Amin 1999). However, examples of public and private cooperation can be found at all societal levels. In this chapter it is the institutional shift of power upwards and downwards between levels of government in the political system that is in focus.1 The states are no longer the only relevant political units, and the national political institutions are not the only ones making binding decisions. In most European states there are now at least four political levels where decisions of importance for the citizens are made; local, regional, national and the European level (Loughlin et al. 1999). Since the latest enlargement in 2007 there are now 27 member states in the EU, but the EU is an important political factor even for those European countries that are not members. Political decisions in certain policy areas are being made in negotiations with the EU, and these decisions affect all European countries whether they are member states or not. From a multilevel governance (MLG) perspective we can see that these institutional changes have affected the reality of where (i.e. at what levels of government) political decisions are being made. However, the question remains if this is a distribution of political power that is supported by the majority of the people. Therefore, we want to explore the views of the European citizenry on what levels of decision making they prefer. The transformations and reforms of the political system in Europe occur at different speeds and in different ways across countries. Therefore, we expect the general view on where decisions should be made to vary across countries in Europe. Put into a wider context, we want to examine the possibilities for

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multilevel governance via its public support. The first question is: ‘Can institutional contexts be discerned in people’s views about what political entity they think should be responsible for various political decisions?’ Or, in other words, do people prefer different levels of governance in different countries. Looking at a Nordic and a European context it is obvious that the largest change in governance is related to the European Union and the European level of decision making. The supranational level, the EU, has developed into something of its own, sui generis (Guttman 2001) or a multilevel, multidimensional polity, as it is sometimes described (Abromeit 1998). The EU has expanded both vertically and horizontally as power has shifted from the national governments to the EU, while the expansion of member states has increased the EU’s horizontal jurisdiction by including more people. For this, predominantly vertical, expansion to continue, the political entities need public support formed by a collective entity (e.g. Scharpf 1999). This form of support varies across groups of people, but more importantly across countries or institutional settings. The second question is: ‘What effect do different contexts have on people’s support for European level governance?’ We examine institutional (time of membership in the EU), articulation (political party articulation of the EU) and economic (net contribution to the EU) contextual effects.

SUPPORT FOR EUROPEAN LEVEL DECISION MAKING Scholars who are interested in the multilevel changes in Europe have mostly been interested in individuals’ attitudes to European integration. The public support for a continuous integration process is obviously important, but such general support can imply different things for different individuals. In this chapter we have chosen a different way to explore the support for multilevel governance in Europe; we use more specific questions on the preferred level of government for a set of different policy areas. The levels of government are also not limited to the European or the national level, but range from local to international levels. We believe this procedure will improve our understanding of support for multilevel governance, and provide an interesting test for explanatory theories. As most scholars have focused on individuals’ attitudes to European integration, the theoretical explanations tend to have this micro-focus as well. There are two main categories of explanations for individuals’ attitudes to European integration in the literature: one based on utility or selfinterest, and the other based on affective feelings of identity. Gabel (1998) shows that support for the EU increases when material gains within a

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country increase. Several studies have discussed the importance of identity in explaining support for European integration (Carey 2002; Hooghe and Marks 2004; McLaren 2004), although the question of identity is somewhat problematic. There are, for example, studies that support the idea that a strong national identity enforces Euro scepticism (McLaren 2002) as well as the reverse (Citrin and Sides 2004). Hooghe and Marks (2005) are probably correct in their assumption that the direction of the relation depends on the exclusiveness of the national identity and not on the absolute strength. People that identify only with the nation are more inclined to have negative attitudes towards European integration. Similar theoretical reasoning can be found regarding the explanation for trust in political institutions at different levels. Berg (2007) has, for example, shown that people who identify with both the national and the European levels have higher degrees of trust in political institutions at both those levels. There are, however, other factors that are of importance for people’s attitudes towards different levels of government, like the degree of satisfaction with the services delivered by the institutions (Rothstein 1998). People are more likely to want the national government to be responsible for welfare issues if they think that they are doing a good job in delivering welfare. Another factor is trust in the political institutions, where people are more positive towards an institution that they trust. The main aim in this study is not to focus on individual explanations, but to examine how contexts shape people’s attitudes. Apart from the individual level explanations mentioned above, there are other macro-theories that are likely to be important for explaining variations in multilevel governance attitudes. Brinegar and Jolly (2005) even show that contextual factors can be of more importance than individual explanations in assessing attitudes towards European integration. As with individual explanations, there are a number of possible contexts that are likely to be of importance, and we focus on three of them. First, we have the political institutions – for example, the parliament, laws and regulations and so on. Political institutions affect people’s attitudes in a number of ways (see e.g. Svallfors 2006). Political institutions affect the visibility of social phenomena as people are more likely to have salient attitudes towards specific phenomena if these phenomena exist within an institutional setting. Institutions also structure the perceived possibilities that people view as attainable, in relation to what exists (Hall and Taylor 1996). Finally, institutions create and sustain norms about what is fair and just. An example of this is that people who live in welfare states tend to think that a more comprehensive welfare state is better, compared to people living in countries that lack a comprehensive welfare state. There are a number of such institutions that could be of importance, but

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in this chapter we limit our analysis to the degree of dispersion of political power between political entities. In other words, we focus on the existence of multilevel governance in terms of the political institutions that are likely to affect people’s attitudes. There is great variation in how long, and if at all, countries have been members of the EU. The EU itself has also changed dramatically over the years; it has become a more powerful organization both in terms of the number of political issues handled and the number of member states. Put differently, European integration is both deeper and wider. Even though we cannot measure changes over time, there are large differences between the European countries in the degree of ‘supranationality’ expressed as being a member of the EU or not, or alternatively related to the length of the membership period. Bruter (2005), for example, discusses how exposure to European institutions affects individuals’ degrees of European identity. He finds correlations between how the European integration project was framed during the time of membership and the aggregated levels of European identity in those countries. Exposure to the EU can also be theoretically motivated and measured in another way. Medrano and Gutiérrez (2001, p. 772) point out that the political framing of the EU by the elite and the media in different countries might affect perceptions of the EU; whether it is presented as a threat to national or subnational identities or not. Hooghe and Marks (2004) argue in a similar way, as they explain that country differences about opinions on European integration are affected by the framing of Europe by the national political elite. The Nordic countries are interesting examples. On the one hand, the countries are generally perceived to be very similar in several ways, especially as welfare states. They are thought of as belonging to the same regime (Esping-Andersen 1990) and sometimes described in terms of ‘the Scandinavian model’ (Rothstein 1998). None of the four Nordic countries is federal, and therefore we do not expect a large share of people to prefer the regional or local level of decision making concerning several different policy areas. On the other hand, the Nordic countries have clearly diverse historical experiences regarding war, and international affiliation during the cold war, as well as variations in membership of the European Union. The idea of multilevel governance may therefore be expected not to follow the same pattern in the Nordic countries for all policy areas. The general idea of supranational (or European) decision making is more likely to be supported in countries with longer experience of being a member of the EU. Therefore, we expect Danes to be the most supportive of European level decision making and Norwegians to be the least supportive, with the Finns and the Swedes somewhere in between. The second macro, or contextual, theory concerns political articulation. Depending on whether the articulation of the EU is positive or negative,

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people are likely to be more or less supportive of the European level of decision making (Hooghe and Marks 2005, 2004). The political climate is becoming increasingly complex and people cannot survey the whole political landscape. This is especially true when it comes to the European level where citizens are not very well informed and therefore need proxies to help attitude formation (Anderson 1998). Political articulation functions as such a proxy by mediating the link between institutions and attitudes. This mediation increases the visibility of specific issues and enables people to identify their interests. People form attitudes about what is articulated and the direction of these attitudes is expected to coincide with the articulation of a specific issue. Carey and Burton (2004) show that attitudes towards European integration in Britain were substantially strengthened when both political parties and the mass media were articulating the same thing. The political articulation of the EU does differ both in content and extent across the European countries. Hay and Smith (2005) show that there are large differences between the articulation of European integration between the two neighbouring countries of Britain and Ireland. The differences across countries in media articulation are also evident comparing Triandafyllidou’s (2003) study of Italy, and Kuus’s (2002) study of Estonia. The articulation of European integration covers different issues, which are related to practical political circumstances. The latter is also true for the Nordic countries where the articulation on the EU and the European integration revolves around different issues in different countries dependent on their general involvement. This involvement can range from not being a member at all to being a member of the monetary union. The debate about joining the EU got underway with new vigour during the early 1990s in Norway, Finland and Sweden. The start of the debate was similar in the three non-member countries as it evolved around the necessity of these countries to be members (Jensen et al. 1998), but it resulted in different referenda results. Moreover, it is also obvious that the articulation on the European level decision-making process has a long history in Denmark compared with the other Nordic countries, for example, the six referenda concerning the EU that have taken place in Denmark since 1972 (Hansen and Buch 2002). The country differences are measured using the political party manifestos, as analysed by the manifesto data (Budge et al. 2001). The third, contextual factor is economic self-interest in a wide perspective. Looking at individual self-interest we know that individuals who benefit from increased European integration are more likely to support such integration; that is people with higher levels of education, and so on. The focus here is not individual self-interest but the so-called sociotropic or collective self-interest. Previous studies have shown that a country’s relative

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position in the economic hierarchy can explain aggregated attitudes towards European integration (Eichenberg and Dalton 1993). The question here is: Are people also more likely to support increased integration if their country benefits economically from such integration? In other words, is sociotropic self-interest a possible explanation for attitudes towards European level decision making? If this is the case, we expect that sociotropic interest differs as there are substantial country differences in how they benefit from increased European integration. The country benefits are measured via the monetary net contribution to the European Union. There are clear contextual differences between the Nordic countries. The three member countries are all net contributors, but there are substantial differences in contribution amounts in that Sweden is one of the largest net contributors per capita compared with Finland, which barely reaches positive contribution figures.

METHOD As discussed above, we operationalize attitudes towards MLG by using a question about where people think specific policies ought to be made. The question is phrased as follows: ‘Policies can be decided at different levels of government. Using this card, at what level do you think the following policies should mainly be decided?’ The possible answers are: international, European, national and regional/local level. The policy areas covered are: environment, organized crime, agriculture, defence, welfare, aid to developing countries, immigration and interest rates. This question measures attitudes towards multilevel governance in a more specific way than questions about support for European integration, or whether one perceives the EU to be a good or a bad thing. Furthermore, this is a question about an abstract form of governance as people do not need to relate to specifically named existing political institutions. This means that people who want decisions to be made at the European level do not necessarily want them to be made by the EU. However, as the existing institutions do structure what is perceived as possible, and as there are no other plausible alternative European decision levels, this is not a large problem. The specific institution can also be seen as a question of form, but we are mainly interested in the idea of multilevel governance. In order to measure context effects on individual attitudes we apply the multilevel analysis technique. Multilevel analysis assumes that individuals interact with the social context to which they belong, and is an empirical way of understanding the relationship between the structure and the individual. The data structure in the population is hierarchical in multilevel

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modelling. The population is seen as a multistage sample from this hierarchy, such as individuals in countries. This makes it possible to simultaneously test the effect of structure and individual characteristics on an individual outcome. The use of this modelling has an empirical advantage over regression analysis, because it does not underestimate standard errors, which is the case if macro-level variables were to be included in an OLS regression analysis. The errors are generated owing to the lack of variability in the macro-level indicators. It has also a theoretical advantage: we are testing contextual effects and therefore we need to be able to draw conclusions at this level of analysis in order to avoid the ecological (interpreting aggregated data at an individual level) and atomistic (interpreting individual data at a higher level) fallacies.

RESULTS: ATTITUDES TO MULTILEVEL GOVERNANCE IN EUROPE The first question we set out to examine is whether there are discernable country patterns in people’s attitudes towards multilevel governance. We are, as stated above, asking where people think policies should be made in eight different policy areas. The policy areas are: protecting the environment, fighting against organized crime, agriculture, defence, social welfare, aid to developing countries, immigration and refugees, interest rates. People’s attitudes towards the level of decision making for these policy areas do, needless to say, vary across countries. However, we do not probe into specific cross country differences. We instead examine whether there are more general cross-country differences or similarities to be found. In order to be able to examine whether there are indeed cross-country patterns to be found we need to order data in a meaningful way. One way of doing this is to identify clusters that share similar characteristics. We do this by using a cluster analysis based on latent class analysis (LCA). This particular method’s advantage over others is that it is developed to handle categorical data. It is assumed that the total associations between the observed variables or indicators (level of government in this case) are explained by one or more latent variables(s). A discernable pattern of MLG among the people of Europe exists, but the question is whether cross-country differences exist. We added country as a covariate to the cluster analysis so that we would be able to answer this question. In practice what this means is that we correlate country with the clusters in order to examine whether the countries can be associated with different clusters. The advantage of this procedure is that the cluster characteristic is the

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Table 5.1

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Country correlation with latent variables

Country

Austria Belgium Switzerland Czech Republic Germany Denmark Spain Finland France United Kingdom Greece Hungary Ireland Israel Italy Luxembourg Netherlands Norway Poland Portugal Sweden Slovenia

National/ European National International Local/ international regional mix 0.32 0.12 0.60 0.56 0.28 0.29 0.17 0.49 0.16 0.43 0.30 0.31 0.15 0.30 0.00 0.27 0.22 0.67 0.21 0.24 0.45 0.16

0.30 0.46 0.15 0.21 0.50 0.36 0.26 0.13 0.40 0.04 0.27 0.19 0.16 0.11 0.31 0.38 0.46 0.08 0.14 0.27 0.20 0.29

0.09 0.05 0.04 0.11 0.04 0.20 0.19 0.21 0.14 0.26 0.28 0.40 0.53 0.12 0.25 0.07 0.05 0.14 0.42 0.34 0.19 0.23

0.13 0.26 0.19 0.07 0.14 0.09 0.26 0.03 0.23 0.11 0.08 0.05 0.02 0.22 0.11 0.25 0.23 0.06 0.06 0.11 0.08 0.16

0.16 0.11 0.03 0.05 0.05 0.06 0.12 0.14 0.07 0.17 0.07 0.04 0.13 0.25 0.34 0.03 0.05 0.06 0.17 0.04 0.07 0.16

same in all countries; that is, the cluster has the same meaning in all countries. The result of this analysis is presented in Table 5.1. The interpretation is the same as with individuals; the higher the value, the larger the chance that a country belongs to this particular cluster. The countries clearly belong to different clusters. Looking at the Nordic countries for example we see that Norway, Finland and Sweden belong to the first cluster. Depending on the issue, in this cluster people want some issues to be decided at the national level and other issues at the international level. Furthermore countries like Switzerland, the Czech Republic and the UK clearly belong to this cluster. With the exception of the UK, we are dealing with small countries that are either not members of the EU, or have been members for only a short period of time. Belgium, Germany, Denmark, Luxembourg and The Netherlands clearly belong to the European cluster that wants decisions to be taken predominantly at the

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0.6 0.5 0.4 0.3 0.2 0.1

G er m Be any N et lgiu he m rla nd Lu Fra s xe nc m e b D our en g m ar k Ita Au ly s Sl tria ov e G nia re Po ece rtu C ga ze ch Sp l R ain ep u Sw blic ed H en un ga r I Sw re y itz land er la Po nd la Fi nd nl an d Is U ra ni te No el d rw Ki ay ng do m

0

Figure 5.1 Latent class scores per country: the higher the values, the more positive towards European level decision making European level. Denmark is not as clearly European in the same way as, for example, Norway is national/international, but it cannot be dismissed that Denmark belongs to a different cluster from the other Nordic countries. Ireland, Poland, Portugal, and Hungary belong to the national cluster where people want most issues to be decided at the national level. No country belongs clearly to the cluster with a preference for decisions at the local or regional level, or to the exclusively international cluster. Spain does, however, display a strong sense of international preferences combined with the European level, and Italy displays a strong sense of locality mixed with the European level. The most interesting level from a multilevel governance perspective is the European level, as European integration and the creation of a supranational level of decision making most clearly challenges the classical view of the strong nation state. If we focus only on attitudes towards decision making at the European level, we see more clearly in Figure 5.1 that three of the Nordic countries are relatively similar, but Denmark deviates somewhat from this pattern. In fact, Denmark shows a preference for European decision making more in line with the six original members of the EU. We have established that there are large variations between the European countries regarding the preference for a European level of decision. Now it is time to examine the theoretical explanations. We stated above that political institutions, political articulation and ‘sociotropic’ or collective selfinterest are likely to affect people’s support for various levels of decision making.

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Explaining differences We have already found that there are aggregated country differences where people think decisions ought to be made. The question is whether such differences can, at least partly, be derived from contextual differences. In order to simplify the analysis, we only focus on the preference for European level decision making. In order to be able to do that we have adopted the individual cluster scores on cluster 2. The higher the value an individual has, the higher the probability that he/she belongs to cluster 2. Therefore, the higher the value, the more positive towards European level decision making a person is.2 In order to be able to measure context effects on individuals’ attitudes we apply multilevel analysis. The aim is not to explain the effect of individual characteristics. The focus is on the effect of specific contextual conditions rather than individual characteristics. The individual level indicators need to be included in order to avoid the risk that the effect of group level indicators is wrongly estimated. For example, if education has a strong effect while being unevenly divided between countries it could be the cause for the country level differences. The latter is something that clearly has to be avoided. The included indicators are: education, which is measured in terms of the number of years that the individual has attended full-time schooling, age, sex and household income. Household income is measured on a 12-point scale in all the examined countries. Individual attitudes have not been taken into account for two reasons. The first is a theoretical reason, as we predict a direct effect of the contextual indicators on the examined outcome. It does not refute the possibility that such causation can be mediated by other attitudes, only that there is a direct link between them. The second reason is related to the causation problem. Few longitudinal studies have been performed to make the causal order of various attitude complexes clear beyond doubt, which means that this needs to be explored further before it can be of any use to this study. The contextual level indicators in the analysis are operationalization of political institutions, articulation and sociotropic self-interest. Political institution is measured by the relative time a country has been a member of the EU. We set the variable to vary between zero (for the nonEU members) and seven, where each number corresponds to the phase in which the country joined the EU. Political articulation is adopted from manifesto data (Budge et al. 2001). The manifesto data set is based on extensive content analyses of all political party manifestos in a large number of countries (25 for the dataset used here). The manifesto data are analysed for numerous different areas and we have adopted one of the available indicators that deal with the European

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Union (European Community). This indicator measures favourable statements about the EU, willingness to expand the union and the party’s desire to remain/become a member of the Union. The higher the value, the more frequent the positive emphasis of the Union within those party manifestos. It means that the higher the frequency, the more prevalent the discourse or articulation within a single country. We have chosen to average the values in the elections from 1948 until the latest available party election (1998). The reason for this is that we want to measure a trend of articulation. Sociotropic self-interest is measured via monetary net contribution to the EU per capita. A small problem with the analysis is that N is ‘only’ 21 cases, and thus the variability between countries is relatively small. Nevertheless, it is perfectly possible to perform this kind of modelling with this number of cases. Snijders and Bosker (1999) provide a rule of thumb when they state that if N is equal or greater than 10, a random intercept model (i.e. a linear hierarchical model) is preferable to a fixed model as a means of performing a regression analysis. Still, the number of countries does limit our analysis because of the lack of possible variation at the country level. Therefore, we test the context variables independently in three different models. We are using a so-called fixed effect model where it is assumed that the individual characteristics have the same or similar effect in all countries; that is, a model without random slopes. This is rarely the best model, but the fact that there is very small variation between countries makes the simpler solution preferable. The first model (Model 0) to be tested is the ‘empty model’ (one without any country or individual level indicators). The point of using this model is to ascertain whether there is country level variance at all; that is, whether there are country differences in European integration. If this is not the case then there is no need for multilevel modelling, as a standard OLS regression would result in the same output. Model 0 shows that the country level variance constitutes approximately 15 per cent of the total unexplained variance. This means that there is country level variance to be explained. Model 1 shows that income, education and age have positive effects on attitudes to European decision making and that men are slightly more positive to that than women. The model also includes the political institutional indicator, or time of EU membership. This indicator has a rather strong effect on people’s attitudes towards European decision making. The average difference between countries that are not EU members and the countries that have been so from the beginning is 0.26, on a scale that varies between zero and 1. Moreover, 57 per cent of all people score below 0.10 on the dependent variable, which further strengthens the quite large effect. The latter is also evident in that the unexplained variance at country level drops

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Table 5.2 Multilevel model (REML) with LCA cluster scores for support of European level decision making as dependent variable Model 0 Fixed effects Individual indicators Women Household income Education Age Fixed effects Country indicators EU membership Political articulation Net contribution

– – –

Random effects Variance component Between countries Within countries

0.019 0.105

Model 1

Model 2

Model 3

0.0464** 0.0074** 0.0085** 0.0013**

0.0479** 0.0077** 0.0094** 0.0018**

0.0526** 0.0107** 0.0083** 0.0018**

0.0375** – –

– 0.103** –

– – 0.00021

0.012 0.105

0.014 0.107

0.019 0.117

Note: ** Significant at 99 per cent or not at all.

dramatically. The variable explains 37 per cent of the unexplained variance on the country level. The large effect of membership time cannot be explained by general attitudes towards the EU, because the aggregated evaluation of how good the EU is does not affect the preferences for European level decision making (not displayed in the table). Moreover, the attitudes towards membership in the EU do not become increasingly positive over time. Figures from Eurobarometer show that at an aggregated EU level the proportion of people supporting EU membership has not changed between the early 1970s and today. There are changes in various countries where people have become more positive, for example, in Luxembourg and The Netherlands, but more negative in France and Germany. At an individual level there is only a small correlation between trust in the EU parliament and the index of European level decision making (.10 in the whole EU), which further strengthens the understanding that the independent variable measures something more than just attitudes towards the EU. It seems that the exposure to European decision making and institutions makes people become more apt to support such decision making. Model 2 displays the same analysis with the inclusion of the political articulation indicator. The effect of this indicator is also rather large in that one whole step on the political articulation index accounts for a 10 per cent

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increase in people’s attitudes towards European decision making. The political articulation index varies in practice from 0.27 (Finland) to 3.48 (Germany), which means that the whole span accounts for a 0.33 unit increase in average levels of attitudes towards European decision making. As with the membership time in EU, we see that the indicator explains a large proportion of the variance at the country level (26 per cent). Model 3 tests the sociotropic self-interest explanation; namely that people are more apt to support European level decision making if they, or their country, benefit from European integration. This does not seem to be the case because the net contribution does not affect people’s attitudes towards European level decision making. Moreover, it does not matter if we dichotomize the monetary indicator or include the non-member countries in the analysis; there is no effect from the net contribution indicator. This does not imply that self-interest itself is not important. People who are more likely to benefit from an increase in European decision making are also more positive towards this, such as those with high incomes. We do acknowledge that it may be difficult to separate self-interest from general economic conditions. Therefore, we also tested for objective and subjective economic contexts via GDP and the respondents’ aggregated apprehension of the country’s state of economy. None of these contexts matter, which indicates that neither collective self-interest nor the subjective or objective economic contexts matter for the support for European level decision making. This contradicts earlier findings (e.g. Hooghe and Marks 2005) where this has shown to be of importance. The reason for the diverging results could be the difference in the dependent variable, which further corroborates the understanding that a preference for European level decision making does not have to automatically imply the EU. Furthermore, a preference for a European level of decision making for certain policy areas is not the same as supporting the process of European integration per se. It seems that the longer people are exposed to decision making at a higher level, as well as the more cues or articulation they are exposed to, the more they are willing to favour decision making at a European level. The country’s economy or the sociotropic benefits for the country do not matter at all. It is not self-evident that the institutional context makes people become more positive and not the other way around; that is, those countries where people are more positive join the EU at an earlier stage. The latter cannot be dismissed, but it is a far-fetched idea. For example, the new EU members from Eastern Europe could not join the Union at an earlier stage regardless of the populations’ attitudes. However, these countries still fit the model as people in these countries have less favourable attitudes towards European level decision making. It is true that people’s attitudes towards EU membership and similar issues do not grow more positive over

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0.50 Belgium

Latent class scores for Europe, higher value indicate more European friendly

Netherlands France

0.40

Luxembourg Denmark

Slovenia

0.30

Italy

Austria Portugal

Greece

Spain

0.20

Hungary

Sweden

Czech Republic Ireland Switzerland Poland

Finland

Israel

0.10

Norway R Sq Linear = 0.461 United Kingdom

0.00 1.00

2.00

3.00

4.00

5.00

6.00

7.00

Time of membership in EU

Figure 5.2 Membership time in EU and country support for European level decision making time,3 but we are measuring a more abstract form of attitude (albeit concerning specific policy areas) towards Europe and the EU. Still, it remains to be seen if people’s attitudes towards European decision making become more positive over time. The relation between the context variables and the support for European level decision making becomes even more obvious in a simple scatterplot between EU membership and political articulation on the one hand and European level decision making on the other (see Figures 5.2 and 5.3). We see that the length of time a country has been a member of the EU explains a staggering 46 per cent of the variance in latent class scores for the European level (0.70 if the UK is excluded from the analysis). Or, in

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0.50

Latent class scores for Europe, higher value indicate more European friendly

Netherlands

Belgium

France

0.40

Luxembourg Denmark

Italy

Austria

0.30 Portugal

Spain

Greece

Sweden

0.20 Ireland

Switzerland

Finland

0.10

Norway

R Sq Linear = 0.356 United Kingdom

0.00

0.00

1.00

2.00

3.00

4.00

Manifesto data positive towards EU (108)

Figure 5.3 Political articulation and country support for European level decision making other words, the longer a country has been a member of the EU, the more its people are inclined to be supportive of the European level of decision making. The only outlier is Britain, which has been a member of the EU for a long time, but where people are nonetheless not very supportive of Europe as a decision-making arena. If we change focus to the Nordic countries, we see that Finland, Norway and Sweden are clustered together whereas Denmark belongs to the Central European cluster. The more positive the discourse around the EU, the more people are inclined to be supportive of the European level of decision making. As before, Britain is an outlier (R square is 0.5 if Britain is excluded from the analysis). As with membership in the EU, it is obvious that three of the Nordic countries display similarities, whereas Denmark is somewhat of an outlier.

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DISCUSSION We have seen that there are differences between the Nordic countries in people’s preferred level of decision making. Norway, Finland and Sweden primarily belong to an international/national cluster, whereas Denmark belongs to a more European cluster. That the Nordic countries cluster in the national/international cluster is not surprising. They are all small countries that have been heavily dependent on free trade and an international market for their economic sustenance. At the same time, they have developed the Nordic welfare state model that relies on a universal programme, which is run by strong decommodifying, or redistributive, states. Denmark joined the EU relatively early (1973) and has, consequently, more experience of European level decision making, which we can clearly see as Denmark clusters closer to continental Europe. Given the results displayed here, if Denmark had joined the EU at a later stage, we would have expected it to belong to the national/international cluster. The other European countries also cluster as expected as the EU core states are more related to the European cluster than other countries. We saw, for example, that Belgium, Germany, Denmark, Luxembourg and The Netherlands clearly belong to the European cluster wherein people predominantly want decisions to be taken at the European level. Ireland, Poland, Portugal, and Hungary belong to the national cluster where people want most issues to be decided at the national level. No country belongs clearly to the cluster with a preference for decisions at the local or regional level, or exclusively to the international cluster. Spain does, however, display a strong sense of international preferences combined with the European level, and Italy displays a strong sense of locality mixed with the European level. The country classifications into various clusters cannot explain why people in those countries hold diverging views on the preferred level of decision making. For this reason we set out to test how different contexts affect people’s preferences. We chose to test only preferences for European level decision making by asking why there are substantial cross-country differences in people’s support of European level decision making. We tested three different context effects. First, political institutions (measured through the time a country has been an EU member) proved to have rather large effects on preferences regarding European level decision making. The longer a country has been a member of the EU, the more positive people are towards European level decision making. This finding is not simply related to increasing acceptance of the EU itself. If the latter was the case we would expect people’s attitudes towards, for example, membership of the EU to have become more positive over time. This is, however, not the case as the proportion of people who

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think that membership of the EU is a good thing has been fairly stable since the early 1970s. Moreover, people’s trust in the European Parliament and their preference with respect to the European level as the prime level of decision making does only correlate weakly. Taken together it indicates that people do not equate the European level with the EU itself, or that people make a distinction between European institutions and the EU. Second, political articulation (political party articulation of the EU) was also shown to have a moderately strong effect on the preferred level of decision making. The more positive the articulation, the more people prefer the European level. Articulation is related to time of membership, because the EU is more positively articulated in countries that have been members for a longer time. This relation cannot be interpreted in terms that would equate an increase in articulation with time of membership as there is no correlation between articulation and membership time once the countries become members. It is also interesting to note that negative articulation does not have any effect. The reason for this is most likely to be found in the fact that the parties that articulate negatively around the EU are the smaller and more marginalized parties that have much less impact on the general discourse of Europe. Third, sociotropic or collective self-interest (measured via net contribution to the EU) did not have any effect on the preferred level of decision making, nor did objective or subjective economic conditions. This makes it obvious that collective self-interest plays a marginal role when people assess at what level political decision making ought to take place. This does not mean that self-interest does not play a role. At an individual level people who are most likely to benefit from a higher level of decision making (welleducated affluent people) are also the ones who are most positive (see also Gabel 1998). The reason that these groups are more positive does not have to be self-interest, but it cannot be ruled out that this is the case. The Nordic countries do not deviate from the displayed pattern. This means that we can, to some extent, explain why the Danes are much more positive about European level decision making than their counterparts in the other examined Nordic countries. They have simply been members of the EU for a longer time. Moreover, the positive articulation of the EU is much more common in Denmark than in Finland, Norway or Sweden. People do evaluate possibilities with reference to what actually exists, so it may come as no surprise that people are more positive to European level decision making in places where they have had long-term experiences of such decision making. The level of positivity stands in spite of the fact that they do not trust or evaluate the EU more positively over time. Good or bad; if it exists you get used to it and it becomes the reference point when assessing possibilities – a thought that has a nice ring in terms of European integration.

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NOTES 1. This is what Hooghe and Marks (2003) call type I multilevel governance: a type of governance that focuses on the political institutions at different levels, which have a broad range of purposes and are designed around particular communities and the members’ identification with those communities. This is the type of governance that is most widespread and commonly known, where every citizen is part of a hierarchy of political communities that are separated, though intersecting, from each other. Type II multilevel governance on the other hand is task-specific, functional and known for intersecting memberships and networks. It is a system where jurisdictions are aimed at solving a specific task across territorial levels. 2. We did also test a simpler dependent variable. We counted the number of European scores for each individual on the eight items and used this as the dependent variable. The results from this analysis are very similar to the analysis with the Latent class scores, but the method used here is preferable as it holds the content of the clusters constant across countries. 3. For example, the Eurobarometer http://europa.eu.int/comm/public_opinion/index_en. htm.

REFERENCES Abromeit, Heidrun (1998), ‘How to democratise a multi-level, multi-dimensional polity’, in Albert Weale and Michael Nentwich (eds), Political Theory and the European Union. Legitimacy, Constitutional Choice and Citizenship, London: Routledge, pp. 112–24. Aldecoa, Fransisco and M. Keating (eds) (1999), Paradiplomacy in Action. The Foreign Relations of Subnational Governments, Regional and Federal Studies. London: Frank Cass Publishers. Amin, Ash (1999), ‘An institutionalist perspective on regional economic development’, International Journal of Urban and Regional Research, 23 (2), 365–79. Anderson, Chris (1998), ‘When in doubt, use proxies: Attitudes toward domestic politics and support for integration’, Comparative Political Studies, 31 (5), 569–601. Anderson, James (ed.) (2003), Transnational Democracy. Political Spaces and Border Crossings, London: Routledge, Taylor & Francis Group. Berg, Linda (2007), ‘Multi-level Europeans: the influence of territorial attachment on political trust and welfare attitudes’, Department of Political Science, Gothenburg University. Brinegar, Adam P. and S.K. Jolly (2005), ‘Location, location, location. National contextual factors and public support for European integration’, European Union Politics, 6 (2), 155–80. Bruter, Michael (2005), Citizens of Europe? The Emergence of a Mass European Identity, New York: Palgrave Macmillan. Budge, Ian, H.D. Klingemann, A. Volkers, J. Bara and E. Tanenbaum (2001), Mapping Policy Preferences: Estimates for Parties, Electors and Governments, 1945–1998, Oxford: Oxford University Press. Carey, Sean (2002), ‘Undivided loyalties. Is national identity an obstacle to European integration?’, European Union Politics, 3 (4), 387–413.

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Carey, Sean and J. Burton (2004), ‘Research note: The influence of the press in shaping public opinion towards European Union in Britain’, Political Studies, 52, 623–40. Citrin, Jack and J. Sides (2004), ‘Can there be Europe without Europeans? Problems of identity in multinational community’, in Richard Herrmann, Thomas Rise and Marilyn B. Brewer (eds), Transnational Identities. Becoming European in Europe, Lanham, MD: Rowman & Littlefield, pp. 161–85. Eichenberg, Richard and R. Dalton (1993), ‘European community: The dynamics of public support for European integration’, International Organization, 47 (4), 507–34. Esping-Andersen, Gøsta (1990), The Three Worlds of Welfare Capitalism, Cambridge: Polity. Gabel, Matthew J. (1998), Interest and Integration. Market Liberalization, Public Opinion, and the European Union, Ann Arbor, MI: Michigan University Press. Goldmann, Kjell (1994), ‘Sverige, EG och politikens internationalisering’, in Suveränitet och Demokrati. Bilagedel med Expertuppsatser, SOU 1994:12. Guttman, Robert J. (ed.) (2001), Europe in the New Century. Visions of an Emerging Super Power, Boulder, Co: Lynne Rienner Publishers. Hall, Peter A. and R.C.R. Taylor (1996), ‘Political science and the three new institutionalisms’, Political Studies, 44 (5), 936–57. Hansen, Kasper M. and R. Buch (2002), ‘The Danes and Europe: From EC 1972 to Euro 2000 – Election, referendums and attitudes’, Scandinavian Journal of Political Studies, 25 (1), 1–26. Hay, Colin and N.J. Smith (2005), ‘Horses for courses? The political discourse of globalisation and European integration in the UK and Ireland’, West European Politics, 28 (1), 124–58. Held, David (1991), ‘Democracy, the nation-state and the global system’, in David Held (ed.), Political Theory Today, Cambridge: Polity Press, pp. 197–235. Hooghe, Liesbet and G. Marks (2003), ‘Unraveling the central state, but how? Types of multi-level governance’, American Political Science Review, 97 (2), 233–43. Hooghe, Liesbet and G. Marks (2004), ‘Does identity or economic rationality drive public opinion on European integration?’, Political Science and Politics, 37 (3), 415–20. Hooghe, Liesbet and G. Marks (2005), ‘Calculation, community, and cues: Public opinion on European integration’, European Union Politics, 6 (4), 419–43. Jensen, Anders Todal, Pertti Pesonen and Mikael Giljam (1998), To Join or Not to Join. Three Nordic Referendums on Membership in the European Union, Oslo: Scandinavian University Press. Keating, Michael and James Hughes (eds) (2003), The Regional Challenge in Central and Eastern Europe, Brussels: P.I.E. – Peter Lang S.A. Kuus, Merje (2002), ‘European integration in identity narratives in Estonia. A quest for security’, Journal of Peace Research, 39 (1), 91–108. Loughlin, John et al. (Committee of the Regions) (1999), Local and Regional Democracy in the European Union. CoR E-1/99, Brussels: Committee of the Regions. McLaren, Lauren M. (2004), ‘Opposition to European integration and fear of loss of national identity: Debunking a basic assumption regarding hostility to the integration project’, European Journal of Political Research, 43 (6), 895–911.

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McLaren, Lauren M. (2002), ‘Public support for the European Union: Cost/benefit analysis or perceived cultural threat?’, The Journal of Politics, 64 (2), 551–66. Medrano, Juan Díez and P. Gutiérrez (2001), ‘Nested identities: National and European identity in Spain’, Ethnic and Racial Studies, 24 (5), 753–78. Newman, Peter (2000), ‘Changing patterns of regional governance in the EU’, International Journal of Urban and Regional Research, 37 (5/6), 895–909. Olesen, Thorsten B. (2000), ‘Choosing or refuting Europe? The Nordic countries and European integration 1945–2000’, Scandinavian Journal of History, 25 (1–2), 147–68. Oscarsson, Henrik and Sören Holmberg (eds) (2004), Kampen om Euron, Göteborg: Statsvetenskapliga Institutonen. Pierre, Jon and Guy B. Peters (2000), Governance, Politics and the State, Political Analysis, New York: St Martin’s Press. Rothstein, Bo (1998), Just Institutions Matter: The Moral and Political Logic of the Universal Welfare State, Cambridge: Cambridge University Press. Scharpf, Fritz (1999), Governing in Europe. Effective and Democratic, Oxford: Oxford University Press. Siune, Karen and P. Svensson (2002), ‘The Danes and the Maastrich Treaty. The Danish EC referendum of June 1992’, Electoral Studies, 12 (2), 99–111. Snijders, Tom A.B. and Roel J. Bosker (1999), Multilevel Analysis, London: Sage. Svallfors, Stefan (2006), The Moral Economy of Class. Class and Attitudes in Comparative Perspective, Stanford, CA: Stanford University Press. Triandafyllidou, Anna (2003), ‘Research note: The launch of the euro in the Italian media-representation of political and economic integration’, European Journal of Communication, 18 (2), 255–63.

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APPENDIX Table 5A.1

Latent class analysis with eight policy areas National/ European National International Local/ international (Cluster 2) (Cluster 3) (Cluster 4) regional mix (Cluster 5) (Cluster 1)

Overall probability indicators Agriculture International level European level National level Regional or local level

0.3146

0.2573

0.1903

0.1318

0.1061

0.1887

0.1251

0.0054

0.6063

0.0745

0.2346 0.4291 0.2309

0.5497 0.1606 0.0954

0.0526 0.3214 0.2236

0.1149 0.0339 0.0394

0.0482 0.055 0.4107

0.2216

0.1008

0.2089

0.1024

0.4545 0.1708 0.0895

0.2346 0.3822 0.0723

0.046 0.0265 0.0836

0.0953 0.0765 0.6358

0.2455

0.0366

0.2208

0.0686

0.5512 0.0929 0.0344

0.1722 0.5983 0.3041

0.0234 0.0118 0.0111

0.0596 0.1282 0.5787

0.2918

0.167

0.0448

0.3871

0.1093

0.2119 0.4119 0.0106

0.5827 0.1177 0.0491

0.0833 0.3575 0.0454

0.0602 0.0242 0.034

0.0618 0.0887 0.861

0.4479

0.2362

0.0348

0.2341

0.047

0.1704 0.231

0.5996 0.1442

0.1112 0.4899

0.0585 0.0273

0.0603 0.1076

Aid to developing countries International 0.3663 level European level 0.1697 National level 0.344 Regional or 0.1188 local level Fight against organized crime International 0.4284 level European level 0.1935 National level 0.1688 Regional or 0.0718 local level Defence International level European level National level Regional or local level Environment International level European level National level

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Table 5A.1

Nordic social attitudes in a European perspective

(continued) National/ European National International Local/ international (Cluster 2) (Cluster 3) (Cluster 4) regional mix (Cluster 5) (Cluster 1)

Regional or local level Interest rates International level European level National level Regional or local level Immigration International level European level National level Regional or local level Welfare International level European level National level Regional or local level

0.153

0.1013

0.3483

0.0282

0.3692

0.2045

0.1692

0.0493

0.4553

0.1217

0.1901 0.4388 0.1589

0.538 0.1344 0.0862

0.089 0.3089 0.0519

0.0994 0.0519 0.0895

0.0836 0.066 0.6135

0.3031

0.1737

0.0987

0.3109

0.1135

0.2047 0.4174 0.1763

0.5391 0.1515 0.0824

0.1349 0.3205 0.0754

0.0555 0.0371 0.0916

0.0658 0.0735 0.5742

0.1584

0.0967

0.0049

0.6545

0.0855

0.1187 0.4214 0.1942

0.6187 0.2153 0.1081

0.0427 0.2572 0.2255

0.1532 0.0509 0.0441

0.0667 0.0553 0.4281

Notes: The result of the latent class analysis shows that there are five clusters. The figures should be interpreted as probabilities or correlations between the item and the cluster. For example, any person who has answered ‘international level’ on the ‘agriculture’ item has a 20 per cent chance of belonging to cluster 1 and a 60 per cent chance of belonging to cluster 3 and so on. We also see that there are obvious patterns in the correlation between the items and the clusters as there is one cluster for each level of government and an extra cluster that mixes the national and international levels. The model improvement between a five cluster model and a one cluster model is approximately 80 per cent and there is almost no improvement between a five and a six cluster model. However, we are interested in equalizing the clusters so that they mean the same thing in all countries. Therefore, we include country as a covariate in the model (see Table 5.1 in the text). The model improvement between a one cluster model and a five cluster model is now ‘only’ 31 per cent, which indicates that the cluster composition does vary somewhat across countries. However, this can partly be explained by the extreme degrees of freedom that are associated with this procedure. The latter also makes the objective model improvement less important. We are interested in the qualities that best order the data and this is a five cluster model in this case.

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Table 5A.2

109

LCA: L2 model estimation

Without country

1-cluster

2-cluster

3-cluster

4-cluster

5-cluster

82889

59472

47749

40465

37563

6.

Political activism Frode Berglund, Øyvin Kleven and Kristen Ringdal

INTRODUCTION Politically active citizens are generally seen as a prerequisite for a wellfunctioning democracy. This chapter will describe the levels and crossnational patterns of political activism in Europe based on the European Social Surveys of 2002 and 2004. The main focus is on citizens’ actions that are aimed at influencing political decisions. These actions include directly contacting politicians, writing petitions and involvement in public demonstrations, but exclude participation in elections. The political cultures of the countries may be seen as important contexts for political activism. More specifically, we employ a classification of the countries by democratic traditions, thereby distinguishing between the Nordic countries, the old and the new democracies in Western Europe and the new democracies of Eastern Europe. Although we focus on the current situation in Europe, an overview of the general trends in political participation since the 1960s may help to widen the perspective on the present. We may distinguish between three broad interpretations of trends in political participation in the Western democracies: the democratic crisis scenario, the changing conception of citizenship (Dalton 2008), and the rise of post-materialism (Inglehart and Catterberg 2002). The successive decline in election turnouts in combination with decreasing numbers involved in party membership and party organizations in most countries has led observers and researchers alike to conclusions that suggest a growing democratic crisis (Dalton 2008, p. 2). Since the 1970s, election turnouts have been declining in most countries (Blais 2000; Gray and Caul 2000; Franklin 2004; IDEA 2004; Norris 2002). People are leaving elite organizations and churches are losing members (Putnam 2000). Furthermore, party membership has shown clear downward trends in most countries (Scarrow 2000). The latter findings may be partly explained by the erosion of party loyalty. Voters have become more volatile and change their party preference more often than before. The mass media 110

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have replaced the party organizations as the main source of political information. Political campaigns are increasingly conducted through the mass media and at the expense of local party organizations. Dalton (2004) argues that there is a decline in political support in almost all advanced industrial democracies. Many people, especially the younger generations, increasingly challenge the authority of government by organizing and participating in mass demonstrations. The rise of populist movements in Europe is particularly disturbing, and especially so in reference to radical right and neoNazi organizations. These trends have led many observers of politics and researchers to foresee a general democratic crisis developing in America as well as in Europe. Dalton (2008) argues that the crisis interpretation is premature and stems from a one-sided view of the role of the citizens. He interprets the change as a shift in the balance between the traditional and the new face of citizenship. The core of the traditional citizenship is to be a good citizen, to support the government and to participate in elections. Since the 1970s, a new conception of engaged citizenship has become more common in America. The new face of citizenship inspires more direct, action-oriented political participation in a collective framework. Politics is seen in a wider perspective than just participating in the election process. Whereas the traditional face of citizenship promoted loyalty, the new face promotes autonomy and scepticism of government. The ‘democratic crisis’ is actually a change in the way citizenship is perceived, from being based on norms about the citizen’s duties, to an emphasis on the engaged citizen. The result has been a decline in traditional political participation, but this has been accompanied by a growth in unconventional issue-oriented political actions. In Dalton’s view voting is a form of political participation that demands limited cognitive skills, resources and motivation. As political skills have improved as a result of educational expansion, citizens have realized the limits of voting as a means to influence political change. The increasing skills and changing norms in the public encourage citizens to engage in more demanding forms of political action. The changing citizenship norms are the results of complex changes in social conditions: generational change from post World War II to X and Y generations, the great increase in living standards, the expansion of education, the change in the industrial and occupational structure brought about by the information revolution, the change in gender roles, and the emphasis on civil rights (Dalton 2008, p. 4). Generational change is also at the core of Inglehart and Catterberg’s (2002) interpretation of changes in political activism. In his seminal work on value change in modern societies, Inglehart (1977) predicted a decline in rates of traditional elite-directed political participation and a rise in rates of elite-challenging political activism. The main source of the change would be

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the intergenerational shift from materialist to post-materialist values, as generations who had not experienced the economic depressions of the 1930s entered into the electorate. Materialists tend to be preoccupied with the satisfaction of immediate psychological needs, whereas post-materialists take economic security for granted and orient themselves towards selfexpression and the quality of life. At the same time, the young generations are more educated and have better access to relevant information. In sum, the younger generations have higher levels of political skills than the generations they replace. This change in political skills provides the younger generations with a wider perspective on political participation and therefore they are more able to take part in more demanding, unconventional political actions such as political protests or the boycotting of products. Similarly, Barnes et al. (1979) predicted a spread in unconventional political participation.1 They developed a set of scales to measure both conventional political action, such as voting and writing to one’s representative in parliament; and unconventional forms of political action, such as demonstrations, petitions, boycotts and so on. Finding the latter to be more popular among younger than older persons, they interpreted this as a generational change that would increase the potential for political protests and other forms of unconventional political activism. These predictions from the late 1970s are to a large extent supported by the comparative study of Inglehart and Catterberg (2002), which was based on the European and the World Value Surveys, and Dalton’s study (2008), which was based on data from the USA. The main finding of the former is that a significant change in: elite-challenging political participation has taken place – to such an extent that petitions, demonstrations, boycotts, and other forms of elite-challenging activities are no longer unconventional, but have become more or less normal actions for a substantial part of the citizenry of post-industrial nations. (Inglehart and Catterberg 2002, p. 302)

Such observations have motivated Norris to suggest a change in approach: instead of distinguishing between conventional and unconventional political activism to distinguish between: Citizen-oriented actions, relating mainly to elections and parties, and causeoriented repertoires, which focus attention upon specific issues and policy concerns, exemplified by consumer politics (buying or boycotting certain products for political or ethical reasons), petitioning, demonstrations and protest. (Norris 2007, p. 639–40)

We will continue to use the labels of conventional and unconventional political action, but Norris’ description highlights the main difference

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between the two types of political actions that are described in the empirical part of this chapter.

INDIVIDUAL AND CONTEXTUAL EXPLANATIONS OF POLITICAL ACTIVISM In this section we begin by examining the standard paradigm for explaining political activism (Norris 2007). More recently this has been supplemented by contextual perspectives. In our study the countries are seen as important contexts for political actions and we discuss expectations about differences in the levels of political activism between groups of countries with different democratic traditions. In her recent review, Norris (2007) describes the standard paradigm established by a series of studies in the socio-psychological tradition of the 1960s–70s (Almond and Verba 1963; Verba and Nie 1972; Verba et al. 1978; Barnes et al. 1979). With reference to an explanation concerning who became active, the basic model builds mainly on structural resources, notably education, income, gender, age and ethnicity. Socio-psychological variables were also seen as important motivating forces. People are more likely to participate if they feel informed, interested and efficacious. We build our individual level explanatory model around variables that are suggested by the standard paradigm. We supplement the paradigm by viewing countries as important contexts for political participation. In the simple descriptions we show details for seven types of political actions for each of the 25 countries in our study. In the multilevel analysis, however, we introduce a classification of the countries by democratic traditions as our contextual variable. We distinguish between Nordic countries, the old and the new democracies in Western Europe, and the new democracies in Eastern Europe. The Nordic countries are relatively small, with a rather homogeneous population. They have long traditions in local democracy and have also been characterized by stability and low levels of conflict. Furthermore, the social-democratic tradition common to the Nordic countries, which favours cooperation and local participation, is an important part of their democratic tradition. Therefore, we expect high levels of both types of political participation in the Nordic countries. The lack of serious conflicts leads us, however, to expect low levels of serious protest actions. We also expect similar high levels of political action in the old Western democracies because of their long democratic traditions. The new democracies in Western Europe (Greece, Portugal and Spain) established democratic rules in the 1970s, and share a common past of rule

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through dictatorship. During the dictatorships, political organizations and political activism were actively discouraged. Therefore, we expect rather lower levels of political activism in these countries than in countries with longer democratic traditions. Such an expectation is in accordance with findings reported by Inglehart and Catterberg (2002). The former communist countries in Eastern Europe also had regimes that strongly discouraged local political activity outside the communist party. Yet, elite-challenging political actions played an important role in the democratization process in several of these countries. After the transition from communism to democracy, which took place around 1990, the turnout at the first elections was high. After the early euphoria, however, the post-communist countries experienced disillusionment with democracy. The main reason was the severe economic hardship that large parts of the population had to endure as a consequence of the transition to market economies. Inglehart and Catterberg (2002, p. 300) observe that both participation in elections and the engagement in direct political action declined. In consequence of this change, we expect the lowest levels of political activism in the new democracies in Eastern Europe. This is consistent with the finding in Inglehart and Catterberg (2002) that the level of elite-challenging political actions was lower in the post-communist countries than in the new democracies in the West. Inglehart and Catterberg (2002) also found a positive relationship (r  .5) between economic development of the country measured by the Gross Domestic Product (GDP) per capita, and engagement in political activism. If we relate this to our country classification, the Nordic countries and the old democracies all have high levels of economic development, whereas the post-communist countries are clearly the poorest countries in Europe, with the new Western democracies in the middle. This situation makes it almost impossible to distinguish between the effects of economic development as measured by GDP per capita and democratic culture tapped by the country classification in the multilevel models. It is especially difficult to distinguish between such effects as the number of countries is low. The development described by Inglehart and Catterberg (2002) may be interpreted as a growing tendency for unconventional activism to become an alternative channel of influence. However, earlier research suggests that this view may be too simple. Citizens who are most engaged in conventional political activities may also be active in unconventional political activities (Martinussen 1977, Verba et al. 1978). We pursue this dual political activity by examining the correlations between the two types of political activism at both the individual and the country level. Further, we examine whether the explanatory variables show similar or different relationships to conventional and unconventional political activism.

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DATA AND VARIABLES Our analysis builds on a pooled sample of the two first rounds of the European Social Survey in 2002 and 2004. In this section we document the variables used in the empirical part. We start with our list of dependent variables; the seven separate indicators and the two compound measures of political activism that are based on them. Measures of Political Activism Seven identical questions on political activism were asked in both rounds of the ESS in 2002 and 2004: There are different ways of trying to improve things in [country] or help prevent things from going wrong. During the last 12 months, have you done any of the following? 1. 2. 3. 4. 5. 6. 7.

Contacted a politician or government official Worked in a political party or action group Worked in another organization or association Worn or displayed a campaign badge/sticker Signed a petition Taken part in a lawful public demonstration Boycotted certain products

The first two questions are definitely citizen-oriented actions and relate mainly to elections and parties (Norris 2007). This type of political activism is also known as conventional political participation. Questions 5–7 are definitely cause-oriented repertoires and focus on specific issues and policy concerns. They are also characterized by unorganized or at most ad hoc organized activities. A statistical analysis of the relationships among the questions indicates that question 3 goes with questions 1 and 2. They were used to construct a measure of conventional political activism. A factor analysis shows that question 4 is also related to the first three questions, but more so to the questions on cause-oriented political activism. On this basis, questions 4–7 were used to construct a measure of unconventional or causeoriented political activism. Both measures are counts of the number of each kind of political activity that the respondents had participated in during the 12 months prior to the interviews. This result is a scale of conventional political activism that ranges from 0 to 3 and a scale of unconventional political activism that ranges from 0 to 4. As both scales are heavily skewed towards 0, the statistical analysis is based on collapsed versions of the scales, and only distinguishes between those who have been engaged in the two kinds of political activism and those who have not.

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Individual Level Explanatory Variables The traditional model of explaining political activism in comparative research suggests that structural resources play a significant role in explaining individual differences. In consequence, we should include the familiar sociological background variables: gender, age, education, social class, and income. The gender variable is coded ‘1’ for male and ‘0’ for female respondents. Education is measured in years as reported by the respondents. Social class is based on the Erikson and Goldthorpe (1992) class schema, which distinguishes between a set of classes that range from the upper service class to unskilled workers. In our analysis, we only distinguish between the respondents whose present or last occupation may be classified in the service class (scored 1) and others (scored 0). For income, we use an indirect measure based on a question about coping on present income with four response categories. We recode this question into two categories that distinguish between those who have problems coping on their present income and those who live comfortably on their present income.2 Socio-psychological variables may add to the resource based models of political participation by providing mechanisms that link the structural variables to political activism. Socio-psychological variables may also be seen to have effects on political activism that are independent of the structural variables. In the ESS, we include a question on the respondents’ interest in politics in order to explain political activism.3 In addition, we include political efficacy: the subjective belief that politics may be influenced by the respondent. Political efficacy is measured by these two questions in the ESS: How often does politics seem so complicated that you can’t really understand what is going on? How difficult or easy do you find it to make your mind up about political issues?

Both questions, which have five response categories, are positively correlated and the mean score is used to form a political efficacy scale that ranges from 1 (low) to 5 (high).4 As traditional political participation in elections may be related to political activism, we have added a variable that indicates whether the respondent voted in the last national election or not. Finally, political activism, and especially protest activities, has traditionally been linked to the left side of politics. Therefore, we also include a measure of ideological selfclassification, which is scored so that high values indicate that the respondents see themselves on the left wing of politics.5

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Country Level Explanatory Variables We use only one explanatory variable at the country level: a country classification of democratic traditions. We distinguish between Nordic countries (Denmark, Finland, Iceland, Norway and Sweden), old democracies in Western Europe (Austria, Belgium, France, Germany, Ireland, Italy, Luxembourg, The Netherlands, Switzerland and the United Kingdom), new democracies in Western Europe (Greece, Portugal and Spain), and new democracies in Eastern Europe (the Czech Republic, Estonia, Hungary, Poland, Slovakia, Slovenia and the Ukraine).

RESULTS We start by describing political activism in Europe and present detailed results for each of the seven questions. Then we display country results for the two summary scales of conventional and unconventional political activism. Finally, results from a multilevel binary regression analysis of the two types of political activism are presented. Conventional and Unconventional Political Activism The results for the three questions that tap conventional political activism are displayed in Table 6.1. The numbers represent percentages involved in each activity and the countries are ranked within each activity. The first activity is Contacted politician or government official. The level in Iceland, Norway and Finland is high (23–30 per cent). Denmark is also in the upper part of the ranking with 19 per cent engaged in this type of activity, whereas Sweden only has an average score (15 per cent). The level of the second activity, Worked in political party or action group, is high in Iceland, and Norway (9–14 per cent). The levels in Denmark, Finland and Sweden are, however, only on average on this topic (4 per cent). People in the Nordic region report to have Worked in another organization or association in order to improve things to a larger extent than the rest of Europe. Iceland tops the list with 49 per cent, followed by Finland with 31 per cent, Norway with 27 per cent, and Sweden with 24 per cent. Denmark is a little lower on the list with 20 per cent, which is the same level as Austria, Luxembourg (21 per cent), Holland (20 per cent), Belgium, and Germany (19 per cent). Greece, Portugal and former East European countries like Poland, Estonia, Hungary, the Ukraine and Slovenia show the lowest levels of this type of organizational activity. In Table 6.2 the levels of cause-oriented or unconventional political

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Table 6.1 Conventional political activities over last 12 months, ESS 2002, 2004a (percentages) Contacted politician or government official

%

Worked in political party or action group

%

Worked in another organization or association

%

Iceland Norway Finland Ireland Luxembourg Czech Republic Austria Denmark United Kingdom France Switzerland Belgium Sweden Greece Netherlands Spain Hungary Italy Germany Slovenia Estonia Ukraine Poland Portugal Slovakia

30 23 23 22 20 19 19 19 17 16 16 16 15 14 14 12 12 12 12 12 9 9 8 8 7

Iceland Austria Norway Switzerland Spain Greece France Belgium Ireland Denmark Sweden Luxembourg Finland Ukraine Czech Republic Germany Netherlands Slovenia Italy Slovakia United Kingdom Poland Portugal Estonia Hungary

14 10 9 7 7 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 2 2

Iceland Finland Norway Sweden Austria Luxembourg Denmark Netherlands Belgium Germany France Spain Switzerland Ireland Czech Republic United Kingdom Slovakia Italy Poland Greece Portugal Estonia Hungary Ukraine Slovenia

49 31 27 24 21 21 20 20 19 19 17 17 15 13 10 9 8 8 6 6 3 3 2 2 2

Note:

a

Italy only 2002, Ukraine, Estonia, Iceland, Slovakia only 2004.

activism are displayed. On the first activity, Worn or displayed campaign badge or sticker, there is a wide variation among the Nordic countries. Iceland has the highest level with 34 per cent, Norway is second with 23 per cent, and Finland is third with 15 per cent. The Ukraine is fourth (13 per cent) followed by Sweden and France (12 per cent), and Spain (11 per cent). Denmark is the median country with a level of 7 per cent. The second activity is Having signed a petition within the last 12 months. With levels of participation that range from 38 to 49 per cent, Iceland and Sweden top the list followed by Switzerland, Norway and the UK. Denmark is somewhat

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a

49 45 39 38 38 33 31 29 28 26 25 25 25 25 24 23 17 14 9 9 8 6 5 4 4

% Spain Ukraine Luxembourg Iceland France Italy Norway Germany Switzerland Austria Belgium Sweden Denmark Ireland Greece United Kingdom Portugal Slovakia Czech Republic Netherlands Hungary Slovenia Estonia Finland Poland

Taken part in lawful public demonstration

Italy only 2002, Ukraine, Estonia, Iceland, Slovakia only 2004.

Iceland Sweden Switzerland Norway United Kingdom France Germany Denmark Belgium Austria Slovakia Ireland Finland Luxembourg Spain Netherlands Italy Czech Republic Ukraine Slovenia Poland Portugal Hungary Estonia Greece

34 23 15 13 12 12 11 9 9 8 8 7 7 6 5 5 5 5 4 4 3 3 3 2 2

Iceland Norway Finland Ukraine France Sweden Spain Switzerland United Kingdom Ireland Austria Italy Denmark Belgium Luxembourg Slovakia Germany Czech Republic Netherlands Portugal Poland Estonia Greece Hungary Slovenia

Note:

Signed petition

%

Worn or displayed campaign badge/sticker 26 22 18 15 15 11 10 10 8 8 7 7 7 6 5 4 4 4 4 4 3 2 2 2 1

% Sweden France Iceland Switzerland Finland Denmark Germany United Kingdom Norway Austria Luxembourg Ireland Slovakia Belgium Spain Netherlands Czech Republic Italy Greece Hungary Poland Estonia Slovenia Portugal Ukraine

Boycotted certain products

Table 6.2 Unconventional political activities over last 12 months, ESS 2002, 2004a (percentages)

34 28 28 28 28 26 24 23 22 21 15 12 12 11 11 9 8 8 7 5 4 4 4 3 2

%

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lower with 29 per cent, but still clearly over the median, 25 per cent, where Finland is found. Portugal, Greece and the former East European countries have the lowest percentages of people who have signed a petition. The most typical protest activity is taking part in lawful public demonstrations. In this political activity the Nordic countries show a lower level. Spain tops the list with 26 per cent and the Ukraine follows with 22 per cent. Luxembourg is third at 18 per cent. Iceland is fourth at the same level as France, 15 per cent. Norway is number seven (10 per cent), which is about the same level as Italy and Germany. Sweden and Denmark are median countries, with participation rates of 7 per cent. Participation in public demonstrations in Finland is very low (2 per cent). Only in Poland do we find a lower participation rate. This is the only activity where a Nordic country is below the median value. When it comes to Boycotting certain products in order to improve things, the Nordic countries all show high levels. This type of activism is most frequent in Sweden with 34 per cent. Iceland, Finland, France, and Switzerland follow with 28 per cent and Denmark with 26 per cent. Norway shows the lowest level among the Nordic countries with 22 per cent, but this level is markedly higher than the median of 12 per cent. In summary, we have seen that, although there are differences among the Nordic countries, several of them are found at the top of most of the seven political activities. The Nordic countries do not, however, distinguish themselves from other European countries in the political activity of taking part in lawful public demonstrations. From these seven questions, we formed summary measures of political activism. A total of 25 per cent of the total sample had participated in one or more conventional political activity within a 12-month period prior to the interview. Most of these only participated in one of the three conventional political activities. The participation rate was higher for unconventional political activism as 34 per cent reported one or more of the four activities. Among these around 10 per cent reported two activities. Country percentages for the summary measures of the two kinds of political activism are found in Figure 6.1. Iceland is the star with very high levels of political activism. In the combined classification, the other Nordic countries also excel; as they are found towards the upper right corner of the figure. At the opposite corner of the figure, we find some of the East and South European countries. The figure shows a close relationship between the two kinds of political activism at the country level. This visual impression is confirmed by a strong positive correlation (r  .85). Political activism, and especially participation in unconventional political activities, may be seen as a challenge to traditional political participation in elections. At the country level voter turnout at national elections is

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Political activism Iceland

60

Conventional political activity (%)

50

Finland

Norway

40 Luxembourg

30

Netherlands Czech

Austria Belgium Germany Spain

20

Greece Hungary

10

Estonia Portugal

Sweden

Denmark

Ireland

France Switzerland UK

Italy Slovenia Poland

Slovakia Ukraine

0 10

20

30

40

50

60

70

Unconventional political activity (%)

Figure 6.1 Conventional and unconventional political activities, at least one activity last 12 months by country: correlation at country level, r  .85 positively correlated with both types of political activism: stronger for conventional political activities (r  .40) than for unconventional political activities (r  .27). In other words, there is a tendency, although not a strong one, for countries with high electoral turnouts also to have more political activism than countries with low turnouts. The Multilevel Analysis of Political Activism The purpose of the multilevel analysis reported in Table 6.3 is to offer a more thorough analysis of the individual and contextual roots of political activism in Europe. The dependent variables are the two indicators that differentiate between the respondents who had participated in any conventional and unconventional political activities during the 12 months prior to the interview and those who had not. The analysis builds on a multivariate binary logistic regression model where the separate regression equations for two types of political activism are estimated simultaneously in MLwiN (Rasbash et al. 2004).

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Country classification: Nordic democracies (reference category) Old democracies New democracies in Western Europe New democracies in Eastern Europe

Constant Male Age in years Age in years, squared Years of education Service class Difficult to cope on present income Political interest Political efficacy Left-scale, self-classification b Voted in last national election

b 2.783*** 0.350*** 0.065*** 0.001*** 0.007*** 0.458*** 0.241***

Model 2

0.000 0.577** 1.222*** 1.461***

1.000 0.562 0.295 0.232

Model 2

0.000 0.945*** 0.606** 1.700***

1.000 0.389 0.546 0.183

OR b OR 0.352 1.620*** 0.198 0.948 0.248*** 0.780 1.029 0.005*** 1.005 1.000 0.000*** 1.000 1.009 0.007** 1.007 1.556 0.279*** 1.321 0.845 0.064*** 0.938 0.500*** 1.649 0.140*** 1.150 0.069*** 1.072 0.306*** 1.358

Model 1

Unconventional political activity

OR b OR b 0.062 3.575*** 0.028 1.044*** 1.419 0.181*** 1.199 0.054*** 1.067 0.039*** 1.040 0.029*** 0.999 0.000*** 1.000 0.000*** 1.007 0.003** 1.003 0.009*** 1.582 0.248*** 1.282 0.442*** 0.786 0.093*** 0.911 0.168*** 0.490*** 1.632 0.196*** 1.216 0.020*** 1.020 0.421*** 1.524

Model 1

Conventional political activity

Table 6.3 A multilevel logistic regression analysis of political activities, ESS 2002 and 2004 (n  78810)a

123 0.225 0.490

Correlations in model 2: Individual level: conventional x unconventional Country level: conventional x unconventional

0.155 0.489 0.644

0.040

0.184 0.170 0.089 0.559 0.647

0.073

Notes: a b: logistic regression coefficient in logit scale, OR: odds ratio  exp(b). Level of statistical significance is indicated in this way: * p  .05, ** p  .01, *** p  .001. ICC: intra-class correlation, which shows the proportion of variance in the dependent variables that stem from variation between countries, assuming an individual level variance of 3.29. Correlations are among conventional and unconventional political activism at the individual level and at the country level separately for the null model and model 2. b The result for an instrumental variable that indicated whether the respondent had answered the question on left or right self-classification has been omitted from the table.

0.283 0.845

0.104 0.089

Correlations in null model: Individual level: conventional  unconventional Country level: conventional  unconventional

Proportion of level 2 variance explained by: Compositional effects The country classification Sum, explained by both type of effects

ICC for the null model Intra-class correlations for models 1 and 2 (ICC)

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Let us begin by taking a look at the bottom of the table. The multivariate model provides estimates of the correlation between the two political activism indicators in the null model (the model with no explanatory variables), and the final model (model 2). In the null model, the correlation is 0.85 at the country level and 0.28 at the individual level. The former confirms the high correlation found in Figure 6.1, and the latter indicates that the two kinds of political activism are moderately and positively correlated. The latter implies that persons who are engaged in conventional political activism also tend to be engaged in unconventional political activities, although this tendency is not strong. The intra-class correlation (ICC) for the null model shows the proportion of the variance in the dependent variables that stems from variation among the countries. The proportions are 0.10 for conventional and 0.18 for unconventional political activism. This means that there is clearly more variation among the countries in unconventional than in conventional political activism. The between-country variation in political activism may be explained either by compositional effects that stem from differences among the countries on the characteristics of the respondents, or by country level explanatory variables (the country classification). The ICC for the final model shows the remaining between-country variation after the introduction of explanatory variables at the individual and country level in model 2. For conventional political action the ICC is 0.04 and for unconventional political action, the ICC is 0.07. These results indicate that about 65 per cent of the between-country variation in both types of political activism, for the most part, is explained by the country classification. The compositional effects explain only a minor part of the between-country differences in political activism. Another indication of the importance of the country classification is the residual correlation between conventional and unconventional political activism at the bottom of Table 6.3. Controlling for the country classification in model 2 reduces the correlation between the two types of political activism from 0.85 in the null model to 0.49. We now shift focus to the coefficients for the individual level explanatory variables in Table 6.3. To simplify, the model assumes that the effects of the individual level variables are common for all countries. The coefficients stem from a binary logistic regression analysis. In the first column the regression coefficients in the log-odds (logit) scale are reported. As they are hard to interpret, odds ratios are presented in the second column for each of the two models. The first model contains only structural resources, and the remaining individual variables and the country classification are added in model 2. The results in model 2 reveal that men have on the average 20 per cent higher odds of having reported one or more conventional political activity

125

Political activism 70.0

Political activities (%)

60.0 50.0 40.0 30.0 20.0 10.0 0.0 15 20 25 30 35 40 45 50 55 60 65 70 75 80 Age East unconv

East conv

Nordic unconv

Nordic conv

Figure 6.2 Conventional and unconventional political activities by age in the Nordic and Eastern European countries: model-based estimates from Table 6.3 than women (OR  1.2), and the difference in odds is twice as large in model 1 without the socio-psychological variables. Somewhat surprisingly, the tendency is the opposite for unconventional political activism (OR  0.78), where women are clearly in the lead. The age effect is captured by two variables, age and age squared. This complicates the interpretation of the results. As age is thought to be a central factor in explaining engagement in unconventional political activism, we have displayed the age effect for the two types of political activities in Figure 6.2 with separate curves for the Nordic and the Eastern European countries. In addition to the country differences that are commented on below, the two main observations are the clear differences in both the levels and shape of the age profiles for the two types of political activism. The level of activity is clearly higher for unconventional than for conventional political activities, perhaps with the exception of the oldest respondents. The engagement in conventional political activism tends to

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increase weakly until the respondents are in their late 40s, but then decreases. The age profile for unconventional political activism is quite different. The participation rates are at the peak among the youngest respondents and show a gradual decrease as the age increases. Years of education has only a weak positive effect on political activism in model 2 and not the central role one might expect. The effect of 10 years of extra education is to increase the odds of participation in conventional political activities by about 7 per cent and to increase the odds of engagement in unconventional political activism by 13 per cent. Model 2, which is only based on the direct effects of education, does not, however, tell the whole story. Education may have indirect effects through social class and the socio-psychological variables. The omittance of these variables increases the effect of education dramatically, as ten years of extra education is expected to increase the odds of having participated in both conventional and unconventional political activities by more than 100 per cent. If we revert to Table 6.3, belonging to the most rewarded social class, the service class, strongly increases the chances of engaging in all kinds of political activism. The net effect of being in the service class is to increase the odds of engaging in political activism by around 30 per cent in model 2 and around 50 per cent in model 1 – without the socio-psychological variables. Having difficulties coping on present income is negatively related to conventional political action, but seems to enhance the chances of engaging in unconventional political activities. Next follows the socio-psychological variables that we expect may motivate political activism. Political interest is clearly the most important predictor in this group. The odds of engaging in both conventional and unconventional political activism are about four times higher for persons who are very interested in politics compared to those who have no interest in politics at all. Political efficacy works in the same direction. Those who have the highest level of political efficacy have more than two times higher odds of engaging in conventional political activities than those with the minimum level of political efficacy. The effect is in the same direction, but weaker, for unconventional political activism. Moreover, having voted in the last national election seems to enhance the chances of a person reporting political activism. The odds of having been engaged in conventional political activism are about 50 per cent higher for those who voted than for those who did not. The effect is weaker for unconventional political activism. Protest politics has traditionally been thought of as stemming from left radicalism. This was the motivation for adding the scale for leftist political orientation. Table 6.3 shows that there are statistical significant relationships between the left-scale and both types of political activism. The effect

Political activism

127

is rather weak for conventional political activism, but stronger for unconventional political activism. As far as the latter is concerned, the odds of having engaged in unconventional political activism are twice as high for people on the left as for people on the right end of the scale. The last panel shows the results for the country classification. These results show the net differences among the groups of countries when all individual level explanatory variables are controlled. The Nordic countries form the reference category, the regression coefficient and the odds ratio set to 0 and 1 respectively for comparison. All regression coefficients are negative and statistically significant for both types of political activism. In other words, the Nordic countries show the highest level of conventional as well as unconventional political activities when all individual level variables are controlled. The odds of having been engaged in conventional political activities within the last 12 months for a randomly picked citizen in the old democracies are around 40 per cent lower than the odds for Nordic citizens. The new democracies in Western or Eastern Europe are fairly similar with 70–80 per cent lower odds than for Nordic citizens. Put in another way, the odds of having been engaged in conventional political activities are 1.7 times higher in the Nordic countries than in the old democracies, and between three and four times higher than in the new democracies in Europe. The differences among the groups of countries are even larger for unconventional political activism. The Nordic countries show the highest levels of activity, and the countries in Eastern Europe show the lowest engagement in unconventional political activities. The middle categories, the old and the new democracies in Western Europe, show similar levels of unconventional activism. The odds of a randomly picked citizen having engaged in one or more unconventional political activities within the last 12 months in the two latter country categories are 50–60 per cent lower than the odds in the Nordic countries. In Eastern Europe the odds are 80 per cent lower. In other words, the odds of having engaged in unconventional political activities are between 1.8 and 2.5 times higher in the Nordic countries than in other West European countries, and more than five times higher than in Eastern Europe. The contrast between the two extreme country categories is displayed in Figure 6.2 with separate age-participation profiles for the Nordic and East European countries.

DISCUSSION If we begin with the individual level relationships, we found no consistent gender differences. Men are more frequently engaged in conventional political activism than women, but for unconventional political activism women

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are ahead of the men. Age is related to both types of political action, but the age-participation profiles are different. The level of unconventional political action is highest among young people but declines at an even rate in relation to increased age. Conventional political action, on the other hand, shows an increase up to the ages of 40–50, but declines in later years. The age differences may be a result of either age or cohort effects. An age effect will imply that persons change according to the observed age profiles as they grow older. A cohort effect is a stable generational effect that will leave a lasting imprint on the individuals. As our study is based on a crosssectional study, we are unable to empirically distinguish between the two interpretations. However, a longitudinal study from Norway indicates that unconventional actions are related to age rather than generation (Berglund 2006). In Norway, citizens sign campaigns and participate in demonstrations in their twenties, but then they withdraw from this area. This pattern might fit with the pattern we have shown above, but we need more research, or rather adequate time series, in order to reveal whether political activism is a matter of generation or life-cycle. Furthermore, education matters, and especially for unconventional political action, and is mainly mediated through the effects of the socio-psychological variables. Having a job located in the service class increases the chances of engaging in political activities in general. Interest in politics represents an important motivating factor for political activism. Furthermore, political efficacy works in the same direction although the relationship is weaker. Traditional political participation in terms of having voted at the last national election is positively related to political activism, and especially so for conventional political activities. Our multilevel analysis shows that country-specific conditions have a significant impact on the level of political activism even after controlling for individual level variables. The level of both conventional and unconventional political activism is highest in the Nordic countries, followed by the old democracies in Western Europe. The new democracies in Western Europe (Greece, Portugal and Spain) show levels of political activism that are only slightly higher than the new democracies in Eastern Europe, which have the lowest levels of political activism. Among the Nordic countries, Iceland is clearly the one with the highest level of political activism, Sweden and Norway show somewhat lower levels of political activism, but significantly higher than Finland. For Denmark, the level is the lowest among the Nordic countries, and at about the same level as in the old democracies. Lastly, our analysis shows that the two types of political activism are positively correlated in Europe; only moderately so at the individual level (r.28), but strongly correlated at the country level (r.85). The individual level variables, with the exception of gender and age, show a quite

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129

similar relationship to conventional and unconventional political participation. Moreover the net country differences were somewhat larger for unconventional than for conventional political activism. The findings are consistent with recent research that shows unconventional political activities are becoming more frequent than conventional political activities. The correlation between the two types of activism shows, however, that quite a few citizens manage to be political omnivores.

NOTES 1. Note that Barnes et al. (1979) focused mainly on the citizens’ attitudes towards different forms of political activism. 2. Which of the descriptions on this card comes closest to how you feel about your household’s income nowadays? 1. Living comfortably on present income. 2. Coping on present income. 3. Finding it difficult on present income. 4. Finding it very difficult on present income. 3. How interested would you say you are in politics – are you . . . very interested (1), quite interested (2), hardly interested (3), or, not at all interested (4). Note that we have reversed the scale so that high values mean high interest in politics. 4. The internal consistency of the scale as measured by Cronbach’s alpha is 0.62. 5. In politics people sometimes talk of ‘left’ and ‘right’. Using this card, where would you place yourself on this scale, where 0 means the left and 10 means the right? Note that we have reversed the scale so that high values mean being on the left side of politics.

REFERENCES Almond, Gabriel A. and Sidney Verba (1963), The Civic Culture: Political Attitudes and Democracy in Five Nations, Princeton, NJ: Princeton University Press. Barnes, Samuel H., Max Kaase, Klaus R. Allerbeck, Barbara G. Farah, Felix Heunks, Ronald Inglehart et al. (1979), Political Action. Mass Participation in Five Western Democracies, Beverly Hills, CA: Sage Publications. Berglund, Frode (2006), ‘Same procedure as last year? On political behavior amongst senior citizens’, World Political Science Review, 2 (1), article 1, available at www.bepress.com/wpsr/vol2/iss1/art1/. Blais, André (2000), To Vote or Not To Vote. The Merits and Limits of Rational Choice Theory, Pittsburgh, PA: University of Pittsburgh Press. Dalton, Russel J. (2004), Democratic Challenges, Democratic Choices. The Erosion of Political Support in Advanced Industrial Democracies, Oxford: Oxford University Press. Dalton, Russel J. (2008), The Good Citizen. How a Younger Generation is Reshaping American Politics, Washington, DC: CQ Press. Erikson, Robert and John H. Goldthorpe (1992), The Constant Flux. A Study of Class Mobility in Industrial Societies, Oxford: Clarendon Press.

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Franklin, Mark N. (2004), Voter Turnout and the Dynamics of Electoral Competition in Established Democracies since 1945, Cambridge: Cambridge University Press. Gray, Mark and M. Caul (2000), ‘Declining voter turnout in advanced industrial democracies, 1950–1997’, Comparative Political Studies, 33 (9), 1091–122. IDEA (2004), Voter Turnout in Western Europe Since 1945: A Regional Report, Stockholm: International Institute for Democracy and Electoral Assistance (IDEA). Inglehart, Ronald (1977), The Silent Revolution: Changing Values and Political Styles among Western Publics, Princeton, NJ: Princeton University Press. Inglehart, Ronald and G. Catterberg (2002), ‘Trends in political action: The development trend and the post-honeymoon decline’, International Journal of Comparative Sociology, 43 (3–5), 300–316. Martinussen, Willy (1977), The Distant Democracy. Social Inequality, Political Resources and Political Influence in Norway, London: Wiley. Norris, Pippa (2002), Democratic Phoenix: Reinventing Political Activism, Cambridge: Cambridge University Press. Norris, Pippa (2007), ‘Political activism: New challenges, new opportunities’, in Charles Boix and Susan C. Stokes (eds), Oxford Handbook of Comparative Politics, Oxford: Oxford University Press, pp. 628–49. Putnam, Robert D. (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Rasbash, Jon, Fiona Steele, William Browne and Bob Prosser (2004), A User’s Guide to MLwiN Version 2.0. Bristol: Centre for Multilevel Modelling, University of Bristol. Scarrow, Susan (2000), ‘Parties without members? Party organization in a changing world’, in Russel J. Dalton and Martin P. Wattenberg (eds), Parties without Partisans: Political Change in Advanced Industrial Democracies, Oxford: Oxford University Press, pp. 79–101. Verba, Sidney, Norman H. Nie (1972), Participation in America: Political Democracy and Social Equality, New York: Harper & Row. Verba, Sidney, Norman H. Nie and Jae-On Kim (1978), Participation and Political Equality: A Seven Nation Comparison, New York: Cambridge University Press.

7.

Trust in political institutions Ola Listhaug and Kristen Ringdal

INTRODUCTION In this chapter we investigate how the Nordic countries rank on political trust in Europe. Citizens’ trust in the major institutions in a society is important for the state of democracy as well as for the functioning of broader social and economic processes in society. High trust levels signify that institutions are working effectively, thus reducing the chance that nondemocratic forms of government will receive support. High trust levels facilitate social and economic exchange and reduce transaction costs in markets. Trust reduces the need for control and supervision, which saves money for the government as well as for firms and other actors in the private sector. In the comparative dimension, countries with high trust will be at an advantage in attracting investments, trade and tourism. For these reasons we see political trust as a success criterion for societies. Based on what we know from previous research, the Nordic countries place favourably on political trust measures. But, whereas we know that the Nordic countries score high on political trust, we know little about the reasons behind this pattern. Is there a peculiar quality to the Nordic countries – a Nordic model (Østerud 2005) – or is their success in creating political trust among their citizens primarily a reflection of the fact that they are small, rich, and homogeneous in social and economic terms? Are there other countries that share these characteristics and also have high levels of political trust? In most cases high trust levels are only possible to achieve when institutions receive support from major social and political groups in society. This is an indicator that social integration is working successfully. At a time when divisions in societies may regain their importance because of the immigration of groups that differ by religion and other cultural aspects from native populations, support for institutions that bind groups together becomes increasingly important. The recent territorial expansion of the European Union, the establishment of the European Economic Area, and the Schengen treaty area are factors that facilitate geographical mobility, and, indirectly, contribute to the increasing ethnic diversity of European countries. 131

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Trust in political institutions is part of a wider concept of political trust that builds on a classification by Easton (1965) and is available in a more recent version by Norris (1999). This conceptualization classifies trust in a hierarchy that ranges from specific to general: political actors (elected political officials and political leaders), regime institutions (electoral institutions, order institutions, public service institutions), regime performance (evaluation of how the actual democracy works), regime principles (support for the basic ideas of democracy), and political community (identification with the nation). Political trust is not limited to the nation state but is increasingly relevant at supranational level. In Europe, trust in the European Union is crucial as the EU is in the process of increasing its political authority over the member states. The success of the Union will depend on how strongly the evolving institutions are able to connect with the identifications and interests of the publics in the member states. The EU might be successful in economic terms, but a broader cultural unity is lacking. In the words of Johan P. Olsen: The EC/EU has had some success in conceptualizing Europe as an economic unit, but less so with the idea of political, cultural, and social unity in Europe based on a common heritage such as Christendom, Latin, and Roman Law, or common, future political projects. (Olsen 1995, p. 26)

Although this remark was made more than ten years ago, its relevance has increased with the increased political and cultural diversity of the EU resulting from the inclusion of new member states from Eastern Europe, and the potential inclusion of Turkey, a major Muslim country. It seems obvious that citizens’ trust in EU institutions is a key measure of the success of the European Union in establishing a more firmly grounded legitimacy. In this chapter we restrict the analysis of political trust at the EU level to the support for the European Parliament. Our expectations for trust in the EU institutions are different from what we expect for national institutions. The Nordic countries have had a problematic relationship with the European Union. Norway has twice rejected membership in national referendums. Iceland is not a member, and Denmark, a member since 1973, has on several occasions been at odds with the EU on important policy directions and institutional reforms. Sweden and Finland became members in 1995. Finland has had some success in mobilizing public support for EU institutions, while Swedish mass publics have been quite negative towards membership. We expect that trust in the European Parliament will reflect the basic EU orientations and experiences with EU membership and show a quite different pattern across the five countries than trust in national political institutions.

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133

RECENT RESEARCH: TRENDS AND COMPARISONS Recent research on trust in institutions and other aspects of political trust has been overwhelmingly associated with concerns for trends – is trust declining or not? The large ‘Beliefs in Government’ project (BIG) of the European Science Foundation published its findings in 1995 (but time series data ended c. 1990) and concluded that there was no general decline in political trust in Western Europe (Klingemann and Fuchs 1995). Pippa Norris (1999) concluded in her follow-up of BIG (she extended the time series past the mid-1990s and broadened the data to cover non-Western countries) that citizens remained committed to the values of democracy, but had become more critical of the core institutions of democracy. In the most recent work on trends in political trust Russell Dalton demonstrated that political trust is declining in advanced industrial countries (Dalton 2004). The ‘Third Wave’ of democratization and the process of globalization have stimulated studies that take a closer look at political trust in a comparative perspective. Much of the comparative research on political trust uses data from the European Values Study/World Values Survey (EVS/ WVS). These surveys have been performed in more than 80 countries and territories and cover all inhabited continents and constitute the most global dataset that we have of relevant data on trust. All surveys have included at least some questions on political trust, and a number of the survey waves have had political trust and support of democracy as a major topic. Using Values Survey data from 1995 to 1997 Klingemann (1999) found that support for democratic ideals and principles is robust in all parts of the world, but the support is somewhat stronger in Western Europe than in the rest of the countries. Listhaug and Aardal (2003) performed a detailed analysis of variations of democratic support in Europe using EVS data from 1999/2000. On the basis of Freedom House indicators, and building on previous research by Klingemann (1999), they classified European countries in three groups: stable democracies (countries in Western Europe), new democracies (most of the post-communist countries in Central and Eastern Europe), and transitional democracies (Croatia, Russia, Ukraine and Belarus). They compared these countries on five dimensions of political trust: how the current system is rated compared to the communist regime, satisfaction with how democracy is developing, rejection of non-democratic forms of government, rejection of criticism of democracy, and support for democracy as a principle. They found that on all dimensions, support levels are higher in stable democracies than in new democracies and that the transitional regimes on most of the indicators have the lowest trust readings. The

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negative findings for new democracies and transitional regimes remained when they were controlled for an extensive set of variables that are related to trust. In an extension of this analysis, Anderson et al. (2005) showed that the gap in political trust between winners and losers is larger in new democracies and transitional regimes than in the stable democracies in Western Europe. While it is quite normal for voters who support parties that lose elections to become less trusting towards the political system, the gap between losers and winners should be kept within a reasonable margin. With the definitions and measures that we use it is difficult to decide whether the gap falls outside a boundary where the low trust of losers can be a critical factor for the survival of the democratic system. The study by Listhaug and Aardal (2003) provides some information about the rankings of the Nordic countries. This study is based on the European Values Study data from 1999/2000 and only Denmark, Finland and Sweden are included. Among these countries, Denmark has consistently the highest ranking, and is also one of the countries with the strongest support for democratic values among all European countries. Sweden, and, even more so Finland, demonstrated a somewhat lower support level. One could argue that for all stable democracies the support levels for democratic values are so high that variations within this group are not necessarily of importance. For established democracies it might be more meaningful to compare trust levels in the medium and lower levels of the trust hierarchy, like confidence in institutions and trust in politicians. With data from the first two waves of the European Values Study in 1981 and 1990 Listhaug and Wiberg (1995) compared confidence in six government institutions for the countries in Western Europe. Their analysis includes four Nordic countries, although data for Iceland and Denmark were only available for 1990. At the first time point, Norway is clearly number one for trust in government, but Sweden and Iceland (data were collected in 1984) are also in the top half. In 1990, Norway and Iceland are on top (in that order) and Sweden is about in the middle of the rankings. Extending this time series with data from the 1995–97 World Values Survey, Listhaug (2005) demonstrated that the Nordic countries in the survey, Finland, Norway, and Sweden, remain highly ranked among European countries. Once more, Norway is on top, and is especially strong on trust in parliament. More recently, political trust in Norway has declined, and there are indications that the country’s comparative status in trust rankings has suffered as well. Norway is unique among developed countries as it has an important oil sector that produces a huge surplus in government budgets. The economic

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surplus is put into an oil fund that is invested abroad. The contrast between a growing pile of money that cannot be touched, and citizens’ preferences for spending more to solve problems in Norway, may have led to frustrations that have fuelled the new distrust. A weakness of the studies cited above is that few systematic explanations are introduced to make sense of comparative patterns. In some cases, this might be explained by the fact that we have data from a small number of countries, which makes it difficult to test hypotheses about cross-national variations. In this chapter we attempt to improve on previous research by introducing a more rigorous measurement of trust differences as well as estimating statistical models that include variables that are relevant to explain comparative differences in political trust.

THE MODEL The standard model to explain variations in political trust at the individual level includes two main categories of independent variables: political distance and performance evaluations. We expect that an increasing political distance between government and citizens will lead to a decline in trust. Distance is primarily measured as policy distance on the salient issues of the day as developed in the classic article by Miller (1974), but may also include measures of ideological distance or distance by party through the division of voters who vote for winning parties and those who are on the losing side (Miller and Listhaug 1990, 1998; Anderson and Guillory 1997; Anderson et al. 2005). Political distance can sometimes result in a curvilinear pattern, for instance when voters on either side of the political spectrum are more distrusting than voters in the political centre. This result can be explained by the fact that most governments are either centre-left or centre-right, which can alienate citizens on both sides. Political distance is measured on issues where citizens take different sides or positions. In contrast to this scenario we can have a situation where the electorate agrees on policy positions. In this case policy distance to government becomes irrelevant for political trust. What counts is government performance; how well the government is able to fulfil the goals that citizens agree on. Most of the research on performance tests hypotheses about performance of the economy: good times breed trust in government, bad times lead to a decline in trust levels (Listhaug 2006). Huseby (2000) has extended the analysis of performance to the environment and social policy (care for the elderly and health policy). These policy areas have relatively high consensus about the goals – at least in the Nordic countries. Therefore,

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performance considerations become dominant and trust will be affected by evaluations of how good a job the government is doing in providing care for the elderly and the sick. It is likely that factors that account for variations in trust levels between citizens will also be relevant in the explanation of variations among countries. In most of the reported research, the Nordic countries are placed at the high end of political trust distributions. By most accounts, the policy distances between citizens and government in these polities are small, which possibly reflects an egalitarian social and economic structure and populations that are homogeneous along divisions. Moreover, the Nordic countries have systems of proportional elections that strengthen the political representation of all social and political groups, further reducing political divides. The Nordic countries are also relatively rich and their economies have performed well over extensive periods of time. All are welfare states that take care of basic needs based on universalistic principles. At times the Nordic economies have suffered downturns, such as in Finland in the 1990s, and Sweden has also had problems in keeping up economic growth. Needless to say, the active role of government in solving problems and providing services for citizens tends to increase expectations that are difficult to meet. This is obvious in the current oil case of Norway, but may also have a more general relevance. In the empirical analysis to follow, we attempt to answer two research questions. First, we simply ask where the Nordic countries rank on the various dimensions of political trust. Based on previous research and theoretical arguments, we expect trust in national political institutions to be relatively high when compared with other European countries. For trust in the European Union this expectation will not necessarily be true, because the membership issue has been contentious in the Nordic countries. The second research question attempts to sort out explanations for the crossnational variations in trust. We make a distinction between micro and macro explanatory variables. The set of micro variables includes measures of policy issues that are relevant for political distance, performance evaluations, and demographical controls. The results of this analysis will tell us how much the placement of the Nordic countries can be explained by compositional effects. In addition, we include two macro variables: (natural log of) the size of the country’s population and country’s score on the UN Human Development Index (HDI). The effects of these variables will tell us if the Nordic countries are distinct on political trust because they are small, or because they are rich and highly developed. As an alternative to the detailed macro variables, we introduce a country classification mainly based on welfare regimes.

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METHODS In order to answer the second research question, we employ a multilevel analysis of pooled data from the ESS 2004 covering 24 countries. In the multilevel analysis the respondents constitute level 1 and the countries constitute level 2. The basic multilevel model with a random intercept, used in this chapter, is described in the Appendix. The variables to be used in the multilevel analysis are described below. Political Trust Indicators The ESS 2004 includes seven questions on political trust that cover both national and international political institutions. The questions were introduced in this way: Using this card, please tell me on a score of 0–10 how much you personally trust each of the institutions I read out. 0 means you do not trust an institution at all, and 10 means you have complete trust. First . . . . . . the country’s parliament (B4) . . . the legal system (B5) . . . the police (B6) . . . politicians (B7) . . . political parties (B8) . . . the European Parliament (B9) . . . the United Nations (B10)

Our analysis is based on all the questions except the item about the United Nations. The items that we analyse tap trust for the electoral system (B4, B7, B8), trust in the legal system (B5, B6), and trust in the European Parliament (B9). Individual Level Explanatory Variables These include a set of demographic characteristics, measures of political distance, a set of indicators of performance evaluations, and a set of questions on political issues. The first group: age in years, age squared, and years of education, are included mainly as controls. Political distance is measured in two ways. The first one is whether or not the respondent voted for a party now in government at the last parliamentary election. The second indicator is the left–right scale based on this question: In politics people sometimes talk of ‘left’ and ‘right’. Using this card, where would you place yourself on this scale, where 0 means the left and 10 means the right?

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The first political issue is about immigrants. We formed a scale as the mean of the scores on three questions about negative or beneficial consequences of immigration: ● ● ●

Would you say it is generally bad or good for [country]’s economy that people come to live here from other countries? And . . . would you say that [country]’s cultural life is generally undermined or enriched by people coming to live here from other countries? Is [country] made a worse or a better place to live by people coming to live here from other countries?

The wording at the ends of the 0 to 10 scales varies, but 0 indicates that the consequences are bad and 10 that they are positive. The scale computed as the mean score on the three questions, ranging from 0 to 10, has excellent psychometric properties. It is one-dimensional with high internal consistency (Cronbach’s alpha = 0.84). Next, there are three single questions on different issues. A question from the supplementary self-completion questionnaire is used to make a 0–1 indicator of support for the environment: He/she strongly believes that people should care for nature. Looking after the environment is important to him/her. This question on self-description has response categories ranging from 1, ‘Very much like me’, to 6, ‘Not like me at all’. The two first categories are coded as 1 and the remaining ones are coded 0. We also include a question on income differences: The government should take measures to reduce differences in income levels. The response categories range from 1, ‘Agree strongly’, to 5, ‘Disagree strongly’. The scoring of the question is reversed in our version so that high values mean support for government action to reduce income differences. The final issue included in our analysis is about European unification: Now thinking about the European Union, some say European unification should go further. Others say it has already gone too far. Using this card, what number on the scale best describes your position? [0, Unification has already gone too far . . . 10, Unification should go further]

We include two categories of performance evaluations: assessments of personal well-being and life satisfaction, and an evaluation of how well the country is doing. Life satisfaction is measured by the following question: All things considered, how satisfied are you with your life as a whole nowadays? Please answer using this card, where 0 means extremely dissatisfied and 10 means extremely satisfied.

In addition, we include a question on income adequacy:

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Which of the descriptions on this card comes closest to how you feel about your household’s income nowadays? 1. Living comfortably on present income. 2. Coping on present income. 3. Finding it difficult on present income. 4. Finding it very difficult on present income.

We recode this question into two categories, which distinguish between those who cope or may live comfortably on present income and those who find it difficult. We also include three variables that tap the extent to which the respondent is satisfied with the present state of the economy, education, and the health services: ● ● ●

On the whole how satisfied are you with the present state of the economy in [country]? Still use this card [0 = Extremely bad – 10 = Extremely good]. Now, using this card, please say what you think overall about the state of education in [country] nowadays? Still using this card, please say what you think overall about the state of health services in [country] nowadays?

Country Level Explanatory Variables The low number of countries places severe restrictions on the number of country level variables that are meaningful to include. The two main dimensions covered by our two indicators are the size of the country, which is measured by the natural logarithm of population size, and the standard of living, as measured by the Human Development Index (HDI) published by the United Nations Development Program (UNDP) since 1990. We also tried out gross national product (GDP) per capita and the increase in GDP, but their explanatory power is largely captured by the other two macrovariables. GDP alone was also clearly inferior to the HDI. The macro variables are frequently strongly correlated. The reason for this is that countries tend to cluster, especially towards the ends of the scales. For example, the Nordic countries are small, rich, have long democratic traditions, and they are peaceful. This reduces the possibilities of disentangling the effects of each country characteristic. Another way of dealing with the strong correlations among the macro variables is to replace them with a country classification. We use a classification according to welfare regimes (Arts and Gelissen 2002), and add an extra category for Eastern Europe (Czech Republic, Estonia, Hungary, Poland, Slovakia, Slovenia, and Ukraine). In addition, we distinguish between the Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden), Anglo-Saxon countries (Ireland and the United Kingdom),

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Continental countries (Austria, Belgium, France, Germany, Luxembourg, The Netherlands, and Switzerland) and Southern Europe (Spain, Greece, and Portugal). We use the Nordic countries as the reference category in our multilevel analysis.

RESULTS In this section we present the results of the empirical analysis. We attempt to answer our two research questions. First, we ask where the Nordic countries are located in the rankings of political institutions; are these countries still at the top of the list as previous research has demonstrated? Second, which factors can explain the trust levels? We pursue factors both at country level and at the individual level. Gross Country Differences in Political Trust In Table 7.1, we display the country means on the political trust indicators. The countries are listed from high to low scores on each of the six questions. The Nordic countries are printed in bold so that they will be easy to identify. We may first note that there are large differences in political trust between the countries as the mean ranges from 6–7 to around 2. The midpoint between no trust and complete trust is 5 (on the 0–10 scale). Furthermore, trust in the legal system is higher than trust in the electoral system. Trust in the European Parliament is weaker than for trust in national institutions, and the differences between countries are smaller. The high percentage of ‘Do not know’ answers to the EU question reflects the lower saliency of that institution when compared with national institutions. It is evident that political trust in the Nordic countries is high compared with other countries. For trust in national political institutions the Nordic countries are found in the top group for all institutions. Denmark is the clear leader and tops the ranking for four of the five institutions and is number two on the fifth, police, where Finland holds the top position. All five countries are placed in the top third on all rankings, with a minor exception for trust in politicians, where Sweden is number nine of the 24 nations. Norway, which used to be a leader in political trust, is now in the lower part of the Nordic distribution, which provides further support for the theory that the big oil fortune that Norway is building in foreign investments leads to frustrated economic expectations that undermine political trust (Listhaug 2005). As expected, we find that trust in the European Parliament shows a quite different distribution. The Nordic countries are now scattered, with a

Trust in political institutions

Table 7.1

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Political trust in 2004: country means

A. Trust in country’s parliament Denmark 6.286 Finland 6.009 Iceland 5.924 Luxembourg 5.762 Switzerland 5.517 Norway 5.424 Sweden 5.351 Spain 5.089 Ukraine 4.797 Austria 4.775 Ireland 4.713 Greece 4.687 Belgium 4.682 Netherlands 4.668 United Kingdom 4.288 France 4.269 Germany 4.214 Estonia 4.191 Slovenia 4.127 Portugal 3.719 Hungary 3.634 Czech Republic 3.186 Slovakia 3.051 Poland 2.405

B. Trust in politicians Denmark Luxembourg Iceland Finland Switzerland Netherlands Norway Belgium Sweden Ireland Ukraine Spain Greece United Kingdom France Estonia Austria Germany Slovenia Czech Republic Hungary Slovakia Portugal Poland

5.589 5.178 4.971 4.877 4.770 4.690 4.244 4.240 4.191 3.924 3.736 3.685 3.595 3.589 3.486 3.315 3.254 3.230 3.099 2.727 2.682 2.526 2.058 1.917

C. Trust in political parties Denmark Finland Luxembourg Iceland Netherlands Switzerland Sweden Norway Belgium Ireland United Kingdom Spain Ukraine Greece France Austria Slovenia

D. Trust in the legal system Denmark Finland Norway Switzerland Luxembourg Iceland Austria Sweden Germany Netherlands Greece Ireland United Kingdom Estonia Belgium France Spain

7.214 6.897 6.352 6.140 6.137 6.009 5.829 5.769 5.542 5.496 5.382 5.205 5.116 4.907 4.830 4.766 4.717

5.647 4.996 4.971 4.885 4.800 4.636 4.398 4.340 4.286 3.973 3.676 3.668 3.611 3.505 3.397 3.396 3.209

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Table 7.1

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(continued)

Germany Estonia Czech Republic Hungary Slovakia Portugal Poland

3.184 3.088 2.745 2.711 2.663 2.085 1.891

Hungary Portugal Ukraine Slovenia Czech Republic Slovakia Poland

4.429 3.939 3.910 3.849 3.720 3.583 3.006

E. Trust in the police Finland Denmark Iceland Norway Switzerland Ireland Sweden Germany Luxembourg Austria United Kingdom Greece Netherlands Spain Belgium Estonia France Hungary Portugal Slovenia Poland Slovakia Czech Republic Ukraine

7.956 7.936 7.279 7.131 6.858 6.589 6.486 6.477 6.472 6.185 6.116 6.031 5.967 5.906 5.784 5.692 5.661 5.174 5.056 4.710 4.576 4.352 4.226 3.299

F. Trust in the European Parliament Ireland 5.370 Greece 5.344 Iceland 5.288 Hungary 5.223 Luxembourg 5.223 Spain 5.051 Finland 4.996 Belgium 4.983 Estonia 4.874 Denmark 4.833 Ukraine 4.826 Slovakia 4.738 Switzerland 4.609 Netherlands 4.606 Norway 4.552 Slovenia 4.534 Czech Republic 4.383 France 4.306 Poland 4.261 Germany 4.183 Portugal 4.037 Austria 4.022 Sweden 3.955 United Kingdom 3.548

non-member country, Iceland, in third place, Finland is number seven, Denmark is in tenth place, Norway is number 15, and Sweden is next to last among the 24 countries. On average, the Nordic countries score weakly on European trust compared with trust in national political institutions. The similarity in the rankings across the five indicators of trust in national political institutions indicate that the data may be simplified by constructing one or more composite scales based on the five indicators. There are two advantages of scales as opposed to single indicators: first, the

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number of dependent variables in our analysis will be smaller, and second, composite measures have large variability and are more reliable than each single indicator. A factor analysis of the five questions on trust in national institutions gave a one-dimensional solution in the total sample. However, it is important to validate the measurement model by looking at each country separately, and having done so, a clear picture emerges. Two factors are needed to obtain a measurement model with a similar factor structure across all the countries. These two factors explain more than 78 per cent of the variation in the five indicators in all countries. Not surprisingly, the first dimension covers trust in the electoral system and the second dimension captures trust in the legal system. We therefore constructed a scale for each of the dimensions as the means of the scores on each of the relevant indicators. Both scales measuring trust in the electoral and in the legal system have excellent psychometric properties. They are one-dimensional and their internal consistency, which is measured by Cronbach’s alpha is 0.90 and 0.79 respectively. The mean scores for each country on the two scales are show graphically in Figure 7.1. The high correlation between the two political trust dimensions at the country level is clearly visible in that the points for the countries are found along a narrow band from the lower left to the upper right corner. The actual correlation at the country level is .90. The scales are also rather strongly correlated at the individual level (r = .65). The clusters of countries are evident, with the Nordic countries plus other smaller rich countries at the top on both dimensions, whereas the four Eastern European countries are found in the lower left corner, as they scored low on trust both in the electoral and in the legal systems. This brings us to our multilevel analysis which has two purposes. First, we attempt to explain the observed differences among the countries and, second, to estimate within-country differences captured by the individual level explanatory variables in the model. A Multilevel Analysis of Political Trust The dependent variables in the multilevel analyses are the three measures of trust; in the electoral, the legal system, and in the European Parliament. The explanatory variables include demographic controls and political distance measures: voted for the party in government, and the left–right scale. In order to capture non-linear relationships to political trust, the left–right scale is decomposed into six categories with the middle category as the reference category in the multilevel analyses. The remaining individual level explanatory variables are the performance evaluation indicators and the political issue indicators. Finally, three country level explanatory variables,

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Nordic social attitudes in a European perspective 7.00

Trust in electoral system, country mean

6.00

DK IS LU

5.00

CH

NL BE ES

UA

4.00

FR EE

SI 3.00

FI

SE

IE

NO

GR AT GB DE

CZ SK

HU PT

PL

2.00

1.00 3.00

4.00

5.00

6.00

7.00

8.00

Trust in legal system, country mean Note: AT  Austria; BE  Belgium; CH  Switzerland; CZ  Czech Republic; DE  Germany; DK  Denmark; EE  Estonia; ES  Spain; FI  Finland; FR  France; GB  United Kingdom; GR  Greece; HU  Hungary; IE  Ireland; IS  Iceland; LU  Luxembourg; NL  Netherlands; NO  Norway; PL  Poland; PT  Portugal; SE  Sweden; SI  Slovenia; SK  Slovakia; UA  Ukraine.

Figure 7.1

Trust in electoral and legal system: gross country means

the HDI, the natural logarithm of population size, and the country classification, are included in some models. The results from the multilevel analyses of the three political trust measures are presented in Tables 7.2–7.3. Table 7.2 shows the variance components in four models for each of the three dependent variables. Model 0, the null model, has no explanatory variables. Its purpose is to split the variance in the dependent variables into a within-country or individual level component (Se) and a between-country or country level component (Su). These components are also the basis for the calculation of the intra-class correla-

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Table 7.2 Variance components from a multilevel regression analysis of political trust in Europea Model 0 Model 1 Model 2 Model 3 Model 4 Trust in electoral system Individual level variance (Se) 3.670 3.631 2.706 2.706 2.706 Country level variance (Su) .897 .866 .282 .265 .196 Explained individual level .000 .011 .262 .262 .262 variance Explained country level .000 .035 .686 .704 .782 variance Intra-class correlation .196 2 Log likelihood 132929.5 132588.3 123138.4 123137.0 123130.1 Trust in legal system Individual level variance (Se) 4.136 4.109 3.282 3.282 3.282 Country level variance (Su) 1.198 1.157 .444 .302 .207 Explained individual level .000 .006 .207 .207 .207 variance Explained country level .000 .034 .629 .748 .827 variance Intra-class correlation .225 2 Log likelihood 138153.8 137943.9 130637.3 130628.5 130619.9 Trust in European Parliament Individual level variance (Se) 5.296 5.181 4.124 4.124 4.124 Country level variance (Su) .235 .229 .318 .165 .144 Explained individual level .000 .022 .221 .221 .221 variance Explained country level .000 .022 0b .296 .385 variance Intra-class correlation .042 2 Log likelihood 135063.7 134404.7 127582.5 127567.51 127564.5 Notes: a Model 0: only intercept, Model 1: M0  demographic variables, Model 2: M1  attitudinal variables, Model 3: M2  country variables, Model 4: M2  country classification. Explained variance: proportion of the variance in the null model explained by models 1–4. All variance components are statistically significant at the .01 level. b Because of an increase in the between-country variance component this value is set to zero.

tion, which shows the proportion of the variance in the dependent variable that is a result of differences between the countries. This proportion is 0.20 and 0.23 for trust in the two national institutions, but only 0.04 for trust in the European Parliament.

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Table 7.3 A multilevel analysis of political trust in Europe: fixed regression coefficients from model 3a Description

Trust in electoral system B

Regression constant Age in years Age in years squared Gender, 1  male, 0  female Years of full-time education Voted for government party? Did not vote, did not know Yes No (reference category) Left–right scale 0–2 Left 3–4 Left 5 Middle (reference category) 6–7 Right 8–10 Right Do not know Immigration good for country Environment important Government should reduce income differences EU unification should go further How satisfied with life as a whole Living comfortably on family income How satisfied with economy in country State of education in country State of health services in country

.248 5.508 .025*** .006* .000*** .000* .086*** .104*** .009** .014*** *** *** .201*** .156*** .178*** .091** .000 .000 *** *** .078* .300*** .090** .053 .000 .000 .161*** .042 .204*** .027 .260*** .230*** .122*** .109*** .065** .050* .017 .030** .059*** .040*** .014** .095*** .027 .090** .255*** .180*** .111*** .131*** .115*** .123***

Natural logarithm of total population Human development index Country classificationb Nordic (reference category) Anglo-Saxon countries Continental countries Southern Europe Eastern Europe

.048 .002

Number of respondents

.000 .693 .112 .278 .686* 31 565

Trust in legal system B

Trust in EU Parliament B 11.105*** .053*** .000*** .178*** .010** *** .035 .157*** .000 *** .033 .144*** .000*** .138*** .200*** .330*** .121*** .096*** .001 .204*** .016* .054 .193*** .126*** .077***

.009 .068 .008** .009*** ** ** .000 .000 .713 .103 .410 .389 .493 1.054** 1.301*** .969*** 31 873

29 455

Notes: a B: (metric) regression coefficients. Statistical significance is marked in this way: * p  .05, ** p  .01, *** p.001. The significance marks for the categorical variables ‘voted for government party’, left–right scale, and the country classification are based on the F-test for the set of categories in SPSS 15. b Coefficients for country classification from model 4.

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The two variance components in model 0, the baseline, may also be seen as estimates of the maximum amount of variation at the individual level and at the country level that our models can explain. Model 1 adds the demographic controls: age, age squared and years of education. These variables explain only a minor part of the variance at the individual as well as at the country level. In model 2, the remaining individual level explanatory variables are added. They include measures of political distance, performance evaluations and political issues. These variables explain more than 20 per cent of the individual level variation in the three political trust measures. These variables also explain about two thirds of the variation between the countries in trust in the electoral system and trust in the legal system.1 However, the individual level variables explain nothing at all of the between-country variation in the trust in the European Parliament. In model 3, we introduce the two macro variables: the HDI and population size. They increase the amount of explained country level variation to 70 per cent for the first and to 75 per cent for the second national trust measure. The two variables also explain about 30 per cent of the country level variation in our third trust measure. Model 4 is an alternative to model 3 in that the two macro variables are replaced by the country classification. For the two trust scales, the country classification does marginally better in terms of explanatory power than the macro variables in model 3. For trust in the European Parliament, the country classification explains about 39 per cent of the between-country variance. Models 3 and 4 perform almost equally well, with an advantage to model 4. The individual level variables do, however, have almost identical coefficients in models 2–4. Therefore, Table 7.3 is mainly based on model 3. The results for the country classification from model 4 are presented as an additional panel at the bottom of the table. Starting from the top, all three types of political trust show a weak curvilinear relationship to age. The level of trust decreases slightly until people reach 40 to 50 years of age, and thereafter increases. Therefore, the level of support is highest among older people, at least for the two dimensions of trust in national institutions. Men show slightly lower levels of political trust than women. Trust also increases with years of education completed, but this effect is rather weak. The predicted difference between a person with no education and one with 20 years of education is only about 0.2 points on the trust scales ranging from 0 to 10. The first of the political distance measures is whether one voted for a party in government. In model 3 this variable is represented by two categories: ‘Yes’, and ‘Did not vote’, and those who voted for parties in

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opposition constitute the reference category. The results are as expected: those who did not vote show the lowest level of trust, and those who voted for a party in government show the highest level of trust. The differences are statistically significant but they are rather small. The left–right scale is represented as a categorical variable with six categories, the middle one being the reference category. People who identify with the left have lower trust in the legal system than others, followed by those who answered ‘Do not know’. People identifying with the right side of politics show high trust in the electoral system and in the European Parliament, but they do not distinguish themselves in trust for the legal system. Those who answered ‘Do not know’ show low levels of trust on all three measures. Next follow the issue indicators. Only the immigration issue has any substantial effect on trust. Citizens who evaluate the effects of immigration as positive have higher political trust than those who evaluate the effects of immigrants as negative. As to be expected, the question on the EU issue is rather strongly and positively related to trust in the European Parliament. We have five performance variables in the model. The two variables that capture the conditions for the respondents show only minor effects on political trust. The three variables that tap the performance of the country, satisfaction with the economy, the education and the health services in the country, all show relatively strong effects. As they all are measured in the same 0–10 scale, their effects are directly comparable. All signs of the coefficients are positive, which indicates that high satisfaction with performance is related to all three dimensions of political trust. Satisfaction with the economy of the country shows the strongest effect. The maximum effect of this performance evaluation indicator is around 2.5 on the scale from 0 to 10 for trust in the electoral system. Its effect on the two remaining trust measures is smaller but still substantial. The effects of evaluation of the education system and the health system are smaller, their maximum effects are around one point on the 0–10 trust scales. Finally, the two last panels in Table 7.3 show the results for the country characteristics in models 3 and 4. Population size is negatively related to all three dimensions of political trust, but the relationships are not statistically significant. The Human Development Index (HDI) is positively related to political trust in the electoral system and the legal system. However, only the latter, rather strong relationship, is statistically significant. The strongest relationship is with trust in the European Parliament. This relationship is strongly negative and statistically significant.

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The country classification provides more detailed results on net differences among groups of countries. The reference category for the country classification is the Nordic countries. Without any exceptions, all other coefficients are negative for trust in the electoral and legal systems. This indicates that, even after controls for all our individual level variables, the Nordic countries still show the highest levels of political trust. However, the net differences between the countries are rather small and only the Eastern Europe countries scored significantly lower than the Nordic countries, more so for trust in the legal system than for trust in the electoral system. For trust in the European Parliament the pattern is different. The South and the East European countries show the highest trust in this institution. At the other end, we find the Nordic and the Anglo-Saxon countries with the lowest trust in the European Parliament, with the Continental countries in the middle.

DISCUSSION The main purpose of this chapter has been to examine country differences in trust in political institutions, with a special focus on the Nordic countries. Previous research, as well as the present study, has demonstrated that the Nordic countries rank very high in political trust in national institutions, but that their support for European institutions is weaker. We have tried to explain these patterns by analysing the most recent survey data from ESS by means of a multilevel statistical model where individuals constitute level 1 and countries constitute level 2. Initially we found it necessary for both theoretical and statistical reasons to distinguish between three dimensions of political trust: trust in the electoral system, trust in the legal system, and trust in the European Parliament. The two first dimensions were fairly strongly correlated, especially at the country level. The Nordic countries and other small rich countries registered the highest level of trust in the two national political institutions. At the bottom were the East European countries. The pattern was quite different for trust in the European Parliament. On this dimension, the Nordic countries scored lower, whereas the South European countries registered the top scores. Furthermore, the overall country differences were smaller for this dimension than for trust in the two national political institutions. How can we explain these gross country differences? The country differences may be a result partly of compositional effects and partly of macro characteristics of the countries. Our multilevel analysis clearly shows that the demographic controls cannot explain the variation between

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the countries in political trust, whereas the attitudinal explanatory variables, especially the evaluation of performance indicators, do explain the major part of this variation. The attitudinal explanatory variables are, however, unrelated to the variation in trust in the European Parliament between the countries. Adding the country classification in model 4 showed the net differences in political trust between the country categories. After controlling for all individual level variables, the between-country differences are smaller than the gross ones, but the basic pattern remains, with the Nordic countries highest on trust in national political institutions, and the East European countries with the lowest levels of trust. Adding the macro characteristics of countries in model 3 explained most of the remaining between-country differences in all three dimensions of political trust. The Human Development Index in particular is related to all three dimensions of political trust. Countries high on the HDI register high trust in the electoral and the legal system, but they are less inclined than others to trust the European Parliament. This shows that the high trust levels in the Nordic countries may be explained by a combination of compositional effects and macro characteristics. The compositional effects are caused by the high scores on the indicators of the country’s performance, especially evaluation of the economy, and indicators of political distance. The macro effects are caused by the top positions of the Nordic countries on the HDI, which again reflects the good living conditions in these countries.

NOTE 1. For trust in the legal system, we observe abnormalities as the explained variance actually turns negative. This may happen in maximum likelihood estimation if the variance component is small at the outset.

REFERENCES Anderson, Christopher J., André Blais, Shaun Bowler, Todd Donovan and Ola Listhaug (2005), Losers’ Consent: Elections and Democratic Legitimacy, Oxford: Oxford University Press. Anderson, Christopher J. and C.A. Guillory (1997), ‘Political institutions and satisfaction with democracy’, American Political Science Review, 91 (1), 66–81. Arts, Wil and J. Gelissen (2002), ‘Three worlds of welfare capitalism or more? A state-of-the-art report’, Journal of European Social Policy, 12 (2), 137–58. Dalton, Russell J. (2004), Democratic Challenges, Democratic Choices, Oxford: Oxford University Press.

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Easton, David (1965), A Systems Analysis of Political Life, New York: John Wiley. Huseby, Beate (2000), ‘Government performance and political support’, PhD dissertation in Political Science, Trondheim, The Norwegian University of Science and Technology. Klingemann, Hans-Dieter (1999), ‘Mapping political support in the 1990s: a global analysis’, in Pippa Norris (ed.), Critical Citizens, Oxford: Oxford University Press. Klingemann, Hans-Dieter and Dieter Fuchs (eds) (1995), Citizens and the State, Oxford: Oxford University Press. Listhaug, Ola (2005), ‘Oil wealth dissatisfaction and political trust in Norway: A resource curse?’, West European Politics, 28 (4), 834–51. Listhaug, Ola (2006), ‘Political disaffection and political performance: Norway 1957–2001’, in Mariano Torcal and Jose Ramon Montero (eds), Political Disaffection in Contemporary Democracies, Oxford: Routledge. Listhaug, Ola and Bernt Aardal (2003), ‘Support of democracy in Europe’, paper prepared for the conference on Democracy in the New Europe, Institut d’Études Politiques de Paris de Dijon, 13–16 November. Listhaug, Ola and M. Wiberg (1995), ‘Confidence in political and private Institutions’, in Hans-Dieter Klingemann and Dieter Fuchs (eds), Citizens and the State, Oxford: Oxford University Press. Miller, Arthur H. (1974), ‘Political issues and trust in government: 1964–1970’, American Political Science Review, 68 (3), 951–72. Miller, Arthur H. and O. Listhaug (1990), ‘Political parties and confidence in government: A comparison of Norway, Sweden and the United States’, British Journal of Political Science, 20, 357–86. Miller, Arthur H. and O. Listhaug (1998), ‘Policy preferences and political trust: A comparison of Norway, Sweden and the United States’, Scandinavian Political Studies, 21 (2), 161–87. Norris, Pippa (ed.) (1999), Critical Citizens, Oxford: Oxford University Press. Olsen, Johan P. (1995), ‘Europeanisation and nation-state dynamics’, Arena Working Paper 9/95. Østerud, Øyvind (2005), ‘Introduction: The peculiarities of Norway’, West European Politics, 28 (4), 705–20.

8.

Disagreement about the division of work among couples in Europe: the role of gender ideology and labour involvement Mikael Nordenmark

INTRODUCTION Although paid and unpaid work is still divided between women and men according to a traditional pattern, there is a distinct indication that women are becoming increasingly involved in employment and men more engaged in household work and childcare. This means that the division of work between women and men who form couples is not as taken-for-granted as it previously was. What does this scenario mean for the occurrence of conflicts and disagreements about the division of labour among couples? This chapter examines various factors that can explain the level of disagreement about division of housework and time spent in employment among couples in Europe. A major focus of the chapter is if attitudes towards gender roles and levels of involvement in employment and household work can explain to some extent the variation between states regarding the experience of disagreements about division of work among couples. Analyses are based on an extensive cross-country data set that includes 24 European countries collected within the framework of European Social Survey 2004 (ESS).

RESEARCH ON DISAGREEMENT ABOUT DIVISION OF WORK Research attempting to explain variation in perceptions of unfairness and disagreement in relation to the division of labour among couples often points out both pragmatic or instrumental explanations and explanations related to symbolic or relational meanings of gender, household work and childcare. 152

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Explanations and theories concerning perceptions in relation to division of labour from an instrumental or pragmatic view are time use and economic-based power theories. These highlight the importance of factors like time usage and availability, individual resources and power in explaining how men and women judge the division of paid and unpaid work. Most studies point out that the understanding of perceptions of unfairness and disagreements is to some extent related to the actual division of labour and time within the household. A number of studies argue that an equal division of work generates more conflicts between spouses than a more traditional division (Bahr et al. 1983; Moen and Yu 1998; Scanzoni and Fox 1980). This means that there is a higher level of disagreement among couples when the spouses share the responsibility for paid and unpaid work. The explanation given for this result is that an equal division of labour implies an uncertainty about social roles and what each person should do. This uncertainty among couples, characterized by an egalitarian division of labour, can increase the risk of role conflicts and disagreements. On the other hand, there is no consensus among academics regarding the meaning of a traditional and non-traditional division of labour between spouses for the level of conflicts and disagreements. Studies that focus on experiences of fairness and unfairness in relation to division of labour show that people in relationships that are characterized by a relatively equal distribution of paid and unpaid work evaluate the division as fairer than spouses who do not share labour to the same extent (Baxter 2000; Lennon and Rosenfield 1994; Perry-Jenkins and Folk 1994; Sanchez 1994; Sanchez and Kane 1996; Wilkie et al. 1998). Some studies have found that women’s estimated degree of experienced fairness is primarily related to men’s time spent on ‘female’ tasks. The greater the part of the household work done by the man, the more satisfied is the woman (Blair and Johnson 1992; Dempsey 1999; Lennon and Rosenfield 1994). Individual resources and power relations have also been identified as important for how perceptions within couples are formed. Women who have small economic resources and a low educational level have been found to be more likely to see an unequal division as fair and unproblematic, whereas women who have extensive economic resources and qualified jobs do not. A possible explanation of these results is that women with limited resources and power are more afraid of questioning an unequal division of labour (Lennon and Rosenfield 1994). Theories highlighting the importance of more subjective factors like the symbolic or relational meanings of gender, household work and childcare argue that the level of disagreement in one way or another is related to how an unequal division of labour is perceived by the individual. One factor included among the subjective approaches is gender ideology. Gender

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ideology is defined as the beliefs or attitudes a person holds about gender (Hochschild 1997). The hypothesis is that these beliefs determine to a large extent how an individual perceives and judges a certain division of labour. The assumption has been supported in studies indicating that gender ideology plays an important role in forming perceptions of unfairness and dissatisfaction within couples (Blair and Johnson 1992; Greenstein 1996; Hochschild 1989). The explanation is that an individual’s gender ideology may influence how a certain division of labour is valued and what standards and references are used to judge outcomes. For instance, people with an egalitarian gender ideology may give priority to equality and independence, while people with a more traditional gender ideology might give priority to stability and harmony. This difference in gender ideology can mean that these people evaluate the same division of labour in different ways. Because a traditional division of labour, and the outcomes from a traditional division of labour, are not in line with the expectations of those with an egalitarian gender ideology, there is a high risk that they will look at the division as unfair and problematic. This means that, compared to people with a more traditional gender ideology, people with an egalitarian gender ideology will express more dissatisfaction and other complaints in a situation that is characterized by a traditional division of labour (Greenstein 1996; Nordenmark and Nyman 2003). Because women normally have the main responsibility for household work and children even though they are employed, the assumption is that especially women with an egalitarian gender ideology will perceive this situation as unfair, unequal and problematic (Greenstein 1995; Strandh and Nordenmark 2006). Disagreement about Work in Various National Contexts Research shows that gender ideology among individuals and the level of engagement in employment and household work varies between national contexts (Nordenmark 2004; Strandh and Nordenmark 2006). This opens up the possibility that the level of disagreement among couples about how much time women and men spend in employment and household work will also vary between nations. On the basis of the above discussion, one can assume that, depending on the gender ideology and actual involvement in employment and household labour among cohabitants, disagreements will be more frequent in some national contexts than in others. Which national contexts in Europe are characterized by a relative egalitarian gender ideology and division of labour between spouses, and which nations are characterized by a more traditional gender ideology and division of labour? In research about organization and characteristics of different types of welfare states and gender regimes (Duncan 1996; Esping-Andersen

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1990, 1999; Lewis 1992; Walby 1994) the Nordic states are normally classified as representing an egalitarian gender regime. Family policy is comprehensive, encourages female labour market participation and emphasizes gender equality and women’s independence from men. As a result the female employment rate is almost as high among women as among men. The former Eastern Europe states have not been classified into welfare state types as often as other European regions. One obvious reason for this is that they have been in transition and consequently more difficult to categorize. The communist legacy was a generous and interventionist social policy, which was based on the right (and to some extent duty) of full-time employment for both men and women. Family policy was characterized by extensive labour-market rights and the provision of caring services available for parents. This legacy is still relatively strong, although there has been pressure applied to reform these systems in connection with the transition process. The United Kingdom is an example of an Anglo-Saxon type of welfare regime where market-led solutions are preferred to state intervention. Social policy measures are limited to means-tested benefits and modest social insurance plans, while private welfare schemes are stimulated. There is relatively little public provision of services, which means that the government to a small extent facilitates the combination of work and family obligations. Although there is a political goal to create gender equality in an Anglo-Saxon welfare state, the state does little to facilitate this, and the result could be labelled a male breadwinner model where women’s incomes are secondary to men’s. Conservative or family-centred welfare states located in Central and Southern Europe are characterized by a relatively passive social policy and the preservation of traditional family ties and norms. Family policy consists mainly of support from the state for the male breadwinner family. There are few policy measures that aim at the break-up of the traditional division of labour and the strengthening of women’s independence from men. As a result the rate of female labour market participation rate is relatively low. Therefore, Continental Europe and states located in Southern Europe can be classified as representing a relatively traditional or conservative gender regime characterized by a relatively traditional division of labour between women and men. This is especially significant in Southern Europe. In conclusion, states and different areas in Europe represent different gender regimes. Some, like the Nordic states, have invested in an extensive family policy with an aim to facilitate the combination of work and family responsibilities and gender equality. At the other end of the continuum one can find states located in Continental and Southern Europe that have a relatively passive family policy, which results in a low female employment rate and the preservation of traditional gender roles. Between these two

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opposite poles are the states that are not so clear-cut in relation to type of gender regime; the former Eastern Europe states and states belonging to the Anglo-Saxon welfare regime type. The former Eastern European countries have a history characterized by an extensive family-related policy in order to create equality, but it is unclear how much support this ambitious policy, which was put forward by a non-democratic government, has had among the people. In the Anglo-Saxon countries there is a political goal to create gender equality, but there is relatively little done by the government to realize this goal (Strandh and Nordenmark 2006). As has been shown, research on the importance of gender ideology and the division of labour for disagreement about labour involvement among couples indicates that an egalitarian ideology and division of labour (defined as a relatively high involvement in housework among men and a relatively high involvement in paid work among women) are related to a relatively high level of disagreement. If this is true there should be a higher level of disagreement about how to divide labour among couples who live in a typical egalitarian gender regime, like the Nordic countries, compared to a more conservative or traditional gender regime, like Continental and Southern Europe. On the basis of this discussion it is interesting to analyse the importance of (1) gender ideology and (2) involvement in employment and household work, with regard to the experience of disagreements regarding involvement in paid work and household work among couples living in various national and political contexts. The study will analyse the following two hypotheses: 1.

2.

Cohabitants in nation states that are characterized by an egalitarian gender regime (Nordic states) disagree more often about the level of involvement in labour compared with couples living in a more traditional or conservative gender regime (Continental and Southern Europe). Cohabitants who hold an egalitarian gender ideology and are characterized by a relatively egalitarian division of labour more often disagree about the level of involvement in employment and household work compared with those who have a more traditional gender ideology and division of labour.

METHOD The data used come from an international investigation called the European Social Survey 2004 (ESS). The ESS is a comparative study that was conducted in 24 countries. It includes thematic sections that appear

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cyclically across the investigation occasions. The investigation for 2004 has the in-depth theme ‘Family, work and well-being’. This section focuses on the relation between work, family and well-being, as well as on the meaning of working life and family life for level of disagreement about working hours and division of housework. The investigation also contains questions about gender role attitudes and how individuals experience the balance between gainful employment and family life. ESS is a further development of the International Social Survey (ISSP) in two respects: (1) data are collected via interviews, which results in a higher response frequency and better quality data, and (2) the standardization of background variables has been developed. The dependent variables of most interest in this study are the variables that measure levels of disagreement about housework and working hours. The two questions that this study uses in order to analyse disagreement about housework and working hours are: How often do you and your partner disagree about how to divide housework? How often do you and your partner disagree about the amount of time spent on paid work? Response alternatives are: 1 Never, 2 Less than once a month, 3 Once a month, 4 Several times a month, 5 Once a week, 6 Several times a week and 7 Every day. The total level of disagreement is measured by an index, which is a summation of the responses to these two questions (Cronbach’s alpha 0.52). The index range is from 2 to 14; the higher the score, the more disagreement about labour involvement among the spouses. The main independent variables are gender regime, gender ideology and the questions that measure the respondent’s and partner’s level of involvement in employment and housework. Gender regime is measured through the different social and family policies of national states. The index range begins at 1 (states representing an egalitarian gender regime) and ends at 5 (states representing a traditional gender regime) (see Table 8.1). Gender ideology is indicated by a ‘gender ideology index’, which is constructed from the following three statements about gender roles and work involvement: A woman should be prepared to cut down on her paid work for the sake of her family. Men should take as much responsibility as women for the home and children (reversed). When jobs are scarce, men should have more right to a job than women. The answers to each statement, which are classified in five steps from ‘Agree strongly’ to ‘Disagree strongly’, have been summarized in an additive index (Cronbach’s alpha 0.53) with a range from 0 to 12; the higher the score, the more egalitarian the values. The level of involvement in work is measured by two questions about time spent on employment and housework. Respondent’s and partner’s involvement in paid work is measured by the question: How many hours do you/your partner normally work per week in your main job, overtime

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included? Respondent’s and partner’s level of involvement in housework is indicated by the following questions: About how large a part of total time do you/your partner spend on housework on a typical weekday (1 None or almost none, 2 Up to 1⁄4 of the time, 3 More than 1⁄4, up to 1⁄2 of the time, 4 More than 1⁄2, up to 3⁄4 of the time, 5 More than 3⁄4, less than all of the time, 6 All or nearly all of the time)? The multivariate analysis controls for the following variables. The distribution of income among the couples measured by the following question: Around how large a proportion of the household income do you provide yourself ? (1 None, 2 Very small, 3 Under a half, 4 About a half, 5 Over a half, 6 Very large, 7 All). The highest level of education achieved measures educational level (1 Did not finish elementary school, 2 Elementary school, old, 3 Elementary school, 4 Lower secondary and elementary school, old, 5 Vocational school 1963–70, 6 Two years high school, 7 Three to four years high school prior to 1995, 8 Vocational high school after 1992, 9 Theoretical high school after 1992, 10 University, no exam, 11 University, exam less than three years, 12 University, exam more than three years). The presence of children is indicated by the question: Do you live with children? (1 Yes, 0 No). Finally, the study also controls for the date of birth (1902 to 1992).

RESULTS All analyses include cohabiting people from different regions of Europe. As many of the independent variables are assumed to have a different meaning for men and women respectively, all results are presented separately for men and women. Mean values on the gender ideology index show that women have, in general, a somewhat more egalitarian gender ideology than men. Of a highest possible value of 12 the mean value is 6.9 for men and 7.2 for women. The mean number of working hours in employment among respondents and partners indicates that men work on average 10 hours more per week than women. When men report how much time they spend on housework almost a third say that they do none or almost no part of the housework, and when women report how much time their partner spends on housework the corresponding figure is 40 per cent. Thirty-eight per cent of the women report that they do all or nearly all of the housework, but if the men judge their partner’s level of involvement in housework the proportion is 26 per cent. Mean values for respondent’s and partner’s involvement in housework indicate that women devote at least twice as much time as men to housework. About half of both women and men report that they never disagree about how to divide housework. Around 12 per cent disagree once a week

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or more about the division of household tasks. Mean values are around the same for both women and men: 2.2 and 2.3 respectively. In the light of the research that has shown that conflicts and quarrels about the division of household responsibilities are one of the most common reported causes of separations and divorces, these results are relatively unexpected. It is even rarer that couples in Europe disagree about time spent on paid work than they do about time spent on housework. Close to 70 per cent of men and women never disagree about how much time they and their partner spend in employment. Around 6 per cent disagree once a week or more. The mean value is 1.7 for both men and women. Gender Ideology, Division of Labour and Disagreement in Different Gender Regimes This section shows the results of the analyses based on the hypotheses presented earlier. The hypotheses to be tested are: Couples in nation states characterized by an egalitarian gender regime (Nordic countries) disagree more often about the level of involvement in labour compared with couples who live in a more traditional or conservative gender regime (Continental and Southern Europe). Couples who hold an egalitarian gender ideology, and are characterized by a relatively egalitarian division of labour, disagree more often about the level of involvement in employment and household work compared with those who have a more traditional gender ideology and division of labour. Table 8.1 shows how gender ideology, involvement in housework and disagreements about paid and unpaid work vary between the states included in ESS 2004. Gender ideology measures gender role attitudes among people and ‘part spent on housework’ indicates the degree to which the division of labour is segregated by gender. This makes it possible to form a picture of the connection between attitudes and behaviour in each state. The last three variables analysed correspond to the measures of disagreements regarding work involvement among couples. Taken as a whole, the values of the variables indicate how gender ideology and the division of labour are related to disagreements concerning paid and unpaid work, and how the situation is in each nation state. The states are categorized according to the type of gender regime that each state represents (from egalitarian to a conservative). On the basis of this evaluation the states are grouped into 1 Nordic states, 2 Eastern Europe, 3 Anglo-Saxon states, 4 Continental states and 5 Southern states. The gender ideology among people in different European states confirms that there seems to be a relationship between individual attitude towards gender roles and type of gender regime. As the results in the two first

160

8.56 8.70 8.84 8.27 8.30 8.26

6.10 6.51 6.16 6.61 6.20 7.21 6.27 5.81

7.23 7.24 7.21

Eastern Europe Estonia Czech Republic Slovakia Poland Slovenia Hungary Ukraine

Anglo-Saxon states UK Ireland

Men

7.11 7.09 7.46

6.61 6.98 6.97 7.11 6.81 7.55 6.49 6.36

8.88 8.88 9.22 8.67 8.72 8.35

Wom

Gender ideology

Nordic states Sweden Denmark Norway Finland Iceland

Gender regime

2.45 2.46 2.23

2.49 2.51 2.64 2.59 2.27 2.40 2.27 2.69

2.70 2.83 2.57 2.58 2.74 2.63

Men

4.64 4.61 5.09

4.22 4.28 4.47 4.28 4.47 4.32 4.60 3.95

4.24 4.20 4.14 4.30 4.35 4.49

Wom

Part spent on housework

2.33 2.36 1.75

2.30 2.14 2.41 2.59 2.39 2.27 2.01 2.22

2.50 2.38 2.29 2.56 2.88 2.66

Men

2.13 2.14 1.90

2.33 2.21 2.50 2.82 2.51 2.34 2.10 2.20

2.43 2.21 2.32 2.51 2.86 2.30

Wom

Disagree housework

1.74 1.76 1.44

1.80 1.61 1.90 2.39 1.89 1.71 1.83 1.63

1.78 1.78 1.55 1.68 2.16 2.00

Men

1.67 1.68 1.56

1.77 1.68 1.96 2.33 1.88 1.54 1.86 1.61

1.72 1.74 1.57 1.67 1.89 1.89

Wom

Disagree working hours

4.09 4.14 3.19

4.03 3.79 4.28 4.90 4.28 3.89 3.73 3.74

4.37 4.24 3.93 4.30 5.20 4.66

Men

3.84 3.87 3.43

4.11 3.90 4.45 5.14 4.51 3.91 3.93 3.80

4.25 4.08 3.98 4.22 4.90 4.22

Wom

Disagree combination

Table 8.1 Gender ideology, part of total time spent on housework, disagreement about housework, disagreement about working hours and combined measure of disagreement by gender regimes (cohabitants, mean)

161

7.15 7.35 7.65 6.93 6.78 6.49 6.57 7.57

6.44 6.68 6.04 5.83

6.90 11142

Continental Europe Belgium Netherlands Luxembourg Germany Austria Switzerland France

Southern Europe Spain Portugal Greece

Total mean N

7.18 12047

6.79 6.95 6.35 6.72

7.47 7.56 7.70 7.06 7.41 7.22 6.56 7.59

2.36 11157

1.96 2.09 1.71 1.68

2.36 2.38 2.46 2.29 2.27 2.37 2.23 2.46

4.61 12104

5.08 4.90 5.28 5.42

4.74 4.66 4.81 4.91 4.64 4.82 4.86 4.83

2.21 11192

1.95 2.11 1.70 1.50

2.17 2.32 2.13 2.35 2.39 2.45 2.10 1.88

2.27 12070

2.09 2.35 1.88 1.54

2.31 2.30 2.15 2.57 2.45 2.54 2.14 2.17

1.74 9741

1.83 2.00 1.60 1.35

1.66 1.66 1.48 1.89 1.54 1.90 1.63 1.84

1.72 10661

1.92 2.16 1.82 1.31

1.65 1.63 1.42 1.81 1.50 1.91 1.58 1.89

3.95 9697

3.75 4.06 3.30 2.87

3.88 4.00 3.64 4.25 3.99 4.31 3.74 3.77

4.01 10600

3.97 4.44 3.72 2.84

3.98 3.96 3.58 4.40 3.96 4.43 3.74 4.11

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columns in Table 8.1 show, people in the Nordic states have the most egalitarian gender ideology. All Nordic states have scores above 8.2 on the gender ideology index whereas all the other states have scores that range from 5.8 to 7.7. The outliers are the former Eastern European countries. They were classified as representing a relatively egalitarian gender regime, however, as the results in Table 8.1 show, the attitudes among individuals are very traditional. As expected, the mean scores for the countries placed in Southern Europe are relatively low, which indicates the presence of traditional views of how women and men should behave. In most countries women have more egalitarian values than men. If men do a relatively large part of the housework, which corresponds to a high mean score, a relatively egalitarian division of labour is in evidence. With the exception of the states belonging to the former Eastern Europe, the pattern regarding involvement in housework is similar to the pattern regarding gender ideology. Instead of being placed in the bottom, which was the case in relation to gender ideology, the mean scores indicate that men in the former Eastern European cluster are at the same level as men in the Anglo-Saxon states and women in former Eastern Europe are at the same level as women in the Nordic states. The relatively low mean score among men and the relatively high mean score among women living in Southern Europe indicate that housework seems to be most gendered in these states. Once again, the Nordic countries come out on top as the division of labour is most egalitarian or equally divided between spouses. Men do a larger part and women a lesser part of the housework compared to most other states. So far, the overall impression of the results in Table 8.1 is that there seems to be a relationship between gender regime on a macro level and gender ideology and division of labour among couples on a micro level, although the relationships are not that distinct among the Eastern European states. The main question to be answered at this stage of the analysis is if it is possible to find some support for hypothesis 1; that couples disagree more about the division of housework and time spent in paid work in states categorized by a relatively egalitarian social and family policy and egalitarian division of labour. If this is true people in the Nordic countries should report more disagreements than people living in other parts of Europe. The lowest levels of disagreements should be found in states located in Continental and Southern Europe. However, there is no clear-cut picture in this case. A reading of the mean scores that indicate levels of disagreement about division of housework could conclude that the Nordic states in general have relatively high scores (high levels of disagreement). The mean score is 2.50 for Nordic men and 2.43 for Nordic women, which are higher scores than means for all other

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clusters of states, and the total mean score for all states included (2.21 and 2.27). People living in Southern Europe experience the lowest level of disagreement about the division of housework. They also have a very traditional gender ideology and division of labour. All these results provide some support for hypothesis 1. On the other hand, there are also large variations within each cluster of states. For instance, the scores are highest among Finnish men and women, but the mean scores among Swedes and Danish people are in general around the total mean scores for all states. The mean score for Southern Europe is relatively low but the mean score for Spanish women is close to the mean score for Nordic women. Results regarding disagreements about the number of hours spent in paid work are even more complex and difficult to interpret in relation to hypothesis 1. The mean scores among the Nordic states are close to the total mean score for all countries and there are large variations within categories of gender regimes. For instance, among women in Southern Europe the mean values range from 1.31 in Greece to 2.16 in Spain, which are among the lowest and highest mean scores on disagreement about working hours. A general conclusion is that there are relatively small variations between the clusters of states regarding the level of disagreements about working hours. The scores indicating disagreements about involvement in work in general (the combined measure of disagreements) offer some support for hypothesis 1. Mean scores for the category ‘Nordic states’ are higher than mean scores for all other categories of states. The mean values for countries classified as Continental and states located in Southern Europe are substantially lower, which is in line with the suggested hypothesis. The highest mean values are found among Finnish and Slovakian men and women, which indicate that disagreements about work are relatively common among couples in Finland and Slovakia. However, also in this case there are significant variations within each cluster of states. The largest variation is again found among women living in Southern Europe. The mean score is 4.44 for Spanish women and 2.84 for women living in Greece. In conclusion, the descriptive results in Table 8.1 support to some degree hypothesis 1. The Nordic countries are categorized by a relatively egalitarian gender ideology and division of labour among men and women. If an egalitarian gender ideology and division of labour generate more disagreements about labour, there should be relatively high mean values on the questions about disagreements among people living in Nordic states. The hypothesis receives stronger support if disagreement about division of housework is examined than if paid work is examined. One conclusion is that the hypothesis gets some support; however, it is notable that there is substantial variation within the different type clusters representing different

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gender regimes. In the next section, we investigate if cohabitants who hold an egalitarian gender ideology and are characterized by a relative egalitarian division of labour disagree more often about the level of involvement in employment and household work compared with those who have a more traditional gender ideology and division of labour. Table 8.2 shows correlation coefficients between the variables of most interest in this study. Coefficients are shown in normal style for men and in italics for women. The most interesting correlations in relation to the research questions in this study are the associations between variables that measure gender ideology and level of involvement in paid and unpaid work, and levels of disagreement regarding level of involvement in labour. Gender ideology is significantly positively correlated with disagreement about how to divide housework among both women and men, but the correlation is stronger among women. This means that people, and especially women, with egalitarian values disagree more often about how to divide housework than people who hold more conservative attitudes towards gender roles. There is a similar tendency regarding disagreement about working hours. It is more common that people, and especially women, with egalitarian values report that they disagree about the amount of time spent on paid work. Furthermore the combined measure of disagreement regarding work involvement is significantly positively correlated with gender ideology. In summary, this means that the more egalitarian values that couples in Europe hold, the more they disagree about how to divide work, and this is most prominent among women. The results illustrate that the respondents’ numbers of working hours are negatively correlated with disagreements regarding division of housework among both women and men. Furthermore, there is a significant positive correlation between the respondent’s and partner’s working hours, and disagreements about the amount of time spent on paid work. The more women and men work, the more they disagree about working hours. The correlations are stronger for male respondents and partners than for female respondents and partners. The significant correlations between the time the respondent spent on housework and disagreement concerning division of housework and working hours can be found among men. There is a significant positive correlation between the time men spend (of the total time) on housework and disagreements regarding housework. However, the results that relate to the partner’s level of involvement in household work indicate that the more men are involved in housework as a partner, the less frequently the women report disagreements about labour involvement. Other variables are correlated as follows. In Europe, gender ideology is negatively correlated with the respondents’ working hours among men, but

165

– 0.028** 0.077*** 0.119*** 0.131*** 0.099*** 0.039*** 0.091***

Working hours partner 0.026 0.142*** – 0.125*** 0.148*** 0.006 0.092*** 0.054***

Working hours 0.058*** – 0.170*** 0.104*** 0.082*** 0.030** 0.048*** 0.006

Notes: Coefficients are shown in normal type for men and in italics for women. * p .05; ** p  .01; *** p  .001.

Gender ideology Working hours Working hours partner Part on housework Partner housework Disagree housework Disagree work hours Disagree comb

Gender ideology 0.198*** 0.078*** 0.138*** – 0.599*** 0.006 0.018 0.005

Part on housework

Table 8.2 Bivariate correlations for cohabiting men and women (Pearson)

0.186*** 0.087*** 0.153*** 0.634*** – 0.024** 0.036*** 0.034***

Partner housework

Disagree working hours

0.043*** 0.021* 0.031*** 0.082*** 0.018 0.067*** 0.035*** 0.001 0.010 0.019 – 0.385*** 0.341*** – 0.861*** 0.772***

Disagree housework

0.040*** 0.033** 0.025 0.023* 0.009 0.862*** 0.800*** –

Disagree comb

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significantly positively correlated among women. This means that egalitarian values are related to fewer working hours among men but more working hours among women. The negative correlation among men is substantially stronger than the positive correlation among women. There is a significant negative correlation between gender ideology and partners’ working hours among women. This means that the more egalitarian values women have, the fewer working hours their partners have. Table 8.2 illustrates that there is a significant positive correlation between gender ideology and the proportion of total time spent on housework among men. Among women the correlation coefficient is significantly negative, which means that egalitarian men do more housework than conservative men and egalitarian women do less housework than conservative women. When looking at partners’ levels of involvement in housework there is a reverse pattern. Among men there is a significant negative correlation between gender ideology and partners’ part of total time spent on housework, but among women the coefficient is significantly positive. Furthermore, the partners of egalitarian men do relatively less housework and partners of egalitarian women do relatively more housework. Correlations between gender ideology and a respondent’s/partner’s level of involvement in housework are stronger among men than among women, which indicates that men’s gender ideology is of more importance for the division of household labour. Correlations between respondents’ working hours and partners’ working hours are significantly positive among both women and men. The more the respondent works, the more their partner works. Furthermore, the more men and women work in a paid job, the lower the engagement in housework and the higher engagement in housework among their partners. A partner’s number of working hours is significantly negatively correlated with their own involvement in housework, but significantly positively correlated with the respondent’s level of involvement in housework. Moreover, the larger part of the housework that is done by respondents, the lower the level of housework involvement among partners. Disagreements about division of housework and the time spent on paid labour are strongly correlated with each other and therefore these two measures of disagreement are very strongly correlated with the combined measure of disagreement about labour involvement. The next step is to analyse the relationships between independent and dependent variables when controlling for other factors of importance. Table 8.3 includes the results from a multilevel analysis. The large advantage with this method is that it makes it possible to measure the effect of individual factors in relation to contextual conditions, such as type of gender regime.

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Table 8.3 Fixed effects from multilevel modelling: disagreements about housework, working hours and the combination of these two, by gender ideology, time use variables, control variables and gender regime (cohabitants, estimates) Individual variables

Disagree housework Disagree working hours Men

Women

Men

Women

Disagree combination Men

Women

Gender ideology .043*** .050*** .039*** .003 .079*** .054*** Working hours .002 .003* .011*** .003* .012*** .001 Partner’s work .001 .002 .004** .015*** .003 .013*** hours Part spent on .046 .005 .007 .017 .045 .021 housework Part partner .030 .091*** .004 .045* .034 .140*** spent on housework Part of .003 .084*** .036* .029* .035 .117*** household income Educational level .058*** .030* .065*** .049*** .123*** .082*** Children .103* .150*** .085* .095** .183** .264*** Year of birth .023*** .018*** .015*** .008*** .037*** .027*** Country variable Gender regime

.127**

.089*

.040

.007

.165** .098

Notes: * p  .05; ** p  .01; *** p  .001.

The results from the multivariate analysis regarding disagreements about how to divide housework indicate that the individual variable gender ideology is significant related to disagreement about division of housework among both men and women, but the relationship has become negative among men but is still positive among women. This means that the more egalitarian attitudes men have, the fewer disagreements they report regarding housework, and the more egalitarian attitudes women have the more frequently they disagree with their partner about the division of housework. Gender ideology is related to disagreements about hours spent on paid work in a similar way. Cohabiting men with an egalitarian gender ideology report disagreements less frequently about the number of hours spent on paid work compared with men with a more traditional gender ideology. However, the positive relationship between gender ideology and disagreements about working hours among cohabiting women is non-significant.

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The results regarding the combined measure of disagreement indicate that gender ideology is, once more, negatively related among men, but positively related among women. In sum, this means that it is only among cohabiting women where one can find a significant positive relationship between gender ideology and disagreements about involvement in labour, meaning that women with an egalitarian gender ideology report disagreements about how to divide labour within the household more frequently than women with a more traditional gender ideology. There is a weak significant negative relationship between respondents’ working hours and the dependent variable disagreements about housework among women, which means that the more hours that are worked, the less disagreement there is. Both respondents’ and partners’ working hours are significantly positively related to disagreements about hours spent on paid work among cohabiting men and women. The sizes of the estimates concerning the level of disagreement about working hours show that the respondent’s number of working hours is of more importance than the partner’s working hours among men, and that the partner’s working hours is more important than the respondent’s working hours among women. The combined measure of disagreement about work involvement is strongly related to the respondent’s working hours among men and the partner’s working hours among women. These results also indicate that the man’s number of working hours are of most importance for the level of disagreement about division of labour among both men and women. The level of involvement in housework is of significant importance for disagreements about division of labour only among women. The results for women show that the larger share of the housework that is done by their partner, the lower the risk of disagreement about labour involvement. On the whole, the proportion of household income that each partner provides is significantly positively related to disagreements about work involvement, and this is especially prominent for women. The higher the proportion of the household income the respondent provides, the higher the risk for the report of disagreements. Educational level is significantly positively related to all measures of disagreement about the division of labour among both men and women, which means that the higher the education, the higher the level of disagreements. Furthermore, the presence of children and the year of birth are significantly positively correlated in all models. In general, the occurrence of children increases the risk of disagreement about how to divide labour and this is especially significant among women. Younger cohabiting men and women disagree more often about labour involvement than older cohabitants. The contextual variable gender regime is structured as shown in Table 8.1: 1 Nordic states, 2 Eastern Europe, 3 Anglo-Saxon states, 4 Continental

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Europe and 5 Southern Europe. The construction is based on the assumption that the Nordic states represent the most egalitarian gender regime and Southern Europe the most traditional gender regime. As the results from the multivariate analysis in Table 8.3 show, there is a significant negative relationship between gender regime and the level of disagreement about how to divide housework among both women and men, which means that the more traditional the gender regime, the less disagreement reported. However, there is no significant relationship between gender regime and disagreements about working hours, and the negative relationship between gender ideology and the combined measure of disagreement about work involvement is significant only among men.

DISCUSSION The main aim of this study has been to analyse the following two hypotheses: (1) Cohabitants in nation states that are characterized by an egalitarian gender regime (Nordic states) disagree more often about the level of involvement in labour than couples living in a more traditional or conservative gender regime (Continental and Southern Europe), and (2) cohabitants who hold an egalitarian gender ideology and are characterized by a relatively egalitarian division of labour disagree more often about the level of involvement in employment and household work than those who have a more traditional gender ideology and division of labour. Hypothesis 1 is to some extent supported. Couples in nation states that are characterized by an egalitarian gender regime (Nordic states) do disagree more often about the division of housework than couples living in a more traditional context (Southern Europe). Men who live in Southern Europe experience the lowest levels of disagreement about how to divide housework, whereas men who live in Scandinavia experience the highest levels. The results are, however, more complex regarding disagreements concerning the number of hours spent in paid work. One can also conclude that there are large variations within each category of states regarding the level of disagreement about labour involvement. Hypothesis 2 about the importance of gender ideology and labour involvement is supported among women with regard to the meaning of gender ideology. Cohabiting women who hold an egalitarian gender ideology report disagreements about the division of paid and unpaid work more often than women who have more traditional attitudes toward gender roles. However, the relationship between gender ideology and disagreement about working hours is not significant in a multivariate analysis. There is a similar pattern among men in the bivariate analysis, but in the multivariate

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analysis there is a reverse pattern; the more egalitarian the gender ideology, the less disagreement there is regarding labour involvement. However, it is not more common that couples who are characterized by a relatively egalitarian division of labour (defined as a relatively high involvement in housework among men and a relatively high involvement in paid work among women) disagree more often about the division of paid and unpaid work compared with couples who have a more traditional division of labour. There is more of an inverse pattern, which indicates that an egalitarian division of labour decreases the risk of disagreement. The actual number of working hours is positively related to disagreements about the time spent in paid work, independent of gender. However, the fact that men’s actual numbers of working hours, both as a respondent and a partner, seem to be more strongly correlated to disagreements about working hours indicates that traditional behaviour among men (to be strongly involved in employment) increases the risk of disagreement. Furthermore, the significant relationships regarding the importance of housework involvement for the experience of disagreements about the division of work indicate that an egalitarian division of labour decreases rather than increases the risk of disagreement. The greater share of the housework done by the partner among women (indicating a relative egalitarian division of labour), the lower the level of disagreement about labour involvement.

REFERENCES Bahr, Stephen J., C.B. Chappell and G.K. Leigh (1983), ‘Age at marriage, role enactment, role consensus, and marital satisfaction’, Journal of Marriage and the Family, 45 (4), 795–803. Baxter, Janeen (2000), ‘The joys and justice of housework’, Sociology, 34 (4), 609–31. Blair, Sampson L. and M.P. Johnson (1992), ‘Wife’s perceptions of the fairness of the division of household labor: The intersection of housework and ideology’, Journal of Marriage and the Family, 54 (August), 570–81. Dempsey, Kenneth C. (1999), ‘Attempting to explain women’s perceptions of the fairness of the division of housework’, Journal of Family Studies, 5 (1), 3–24. Duncan, Simon (1996), ‘The diverse worlds of European patriarchy’, in Maria D. Garcia-Ramon and Janice Monks (eds), Women of the European Union: The Politics of Work and Daily Life, London: Routledge, pp. 74–110. Esping-Andersen, Gøsta (1990), The Three Worlds of Welfare Capitalism, Cambridge: Polity Press. Esping-Andersen, Gøsta (1999), Social Foundations of Postindustrial Economies, Oxford: Oxford University Press. Greenstein, Theodore N. (1995), ‘Gender ideology, marital disruption and the employment of married women’, Journal of Marriage and the Family, 57 (1), 31–42.

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Greenstein, Theodore N. (1996), ‘Gender ideology and perceptions of the fairness of the division of household labor: Effects on marital quality’, Social Forces, 74 (3), 1029–42. Hochschild, Arlie (1989), The Second Shift, New York: Avon Books. Hochschild, Arlie (1997), The Time Bind. When Work Becomes Home and Home Becomes Work, New York: Metropolitan Books. Lennon, Clare M. and S. Rosenfield (1994), ‘Relative fairness and the division of housework: The importance of options’, American Journal of Sociology, 100 (2), 506–31. Lewis, Jane (1992), Gender and the development of welfare regimes’, Journal of European Social Policy, 2 (3), 159–73. Moen, Phyllis and Y. Yu (1998), ‘Effective work/life strategies: Working couples, work conditions, gender and life quality’, Social Problems, 47 (3), 291–326. Nordenmark, Mikael (2004), Arbetsliv, Familjeliv och Kön, Boréa: Umeå. Nordenmark, Mikael and C. Nyman (2003), ‘Fair or unfair? Distribution of labour and experienced fairness of household division of labour and gender equality: The Swedish case’, European Journal of Women’s Studies, 10 (2), 181–210. Perry-Jenkins, Maureen and K. Folk (1994), ‘Class, couples, and conflict: Effect of the division of labour on assessments of marriage in dual-earner families’, Journal of Marriage and the Family, 56 (1), 165–80. Sanchez, Laura (1994), ‘Gender, labor allocations, and the psychology of entitlement within the home’, Social Forces, 73 (2), 533–53. Sanchez, Laura and E. Kane (1996), ‘Women’s and men’s constructions of perceptions of household fairness’, Journal of Family Issues, 17, 358–87. Scanzoni, John and G.L. Fox (1980), ‘Sex roles, family and society: The seventies and beyond’, Journal of Marriage and the Family, 42 (4), 743–56. Strandh, Mattias and M. Nordenmark (2006), ‘The interference of paid work with household demands in different social policy contexts: Perceived work–household conflict in Sweden, the UK, the Netherlands, Hungary and the Czech Republic’, British Journal of Sociology, 57 (4), 597–617. Walby, Sylvia (1994), ‘Methodological and theoretical issues in the comparative analysis of gender relations in Western Europe’, Environment and Planning, 26 (9), 1339–54. Wilkie, Jane R., M.M. Ferree and K.S. Ratcliff (1998), ‘Gender and fairness: Marital satisfaction in two-earner couples’, Journal of Marriage and the Family, 60 (August), 577–94.

9.

Non-standard employment and job quality Heikki Ervasti

INTRODUCTION During the last decades, working life has been involved in a process of everaccelerating change. A notable percentage of the European labour force is already employed in non-standard or flexible work arrangements, yet claims for further deregulation are not rare in policy debate. The proponents of deregulation, who are mostly employers and right-wing politicians, view the European labour markets as ‘sclerotic’; that is, too rigid and inflexible to meet the demands of intensified global competition. According to their view, the strongly regulated labour markets and generous welfare states hinder economic performance and generate massive problems in the labour markets, with high levels of structural unemployment being the most visible problem (see Andersen and Jensen 2004 for an overview). Therefore, there are many people who think that less regulation and the enforcement of pure and undisturbed market forces are the only ways to economic success and high levels of employment in European countries. It is commonly argued that the increase in non-standard work will offer certain advantages for both employers and employees (see Belous 1989). From the employers’ point of view, non-standard working arrangements provide numerical flexibility, which helps firms adjust their workforces to uncertain market demands and save notably on employment costs. For example, the subcontracting and outsourcing of non-essential functions make it possible for firms to concentrate on their core areas of competence and to use their resources more efficiently (Kalleberg and Olsen 2004, p. 322). As a positive consequence for employees, it is argued that non-standard labour contracts, like part-time work or temporary work, enable people to adjust their working life to other types of activities, preferences and obligations (see Muffels and Fouarge 2001; Hill et al. 2001). Non-standard work may form a beneficial strategy for many groups of employees like students, parents of small children and other people with caring obligations. Also top 172

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professionals, like for example computer specialists, may prefer the greater discretion of flexible work arrangements to often more binding regularized patterns of working (Spoonley et al. 2002). Moreover, it has been argued that having a non-standard job is better than no job at all and for many workers non-standard forms of employment such as temporary jobs may offer a stepping stone to permanent work (Booth et al. 2002). However, there are also authors who argue that the adverse effects of flexibilization and non-standard work clearly outweigh the possible positive ones. For many authors, the most important prerequisite for flexibilization is to ensure a decent level of social protection and assistance for re-employment to wage earners, and thus to combine flexibility with high social security into a ‘flexicurity’ strategy (see Muffels and Fouarge 2001). Others view flexibilization even more critically and emphasize that a significant proportion of the labour force is suffering from the uncertainty and insecurity caused by non-standard work arrangements: the adjustment of their whole personal lives to the demands of the labour market. From this perspective it is feared that flexible labour market strategies propagate inequality, poorer working conditions and lower job quality, and affect tendencies towards labour force polarization, without any improvement in economic efficiency (for an overview see Esping-Andersen and Regini 2000; Esping-Andersen 2000). For instance, Gray (2004) argues that flexible arrangements impact most on those with the least bargaining power as individuals, namely the low-paid, less well-educated and less experienced workers. Indeed, the changes in the labour markets may generate a paradoxical situation: at the same time as some wage-earners are working more intensely than ever, others have to submit to unemployment or, at best, work in insecure, precarious jobs and for fixed-term contracts. In fact, in many countries left-wing politicians and labour unions have been less enthusiastic than employers to increase flexibility in the labour markets. The idea that work is becoming more demanding and stressful goes a long way back. For decades it was feared that the introduction of Fordist assembly line technologies would result in the deskilling and simplification of work, which in turn would make work more intense and supervisory control tighter (e.g. Braverman 1974). Gradually, however, the assembly line was superseded by computerization and applications of information technology. At this historical point the fear of increasing work pressure is not caused by deskilling, but by the upskilling of work. Increasing emphasis on the quality of production and service delivery requires greater skills, and a continuous need to learn new tasks actually increases work pressure (Gallie et al. 1998; Gallie 2005; Green and McIntosh 2001). It seems that if the requirements are too low, work becomes stressful because of monotony. However, also too high requirements make work strenuous.

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From a historical perspective, Green (2005) observes that, on average, wage-earners have enjoyed rising wages, have operated in safer and more pleasant working conditions and have found work that corresponds to their increasing skill levels to be more satisfactory and rewarding. However, at the same time a significant part of the labour force suffers from the uncertainty and insecurity caused by non-standard work arrangements and attempts to adjust their whole personal lives to the demands of the labour market. Moreover, a notable part of the labour force works much more intensely and experiences increasing mental strain, sometimes to the point of exhaustion. For some employees, work has come under increased and unwelcome control from above, which leaves individual employees with less influence and control over their daily work and experiencing a correspondingly less fulfilling experience than before (Green 2005). The aim of this chapter is to enter into the experience of work in the context of increasing flexibilization and non-standard work arrangements within Nordic and other European labour markets. The main focus of this chapter is on the subjective perceptions among the labour force in relation to their work. Two sets of questions are addressed. The first questions relate to country differences in labour markets and especially the connections between the labour markets and subjective perceptions of job quality. As is well understood, most European countries have pursued policies to deregulate the labour market, at least to a certain degree (see Lodovici 2000; Treu 1992). Yet, European labour markets are not homogeneous (e.g. EspingAndersen and Regini 2000). On the contrary, as shown in other chapters of this volume, in many respects it is possible to divide the European countries into a limited number of socio-economic regimes. Correspondingly, European labour markets can be clustered into five regimes as well. Roughly speaking, and whether it be good or bad for the smooth functioning of the labour markets, the Nordic countries are the ones with the highest levels of social protection, centralized and extensive labour market regulations and high employment protection (see Ervasti 2001). Furthermore the Continental and Southern European countries also have relatively regulated labour markets and especially high employment protection, whereas the Anglo-Saxon and the Eastern European countries have the most liberal labour markets. Therefore, more precisely, the first questions to be answered are as follows: Do we find differences between countries in terms of work arrangements and averages of working experience and do these differences reflect regime-specific variation? Do the Nordic countries form a contrast to the rest of European countries? After the country level differences we move to individual level. The second set of questions concerns the differences in job quality between wage-earners in standard and non-standard employment. The quality of

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non-standard jobs is still an unsolved issue: whereas some argue that nonstandard work is a substandard form of employment, others contend that non-standard work arrangements are beneficial for several groups of employees. To formulate more promptly, the second questions are the following: Are non-standard working arrangements associated with poor job quality? What other factors may account for the variation in job quality? Are there differences between the employment regimes? In order to answer these questions we analyse the ESS Round 2 data, which contain several measures on experiences at work. We use items that measure the possibilities of having influence over one’s own work as well as items that ask about certain qualities of the respondents’ present or past work.

COUNTRY DIFFERENCES IN WORK ARRANGEMENTS The fact that the European labour markets cluster into a limited number of welfare and employment regimes is well acknowledged in literature (Muffels and Fouarge 2001; Esping-Andersen 1990, 1999; Lodovici 2000). For example, Esping-Andersen (1990, p. 142) points out that each welfare regime goes together with a distinctive labour-market and employment regime. However, in certain respects the structural differences between the various labour markets are not always clear-cut. The Nordic countries have the strongest tradition of centralized industrial relations, union coverage and a highly developed welfare state. Because of these characteristics, the Nordic countries are often viewed as a special case: all the worst nightmares about the alleged adverse effects of the too generous welfare state and the too rigid labour markets should come true in these countries. Paradoxically, several empirical labour market indicators show that the Nordic countries are not among the most inflexible ones in a European comparison. For example, as measured with the often-cited OECD index of employment protection (e.g. Lodovici 2000; see also Bertola et al. 2000), the Danish labour markets are the most flexible ones in Europe, followed by the UK, Ireland, Finland and Sweden. In contrast, employment protection is much higher in Central European, and especially Mediterranean countries. As Esping-Andersen (1999, pp. 122–3) notes, this paradox can be explained by the fact that nations apply different methods to obtain worker security. The Nordic strategy of adaptation to the changes in international markets has been to combine high labour market flexibility with strong social guarantees to the individual worker – either in the form of generous

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social protection, pensions or active labour market measures. In Continental and Southern Europe, the same aims have been pursued with strong employment protection. The Continental countries lean on a comparatively strong labour market regulation, and, in consequence, may sacrifice job growth. However, these countries also maintain balanced budgets, wage equality and, the crucial issue here, decent standards of working conditions for at least a certain percentage of the labour force (Esping-Andersen 1999; Cebrian et al. 2003). The liberal countries emphasize unregulated markets and encourage the proliferation of low-wage jobs. This regime combines weak, decentralized industrial relations with weak employment regulation. The result is high employment rates but probably also increased inequality and lower working standards. The best example of liberal labour markets is undoubtedly the US, but the same logic was followed especially in the 1980s and early 1990s in the UK and Ireland. However, Muffels and his colleagues (2002) conclude that the European liberal countries also have fairly decent levels of employment security. The Eastern European countries may be grouped as a separate regime. These countries experienced a rapid shift from extremely regulated labour markets to more flexible systems as they turned into market economies in the late 1980s (Cazes and Nesporova 2003; Wallace 2003). During the last decades the logic of the reform in these countries has been very much the same as in the liberal countries, which has obviously resulted in more efficiency in the labour markets. At the same time, however, increasing inequality has been even more obvious, especially as the levels of social protection are low as a result of the low economic performance and high unemployment since the 1990s. The distributions of two types of non-standard work arrangements, part-time work, and fixed-term work, in the different labour market regimes are depicted in Table 9.1. The countries included in this analysis are categorized in five groups according to the discussion on the employment regimes presented above. Altogether 24 countries are included in the analysis. The group of ‘liberal’ countries consists of the United Kingdom and Ireland, the ‘corporatist’ regime consists of Austria, Belgium, Switzerland, Germany, France, Luxembourg and The Netherlands, the ‘Southern’ regime consists of Spain, Greece and Portugal, and finally, the Czech Republic, Estonia, Hungary, Poland, Slovenia, Slovakia and the Ukraine form the group of Eastern European countries. The frequencies of the non-standard work arrangements included in this analysis follow the lines between the regimes only vaguely. Unlimited work contracts are slightly more general in the Nordic countries than in Central and Southern European countries and the two Liberal countries.

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Table 9.1 Non-standard work arrangements in European country groups: Nordic countries in comparison with other country groups Full-time

Nordic Denmark Finland Iceland Norway Sweden Liberal Corporatist Southern Eastern

Part-time

Unlimited

Limited

No contract

Unlimited

Limited

No contract

73.8 71.5 75.6 56.9 69.4 77.5 53.7 65.8 64.5 71.0

9.7 10.4 14.6 13.2 6.5 8.6 6.9 8.3 18.1 13.5

2.3 4.2 0.6 11.8 4.5 0.4 11.0 1.8 7.2 4.8

8.8 8.5 5.4 11.5 13.9 7.7 17.8 18.2 4.3 7.7

3.4 2.4 2.9 3.9 2.6 4.8 2.6 3.7 2.8 1.7

1.9 3.0 0.8 2.8 3.0 1.1 8.1 2.2 2.6 1.4

However, as Wallace (2003) notes, in some cases the number of fixed-term contracts is a better indicator of regulation than deregulation, because in countries with only a minimum of job protection there is actually no need for the use of fixed-term contracts to the same extent. Indeed, as shown in Table 9.1, the proportions of the labour force in permanent employment are larger in the Eastern European countries than in the other groups of countries. Although regular full-time jobs are the most common in the Nordic countries, it is clear that non-standard work arrangements are part of the everyday life of a significant proportion of wage-earners also in the North. According to our data more than a quarter of Nordic wage-earners are employed in a non-standard job. The numbers of fixed-term employees are notably high in the Nordic countries, and especially so in Finland and Iceland. In fact, in their comparison of labour markets in the USA and Norway, Kalleberg and Olsen (2004) even suggest that an inner logic in the Nordic labour markets stimulates non-standard employment because firms particularly prefer all forms of non-standard employment to the too strictly regulated standard work arrangements. The same argument has been used to explain the notable growth of temporary jobs in Southern European countries in which the levels of work protection are comparatively high (Booth et al. 2002). All in all, however, the largest shares of non-standard employment can be found in the liberal and corporatist countries, where the role of part-time employment is more pronounced than elsewhere in Europe.

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COUNTRY DIFFERENCES IN JOB QUALITY The differences in the structures of the labour markets or the varying frequencies of non-standard work arrangements between the employment regimes do not tell us much about the differences in the quality of working life and the subjective experiences of employees in various parts of Europe. We may well expect that non-standard work has both good and bad sides. In order to measure job quality we need more elaborated indicators. In prior research, a variety of definitions of ‘bad jobs’ has been used. Kalleberg and his colleagues (2000), for instance, conceptualize bad jobs in terms of three bad characteristics in their American survey: low pay, no access to health care and no access to pension benefits. McGovern and his associates (2004) emphasize that unlike in the USA, access to social security benefits is not as crucial a factor in a European context as the welfare state provides the most important benefits for most or all employees. Yet, they use access to employer pension schemes, continuity of income during sickness, wage and the existence of a recognized career or promotion ladder as indicators of job quality. In this analysis we use broader concepts to define a bad job. We agree with earlier studies on the importance of low income and the lack of promotion opportunities, but also include subjective measures about security of work, lack of work autonomy, monotony of work and heavy work-load as indicators of bad jobs. Basically, the last three items correspond to the theoretical Demand–Control Model of work stress (Karasek 1979), according to which job strain results from the interaction of two main dimensions of the work environment: the psychological demands that the job poses on the worker and the control that the worker is allowed to have over the job. The model suggests that the highest strain arises when demands are high and control is low. Low pay is perhaps the least contested indicator of job quality. Also security of work and opportunities for advancement in one’s career are generally considered important as they refer to future success in the labour market. The early dual labour market theorists (Doeringer and Piore 1971; Gordon et al. 1982) emphasized that better opportunities for advancement are one of the characteristics of the primary internal labour markets, whereas dead-end jobs are typical for the secondary segment of the labour market (see also McGovern et al. 2004). The studies by Kalleberg et al. (2000) and McGovern et al. (2004) do not use work autonomy as a characteristic of a bad job. Instead they use it as a control variable in their analysis. However, there is clear evidence that the employees’ possibilities to influence how their daily work is organized and to control their own working time and the pace of their work strongly increase work satisfaction and subjective health and lead to a reduction of

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absence through sickness (Ala-Mursula et al. 2002; see Liu et al. 2005 for an overview). Similarly, task monotony in work is often, although not always, regarded as a stress-generating factor (Fisherl 1993; Melamed et al. 1995; see Thackray 1981). Furthermore, a heavy work-load is often identified as a job-stressor (see French et al. 1982) and thus it may well be used as a subjective indicator of job quality. The indicators for job quality were measured as follows. As the ESS data do not contain a variable that directly measures the personal wages of the respondents, we use a more general variable that taps the satisfaction of the respondent over the total income of his or her household. The respondents were asked to describe their feelings about their households’ income on a 4-point scale from ‘living comfortably on present income’ to ‘finding it very difficult on present income’. Lack of promotion opportunities was measured with an item posing a statement on a scale of 1 to 5 (agree strongly to disagree strongly), which suggests that the respondent’s ‘opportunities for advancement are good’. Security of job was measured with an item that suggests that the respondent’s ‘job is secure’ on a scale of 1 to 4 (from not at all true to very true). The indicator for lack of autonomy in work is based on a scale consisting of three items. These items ask the respondent to say on a scale from 0 to 10 the extent to which he or she is allowed to decide how his or her own daily work is organized, how much he or she is allowed to influence the policy decisions about the activities of the work-place and whether he or she is allowed to choose and change the pace of his or her work. The three items are strongly correlated and the reliability of the scale is satisfactory (.816). Monotony of work is measured with a single item that suggests that ‘there is a lot of variety’ in the respondent’s work. This variable is coded so that high values mean little and low values a lot of variety. Finally, the indicator on work-load is measured with a scale that consists of two items, one that suggests that the respondent’s job requires working very hard and the other that the respondent never has enough time to get everything done in his or her work. The answering options to these items ranged from 1 to 5 (agree strongly to disagree strongly). Table 9.2 describes all the six indicators in terms of means on a scale from 0 to 10 in the Nordic countries as compared to other groups of countries. High values correspond to dissatisfaction and low values to satisfaction with work. Again, we find only vague differences between the employment regimes. However, certain divisions do emerge. As shown in Table 9.2, wage-earners in the Nordic countries are generally slightly more satisfied with their income than their colleagues in other parts of Europe. However, in this sense Finland makes a notable exception among the Nordic countries as the Finnish employees are, on average, approximately as dissatisfied with their income as wage earners in Continental and Southern Europe.

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Table 9.2

Nordic social attitudes in a European perspective

Indicators of job quality; means by country groups (scale 0–10) Dissatisfaction Lack of Lack of Lack of Monotony Heavy with promotion security autonomy of work workincome opportunities of work of work load

Nordic Denmark Finland Iceland Norway Sweden Liberal Corporatist Southern Eastern

1.66 1.00 2.67 1.60 1.55 1.61 2.37 2.42 2.76 4.56

5.58 5.92 5.42 5.00 5.74 5.41 4.66 5.51 5.13 6.13

3.41 3.54 3.18 2.67 3.30 3.54 3.46 4.14 3.82 4.56

3.44 3.52 3.44 3.39 3.25 3.51 4.57 4.63 5.44 5.99

6.82 6.75 6.78 6.83 6.75 6.93 7.04 6.96 7.56 7.40

5.92 5.68 5.95 6.21 5.98 6.00 6.59 5.75 5.85 5.88

With reference to opportunities for advancement that workers perceive in each country, Table 9.2 shows that, on average, the Nordic countries score very near to the average of the corporatist countries in Continental Europe. In both the liberal and the Southern European countries, employees view their prospects for advancement better than their counterparts in the Nordic countries. In Eastern Europe wage earners are the most pessimistic of all about their prospects. Moreover, as shown in Table 9.2, employees in the Nordic countries have a slightly higher sense of security of work than wage-earners elsewhere in Europe. This is interesting in the sense that Danish employment protection stands out as one of the most flexible of all European countries. Probably the high levels of unemployment benefits and the often quite good prospects of finding a new job generate a sense of security among Danes. However, one should further note that even though the levels of social protection are clearly lower in comparison with the Nordic countries, the liberal countries do not score badly, either. With regard to discretion and monotony of work, we find that employees in the Nordic countries generally perceive their jobs to be more often autonomous and less often monotonous than wage earners in other parts of Europe. Finally, considering the work-load employees have in different parts of Europe, no clear patterns seem to emerge. Work-load appears to be the highest among employees in liberal countries, but overall differences are small and do not follow the lines of employment regimes.

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INDIVIDUAL DIFFERENCES IN WORK EXPERIENCE As defined in the introduction, the second task of this chapter is to examine the associations between non-standard work arrangements and the quality of job. This was done by means of multilevel modelling. As shown in earlier research (see Kalleberg et al. 2000; McGovern et al. 2004), the quality of one’s job does not only depend on the nature of one’s employment contract, but the differences between employees working in standard and nonstandard jobs have to be controlled for at least gender, age, educational attainment, occupational status and union membership. In the analyses depicted in Table 9.3 we use the six indicators of job quality described above as the dependent variables and the nature of the work contract (standard vs. six types of non-standard), gender (female = 1), age (in three categories), education (in years), occupational status (according to the Eriksson–Goldthorpe scheme with service classes 1 and 2 combined; unskilled manual = 0) and union membership (currently a member in a trade union = 1) as the independent variables. As the level 2 independent variables we use country groups that are defined the same way as in the previous Tables 9.1 and 9.2. The results of the multilevel analyses are shown in Table 9.3. First we estimated the unconditional empty model with no independent variables (Model 0) and after that included all the independent variables in the model (Model 1). As expected, job quality does not depend only on the nature of the work contract. According to the indicators used in Table 9.3, on average, women have lower levels of job quality compared with men. The only indicator for which we did not find a statistically significant difference between the two genders was security of work. Similarly, a lower level of educational attainment is associated with poor job quality as measured with all the other indicators except the one on heavy work-load. The higher the educational level of a person, the more work-load he or she has. In order to test the effects of age, the sample was divided into three categories. Prime-aged workers (25–55 years old) are contrasted against the youngest (below 25) and the oldest (over 55) age groups. The effects of age do not form a clear pattern. Prime-age workers are less satisfied with their income, perceive their jobs to be less secure and have a heavy work-load more often than younger and older employees. Concerning promotion opportunities and monotony of work, the prime-age group is located in the middle, which indicates that they report a better job quality than the oldest group but a worse one than the youngest group. Autonomy of work seems to increase with age; the youngest group reports the lowest levels of job autonomy.

182

Intercept Full-time, unlimited Full-time, fixed-term Full-time, no contract Part-time, unlimited Part-time, fixed-term Part-time, no contract Unskilled manual worker Other/unknown occupation Skilled manual worker Routine non-manual employee Service class Female

3.14*** Ref. .25*** .10 .07 .47*** .36** Ref. .08 .10 .31*** .74*** .11***

Low pay

6.49*** Ref. .10 .48*** .40*** .73*** 1.53*** Ref. .67*** .57*** .67*** 1.10*** .39***

Lack of promotion opportunities 4.19*** Ref. 1.85*** .99*** .37*** 1.98*** 1.49*** Ref. .33* .24** .26** .51*** .10

Lack of security of work 5.02*** Ref. .49*** .65*** .13* .65*** .07 Ref. 1.37*** .36*** .94*** 1.95*** .22***

Lack of autonomy of work

7.42*** Ref. .09*** .06 .12*** .17** .12 Ref. .41*** .33*** .30*** .53*** .08***

Monotony of work

5.40*** Ref. .09 .02 .62*** .76*** .96*** Ref. .24* .14* .09 .45*** .14***

Heavy work-load

Table 9.3 Individual determinants of work quality: multi-level regression on low pay, lack of promotion opportunities, lack of security of work, lack of autonomy of work, monotony of work and heavy work-load (low values mean high job quality and high values low job quality)

183

* p .05; ** p  .01; *** p .001.

1.37 .55 .26

Su (Model 0) Su (Model 1) ICC

Notes:

Ref. .33*** .42*** .08*** .02 Ref. .33 .40 1.45* 2.15***

Middle age group Youngest age group Oldest age group Education in years Union member Nordic Liberal Corporatist Southern Eastern .38 .15 .05

Ref. .70*** .86*** .06*** .13* 0 .96* .28 .27 .80** 1.00 .82 .09

Ref. .22* .44*** .05*** .17** 0 .35 .16 .47 1.14 1.10 .20 .13

Ref. .71*** .19*** .07*** .20*** 0 1.78*** 1.27*** 2.10*** 2.44*** .09 .03 .09

Ref. .05* .10* .02*** .04** 0 .20 .03 .60*** .38**

.24 .23 .05

Ref. .20** .16** .03*** .04 0 .57 .31 .02 .12

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Moreover, job quality depends on occupational status. Generally, it can be contended that the lower the position in the occupational hierarchy, the poorer the job. In addition, we find some evidence that union members do have better jobs than other employees. Finally, the bottom rows of Table 9.3 show that the differences between the country groups are also approximately the same after controlling for the other variables. In short, even though the differences are not large, wage-earners in the Nordic countries generally report better job quality than their colleagues in other country groups. However, the most notable exception to this pattern is in perceptions in relation to promotion opportunities. Employees in liberal countries report the highest level of promotion opportunities, whereas the Eastern European workers score the lowest. However, the most crucial issue in the analyses of Table 9.3 is the variation between employees working in different work arrangements. Do we find support for the claims that non-standard jobs are a substandard form of employment? Yes, we do. According to most of our six indicators, permanent full-time employees score higher than non-standard employees in job quality. Permanent full-timers are among the most satisfied with their income: they view their promotion opportunities optimistically and consider their jobs to be relatively secure, autonomous and varied when compared with most other groups. However, the multivariate analyses also reveal some exceptions to this pattern. For example, permanent part-timers find their jobs more secure than permanent full-timers. Furthermore, there is a difference between permanent full-timers and full-timers with no work contract in terms of autonomy of work. Full-timers with no contract seem to have the most autonomy. Moreover, permanent full-timers report higher work-loads than most other groups. This result is consistent with earlier findings concerning the concentration of working hours in fewer households and employees. In further analyses (not shown) we also tested to what degree the effects of the form of employment vary across countries and groups of countries. This was done with the expectation that in the Nordic welfare states these differences would be smaller than elsewhere. The hypothesis was not confirmed. The effects of the form of employment were surprisingly similar in all countries, and therefore the analyses are not reported in more detail.

DISCUSSION As well reported in many studies, the prevalence of non-standard jobs has increased during the last decades. Often this is seen as an adjustment of

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firms to increasing competitive pressures. Consistently, in this chapter we have seen that a notable part of the European labour force is employed in non-standard arrangements. Two sets of questions were scrutinized in this chapter. The first task was to see whether variation in work arrangements and job quality specific to country regimes exists in Europe. The answer is that, in this analysis, the country differences only reflect the different employment regimes to a limited extent. However, non-standard arrangements are somewhat less general in the Nordic countries than elsewhere in Europe. In terms of job quality we also found that in satisfaction with income, security of work, as well as work autonomy and variability of work, the Nordic employees score higher than their counterparts in other parts of Europe. However, this is not the whole truth. For job quality measured in terms of perceived promotion opportunities and especially work-load, the Nordic countries scored among the lowest in Europe. All in all, however, the lowest work standards can be found in Eastern parts of Europe. The Continental, liberal and Southern European countries have managed to maintain higher standards. Nevertheless, in the light of evidence obtainable from the ESS, the differences between the country groups should not be exaggerated. Although the Nordic countries score highly in most measures of job quality, the differences are not large when compared with the rest of the European countries. The second task of this chapter focused on individual differences in work experiences. More specifically our task was to examine whether or not nonstandard work arrangements are associated with poor job quality. Our evidence shows that employees in non-standard work arrangements generally perceive the quality of their jobs to be poorer than employees in standard jobs and this result was universal across all countries. We find a clear indication that non-standard work is very often considered to be a substandard form of employment. It is very likely that, in general, the growth of nonstandard jobs is more likely to reflect employers’ than employees’ preferences. Although this analysis suggests that a justified conclusion is that the negative sides of non-standard work outweigh the positive ones, we also found some evidence to support the idea that not all non-standard jobs are bad. For example, in some cases part-time work could not be called a bad job. Particularly the group of permanent part-timers scores surprisingly highly on several indicators of job quality used in this analysis. A small group of wage-earners who find non-standard employment personally preferable to regular work does exist, as according to our original assumptions.

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REFERENCES Ala-Mursula, Leena, J. Vahtera, M. Kivimäki, M.V. Kevin and J. Pentti (2002), ‘Employee control over working times: Associations with subjective health and sickness absences’, Journal of Epidemiology and Community Health, 56 (4), 272–8. Andersen, Jørgen Goul and J.B. Jensen (2004), ‘Employment and unemployment in Europe: Overview and new trends’, in Jørgen Goul Andersen, Jochen Clasen, Wim van Oorschot and Knut Halvorsen (eds), Europe’s New State of Welfare. Unemployment, Employment Policies and Citizenship, Bristol: Policy Press, pp. 21–57. Belous, Richard (1989), The Contingent Economy: The Growth of the Temporary, Part-Time, and Subcontracted Workforce, Washington, DC: National Planning Association. Bertola, Giuseppe, T. Boeri and S. Cazes (2000), ‘Employment protection in industrialized countries: The case for new indicators’, International Labour Review, 139 (1), 57–72. Booth, Alison L., M. Francesconi and J. Frank (2002), ‘Temporary jobs: Stepping stones or dead ends’, The Economic Journal, 112 (480), 189–213. Braverman, Harry (1974), Labor and Monopoly Capital. The Degradation of Work in the Twentieth Century, New York: Monthly Review Press. Cazes, Sandrine and Alena Nesporova (eds) (2003), Labour Markets in Transition: Balancing Flexibility and Security in Central and Eastern Europe, Geneva: International Labour Office. Cebrian, Immalulada, G. Moreno, M. Samek, R. Semenza and L. Toharia (2003), ‘Nonstandard work in Italy and Spain’, in Susan Houseman and Machiko Osawa (eds), Nonstandard Work in Developed Economies. Causes and Consequences, Kalamazoo, MI: Upjohn Institute, pp. 89–129. Doeringer, Peter B. and Michael J. Piore (eds) (1971), Internal Labor Markets and Manpower Analysis, Lexington, MA: D.C. Heath. Ervasti, Heikki (2001), ‘Fragmentation and individualization? The legitimacy of corporatism among the Finnish labour force’, in Henry Milner and Eskil Wadensjö (eds), Gösta Rehn, the Swedish Model and Labour Market Policies. International and National Perspectives, Aldershot: Ashgate, pp. 119–44. Esping-Andersen, Gøsta (1990), The Three Worlds of Welfare Capitalism, Cambridge: Polity Press. Esping-Andersen, Gøsta (1999), Social Foundations of Postindustrial Economies, Oxford: Oxford University Press. Esping-Andersen, Gøsta (2000), ‘Who is harmed by labour market requlations? Quantative evidence’, in Gøsta Esping-Andersen and Marino Regini (eds), Why Deregulate Labour Markets?, New York: Oxford University Press, pp. 66–98. Esping-Andersen, Gøsta and M. Regini (2000), ‘Conclusions’, in Gøsta EspingAndersen and Marino Regini (eds), Why Deregulate Labour Markets?, New York: Oxford University Press, pp. 336–41. Fisherl, Cynthia D. (1993), ‘Boredom at work: A neglected concept’, Human Relations, 46 (3), 395–417. French, John R.P., Robert D. Caplan and R. Van Harrison (eds) (1982), The Mechanisms of Job Stress and Strain, New York: John Wiley & Sons. Gallie, Duncan (2005), ‘Work pressure in Europe 1996–2001: Trends and determinants’, British Journal of Industrial Relations, 43 (3), 351–75.

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Gallie, Duncan, Michael White, Yuan Cheng and Mark Tomlinson (eds) (1998), Restructuring the Employment Relationship, Oxford: Clarendon Press. Gordon, David M., Richard Edwards and Michael Reich (eds) (1982), Segmented Work, Divided Workers: The Historical Transformation of Labour in the United States, New York: Cambridge University Press. Gray, Anne (2004), Unsocial Europe: Social Protection or Flexploitation?, London: Pluto. Green, Francis (2005), Demanding Work. The Paradox of Job Quality in the Affluent Economy, Princeton, NJ: Princeton University Press. Green, Francis and S. McIntosh (2001), ‘The intensification of work in Europe’, Labour Economics, 8 (2), 291–308. Hill, E. Jeffrey, J. Hawkins, M. Ferris and M. Weitzman (2001), ‘Finding an extra day a week: The positive influence of perceived job flexibility on work and family life balance’, Family Relations, 50 (1), 49–58. Kalleberg, Arne L. and K.M. Olsen (2004), ‘Non-standard work in two different employment regimes: Norway and the United States’, Work, Employment and Society, 18 (2), 321–48. Kalleberg, Arne L., B.F. Reskin and K. Hudson (2000), ‘Bad jobs in America: Standard and non-standard employment relations and job quality in the United States’, American Sociological Review, 65 (2), 256–78. Karasek, Robert A. (1979), ‘Job demands, job decision latitude, and mental strain: Implications for job redesign’, Administrative Science Quarterly, 24 (2), 285–308. Liu, Cong, P.E. Spector and S.M. Jex (2005), ‘The relation of job control with job strains: A comparison of multiple data sources’, Journal of Occupational and Organizational Psychology, 78 (3), 325–36. Lodovici, Manuel S. (2000), ‘The dynamics of labour market reform in European Countries’, in Gøsta Esping-Andersen and Marino Regini (eds), Why Deregulate Labour Markets?, Oxford: Oxford University Press, pp. 30–65. McGovern, Patrick, D. Smeaton and S. Hill (2004), ‘Bad jobs in Britain. Nonstandard employment and job quality’, Work and Occupations, 31 (2), 225–49. Melamed, S., I. Ben-Avi, J. Luz. and M.S. Green (1995), ‘Objective and subjective work monotony: Effects on job satisfaction, psychological distress, and absenteeism in blue-collar workers’, Journal of Applied Psychology, 80 (4), 29–42. Muffels, R. and D. Fouarge (2001), ‘Working profiles and employment regimes in European panel perspective’, Tilburg University Institute for Labour Studies (OSA), OSA-Working paper WP2001-12. Muffels, R., T. Wilthage and N. van den Heuvel (2002), ‘Labour market transitions and employment regimes: Evidence on the flexicurity–security nexus in transitional labour markets’, WZB Discussion Paper FS I 02-204, Berlin Wissenschaftszentrum Berlin fur Sozialforrschung. Spoonley, Paul, A. de Bruin and P. Firkin (2002), ‘Managing non-standard work arrangements: Choices and constraints’, Journal of Sociology, 38 (4), 425–41. Thackray, Richard I. (1981), ‘The stress of boredom and monotony: A consideration of the evidence’, Psychosomatic Medicine, 43 (2), 165–76. Treu, T. (1992), ‘Labour market flexibility in Central and East Europe’, International Labour Review, 131 (4,5), 497–513. Wallace, Claire (2003), ‘Work flexibility in eight European countries: A crossnational comparison’, Czech Sociological Review, 39 (6), 773–94.

10.

Attitudes towards immigrants Heikki Ervasti, Torben Fridberg and Mikael Hjerm

INTRODUCTION As shown in other chapters of this book, the Nordic countries have much in common in terms of social structure, institutions and their historical development. However, experiences in the field of modern immigration differ in these countries. In the 1950s and 1960s Finland was still a country of emigration, whereas Sweden was already receiving labour migrants. Denmark and Norway followed Sweden in the 1960s and 1970s, as did Finland in the 1970s and 1980s. During the last decades, all the Nordic countries have experienced a significant increase in the number of foreignborn population, and the exceptional ethnic homogeneity of the Nordic populations has gradually started to acquire more diversity. Currently, most appraisals of future trends in immigration suggest that the figures will increase. There is no lack of awareness of the extra European immigration needed to meet the demands of the labour market as European populations are in a process of ageing. Nevertheless, countries seem to have difficulties in integrating the immigrants who already reside in their territorial space. This is at least the case if integration is measured in such terms as participation rates in the labour market, levels of income and educational attainment, occupational status or voting behaviour, for instance. Moreover, several prior studies indicate that attitudes towards newcomers are not always friendly among the majority populations. All over Europe the integration of immigrants is disturbed by the negative attitudes of notable parts of the population, or even by violent outbursts towards immigrants. In this chapter we analyse attitudes towards immigration and immigrants in Nordic countries and compare them with other European nations. However, we adopt a somewhat different starting point from most other studies. Whereas most prior research has concentrated on individual level determinants of xenophobic attitudes, our main target is country level differences rather than individual differences. More precisely 188

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we use multilevel methods to test the effects of certain country level factors on the attitudinal differences that are found between European countries before and after controlling for individual level independent factors. The theoretical departure point is found in the so-called group threat theory (Blumer 1958), which assumes that individuals identify with one or more groups and that the diverse interests of different groups generate conflicts that in turn generate negative attitudes. This means, in terms of ethnicity and immigration, that one or more minority group threatens the majority group, which elicits anti-immigrant attitudes among members of the latter. The classic example is Bobo’s (1983) study of the transporting of white children by bus to black neighbourhoods in the USA. His research showed that, despite the white parents’ advocacy of general principles of equality between ethnic groups, they strongly opposed the trip to black neighbourhoods when it came to their own children. They experienced a threat to their group position and reacted negatively. There are a number of factors that can be seen as threatening, such as socio-economic factors. Ever since the days of Sherif and Sherif (1953), the existence of prejudice has been explained by the competition for scarce resources. Immigrants pose a threat to the material well-being of the original majority population. As Giles and Hertz (1994) put it, the relationships between different ethnic groups are viewed ‘as a function of their competitive positions’ in this theory. Immigrant workers who come from countries with clearly lower standards of working conditions and wages may distort the labour market of the country receiving foreign labour. Quillian (1995) shows that GDP interacts with the proportion of immigrants to produce anti-minority prejudice in Europe. The less the majority feel that their jobs are in jeopardy, the more likely they are to be in favour of, or at least not against, increased levels of immigration (Espenshade and Hempstead 1996). Similarly, the more people think that immigrants are likely to compete for jobs; the more likely they are to support reduced levels of immigration (Fetzer 2000). The explanation, from a group threat perspective, is that the struggle over scarce resources makes people want to favour their own group over other groups. There are also perceived cultural threats. Empirical studies do not consistently give support to socio-economic explanations. For example, Van der Brug et al. (2000) found that social and economic variables were mostly insignificant in explaining support for anti-immigrant parties in seven European countries. Similar results have also been found in other studies (e.g. Scheepers et al. 2002). As an alternative to socio-economic explanations, cultural aspects have been emphasized as important factors to account for the existence of prejudice. According to this view, the origins

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of prejudice are related to cultural tensions between ethnic groups: foreigners are viewed as a potential threat to national identity and social order and, most importantly, to the values cherished by the original majority population. The par excellence explanation for threat, both cultural and socio-economic, has in many cases been the proportion of the minority population. This has been shown empirically to hold for the relation between whites and blacks in the USA (Fossett and Kiecolt 1989; Glaser 1994; Quillian 1996; Smith 1981; Taylor 1998, 2000), but there are a number of doubts if we consider other circumstances. The relationship seems more problematic if other minority groups are examined (Dixon and Rosenbaum 2004; Hood and Morris 1997; Taylor 1998) and things become more complex outside of a US context (Hjerm 2007; Quillian 1995; Scheepers et al. 2002). It is not only the forms of threat that are of importance, but the context within which the threat is perceived. The political context is one such example that may strengthen or weaken the threat dependent on the politics of immigration (Bauer et al. 2000; Hjerm 2007; Rydgren 2003). However, it is not only the politics of immigration and integration itself that matters. It is also likely that the type of welfare state is decisive for people’s views on immigration. Research about trust, social capital and game theory has taught us that the redistribution of resources is achieved more easily if people trust each other (Rothstein 2003). This is also a reciprocal relationship in that the greater the distribution, and larger the welfare state, the more people will trust each other. North American research on racism and prejudice indirectly supports the idea that institutions function better in a culturally homogeneous environment. The lack of cultural or ethnic attachments and sameness makes redistribution of common resources extremely difficult. Realistic group threat theory (e.g. Bobo 1983; Sears and Jessor 1996) shows that people (white in this case) oppose the redistribution of resources to people (blacks) with whom they do not identify. Sears and Citrin (Citrin et al. 1997; Sears and Citrin 1985) show that the unwillingness to spend money on various welfare state programmes relates to racism. They show that self-interest cannot explain support for public spending on areas like schools, welfare, and healthcare or the preferred size of government, whereas racism can explain such attitudes (see also Gilens 1999). The explanation is that racist whites believe that redistribution is more beneficial for blacks. Similar results have also been suggested by McLaren (2002) who shows that the opposition towards the EU springs from racist or xenophobic attitudes. These attitudes are transformed into political realities, as exemplified by Alesina and Glaeser (2004; see also Luttmer 2001) who show that state redistribution increases with

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ethnic homogeneity across countries (as well as across the US states). The question is, of course, the classical one about the chicken or the egg; does homogeneity make extensive universal welfare states possible or do extensive universal welfare states produce, for example, cultural homogeneity. All in all, we expect people to be more positive towards immigration in more universal and comprehensive welfare states. There are a number of reasons for this. First, as discussed, we expect universal inclusive welfare states to produce a greater amount of trust and solidarity and therefore, in the long run, fewer anti-immigrant sentiments. Second, we expect visibility to be lower as groups are not singled out as explicitly. Third, the available resources for redistribution are less scarce in universal systems. The explicit research question of this chapter is therefore to examine the relation between the type of welfare state and the levels of xenophobic attitudes in each country as well as taking cultural and socio-economic threats into account. We structure this chapter as follows. First, we describe in more detail the country level and individual level variables to be included in the analysis. We explain the theoretical reasons why these variables may be expected to have an effect on attitudes towards immigration as well as their operationalization. After that we present first the descriptive results about the differences in xenophobia between countries and then the results of multilevel analyses. Finally, a discussion concludes.

COUNTRY LEVEL DETERMINANTS OF XENOPHOBIA It is easy to argue that the type of welfare state is decisive for the overarching immigration and integration policies, because it is the welfare state that, in practice, offers the possibilities to obtain health, education and social services needed in the new country, which, in turn, contribute to the new possibility to succeed in the new surroundings. Therefore, it is also reasonable to expect that the type of welfare state itself may structure people’s attitudes towards immigrants. Most probably, comprehensive welfare states like the Nordic ones generate a more positive attitudinal climate towards immigrants because of the more inclusive institutions and the high levels of solidarity between people. Research on trust and social capital shows that redistribution of resources is easier if people trust each other (Rothstein 2003; see also Chapter 7 in this volume). To put it briefly, the larger the welfare state and the higher the social expenditure in a country, the greater the level of redistribution of resources, and consequentially, the more people will trust each

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other. However, everyone does not agree about the positive effects of the welfare state and social capital. The counter-argument suggests that it is precisely the large in-group trust and solidarity that makes people increasingly aversive towards immigrants, because they are perceived as being more of a threat towards redistributive resources in comprehensive welfare states. Especially Alesina and Glaeser (2004) argue that majority populations formulate negative stances towards immigrants as they see a notable part of the social benefits being directed to them. Foreign incomers are seen as a threat as they require their share of the scarce recourses. It is, however, unclear whether this effect should be stronger in countries with marginal or residual social policies or in the more comprehensive welfare states. It may be expected that in marginal welfare states there can be more competition for the modest social benefits and services, however, in the more comprehensive welfare states the absolute amount of resources directed to immigrants is higher, which may also stimulate negative attitudes. In terms of welfare state typology, Denmark, Norway, Finland and Sweden belong to the Nordic model. Austria, Belgium, Germany, France, Italy, Luxembourg, The Netherlands and Switzerland have been classified into the conservative regime. The Czech Republic, Hungary, Poland and Slovenia are classified into the Eastern European model. Great Britain and Ireland belong to the liberal regime, and Spain, Portugal and Greece to the Mediterranean regime. Socio-economic Threats Competition over the scarce resources has been a central theme in earlier discussions concerning the determinants of xenophobia. The basic assumption is that economic problems in particular generate intolerance towards incomers, because the majority population sees them as a threat to their levels of living. Therefore, we would expect that the overall success and especially the economic success of a country in terms of the GDP or the unemployment rate might have an effect on the attitudinal climate in relation to immigrants. Information used is from the following sources: ● ● ●

Total public social expenditure is in percentage of GDP 2001. The source is the OECD Social Expenditure Database (SOCX) 2004. The unemployment rate 2002 is from Eurostat, with the figure for Switzerland taken from the UNDP Human Development Report 2004. GDP per capita (PPP in US$ 1999) is from the UNDP Human Development Report 2001.

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HDI, the Human Development Index 1999, is from the UNDP Human Development Report 2001.

Cultural Threats Finally, we test the effects of visibility of immigration on public attitudes. The visibility of immigration may be measured with two indictors. First, the actual number of immigrants in a country reflects how much and how often representatives of the majority population see and interact with immigrants. Second, it may not be that it is the real number of immigrants that matters, but the way immigration issues are treated in the more general public political discussion may be important. In many European countries immigration has led to an increase in support for small, perhaps populist, parties which often refer to the nationalist feelings of the majority population and aim at reducing the levels of immigration in their countries. Therefore, we also test the possible effects of the nationalist articulation occurring in the countries under scrutiny. The indicators here are as follows: ●

●

Proportion of foreign born: Share of population born outside the country. The proportion of foreign born, except for in Slovenia and Italy, is taken from the latest OECD figures (Dumont and Lemaitre 2004), which, thanks to improved methods of calculation, are slightly higher than other comparable statistics (e.g. SOPEMI 2003).1 The Slovenian figure is derived from the aggregate proportion of foreign-born in the sample and the Italian figure from UN figures. Political articulation of the national way of life: This indicator is adopted from the Manifesto data group (Klingemann et al. 2006). The manifesto data set is based on extensive content analyses of all political party manifestos in a large number of countries. The manifesto data are analysed in numerous different areas and we have adopted one of the available indicators that deals with the national way of life. This indicator appeals to the support for national ideals as well as protection of those ideas from subversion. The higher the value, the more frequent the emphasis of cultural/nation within those party manifestos. It means that the higher the frequency, the more prevalent this discourse is within a single country. The figures used are average figures for the years 1991 to 2003.

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INDIVIDUAL LEVEL DETERMINANTS OF XENOPHOBIA Although our main aim is not to explain individual characteristics, we control macro-level factors and a number of individual level variables. In addition to the macro-level factors we also control for a number of individual level variables, although our main aim is not to explain the individual characteristics. Based on earlier literature, we use income, education, gender, age, religiosity, political orientation and ethnic propinquity as individual level controls. Next, the possible effects of these variables are briefly discussed. Education According to earlier research, socio-economic factors and stratification hierarchies are among the most important determinants of prejudice. According to several studies, persons (Hello et al. 2004; Hjerm 2001) with low-scale social and economic backgrounds are more prone to express xenophobic sentiments than persons with high socio-economic status. More specifically, according to the theory of relative deprivation, those who experience adversity or fewer rewards than groups with whom they compare themselves are most likely to develop prejudices and fear of foreigners. However, the income variable is only available for 17 of the ESS countries in 2002. Therefore, we include education as a measure of socioeconomic status. Furthermore, education may also have a value-based effect on prejudice. Educational institutions may be regarded as vital propagators of democratic and tolerant values. Moreover, higher education may offer broader perspectives with more knowledge about foreign cultures, which, in turn, may reduce prejudice (Jackman and Muha, 1984). Indeed, education has repeatedly been shown to have a positive effect on tolerance towards immigrants (e.g. Coenders and Scheepers 2003; Hjerm 2001; Smith 1981). Education is measured in terms of the number of years for which the individual has attended full-time schooling. Gender According to several earlier studies, the effect of gender has been found to be a statistically significant predictor of attitudes towards immigrants. These studies indicate that women have more tolerant attitudes towards immigrants than men. This may be explained by a certain version of the theory of relative deprivation (Hernes and Knudsen 1992): many highly

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visible male foreigners among the otherwise homogeneous population may increase the competition for women. In other words, the men of the original majority population find themselves in a ‘less favourable position in the sex market’ (Hernes and Knudsen 1992, p. 127). Age Contradictory hypotheses can be posed about the effects of age. From the perspective of socio-economic explanations, the young age groups can be expected to show more prejudice than middle-aged and elderly groups. The economic position of the youth is often insecure. However, regarding the value priorities typical for each generation, age may have the opposite effect. Generation by generation, value priorities are often regarded to develop in a less materialistic and socially more liberal and tolerant direction (Inglehart 1997). This would lead us to suggest, in line with some earlier studies (e.g. Eisinga et al. 1999), that the younger a person is, the less prejudiced she or he is. We have also included a squared variable in order to cover a curvilinear relation between age and xenophobia. Religiosity and Political Orientation The effects of religiosity and political (left–right) orientation are also worth noting. Most religious groups espouse tolerance and love towards members of other groups. However, according to previous research, the relationship between religious beliefs and prejudice is ambiguous. On the one hand, there are studies that show that religious people tend to be more prejudiced than non-religious people (Allport and Ross 1967; Altemeyer 2003). On the other hand, there is also evidence that suggests there is either a slightly positive correlation between religious beliefs and prejudice (Jaakkola 1999), or no correlation when controlled for other factors (Eisinga et al. 1999). Religiosity is measured via a ten-grade scale of how religious the individual considers him/herself. Political Conservatism This has been shown to correlate with racial prejudice (e.g. Sears et al. 1997). Of course, opposition to government spending may be inspired not by racism but rather by more general conservatism and right-wing thinking. However, there is also evidence that political party affiliation directly affects attitudes towards immigrants and asylum seekers so that those supporting the leftist parties hold clearly more positive attitudes than those on the right. Political conservatism is measured via a classical left–right scale.

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Ethnic Propinquity Although the theories discussed above do not lead to assumptions concerning the effects of personal contacts with immigrants, place of residence or marital status on prejudice, these factors are included in the analysis as controls. Empirically, the most well-grounded explanation of the background of prejudice is the so-called contact hypothesis (Brewer and Miller 1988; Welch et al. 2001). According to this simple explanation, contact between groups reduces intergroup prejudice; that is, the more the members of the in-group are in contact and personally know members of the out-group, the less prejudice they show. Moreover, the place of residence and marital status may also affect attitudes towards foreign-born settlers. The general assumption is that those living in big cities have the most liberal attitudes towards immigrants, whereas those living in rural areas are the most prejudiced. Two variables have been included to measure propinquity. First, a measure of the neighbourhood, where respondents were asked if the neighbourhood in which they live could be described as one where almost ‘nobody’, ‘some’ or ‘many’ people are of a different race or ethnic group from most [country] people. Nobody and some were merged into one category. Second, the respondents were asked if they had any immigrant friends or not, and the possible categories are ‘several’, a ‘few’ and ‘none’.

DESCRIPTIVE RESULTS We start the empirical analysis by presenting descriptive results. In order to measure attitudes towards immigration and immigrants we use an indicator that consists of six statements that measure attitudes towards immigrants. The answering options to the statements range from zero to ten on an 11-point scale. The exact wordings of the statements are: 1. Would you say that people who come to live here generally take jobs away from workers in [country], or generally help to create new jobs? 2. Most people who come to live here work and pay taxes. They also use health and welfare services. On balance, do you think people who come here take out more than they put in or put in more than they take out? 3. Would you say it is generally bad or good for [country]’s economy that people come to live here from other countries? 4. Would you say that [country]’s cultural life is generally undermined or enriched by people coming to live here from other countries?

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5. 6.

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Is [country] made a worse or a better place to live in by people coming to live here from other countries? Are [country]’s crime problems made worse or better by people coming to live here from other countries?

The six statements produce a one-factor solution (principal component analysis) in all countries (see Appendix). The indicators also load very similarly to the factor in all countries. Cronbach’s alpha scores are also, as expected, high in all the included countries. Thus, it is clear that the six items measure one and the same dimension in all countries. The same is, of course, the result when testing the indicators in a Latent Class Analysis. Similar items in the International Social Survey Programme also produce one dimension/cluster/class for all the included countries. People simply do not make a distinction between the items included here; they are just positive or negative towards immigrants in general. The items were compiled into an additive index that was standardized to range between zero and 100, whereby the higher the value, the stronger the xenophobia. It can be claimed that single items are ‘factual’ statements that have little to do with xenophobia. However, no classification concerning who is and who is not xenophobic is made, which means that the absolute scores are relatively meaningless. The index also correlates strongly with attitudes towards immigration. The more xenophobic one is the fewer immigrants one is willing to accept.2 Correlations between single items and the index are very similar, which indicates, that they have a similar impact. Moreover, omitting one or more item from the index does not produce any different results. It is perhaps possible to object to single items, but together they clearly make up a valid indicator of xenophobia. Figure 10.1 depicts attitudes towards immigrants in 21 European countries as means on scales that are scored from zero to 100. As can be seen in Figure 10.1, generally the public of the Nordic countries hold more tolerant attitudes towards immigrants than the public of other European countries. Judged by the mean of the scale that combines all the variables in Figure 10.1, the public of the Eastern European and liberal countries hold the most intolerant views. However, there is also certain variation within the country groups. For example, in the light of this analysis, Greeks hold the most negative attitudes towards immigrants in the whole of Europe, whereas the other Mediterranean countries score very near to the European average. Similarly, among the Eastern European countries, only the Czechs and Hungarians have exceptionally negative attitudes compared with the rest of the European nations. Within the Nordic group Sweden stands out with a low score on the xenophobia index, whereas Denmark

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Figure 10.1

Nordic social attitudes in a European perspective

Level of xenophobia across Europe

and Norway are on a similar level to other European countries like Austria, Switzerland, Spain and Italy.

RESULTS FROM THE MULTILEVEL MODELS The first model (Model 0) to be tested is the ‘empty model’ (one without any country or individual level indicators). The point of using this model is to ascertain if there is any country level variance at all. If this is not the case then there is no need for multilevel modelling, because a standard OLS

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regression would result in the same output. We see that approximately 11 per cent of the variation is found between countries (Table 10.1). This 11 per cent score is quite high in these circumstances, as an (hypothetical) extremely large figure would indicate that the variation is lower at an individual level than at a structural level, which is almost impossible. The model is clearly better than a standard OLS model. In Model 1 the individual level socio-demographic variables are introduced and explain around 6 per cent of the within-country variance and around 6 per cent of the between-country variance. The introduction of the individual level attitudinal variables and the measures for relations with immigrants raises the variance explained to around 15–16 per cent both within countries and between countries. In the following models the different country level variables are introduced separately. In Model 3 we see that the welfare state typology accounts for 51 per cent of the unexplained variance at the country level. This model performs far better than the model with the countries’ social expenditure as a percentage of GDP (Model 5). The unemployment rate introduced in Model 6 does not contribute to the explanation at all. Models 4 to 7 deal with the socio-economic indicators. We see in Model 7 that GDP explains some of the country level variance but this model does not perform as well as the model with the welfare state typology, as it only accounts for 39 per cent of the variance at country level. The UNDP Human Development Index performs even better than the GDP as it appears from Model 7. The HDI model actually explains even more of the country level variance than the welfare state typology model. We also see that the percentage of social expenditure (Model 4) matters, whereas levels of unemployment (Model 5) do not. Finally, Models 8 and 9 deal with the cultural threat indicators. The percentage of foreign-born persons living in the country does not explain any more of the variance in xenophobia between the countries than Model 2 did without the variable of the proportion of foreign-born residents. Finally, the last country level variable introduced in Model 9 appears to be of some importance. It is the measure of ‘Positive appeals to patriotism and/or nationalism, suspension of some freedoms in order to protect the state against subversion and support for established national ideas’ in election programmes of political parties. Looking at the detailed results in Table 10.2 we see that the effects of the individual level variables are in accordance with previous research on antiimmigrant attitudes. There is a curvilinear relation between age and xenophobia in that the young and the elderly are more xenophobic than the middle aged. We also see that high levels of education, being on the political left and being

200

29.616 249.100

273085

0.057 0.063

27.927 233.340 0.510 0.159

14.501 209.370

Model 3

0.243 0.159

22.425 209.370

Model 4

0.125 0.159

25.918 209.370

Model 5

241141.6 241112.7 241139.1 241141.8

0.153 0.161

25.080 208.970

Model 1 Model 2

234727

0.147 0.164

25.274 208.370

Model 6

0.527 0.159

14.012 209.370

Model 8

0.249 0.159

22.235 209.370

Model 9

241136.7 241121.5 241136.4

0.383 0.159

18.283 209.370

Model 7

Notes: Su: between-country variance; Se: within-country variance; Explained: proportion of the variance in the null model explained by models 1–9. Model 0: only intercept; Model 1: M0  socio-demographic variables; Model 2: M1attitudinal variables immigrant relations; Model 3: M2 country classification; Model 4: M2  social expenditure/GDP; Model 5: M2 unemployment rate; Model 6: M2 GDP99; Model 7: M2 HDI99; Model 8: M2  % foreign-born variable (LU missing); Model 9: M2national articulation in party election programmes. ESS 1R 2002: 21 countries.

Interclass correlation 0.106 2 Log likelihood 279346.5

Explained Su Explained Se

Su Se

Model 0

Table 10.1 Variance components from a multilevel regression analysis of attitudes to immigrants/xenophobia index

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Table 10.2 Multilevel analyses of attitudes to immigrants/xenophobia index Variables

Xenophobia index Estimate

p

Regression constant Model 1 Age in years Age in years squared Gender, 1male, 0 female Years of full time education

62.333 0.060 0.001 0.326 0.837

.0001*** 0.0174* 0.0153* 0.0669 .0001***

Attitudes and contact Model 2 How religious are you, 0 not at all Left–right scale, 0 left Minority in living area, 0 few Immigrant friends, 1 none – 3  several

0.215 0.804 0.094 4.471

.0111* .0001*** 0.4929 .0001***

2.488 5.524 4.293 10.980 0

0.3279 0.1252 0.1439 0.0008*** 0

Total public social expenditure, % of GDP, 2001 0.510 Unemployment 2002 0.202 GDP 1999 0.389 Human Development Index 1999 99.237 % foreign born 0.311 Articulated nationalism in party election 1.856 programmes

0.0814 0.5119 0.0102* 0.0009*** 0.2256 0.0749

Country level variables Model 3 Country classification: Continental (AT, BE, CH, DE, FR, LU, NL) Anglo-Saxon (IE, GB) Southern (ES, GR, IT, PT) Eastern (CZ, HU, PL, SI) Nordic (DK, FI, NO, SE) – (reference category) Model 4 Model 5 Model 6 Model 7 Model 8 Model 9

Notes: Fixed regression coefficients for demographic, attitudinal and contact variables from model 4. * p .05; ** p .01; *** p .001.

religious all have positive effects on xenophobia. Positive effects can also be found from having immigrant friends, but not from living in a more heterogeneous neighbourhood. We have included random effects for religiosity and political left–right because they have significant effects. In practice, this means that the slopes or effects of these individual indicators vary across countries. There are significant differences between the Nordic countries and the

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Eastern European countries, but there are no significant differences between the Nordic countries and conservative, liberal or Mediterranean countries. However, the type of welfare state does matter for individual levels of xenophobia in the sense that there is a significant difference between some of them; particularly the Nordic group and the Eastern European group of countries. These two groups of countries are also the ones most different in many aspects, such as economic wealth. Looking first at the socio-economic threats we see that there is a significant relationship between the wealth of the country and a low level of xenophobic attitudes among the population. The higher the GDP per capita the less the level of xenophobia in the country, which is expected, as the socio-economic threat is lower in richer countries. But GDP is certainly not a sufficient explanation of the differences in xenophobia between the countries. Sweden is not the most affluent country among the Nordic countries, and the Nordic countries are, in general, not richer than a number of other countries belonging to the conservative and liberal type of countries. These results are strengthened by the fact that the HDI may be seen as an expression of living conditions as it combines life expectancy, level of education and GDP, and the HDI has a highly significant positive effect on xenophobia. Unemployment, however, does not matter. Among the characteristics of the Nordic welfare states is that they are high spenders of government money on their respective social security systems. However, the introduction of total public social expenditure as a percentage of GDP as a country level variable produces a relationship with xenophobia significant only at a 10 per cent level (see Model 5). Furthermore, this model does not perform as well as the welfare state typology or HDI when it comes to the share of variance explained between the countries. Focusing on the cultural threats we see that articulated nationalism has some importance, but it is only significant at a 10 per cent level and, as seen above, the model performs less well than the welfare state typology and HDI in explaining between-country variance. However, contrary to many other studies, the proportion of foreign-born individuals within the country has no effect on xenophobia.

CONCLUDING DISCUSSION The purpose of this chapter has been to analyse country differences in negative attitudes towards immigrants with a focus on the differences between the Nordic countries and between the Nordic countries and other European countries.

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Experiences with immigration differ between the countries, as does the public debate on immigrants and the level of immigration. In a number of European countries public debates on immigration have been rather loud, and tendencies for negative attitudes towards immigrants among majority populations have caused concern. In order to measure attitudes towards immigrants we have constructed an index of xenophobia based on six questions on attitudes concerning the effects of having foreign people coming to live in the country of the respondent. The six statements prove to constitute a single dimension in all countries and measure whether people are for or against immigrants in general. The measure is an index of xenophobia. In general the Nordic countries did not score high on either the single statements or the aggregated xenophobia index. Actually, Sweden’s scores are low in comparison to other European countries – only matched by Luxembourg. Finland scores a little higher but still below the typical level in Europe, and even Denmark and Norway are at the lower end of the countries, but on a level with a number of other countries like Austria, Switzerland and Italy. In our attempt to find country level characteristics that might explain some of the differences between the countries it turns out that the type of welfare state and the HDI are the best performing variables to introduce in a multilevel regression analysis. Both variables can explain around half of the unexplained variance between the countries, although only the difference between the Nordic countries and the Eastern European countries is statistically significant at a 5 per cent level. All our other attempts have not contributed to an explanation or are less convincing than the welfare state typology and the HDI expression of living conditions. However, aspects related to extensive welfare states, such as GDP and total public social expenditure as a percentage of GDP, look more like part of an explanation. All in all it seems that the extensiveness of the welfare state is more important than the characteristics of the welfare state in preventing negative attitudes towards immigrants. The good performance of the HDI indicates that high living standards in a country are of importance irrespective of the type of welfare state. By this we can conclude that the Nordic model does not create more xenophobic sentiments than other welfare state types. The assumed large in-group trust in the Nordic countries does not make people more aversive towards immigrants in the sense that they are perceived as more of a threat towards redistributive resources in comprehensive welfare states. On the contrary, all the Nordic countries are at the lower end of the xenophobia ranking. However, comparing the level of xenophobic attitudes within the Nordic countries, it becomes evident that the extensive welfare state or the comfortable living conditions and basic social security have to be supplemented

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with other aspects to explain the inter-Nordic differences. It appears that the articulation of nationalism in public debate, such as the election programmes of the political parties, might be of some importance for the attitudes expressed by the population. However, if this articulation of nationalism is combined with a weakened threat effect in relation to the size of the foreign-born population, it seems that the cultural threat factor is clearly less prevalent than the socio-economic ones. In combination this is clearly positive in that a strong and prosperous population and economy counter the effects of the perceived cultural threats. Even though we cannot conclude that a universal welfare system state is a context that diminishes threat, thus leading to a lower prevalence of xenophobia, we can at least conclude that it is worth striving for human development and prosperity as a way to diminish xenophobia.

NOTES 1. A comparison of the figures of foreign-born in the country samples with OECD statistics show that the samples are somewhat wrongly estimated. The average for the whole sample is 20 per cent (excluding Italy and Slovenia). Still, the ranking of foreign born is the same in the samples as in the OECD statistics. This means that it is feasible to use the aggregate sample data for Slovenia. For Italy we have used a figure from the UN, which deviates by 11 per cent from the aggregate sample data. Naturally, it makes no difference if the Slovenian aggregate data is adjusted upward by 20 per cent. It is important to note that the results would stay the same if the aggregated sample was used for all countries. Macro data are, of course, not problem-free, but the sample data display the same macro problems (i.e. the sampling frames are related to the same macro condition) as well as a risk of biased responses, which means that two possible error terms are introduced if aggregate sample data are used. 2. Correlations between the six statements about immigration and the index vary between 0.5 and 0.7.

REFERENCES Alesina, Alberto and Edward L. Glaeser (2004), Fighting Poverty in the US and Europe. A World of Difference, Oxford: Oxford University Press. Allport, Gordon. W. and M.J. Ross (1967), ‘Personal religious orientation and prejudice’, Journal of Personality and Social Psychology, 5 (4), 432–43. Altemeyer, Bob (2003), ‘Why do religious fundamentalists tend to be prejudiced?’, International Journal for the Psychology of Religion, 13, 17–28. Bauer, Thomas, Magnus Löfström and Klaus F. Zimmerman (2000), Immigration Policy, Assimilation of Immigrants’ and Natives’ Sentiments towards Immigrants: Evidence from 12 OECD Countries, Stockholm: Ekonomiska Rådet, Raport March 13 2000. Blumer, Herbert (1958), ‘Race prejudice as a sense of group position’, Pacific Sociological Review, 1 (1), 3–7.

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Bobo, Lawrence (1983), ‘Whites’ opposition to busing: Symbolic racism or realistic group conflict?’, Journal of Personality and Social Psychology, 45 (6), 1196–210. Brewer, Marilynn and Norman Miller (1988), ‘Contact and cooperation: When do they work?’, in P. Katz and D. Taylor (eds), Eliminating Racism: Profiles in Controversy, New York: Plenum Press, pp. 315–28. Citrin, Jack, D.P. Green, C. Muste and C. Wong (1997), ‘Public opinion toward immigration reform’, Journal of Politics, 59 (3), 858–81. Coenders, Marcel and P. Scheepers (2003), ‘The effect of education on nationalism and ethnic exclusionism: an international comparison’, Political Psychology, 24 (2), 313–43. Dixon, Jeffrey C. and M. Rosenbaum (2004), ‘Nice to know you? Testing contact, cultural, and group threat theories of anti-black and anti-Hispanic stereotypes’, Social Science Quarterly, 85 (2), 257–80. Dumont, Jean-Christophe and Georges Lemaitre (2004), Counting Immigrants and Expatriates in OECD Countries. A New Perspective, Paris: OECD. Eisinga, Rob, J. Lammert and J. Peters (1999), ‘Community, commitment and conservation’, European Sociological Review, 7 (2), 123–34. Espenshade, Thomas J. and K. Hempstead (1996), ‘Contemporary American attitudes toward U.S. immigration’, International Migration Review, 30 (2), 559–76. Fetzer, Joel S. (2000), Public Attitudes towards Immigration in the United States, France and Germany, Cambridge: Cambridge University Press. Fossett, Mark and J.K. Kiecolt (1989), ‘The relative size of minority populations and white racial attitudes’, Social Science Quarterly, 70 (4), 820–35. Gilens, Martin (1999), Why Americans Hate Welfare, Chicago: University of Chicago Press. Giles, Michael and K. Hertz (1994), ‘Racial threat and partisan identification’, American Political Science Review, 88, 317–26. Glaser, James M. (1994), ‘Back to the black belt: Racial environment and white racial attitudes in the south’, Journal of Politics, 56, 21–41. Hello, Evelyn, P. Scheepers, A. Vermulst and J.R.M. Gerris (2004), ‘Asociation between educational attainments and ethnic distance in young adults’, Acta Sociologica, 47 (3), 253–75. Hernes, Gudmund and K. Knudsen (1992), ‘Norwegians’ attitutes towards new immigrants’, Acta Sociologica, 35 (2), 123–39. Hjerm, Mikael (2001), ‘Education, xenophobia and nationalism: A comparative analysis’, Journal of Ethnic and Migration Studies, 27 (1), 37–60. Hjerm, Mikael (2007), ‘Do numbers really count? Group threat theory revisited’, Journal of Ethnic and Migration Studies, 33 (7), 1253–76. Hood, M.V. and I.L. Morris (1997), ‘Amigo o enemigo? Context, attitudes, and Anglo public opinion toward immigration’, Social Science Quarterly, 78 (2), 309–23. Inglehart, Ronald (1997), Modernization and Postmodernization: Cultural, Economic, and Political Change in 43 Societies, Princeton, NJ: Princeton University Press. Jaakkola, Magdalena (1999), ‘Maahanmuutto ja etniset asenteet. Suomalaisten suhtautuminen maahanmuuttajiin 1987–1999’, Labor Political Research, 213. Jackman, M.R. and M.J. Muha (1984), ‘Education and intergroup attitudes: Moral enlightenment, superficial democratic commitment or ideological refinement’, American Sociological Review, 49 (6), 751–69. Klingemann, Hans-Dieter, Andrea Volkens, Judith Bara, Ian Budge and Michael

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McDonald (2006), Mapping Policy Preferences II. Estimates for Parties, Electors in Eastern Europe, European Union and OECD 1990–2003, Oxford: Oxford University Press. Luttmer, Erzo (2001), ‘Group loyalty and the taste for redistribution’, Journal of Political Economy, 109 (3), 500–528. McLaren, Lauren M. (2002), ‘Public support for the European Union: Cost/benefit analysis or perceived cultural threat?’, The Journal of Politics, 64 (2), 551–66. Quillian, Lincoln (1995), ‘Prejudice as a response to perceived group threat: Population composition and anti-immigrant racial prejudice in Europe’, American Sociological Review, 60 (4), 586–611. Quillian, Lincoln (1996), ‘Group threat and regional change in attitudes toward African-Americans’, American Journal of Sociology, 102 (3), 816–60. Rothstein, Bo (2003), Sociala Fällor ochTillitens Problem, Stockholm: SNS. Rydgren, Jens (2003), ‘Meso-level reasons for racism and xenophobia. Some converging and diverging effects of radical right populism in France and Sweden’, European Journal of Social Theory, 6 (1), 45–68. Scheepers, Peer, M. Gijsbert and M. Coenders (2002), ‘Ethnic exclusionism in European countries. Public opposition to civil rights for legal migrants as a response to perceived ethnic threat’, European Sociological Review, 18 (1), 17–34. Sears, David O. and Jack Citrin (1985), Tax Revolt. Something for Nothing in California, Cambridge, MA: Harvard University Press. Sears, David O. and T. Jessor (1996), ‘Whites’ racial policy attitudes: The role of white racism’, Social Science Quarterly, 61, 6–53. Sears, David O., C. Van Laar, M. Carillo and R. Kosterman (1997), ‘Is it really racism? The origins of white Americans’ opposition to race targeted policies’, Public Opinion Quarterly, 61 (1), 16–53. Sherif, Muzafer and C. Sherif (1953), Groups in Harmony and Tension. An Integration of Studies on Intergroup Relations, New York: Harper. Smith, A. Wade (1981), ‘Racial tolerance as a function of group position’, American Sociological Review, 46 (5), 558–73. SOPEMI (2003), Trends in International Migration: Annual Report 2002, Paris: OECD. Taylor, Marylee C. (1998), ‘How white attitudes vary with the racial composition of local populations: Numbers count’, American Sociological Review, 63 (4), 512–35. Taylor, Marylee C. (2000), ‘The significance of racial context’, in David O. Sears, Jim Sidanius and Lawrence Bobo (eds), Racialized Politics. The Debate about Racism in America, Chicago: The University of Chicago Press, pp. 118–36. Van der Brug, Wouter, M. Fennema and J. Tillie (2000), ‘Anti-immigrant parties in Europe: Ideological or protest vote’, European Journal of Political Research, 37 (1), 77–102. Welch, Susan, Lee Sigelman, Timothy Bledsoe and Michael Combs (2001), Race and Place. Race Relations in an American City, New York: Cambridge University Press.

11.

Economic morality Kristen Ringdal

INTRODUCTION Recently, the assumption that corruption and low economic morality were mainly a problem in the third world has been challenged by a number of publicly exposed corruption and financial scandals in rich countries. The Nordic countries have been no exception. In Sweden, the biggest corporate scandal for 70 years was revealed in 2003. The chairman of the insurance company Skandia had to resign and three chief executives were charged with financial misconduct and tax fraud. In Norway, the media have exposed dubious practices in both the private and public sectors. In 2003, three top Statoil executives resigned because of their alleged participation in the arrangement of a $15 million ‘consulting contract’ that may have been used to bribe Iranian officials. Do these examples reduce the assumption that the Nordic countries have higher moral standards and ethical economic behaviours than other countries to the status of myth? Often the Nordic countries or Scandinavia are described as an entity with common norms. Is this also a myth, or do we find a common standard of economic morality in the Nordic countries? These two research questions are the point of departure for this chapter. Economic morality is ethics applied to the economic sphere and comprises values, attitudes and behaviour. Corruption is a narrower concept and can be defined as the abuse of (public) power for private gain. Although a great deal of research has focused on corruption in relation to public officials, the definition applies equally to the private sector. Corruption has been seen as a problem that hinders development and modernization and has generated an extensive research literature. This chapter does, however, apply a wider perspective that covers both values and economic practices. The value dimension includes economic trust and norms. Economic trust is the degree to which people at large as customers trust private and public officials to deal honestly with them. By economic norms, we refer to the degree to which people endorse or condemn unethical and illegal economic practices. Economic behaviour is tapped by the exposure of consumers as victims of large- and small-scale fraud and unethical 207

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practices and through their involvement in illegal and unethical practices as offenders. The literature review that follows focuses on two themes: country level and individual level differences in economic morality. The introduction ends with a presentation of research questions. Country Level Studies of Corruption Corruption may be seen as a central indicator of economic morality at the country level. In recent years, many studies of the causes and consequences of corruption have been published. The majority of these studies have been written by economists (Rose-Ackerman 1999; Svensson 2005; Treisman 2000; You and Khagram 2005). This field of research may serve as a background for the formulation of hypotheses on differences between countries. Causes of corruption may be grouped into three broad categories: economic, cultural and political explanations (You and Khagram 2005). Economic factors, especially economic development, have been considered to be the most important ones. Political explanations include democracy and the size of government. Cultural and historical explanations of corruption include the effects of religion, where Protestantism is seen as a safeguard against corruption. You and Khagram found indications that income inequality increases the level of corruption through material and normative mechanisms. Their study also indicates that corruption, in turn, contributes to income inequality, which creates a vicious circle of inequality and corruption. Montinola and Jackman (2002) focus on political explanations. In their public choice explanations of corruption, the main cause is the lack of competition in economic or political arenas. Government intervention can restrict markets through legislative and regulatory mechanisms, and government officials may have the power to distribute highly lucrative government contracts. This may also give rise to bribery as a means of avoiding government regulations. On the other hand, if government officials are well paid, corruption is less likely. Competition among politicians and bureaucrats may minimize corruption in government (Rose-Ackerman 1999). If voters can replace politicians or if citizens have the possibility to reapply to different officials, individual officials have fewer incentives for corruption. Montinola and Jackman found that political competition affects the level of corruption. Corruption was found to be lower in dictatorships than in new democracies, but in countries with a longer democratic tradition, democratic practices inhibit corruption. This is in accordance with Treisman (2000), who maintained that democracies are significantly less corrupt only after 40 years.

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The literature reviewed so far has mainly focused on the developing countries. The transition countries in Europe demand extra consideration. The transition to market economies in the 1990s took place without the legal framework and informal rules that make market economies work. The initial failure of the market economy in the transition countries led to economic decline, which made life more difficult for large sections of the respective populations. In this situation, the traditional ‘shadow economy’ that developed during communism retained its importance and continued to rely on illegal transactions, corruption and bribery (Orenstein 1998; Rose 1999). Another political explanation focuses on the effect of gender. Studies indicate that the greater the representation of women in parliament, the lower the level of corruption (Dollar et al. 2001; Swamy et al. 2001). The latter study indicates that the greater the share of women in senior government positions and the work force, the lower the level of corruption. This may indicate that women have higher standards of ethical behaviour. Studies of Within-country Differences in Corruption Women are considered to be less involved in bribery and less likely to accept bribe-taking (Swamy et al. 2001). This conclusion was based on data from the World Value Survey, which included questions concerning the degree to which 12 immoral or illegal acts can be justified. In addition, data from an enterprise survey in Georgia showed that the frequency of bribery is lower in firms managed by females. Swamy and colleagues discuss the reasons why this is so. Women may be brought up to be more honest or risk averse than men and to have more self-control than their male counterparts. Women, as the weaker sex, may also feel that laws are there to protect the weak and they are therefore more willing to follow the rules. Perhaps the most encompassing study of corruption at the individual level is that by Gatti et al. (2003). They found that women, employed persons, the less wealthy, and older individuals were more averse to corruption than others. Furthermore, they found that the social environment has a strong influence on individual attitudes towards corruption. Those who lived in regions where people were, on the average, less averse to corruption, tended to be more forgiving of others. This confirms the theoretical models that the more the individual incentive to be corrupt, the more corruption is widespread (Andvig and Moene 1990). High moral standards are a part of the belief system of most religions. Therefore, we expect religious people to show higher standards of economic morality than others. The same standards are also expected to be found in economic practices, especially as a protection against committing economic offences.

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Nieuwbeerta et al. (2003) studied street level corruption by means of multilevel models. The chances that an individual will become a victim depend on their social position and how they behave. This is the basis for general criminological theories such as ‘lifestyle theory’ and ‘opportunity structure theory’. People who travel a great deal and partake in nightlife are expected to have a higher chance to meet corrupt customs officials and policemen. Furthermore, the potential victim’s attractiveness may be relevant. People with high income would be expected to become victims of corruption more often than the average person. Nieuwbeerta et al.’s main findings on individual level relationships were that the people who were at most risk of becoming victims of corruption were the young and individuals with high levels of education and income.

RESEARCH QUESTIONS Rather than making an inward-looking analysis of a narrow subject matter, the aim of this chapter is to make a more general sweep over an expansive subject material. The wide scope implies the construction of a set of research questions on several bodies of literature: on differences between countries and especially on the theme of corruption, on consumer victimization, and on committing unethical and illegal economic acts. Differences between European Countries The literature review indicates that a variety of country characteristics may be relevant for any explanation of differences in corruption between countries: the general level of development or affluence, economic equality, an equality culture, and a long democratic tradition are the most important ones. There are two problems with the application of this literature to our context: first, as Nieuwbeerta et al. (2003) found, street level corruption, which is the kind of corruption analysed in our study, may show different relationships from those described in the literature that focuses primarily on high-level corruption. Second, the phenomena of interest in this chapter are diverse, and a number of them are very distant from corruption. Another problem is that country characteristics such as those listed above often appear in combination, which makes it very difficult to estimate their separate effects. Therefore, detailed country level variables are not used in the multilevel analysis. Instead, a country classification based on welfare regimes is used to capture differences among the countries (Arts and Gelissen 2002). The classification groups the countries into the following categories: Nordic, Anglo-Saxon, Continental, Southern and Eastern European. In terms of economic development and

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affluence, the Southern and the Eastern European countries are the least privileged. In addition, the East European countries all share the recent history of communist rule. In terms of democracy, the Nordic, the Anglo-Saxon and the Continental countries have a longer history of stable democracy than the Southern countries and especially the East European countries. The Nordic countries have the lowest income inequalities measured by the gini index, whereas the Anglo-Saxon and the East European countries have the highest levels of income inequalities. To sum up so far, we may expect people in the Eastern and the Southern European countries to have experienced more corruption than people in other countries. If the experiences of corruption are rather widespread, this could also create more permissive attitudes and values. This leads to similar expectations about economic norms, although it is quite possible that there may be discrepancies between morality and practices in the economic sphere. Economic trust may partly reflect general trust in institutions and, if this is the case, the Nordic countries will be expected to score high, whereas the Eastern European countries will be expected to have low scores. However, there is also another aspect of economic development and affluence. As the number of economic transactions is positively correlated with economic development, and transactions are becoming less personal than before, the probabilities of consumers becoming victims of economic wrongdoing may increase, as would the opportunities for unethical behaviour. Based on this, the Nordic countries, along with other rich countries, are expected to have higher numbers of consumer victims than the poorer countries. A similar conclusion can be expected for the numbers of persons committing minor economic offences. Furthermore, the small probabilities of being caught for committing minor offences strengthen this expectation. Differences among Individuals The description of differences among individuals is limited here to consumer victims and offenders. As for the country differences, there are no uniform expectations about the relationships between individual characteristics and the two aspects of economic morality. In the literature on the subject, the chance of becoming a victim of crime may depend on the social position of the victims and how they behave (Nieuwbeerta et al. 2003). A number of criminological theories build on this scenario. Routine activity and lifestyle theories are especially relevant for victimization in our context (Meier and Miethe 1993). The basic idea is that differences in victimization by demographic variables may be explained by differences in the lifestyles of the victims. Routine activity theory (Cohen and Felson 1979) was an attempt to go beyond lifestyles by placing

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emphasis on suitable targets, absence of capable guardians and motivated offenders. Both theories imply that the risk of becoming a victim depends on the potential victims’ characteristics and behaviour that may increase their attractiveness to offenders. In our setting, we would expect that the most economically active persons are more likely to become victims of economic wrongdoing than less active persons. This means that the risk should be high for middle-aged men with high education and high income. In order to explain criminal behaviour, opportunity theories are often used (Cohen and Felson 1979). These theories comprise routine activity theory as well as rational choice theory. We expect that the likelihood of being an offender will decrease with age. There are two reasons for this: first, people will generally be less willing to take risks with increasing age and, second, in general young people are more deprived of economic resources than middle-aged persons. Criminal activity may be a tempting way to compensate for low levels of earnings. Furthermore, women are expected to be more law abiding than men for reasons mentioned above. As to levels of education, the expectations are mixed. On the one hand, education may entail the internalization of high ethical standards, whereas, on the other hand, high education may be a necessity for having the opportunity to commit economic crime. High moral standards in the individual are perhaps the strongest safeguard against unethical and unlawful economic behaviour. In our study, two variables tap this, religiosity and the scale of economic norms. The latter variable is of high value for persons who vigorously condemn unethical economic behaviour. Therefore, both religiosity and economic norms are expected to be negatively related to the probability of being an offender, and more so for serious offences than for minor ones.

DATA AND VARIABLES This chapter builds on the module on economic morality in the European Social Survey (ESS) that was conducted in the autumn of 2004 and which covered 24 countries, including all the Nordic ones. The module with 30 questions covers economic trust and norms and the interactions between producers and consumers. Below, the measures of economic morality used in this chapter will be developed. Economic Morality The first theme is economic trust, which is covered by a block of three questions:

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How much do you trust the following groups to deal honestly with people like you? ● Plumbers, builders, car mechanics and other repair people. ● Financial companies such as banks or insurers. ● Public officials.

The response categories were listed on a card and ranged from 1, ‘Distrust a lot’ to 5, ‘Trust a lot’. It is entirely possible that people with a high mean score on one of these questions score low on others. A statistical analysis does, however, indicate that the three questions tap a common dimension. Therefore, the economic trust scale was computed as the mean of the scores for the three questions to be used in our analysis.1 A high score on the scale ranging from 1 to 5 indicates high economic trust. The overall scale mean of 3.17 is close to the middle response category of ‘Neither trust nor distrust’. A block of four questions taps normative aspects of economic morality. The response categories on the show-card range from 1, ‘Not wrong at all’, to 4, ‘Seriously wrong’. How wrong, if at all, do you consider the following ways of behaving to be? Use this card for your answers, How wrong is . . . ● someone paying cash with no receipt so as to avoid paying VAT or other taxes? ● someone selling something second-hand and concealing some of its faults? ● someone making an exaggerated or false insurance claim? ● a public official asking someone for a favour or bribe in return for their services?

A statistical analysis shows that the four questions tap the same dimension and may be used to construct an economic norms scale as the mean of the scores on the four questions.2 The scale ranges from 1 to 4 and high values indicate that the practices mentioned in the questions are all seriously wrong. The overall mean score of close to 3.5 shows these practices are seen as quite unacceptable by people at large in Europe. The next theme is victimization. Our first measure is based on a block of questions similar to those used to tap economic trust: How often, if ever, have each of these things happened to you in the last five years? Use this card for your answers. ● A plumber, builder, car mechanic or other repair person overcharged you or did unnecessary work. ● You were sold food that was packed to conceal the worst bit. ● A bank or insurance company failed to offer you the best deal you were entitled to. ● You were sold something second-hand that quickly proved to be faulty. ● A public official asked you for a favour or a bribe in return for a service.

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The response categories on the show-card ranging from 1, ‘Never’ to 5, ‘5 times or more’, were re-scored so that 0 indicated ‘Never’, 2 indicated ‘Twice’ and 6 indicated ‘5 times or more’. A statistical analysis revealed that the question about having been asked for a bribe taps a different dimension, and therefore should be analysed separately. The remaining items were summed to form a scale of consumer victimization.3 The overall mean of 2.37 shows that in the four fields covered, the consumers had experienced wrongdoing in more than two instances over the last five years. In total, about two out of three consumers had been victims of such irregularities. The second indicator on victimization is whether the interviewees have been asked for a favour or bribe from a public official over the last five years. Only about 5.5 per cent of the respondents had experienced that. The final measure of economic morality in this study is admitting to having been an offender during the last five years. In the ESS 2004 this is captured by a block of seven questions. A factor analysis indicates that the questions load on two separate dimensions: the first factor is formed by the most serious offences in the three last questions reproduced below. The first three questions, which focus on less serious unethical actions, form the second dimension. The response categories on the card range from 1, ‘Never’ to 5, ‘5 times or more’. How often, if ever, have you done each of these things in the last five years? Use this card for your answers. How often, if ever, have you . . . ● kept the change from a shop assistant or waiter knowing they had given you too much? ● paid cash with no receipt so as to avoid paying VAT or other taxes? ● sold something second-hand and concealed some or all of its faults? ● made an exaggerated or false insurance claim? ● offered a favour or bribe to a public official in return for their services? ● over-claimed or falsely claimed government benefits such as social security or other benefits?

Based on these factors we constructed two indicators. The first takes the value of 1 if the respondent has committed any minor offence during the last five years, and the second one takes the value of 1 for serious offences. Both indicators take the value of 0 for those who have not committed any offence. Defined in this way, a total of 19 per cent of people in Europe have committed minor offences and about 5 per cent have committed serious offences. Measuring wrongdoing as well as victimization in a survey is always problematic. The problem is smaller for victimization, where recall problems are the most severe. It is possible that the respondents tend to under-

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report being a victim because they are embarrassed, but this is probably a minor problem. On the other hand, admitting one’s own unethical and even criminal behaviour to a stranger may be hard, and not compatible with the self-image of the respondent. Therefore, a biased response in the direction of socially desirable behaviour must be expected. This phenomenon will lead to an underestimation of unethical behaviour. If this tendency is independent of country or even individual characteristics, the description of differences among countries and groups may, however, still be unbiased. At the country level, we may suspect that the bias will be strongest in countries with low interpersonal trust, especially the East European countries. Individual Level Explanatory Variables Age in years needs no additional explanation. Age squared is included to capture the possibility of a non-linear relationship between age and economic morality. Gender takes the value of 1 for males and 0 for females. Education is measured by the years of full-time education completed. An indicator of whether the respondent currently has a job or not is also included. Social class is tapped by an indicator distinguishing between the service class and others. The indicator takes the value of 1 for persons currently in EGP social classes I and II (Erikson and Goldthorpe 1992). An indicator of economic hardship was also included that takes the value of 1 for respondents who have difficulties in coping on their present income, and 0 for other responses. Finally, an indicator of religiosity is included. It is based on a single question that consists of the respondents’ selfassessment of how religious they are on a scale from 0 to 10.

RESULTS Initially, the gross country differences in economic morality are described by the measures developed in the methods section. Then multilevel analyses focus on consumer victimization and perpetrators of minor and serious unethical or illegal economic offences. Gross Country Differences in Economic Morality In Table 11.1, the 24 countries are ranked by their mean scores on six measures of economic morality. The Nordic countries are printed in bold so that they can be easily identified. The first measure is the economic trust scale, which is based on three indicators of whether one may trust manual hired help, financial institutions and public officials. High scores on this

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Table 11.1

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Economic morality: country means (n41982)a

A. Economic trust Norway Finland Denmark Iceland Switzerland Austria Slovenia Luxembourg Belgium Estonia Netherlands Sweden Hungary Portugal France Ireland Poland Slovakia Germany Spain United Kingdom Czech Republic Greece Ukraine

Mean 3.48 3.46 3.42 3.41 3.38 3.36 3.32 3.29 3.24 3.23 3.19 3.19 3.19 3.16 3.13 3.10 3.10 3.07 3.06 3.04 2.94 2.94 2.92 2.74

B. Economic norms Iceland Greece Denmark Norway Sweden Portugal Finland Ireland Czech Republic Poland Hungary United Kingdom Spain Estonia Netherlands Switzerland Belgium Luxembourg Slovenia Ukraine Slovakia Germany Austria France

Mean 3.47 3.46 3.46 3.43 3.43 3.35 3.34 3.34 3.33 3.30 3.27 3.26 3.26 3.26 3.25 3.23 3.21 3.18 3.17 3.15 3.12 3.10 3.04 2.90

C. Victim last 5 years (#) Iceland Hungary Slovakia Norway Denmark Germany Sweden Poland Austria Luxembourg Czech Republic Slovenia Estonia Ukraine United Kingdom Netherlands

Mean 4.05 3.97 3.93 3.82 3.32 3.24 3.24 3.17 3.03 3.00 2.84 2.81 2.76 2.67 2.64 2.61

D. Asked for a bribe Ukraine Slovakia Czech Republic Greece Poland Estonia Austria Hungary Portugal Luxembourg Slovenia Spain Denmark Germany Norway Belgium

% 32.5 14.8 12.7 12.5 12.1 10.0 5.6 5.5 3.9 3.7 3.5 2.7 2.2 2.1 1.9 1.7

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Table 11.1

217

(continued)

Belgium Spain France Ireland Switzerland Finland Portugal Greece

2.38 2.22 2.07 2.05 2.00 1.96 1.30 1.26

Sweden Ireland France Iceland Switzerland Netherlands United Kingdom Finland

1.7 1.6 1.5 1.4 1.4 1.3 1.2 0.9

E. Admitted minor economic offences Luxembourg Finland Netherlands Belgium United Kingdom Sweden France Germany Slovenia Austria Czech Republic Iceland Denmark Norway Slovakia Ireland Spain Ukraine Switzerland Poland Estonia Hungary Greece Portugal

%

F. Admitted serious economic offences Ukraine Czech Republic Slovakia Austria Iceland Denmark Poland Germany Spain Luxembourg France Finland Sweden United Kingdom Norway Hungary Portugal Greece Slovenia Switzerland Estonia Belgium Netherlands Ireland

%

29.4 25.3 25.1 24.8 24.0 23.9 23.0 21.5 21.1 20.8 20.4 20.4 20.3 20.2 18.0 16.9 16.5 15.4 15.3 14.5 12.4 12.1 6.6 6.1

16.1 10.6 10.1 9.0 7.3 5.9 5.6 5.3 5.0 4.7 4.4 4.4 4.0 3.7 3.3 3.2 3.1 3.1 2.9 2.9 2.8 2.8 2.1 1.5

Notes: a N varies somewhat because of the number of missing answers on each question. The number reported is the lowest. Economic trust: scale based on three questions. Economic norms: scale based on four questions. Victims last 5 years (#): number of times the victim of economic wrongdoing in four different fields in the last five years. Asked for a bribe: have paid or been asked for a bribe the last five years. Admitted minor economic offences: scale based on three questions. Admitted serious economic offences: scale based on three questions. See Methods section for detailed documentation of these measures.

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scale indicate high trust. Norway tops the list followed by Finland, Denmark and Iceland, with Sweden somewhat in the middle of the list. At the very opposite end of the list, we find Ukraine followed by Greece, the Czech Republic and the United Kingdom. The economic norms scale builds on how wrong the respondents considered four unethical economic behaviours to be. The maximum possible score is obtained by answering ‘seriously wrong’ to all four questions. The ranking of the countries on this dimension is different from economic trust. The Nordic countries are still at the top, this time with Sweden included, but Greece is now number two after Iceland. At the bottom we find France and Austria. The next panel is about the consumers as victims (C–D). The two measures are the victimization scale, which counts the number of times each person has been a victim of economic wrongdoing as a consumer in four different fields, and the single question of whether one has paid or been asked for a bribe or not within the last five years. The rankings are not consistent. Bribery is mainly an East and South European phenomenon, whereas the pattern is more complex for the victimization scale. In the former communist countries of Eastern Europe with Greece in between, 10 per cent or more have been exposed to bribery. In Ukraine almost a third of the population, 15 years of age or above, have paid or been asked for a bribe within the last five years. Bribery is very low in many countries and almost non-existent in Finland and in the UK. Iceland tops the list of consumer victimization with a score of about 4. This score indicates that the average Icelander has been exposed to one or more of the four kinds of wrongdoing about four times within the last five years. The countries directly below Iceland are Hungary and Slovakia, and the other Nordic countries, with the exception of Finland, also have high scores. At the lower end of the scale we find Greece and Portugal. A simple interpretation of these differences is that they stem from two different dimensions. Consumer victimization is strongly influenced by economic prosperity, which brings with it a high number of economic transactions, and thus a higher total risk. The other dimension is the influence of the experience of shadow economies of East European countries. However, there are several exceptions to this pattern as Ireland, Switzerland and Finland show low levels of consumer victimization. The last panel (E–F) in Table 11.1 describes the percentage of people in each country who admitted to unethical economic behaviour. The first column reports minor economic offences, while the second column reports more serious and clearly illegal acts. Examples of minor offences include having paid cash with no receipt in order to avoid paying VAT or other taxes. An example of the more serious offences in the second measure is having made an exaggerated or false insurance claim.

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The list of minor offences is mainly topped by rich countries with Luxembourg and Finland at the very top where 25 to 30 per cent admit to having committed one or more minor offence during the last five years. This type of unethical behaviour is rare in Greece and Portugal where less than 7 per cent admit such behaviours. The Nordic countries are scattered from the middle of the ranking and upwards, whereas most of the East European countries are found in the lower part of the ranking. The countries rank quite differently on the more serious economic offences. Ukraine tops the list with 16 per cent followed by the Czech Republic and Slovakia. At the bottom, we find a rather long list of countries where less than 4 per cent report having committed such offences. The best of these are Ireland and The Netherlands, whereas the Nordic countries are scattered in the middle of the list. Let us end this section with a comparison of the countries on the measures of economic morality with the Corruption Perception Index (CPI).4 High scores on the CPI indicate low levels of perceived corruption. Countries that score high on the CPI, such as the Nordic countries, have low levels of bribery and serious economic offences, but they also distinguish themselves in a negative manner by having high levels of minor economic offences. Countries that score low on the CPI have high levels of bribery and serious economic offences, but rather low levels of minor economic offences.

MULTILEVEL ANALYSES OF VICTIMS AND OFFENDERS This section focuses on the victims of unethical economic conduct and those who admit to being offenders. The time frame for both is within the last five years. The explanatory variables comprise age, age squared, gender, years of education, an indicator of whether the respondent has a job at present, an indicator of whether the respondent belongs to the service class, and an indicator of insufficient income. The two remaining explanatory variables at the individual level are religiosity, measured by the respondent’s self-evaluation, and the measure of economic norms, which is used in the analysis of economic offenders. At the country level, only the country classification is used as the aim of the analysis is to describe gross country differences rather than give a more detailed analysis that would dissect the between-country differences.5 Consumer Victimization In the multilevel analyses, the individual respondents constitute level 1 and countries level 2. Only the first dependent variable is treated as continuous

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and analysed by ordinary multilevel regression analysis. The three remaining outcomes are 0–1 variables that are analysed by means of multilevel (binary) logistic regression models. All the models to be presented are variance component models, that is, only the regression constants (intercepts) are assumed to show random variation across the countries. This variation is captured by the variance components at the bottom of Tables 11.2 and 11.3. This implies that the effects of the individual level variables are assumed to be uniform in all countries. We distinguish between two levels of seriousness of victimization: the consumer as the victim of common unethical practices, and having paid or been asked for a bribe. The former is measured in the number of instances and varies from 0 to 24. Around a third of those interviewed have not been exposed to such practices. Bribery is less common and only about 5.5 per cent of the total sample has been exposed to bribery within the last five years. The left panel of Table 11.2 shows the results from a multilevel regression analysis of the victimization scale. Let us start at the bottom of the table by commenting the random variance components. The intra-class correlation (ICC) shows that country level variance (estimated at .552) only amounts to about 5 per cent of the total variance in consumer victimization. About two thirds of the variation between the countries is explained by the variables in the model presented in Table 11.2. Beginning at the top of the table, age shows a curvilinear relationship with the propensity of being a victim. The frequency increases from 15 years of age to about the age of 40, but thereafter steadily decreases. Additional analysis shows that this curvilinear relationship does not show statistically significant variation across countries. Men are slightly more exposed than women. Furthermore, education and being employed, especially in the service class, are all positively related to victimization. However, in this group of variables, years of education has the strongest effect. Its maximum effect, which is a difference of about 10–15 years of education, is more than one point on the scale. The main interpretation of these results is that high involvement in economic transactions increases the risk of becoming a victim. Insufficient income does, however, also increase the probability of victimization. Religiosity shows a weak negative relationship to victimization. The maximum effect is a decrease in victimization of about 0.2 points. Religious people are perhaps more careful or less economically active than others and therefore somewhat less exposed to economic wrongdoing. Finally, the country classification taps the net differences among groups of countries. The Nordic countries constitute the reference category with the coefficient set to 0 for comparison. The regression coefficients show the

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Table 11.2 Number of times exposed to economic wrongdoing in last five years: a multilevel analysis (n40832 in 25 countries) Variables

Regression constant Age in years Age in years squared Gender, 1male, 0female Years of full-time education Not job last 7 days Service class Insufficient income Religiosity Country classification Nordic countries (reference category) Anglo-Saxon countries Continental countries Southern Europe Eastern Europe Country level variance in: null model (Su_null)a final model (Su_final) Intra-class correlation in null modelb

Consumer victims, regression analysis

Asked for a bribe, logistic regression analysis

B

B

OR

.758* .077*** .001*** .150*** .096*** .126*** .319*** .475*** .021***

5.331*** .034*** .000*** .394*** .036*** .119* .058 .339*** .002

.004 1.035 1.000 1.483 1.036 .888 1.060 1.404 .998

.000 .865* .518 1.379*** .153

.000 .066 .392 1.272** 2.031***

1.000 .936 1.480 3.568 7.622

.552 .208 .051

1.700 .347 .341

Notes: Statistical significance: * p .05 ** p .01, *** p  .001. OR Exp(b): odds ratio. N38129 for the analysis of consumer victims and N 37722 for the analysis of bribery. a Null model: a model without any explanatory variables. b The intra-class correlation shows the proportion of the total variance in the outcome variables that is a result of differences among the countries.

remaining differences between the country means after the effects of individual level variables are removed. As all regression coefficients are negative, the Nordic countries score highest on consumer victimization. The differences are statistically significant for the Anglo-Saxon countries (b  0.87, p  .05) and for Southern Europe (b  1.38, p  .001). Figure 11.1 shows the relationship between age and victimization separately for the Nordic, Southern and Eastern European countries. The distinct curvilinear relationship between age and victimization is clearly evident. The curves for the Eastern and the Nordic countries are quite

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Nordic social attitudes in a European perspective 4.0

Number of times victim

3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 15 20 25 30 35 40 45 50 55 60 65 70 75 80 Age Nordic Eastern Southern

Figure 11.1 Number of times a victim in last five years in the Nordic, Eastern and Southern European countries similar, whereas people in the Southern European countries are clearly less exposed to becoming consumer victims. Having paid or been asked for a bribe within the last five years is the second victimization variable. The results from the multilevel logistic regression analysis of bribery are presented in the right panel of Table 11.2 The regression coefficients are in the log odds scale and difficult to grasp. The odds ratios in the last column are easier to interpret. From the signs and the statistical significance of the coefficients, we observe that the age profile is similar to the one described in the victimization scale. The positive coefficient for gender shows that men are more exposed to bribery than women. The odds ratio indicates that men have about 50 per cent higher odds of having been a victim of bribery than women. Education has a strong and statistically significant effect. Ten years of additional education seems to increase the odds of becoming a victim of bribery by about 150 per cent. Not having a job lowers the odds, but being in the service class has no effect at all. Those who report having insufficient income are significantly more exposed to bribery than others. The final individual level variable, religiosity, has no effect at all. In total, the pattern

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of relationships between the individual level explanatory variables and being exposed to bribery is quite similar to the one observed for the victimization scale. The net country differences are large. This is evident in the variance components at the bottom of the table, as well as in the differences that remain between countries in the final model as captured by the regression coefficients for the country classification. The between-country variation amounts to around a third of the total variance, the largest amount in any of the multilevel analyses. The Nordic and the Anglo-Saxon countries have the lowest level of bribery, followed closely by the Continental countries. Our analysis shows that bribery is definitely most common in Eastern and Southern Europe. The odds of having been exposed to bribery are 3.5 times higher in Southern Europe than in the Nordic countries. In Eastern Europe the odds are 7.6 times higher. The difference between the Nordic, the Eastern, and the Southern European countries is shown in Figure 11.2. The age profile is actually similar in the two groups of countries. However, the profile for the Nordic countries appears almost constant because of the scale effect imposed especially by the Eastern countries. The curves for the Continental and the Anglo-Saxon countries are quite similar to that of the Nordic countries. The probability of being asked for a bribe increases up to about 35 years of age, only to decline rapidly thereafter, especially so for the East European countries. The Offenders We have distinguished between minor, and serious and clearly criminal economic offences. In total, about 19 per cent of respondents did admit one or more minor economic offence within the previous five years. The admittance of serious economic offences is, however, much rarer. In total, about 5 per cent admitted having committed such offences. Table 11.3 reports the results of the multilevel logistic regression analyses of these two measures. The intra-class correlation shows that only about 4 per cent of the total variance in minor offences is a result of differences between the countries. For the serious offences indicator, the country level variance is much larger and amounts to more than 12 per cent of the total variance. For both types of offences the relationship to age shows a similar pattern. The probability of committing offences is high for the youngest age groups, but diminishes thereafter almost linearly as shown in Figure 11.3 for minor offences. The effects of the remaining individual level explanatory variables are relatively small with one exception, economic norms. This variable was introduced to test whether moral norms, as reported by the respondents, do

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Nordic social attitudes in a European perspective 14.0

Asked for a bribe (%)

12.0 10.0 8.0 6.0 4.0 2.0 0.0 15

20

25

30

35

40

45

50

55

60

65

70

75

80

Age Nordic Eastern Southern

Figure 11.2 Asked for a bribe during the last five years by age in the Nordic, Eastern and Southern European countries

prevent offences. The answer is clearly yes. The odds of having committed a minor offence in the last five years are almost 75 per cent lower for the morally strict persons than the morally permissive ones. In terms of serious economic offences, the protection is even higher. This result can be observed by the more than 90 per cent lower odds for those adhering to a strict moral code. The net country differences between the Nordic countries and the other country categories may be seen from the regression coefficients in Table 11.3. All the coefficients are negative, which indicates that the Nordic countries have the highest level of minor offences. However, only Southern and Eastern Europe have levels of minor offences that are significantly lower than the Nordic countries. In Figure 11.3, the age profiles are displayed separately for the Nordic countries, Southern and Eastern Europe. The probability of committing minor economic offences seems to decline almost linearly with increasing age. In the case of the serious offences, most between-country differences seem to be captured by the individual level variables. Although most

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Table 11.3 A multilevel logistic regression analysis of offences last five years Variables

Regression constant Age in years Age in years squared Gender, 1 male, 0 female Years of full-time education Not job last 7 days Service class Insufficient income Religiosity Economic norms Country classification Nordic countries (reference category) Anglo-Saxon countries Continental countries Southern Europe Eastern Europe Variation between countries in null model (Su_null)a final model (Su_final) Intra-class correlation in null model b

Minor offences

Serious offences

B

OR

B

OR

.466*** .009* .000** .105*** .037*** .066* .156*** .022 .030*** .429***

1.593 .991 1.000 1.111 1.037 .936 1.169 .978 .971 .651

.918** .021* .000*** .389*** .029*** .089 .081 .212** .001 .807***

.399 1.021 1.000 1.475 1.030 .915 1.085 1.236 1.001 .446

.000 .127 .062 .939*** .435**

1.000 .881 .940 .391 .647

.000 .743 .360 .324 .098

1.000 .476 .698 .723 1.103

.136 .062 .040

.472 .242 .125

Notes: Statistical significance: * p .05, ** p  .01, *** p  .001. OR Exp(b): odds ratio. N  38918 for minor and N 39833 for serious offences. a Null model: a model without any explanatory variables. b The intra-class correlation shows the proportion of the total variance in the outcome variables that is a result of differences among the countries.

country coefficients are negative, which would indicate that the Nordic countries have the highest level, none of these differences are statistically significant. The relationships between the individual level explanatory variables and committing serious offences are similar to those found for minor offences, however a number of the variables provide clear evidence of stronger relationships. The first one is gender. The odds of having committed a serious offence in the last five years is about 50 per cent higher for men than for women. Whereas insufficient income was unrelated to

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Nordic social attitudes in a European perspective 35.0

Minor economic offence (%)

30.0 25.0 20.0 15.0 10.0 5.0 0.0 15

20

25

30

35

40

45

50

55

60

65

70

75

80

Age Nordic Eastern Southern

Figure 11.3 Committed at least one minor economic offence in the last five years by age in the Nordic, Eastern and Southern European countries minor offences, it is significantly related to serious offences. Those who have problems coping on their present income have more than 20 per cent higher odds of having reported a serious offence, compared to those who cope well on their present income. Economic norms are a much more powerful predictor of serious offences than minor ones. The maximum effect of economic norms is to lower the odds of reporting serious offences by more than 90 per cent.

DISCUSSION This chapter has covered several aspects of economic morality from values to behaviour. The analysis started with establishing gross differences between the countries on six dimensions of economic morality. Then multilevel analyses were performed that included explanatory variables at the individual level as well as a country classification. These analyses did not,

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however, reveal any consistent patterns of differences between the countries for all the dimensions of economic morality. On economic trust and economic norms, the Nordic countries were found at the top of the lists, together with Switzerland and Austria on economic trust, and joined by Greece on economic morality. Most East European countries scored low on both dimensions, although there are exceptions, such as Slovenia’s high score on economic trust. Ukraine is at the very bottom in economic trust and number five from the bottom in economic norms. For these two dimensions, only the gross differences among the countries were analysed. The picture is quite mixed for customer victimization. The chances of having been a consumer victim are quite high in the Nordic, as well as in the Eastern European countries, and low in Southern Europe. Among the Nordic countries, Finland is the exception with low chances of customer victimization. As regards being exposed to bribery, the picture is quite different. The probability is very low in all of the rich European countries. Bribery is mainly found in Southern and Eastern Europe with Ukraine at the very top. About one in three Ukrainians aged 15 years and over have been exposed to bribery within the last five years. Bribery is also rather widespread in Slovakia, the Czech Republic, Greece, Poland and Estonia. The multilevel analysis shows the net differences between the categories of the country classification. The Nordic and the East European countries have the highest levels of consumer victimization. The lowest level is found in Southern Europe. The multilevel analysis of bribery does reveal large net differences among the country categories. The lowest chances of being exposed to bribery are found in the three categories of rich countries. In Southern Europe the odds of being exposed to bribery are about 3.5 times higher, and in Eastern Europe the odds are more than 7 times higher than in the Nordic countries. The picture is also inconsistent for economic offences. Minor economic offences are committed more often in the rich than in the poor countries of Europe. The countries in Southern and Eastern Europe are found at the bottom of the country ranking. The Nordic countries are scattered in the upper half of the ranking with the gross percentage who admitted having committed one or more such acts over the previous five years ranging from 20 per cent in Norway to 25 per cent in Finland. Luxembourg topped the list with 29 per cent. The admittance of serious and clearly illegal economic offences shows a different pattern. At the top of the list we find Ukraine with 16 per cent, the Czech Republic with 11 per cent and Slovakia with 10 per cent. However, Austria, Iceland and Denmark were not far behind with 9–6 per cent. At the bottom of the list we find three rich West European countries, Ireland, the Netherlands and Belgium, but

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several Eastern and Southern countries have also very low figures. In these countries around 3 per cent or less admitted to having committed one or more serious economic offence within the previous five years. The picture changes as the focus shifts to serious economic offences such as admitting bribery or making false insurance claims. These gross differences between the countries largely disappear after controls for individual level variables in the multilevel analyses. Among the individual characteristics, the economic norms did contribute most to explain the country differences. The multilevel analysis of consumer victims and offenders also included a range of individual characteristics as explanatory variables. Age showed a curvilinear relationship to victimization. The chances of becoming a consumer victim increased to a peak at around 40 years of age, but decreased thereafter. The pattern is roughly the same for the likelihood of being exposed to bribery and being exposed to less serious victimization. For offenders the relationship is negative and almost linear. It is young people, between 15 and 30 years of age who most often admit to having committed minor economic offences within the last five years. The higher the age, the less likely a person is to admit such behaviour. The age pattern has the same shape for serious economic offences, but the curves are flatter because of the overall lower frequencies of serious offences. The observed gender differences are in the expected direction. Men are more often consumer victims than women, and the same pattern is found for the commitment of economic offences. The gender differences are largest for the most serious indicators such as bribery and committing serious economic offences. Contrary to expectations, education shows a positive relationship to being a consumer victim and to being an offender. High education seems to increase both the chance of becoming a victim and an offender. Being unemployed reduces the chances of becoming a victim of economic wrongdoing slightly, and this negative relationship is even weaker for the chances of becoming an offender. Having a service class job increases the chances of becoming a consumer victim and of committing minor offences, but it does not increase the chances of being exposed to serious forms of economic wrongdoing. Having insufficient income increases the chances of consumer victimization and seems to increase the chances of having committed serious economic offences. As expected, religiosity seems to constitute moral protection, but the relationship is weak. In the analysis of economic offences, economic norms were introduced as an explanatory variable. This variable has a very strong effect. The maximum effect, which is the difference between those who vigorously condemn four types of unethical acts and those who endorse them, is to reduce the odds of minor offences by 75 per cent and to reduce the odds of serious offences by more than 90 per cent.

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Therefore, the main individual level factors in explaining economic morality seem to be age and economic norms. The age profiles are distinct and different for the probabilities of becoming a victim and becoming an offender. People with high levels of economic norms are unlikely to become perpetrators of street level economic crimes. The country differences in economic morality may be seen as the result of a complex interplay of country characteristics and individual level variables. The most obvious one is economic development and prosperity, which mainly distinguishes the North and West European countries from the countries in Eastern Europe (the Southern European countries are in between). The more advanced the economic development, the more economic transactions, and therefore the higher the risk of becoming a consumer victim. Moreover a high number of transactions increases the temptation to exploit the possibilities of profiting through economic fraud. The second notable factor is the experience of a shadow economy. This phenomenon is part of the communist heritage in Eastern Europe, but was also widespread in Southern Europe. This may explain the high level of corruption and bribery in those two groups of countries. A third factor is economic norms, which is by far the most important individual characteristic that may explain country differences in committing minor and serious economic offences. Two broad research questions were presented at the start of this chapter: Do the recent examples of corruption suggest the assumption that the Nordic countries compare favourably with other countries in relation to high moral standards and ethical economic behaviour is false? Is the idea of a common standard of economic morality in the Nordic countries a myth? On economic trust and morality, the Nordic countries really distinguish themselves in a positive way from other European countries. On bribery, the Nordic countries and the other rich countries in Western Europe are clearly distinct from the Southern and Eastern European countries. However, the picture changes if we use consumer victimization and committing minor offences as indicators of economic morality. In this respect, the Nordic countries illustrate low morality, as do most other prosperous countries. In conclusion, the Nordic countries, as a group, distinguish themselves in terms of moral standards, and in low levels of corruption, but not in street level economic practices. The Nordic countries are more similar in terms of economic trust and norms than in terms of economic practices. Finland scores very low on consumer victimization, but high on the admittance of minor economic offences. Norway scores lowest among the Nordic countries in minor as well as serious economic offences.

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NOTES 1. The scale is one dimensional and has acceptable psychometric properties: reliability as measured by Cronbach’s alpha is 0.67. The mean inter-item correlation is 0.40. 2. This scale has acceptable psychometric properties. Cronbach’s alpha is 0.69, and the mean of the inter-item correlations is 0.38. 3. Cronbach’s alpha for the scale is 0.59, and the mean correlation among items is 0.37. 4. The CPI is published yearly by Transparency International, see http://www.transparency.org/policy_research/surveys_indices/cpi. 5. A more detailed presentation of multilevel models is found in the Appendix.

REFERENCES Andvig, Jens Christopher and K.O. Moene (1990), ‘How corruption may corrupt’, Journal of Economic Behavior and Organization, 13 (1), 63–76. Arts, Wil and J. Gelissen (2002), ‘Three worlds of welfare capitalism or more? A state-of-the-art report’, Journal of European Social Policy, 12 (2), 137–58. Cohen, Lawrence E. and M. Felson (1979), ‘Social-change and crime rate trends – routine activity approach’, American Sociological Review, 44 (4), 588–608. Dollar, Davis, R. Fisman and R. Gatti (2001), ‘Are women really the “fairer” sex? Corruption and women in government’, Journal of Economic Behavior and Organization, 46 (4), 423–9. Erikson, Robert and John H. Goldthorpe (1992), The Constant Flux. A Study of Class Mobility in Industrial Societies, Oxford: Clarendon Press. Gatti, Roberta, S. Paternostro and J. Rigolini (2003), ‘Individual attitudes toward corruption: Do social effects matter?’, World Bank Policy Research Working Paper, WPS 3122. Meier, Robert F. and T.D. Miethe (1993), ‘Understanding theories of criminal victimization’, Crime and Justice, 17, 459–99. Montinola, Gabriella R. and R.W. Jackman (2002), ‘Sources of corruption: A cross-country study’, British Journal of Political Science, 32, 147–70. Nieuwbeerta, Paul, G. De Geest and J. Siegers (2003), ‘Street-level corruption in industrialized and developing countries’, European Societies, 5 (2), 139–65. Orenstein, Mitchell A. (1998), ‘Lawlessness from above and below: Economic radicalism and political institutions’, SAIS Review, 18 (1) (Winter–Spring). Rose, Richard (1999), ‘Getting things done in anti-modern society: Social capital networks in Russia’, Social Capital Initiative Working Paper, 6. Washington, DC, World Bank, Social Development Department. Rose-Ackerman, Susan (1999), Corruption and Government: Causes, Consequences and Reform, Cambridge: Cambridge University Press. Svensson, Jakob (2005), ‘Eight questions about corruption’, Journal of Economic Perspectives, 19 (3), 19–42. Swamy, Anand, Stephen Knack, Young Lee and Omar Azfar (2001), ‘Gender and corruption’, Journal of Development Economics, 64 (1), 25–55. Treisman, Daniel (2000), ‘The causes of corruption: A cross-national study’, Journal of Public Economics, 76 (3), 399–457. You, Jong-sung and S. Khagram (2005), ‘A comparative study of inequality and corruption’, American Sociological Review, 70 (1), 136–57.

12.

The meaning and implications of religiosity Heikki Ervasti

INTRODUCTION Religious life is one of the many issues that distinguish the Nordic countries from the rest of the European countries. All Nordic countries share a strong Lutheran tradition and uniquely close connections between the state and the church. The Nordic countries were already completely Lutheranized in the sixteenth century, and unlike in other parts of Europe, the Reformation eliminated Catholicism among the Nordic native populations (Madeley 2001). This homogeneity of religious life is still visible. In contrast to the purely Catholic countries and the ‘mixed’ Continental Protestant countries with notable proportions of Catholics, Sweden, Finland, Norway, Denmark and Iceland constitute Europe’s only mono-confessional Protestant region. The levels of membership in the dominant Protestant churches are high in all Nordic countries. At least nominally a clear majority of the population, well above 80 per cent in Finland, Norway, Denmark and Iceland, and only slightly below 80 per cent in Sweden, belong to the Lutheran/Protestant church. Other denominations constitute only small minorities. Despite the high nominal church membership rates, the Nordic countries have a reputation for being the most secularized countries in the world (e.g. Gustafsson 1994). Undoubtedly, the overall influence and authority of the church in society has diminished during the post-war period. Similarly, religious attendance has declined. To a certain degree religious values have lost status or have been replaced by new sets of values, which only retain remote links with traditional religious beliefs and the church. Religious institutions, activities as well as modes of thinking and behaviour have lost their previous significance. Religion no longer dominates society and has, in Dobbelaere’s (1993, p. 24) words become ‘a subsystem alongside other subsystems’ that has to compete with other subsystems to attract people. The global tendency of secularization is usually seen as a consequence of general modernization and industrialization, which, in turn, gave rise to demographic development, rising levels of education among the population, 231

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improved political rights, and consequently greater affluence, social and economic equality and existential security (Norris and Inglehart 2004). As the Nordic countries are highly developed and affluent, and have extensive welfare states, it is no surprise that these countries are often characterized as the most secularized ones. However, the case for secularization is not closed. It is quite obvious that religion has not disappeared from the world, not even from the Nordic countries, and nor is it likely to do so in the foreseeable future. Basically, critics of the secularization theory have pointed to at least two different anomalies in the secularization thesis. First, religiosity has become a more private issue than it was in the past. Even if people are not active churchgoers, they may still hold religious beliefs and values. People may be more religious than they look. Religion may have become less influential in the public sphere, but certainly remains an important factor in the private domains of many people’s lives. Moreover, as religiosity has turned to the private sphere, people ‘pick and choose’ what to believe, and select their preferred religious beliefs and practices (Lambert 2004). In addition, people do indeed have an array of alternatives to choose from as the number of new religious movements and especially New Age movements has increased. Second, critics have often emphasized that the historical interpretation maintained by the adherents of the secularization thesis is flawed. According to this view, religion was not as central a part of the culture in the past as is often described by the secularization theorists. For example, Stark (1999) concludes that claims about a major decline in religious participation in Europe are based partly on strongly exaggerated perceptions of past religiosity. Indeed, the critics have already pleaded for no less than the burial of the secularization thesis (Stark and Finke 2000). Even in the Nordic countries some recent studies suggest that the influence of the church is still more pervasive than might be obvious from the secularization perspective, as culture and religion have been so closely intertwined in the creation of national identity in these countries (Bäckström et al. 2004). The aim of this chapter is to analyse the current situation in religious life in the Nordic countries and the rest of Europe. The chapter is divided into four sections. The next section focuses on differences in religiosity between the European nations. We find out which European societies are more secularized than others, and whether or not it is still the case that Nordic countries are more secular than other European nations. Moreover, attention is paid to the social correlates of religiosity in European countries. We analyse to what extent religiosity correlates with certain socio-economic and demographic background variables and whether there is variation in these correlations in different parts of Europe. The following section turns

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to the consequences of religiosity. The main issue is to what extent religiosity still determines people’s political engagement and attitudes as well as social and moral values. In addition, we detect whether this determination varies across the European continent. Finally, a discussion concludes.

RELIGIOSITY AND ITS SOCIAL DETERMINANTS Throughout this investigation, religiosity is defined in terms of three variables used in the European Social Survey (ESS). It must be noted that the focus of this analysis is on traditional religiosity, therefore the variables used in the analysis do not cover the possibly varying dimensions of religiosity or any forms of New Age religiosity. The first item measures individuals’ frequency of religious service attendance. The respondents were asked how often they attend religious services apart from special occasions like feast days, funerals, christenings and so on. The proportions of those attending service at least once a week in each country are presented in Table 12.1. The second indicator measures how often the respondents pray. Table 12.1 shows the proportions of those who reported that they prayed every day. As for the third indicator of religiosity, we used a scale that ranged from 0 to 10 in order to measure the respondents’ answers concerning how religious they considered themselves to be. The frequencies of those scoring eight or more are shown in Table 12.1. The last column of Table 12.1 shows the mean of the three items on a scale from 0 to 10. Note that in Table 12.1 the countries are organized in ascending order from the most religious to the most secular as measured by the mean religiosity scale. Judging by the figures in Table 12.1 we find, as expected, that on average the Nordic countries are among the most secular countries in Europe. Especially church attendance is very low in the Nordic countries. However, the levels of religiosity are also very low in many of the former socialist countries and especially so in Estonia and the Czech Republic. The Catholic countries of Poland, Ireland, Italy and Portugal together with Orthodox Greece are the most devout nations among the ESS countries. In these countries religious involvement is still considerably high and people are more inclined to pray and identify themselves as believers than the people of most other European nations. However, the predominantly Catholic countries in the central parts of Europe, namely France, Belgium and Luxembourg score very low on religiosity. These findings are consistent with earlier research (for example, Ester et al. 1994; Halman et al. 1999). The figures in Table 12.1 indicate certain differences in religiosity between the Nordic countries. Iceland and Finland are more religious than the other Nordic countries. Finland and Iceland do not differ

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Table 12.1 Religiosity in European countries: percentages of people attending religious service at least weekly, praying daily, those who characterize themselves as religious (at least 8 on a scale from 0 to 10) and mean religiosity (on a scale from 0 to 10)

Poland Greece Ireland Italya Portugal Slovakia Ukraine Switzerland Austria Iceland Finland Slovenia Spain Netherlands United Kingdom Germany Luxembourg Hungary Belgium Denmark Norway France Sweden Estonia Czech Republic Note: (2004).

a

Attend religious service at least weekly (%)

Pray daily (%)

Religious (at least 8 on a scale from 0 to 10) (%)

Mean religiosity (3 items)

57.4 22.9 55.6 32.4 30.5 32.8 15.2 13.1 15.5 4.0 4.9 16.6 18.9 13.8 14.3 10.2 12.3 11.6 9.4 3.2 5.2 6.4 3.9 3.9 7.3

45.0 44.4 50.5 31.9 28.6 32.3 35.1 29.0 18.2 20.4 23.7 14.5 19.2 25.6 18.5 14.5 13.0 17.6 14.8 13.0 13.0 11.1 10.2 5.3 6.9

39.4 51.0 29.5 30.4 19.6 33.7 19.7 26.6 21.3 35.2 24.0 18.2 14.8 21.1 17.0 14.8 15.3 17.2 20.8 11.1 11.0 11.6 9.1 8.2 8.6

6.45 6.32 6.19 5.26 4.92 4.85 4.79 4.48 4.23 4.16 3.97 3.76 3.66 3.65 3.37 3.33 3.25 3.19 3.15 2.93 2.89 2.67 2.45 2.41 1.91

Refers to ESS Round 1 (2002/03); data for other countries from ESS Round 2

statistically significantly from other Nordic countries in church attendance, but notable differences can be observed in terms of how religious people consider themselves to be and how often they pray. Finns and Icelanders both pray more often and consider themselves to be more religious than Swedes, Norwegians and Danes. The relatively high levels of religiosity in Finland may still reflect the fact that Lutheranism has

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historically been an especially important factor for the Finnish national identity (see Bruce 2000). Nevertheless, it is not easy to explain what determines the differences between European countries. As explained above, the secularization theory stresses the importance of modernization, but it is very difficult to draw any conclusions for or against this claim because all the countries in this analysis are comparatively rich and highly developed ones. An alternative perspective, the religious markets theory, suggests that multi-denominational countries are more religious than countries with a religious monopoly. According to this view, monopolies are inefficient and lead to low levels of religious participation (Stark and Iannaccone 1994). This view may not be substantiated with these data either. Religious pluralism is the highest in the Continental mixed countries, yet these countries are not the most religious ones in Europe. This is consistent with earlier analyses that included a larger number of countries and did not find correlation between religious pluralism and levels of religiosity (e.g. Norris and Inglehart 2004, pp. 100–101). It is not unlikely that the differences simply reflect the varying European religious traditions. Protestantism in itself has given rise to secularization in the sense that the seeds of individualism were manifest in Protestantism much earlier than in Catholicism. In contrast to Catholics, Protestants are personally responsible before God in religious matters, and the church has a lesser role as a mediator between the believer and God. ‘The Catholic Church, with its extensive, dogmatic, collective creed imposes a more collective identity upon its faithful’ as Jagodzinski and Dobbelaere (1995, p. 81) put it. Protestant individualism has most probably enforced secularization, which can be perceived today as a clear divide between Protestant and Catholic European countries. In fact, according to ESS data, the separation between Catholics and Protestants is also evident at the individual level. All over Europe, the proportion of Catholics who attend religious service on a weekly basis is three times greater than the corresponding percentage among Protestants (30 per cent among Catholics vs. 10 per cent among Protestants). Almost a third – 30 per cent – of Catholics pray daily and 26 per cent identify themselves as religious, whereas only 21 per cent of Protestants report praying daily and 18 per cent consider themselves religious. These differences remain strong and statistically significant even when controlled for demographic and social background variables and country of residence. In order to gain a more detailed picture of religiosity in the Nordic countries and the rest of Europe we turn to the differences in religiosity, and not only between countries but also between different segments of the population. As often noted (e.g. Hayes 1995; Campbell and Curtis 1994), religiosity and religious attitudes are determined in interaction with a number of

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demographic and socio-economic factors such as gender, age, marital status, education, and occupation. We employ multilevel modelling in order to analyse the effects of these individual level differences simultaneously with country differences. Countries are grouped into three categories. The Nordic countries are contrasted against European Protestant (or actually mixed) countries, and a group of mainly Southern European Catholic countries are combined with the two Orthodox countries in our data, namely Greece and the Ukraine.1 As the dependent variable we use a scale consisting of the three indicators of religiosity, which are already familiar from Table 12.1. Each indicator was scaled in equal sequences on a scale from 0 to 10. The indicators are highly correlated and thus the reliability of the scale proved satisfactorily high in all countries and ranged from .74 to .82. First, an unconditional model with no explanatory variables was estimated. The within-country component (Se) was 6.27, the between-country component (Su) was 1.76 and the intra-class correlation (ICC) amounted to 0.22, which suggests that there is a notable amount of clustering of religiosity at the country level, and a more conventional OLS model would be likely to yield misleading results. The results of the final model are depicted in Table 12.2. This model includes the fixed effects of all independent variables. Many of the effects of individual level factors in Table 12.2 are consistent with earlier studies. Prior studies have shown that male, younger, or single individuals are significantly less religious than their older, female, or married colleagues. Indeed, as depicted in Table 12.2, gender and age are clearly the most important determinants of religiosity all over Europe. However, marital status seems to predict religiosity to a certain extent as well. Women are significantly more religious than men. This universal gender difference has traditionally been accounted for by the assumedly different socialization of men and women or, more recently, by the higher risk aversion of women in contrast to men (e.g. Miller and Stark 2002). However, the effects of age on religiosity are not straightforward. The nonlinear effect suggests that young adults and the middle aged are the least religious age groups, whereas both the elderly and the very young groups are more religious. Two alternative explanations may account for the high religiosity among the elderly. It is well possible that people become more religious as they become older. Alternatively, this may be a cohort effect based on the more religious social surroundings and upbringing during the days when the currently elderly people were young. The relatively high religiosity among the youngest age groups may reflect the fact that religiosity is still present in the early education and upbringing of children in most countries. With regard to the differences according to family structure, we find that married persons are more committed to religion than singles all over Europe.

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Table 12.2

Determinants of religiosity: multilevel analysis, fixed effectsa

Variable

Coefficient

Intercept Married Divorced/widowed Never married Education level III Education level II Education level I Age  10 Age squared  1000 High income Middle income Low income Female Male Service classes Routine non-manual employees Self-employed Skilled manual worker Other occupation/outside labour force Unskilled manual worker Nordic countries Continental mixed countries Catholic and Orthodox countries Su (Model 0) Su (Model 1) ICC (Model 0)

1.28*** .50*** .22*** Ref. .14** .19*** Ref. .11* .39*** .35*** .16*** Ref. 1.09*** Ref. .17*** .15*** .34*** .13** .23*** Ref. 1.93** 1.98** Ref. 1.76 .74 .22

Notes: a Countries included in the analysis: Catholic and Orthodox countries: Poland, Ireland, Greece, Italy, Slovakia, Portugal and Ukraine; Protestant/mixed Continental countries: Switzerland, Germany, The Netherlands, the United Kingdom and Estonia; Nordic countries: Finland, Sweden, Iceland, Denmark and Norway. * p.05; ** p.01; *** p .001. Source: ESS 2004; data for Italy from ESS 2002.

Earlier findings about the effects of education and social class are more contradictory. There is evidence that religiosity correlates negatively with levels of social stratification (e.g. Hayes 1995). The lower and vulnerable strata of society are more religious than the upper strata, because religion may offer a haven for the dispossessed (see Norris and Inglehart 2004). Moreover, a central part of the secularization thesis is that rising levels of education contribute to a decline in religiosity. According to this argument,

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people abandon the irrational world-view offered by religion as the levels of scientific and rational education rise. However, the counter-argument states that there is a positive relation between education and religiosity. Religious beliefs might arise because these beliefs can never be proved or disproved and, therefore, depend on faith and the capacity for abstraction. Hence, believing may come more readily to more educated or scientific persons, who have a greater capacity to engage generally in abstract or theoretical reasoning. Thus, Iannaccone et al. (1998) argue that religiosity is compatible with scientific training. In this analysis we find some support for the claims that the lower strata are more religious than the upper segments of society. The service classes, the highest educational categories and the highest income brackets are clearly less religious than the lower occupational, educational and income groups. All in all, our evidence suggests that in contemporary Europe social status correlates negatively with religiosity. To put it briefly, the first part of this analysis shows that religiosity is still one of the central aspects of European culture, although less in the Northern and Central parts of the continent than in the South. We have also learnt that the socio-economic and demographic determinants form a consistent pattern all across Europe. The middle-aged, men and the upper strata are the least religious segments of the population in European countries. However, in order to estimate the influence of religiosity in the everyday life of Europeans, we must analyse the impact of religiosity on an array of political, social and moral values and behaviour.

THE INFLUENCE OF RELIGIOSITY ON POLITICAL, SOCIAL AND MORAL VALUES For centuries religion was the ‘sacred canopy’ that influenced all aspects of social life, including beliefs, attitudes and values as well as behaviour (Berger 1969). According to secularization theory, the influence of religion on other domains of society has been decreasing. The once strong relationship between religion and other social domains is assumed to be less self-evident in contemporary society. At the individual level this would show as a weak association between religiosity and other values and behaviour. However, this need not always be the case. In countries where secularization has proceeded furthest, individuals who retain their religious identity may oppose the various aspects of the secularization process by showing contrasting values with non-religious individuals. Thus, religious persons may start a counter-action; that is, develop a backlash against secularization. These alternative expectations can be tested empirically by

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analysing the associations between religiosity and social, political and moral values. It is crucial to note that religiosity affects various types of values in different ways and to varying degrees. For example, Halman and his colleagues (1999) distinguish between values concerning public and private spheres of life, and show that the impact of religion is generally stronger on values of the private domain than in the public sphere values. The public domain consists of political and economic attitudes and attitudes towards the institutions of the surrounding society, whereas the private domain consists of more personal values like family values and personal moral stances. The division between the private and public domains is not selfevident because most private issues depend at least partly on social determinants that are defined by the society at large and the immediate social surroundings of the individual. Therefore, the line between private and public concerns is not always indisputable. However, we follow this basic divide between values concerning either private or public domains of life and hypothesize that religiosity correlates more strongly with private issues such as family values and personal moral issues than with private issues like political and economic attitudes. What else could be expected of the relationship between religiosity and political, social and moral values? One of the most common expectations regarding the influence of religiosity on political attitudes is that the more religious a person is the more conservative and conventional values he or she holds (see Hayes 1995; Norris and Inglehart 2004). Several studies have found that religious persons tend to support the political right and are less supportive of the left. Moreover, the less religious a person is, the more cynicism about government and political institutions he or she expresses. This is quite natural as Christian religious affiliation typically teaches compliance with established social norms, practices and institutions, as well as the subordination of individual aspirations to those of the community (Kitschelt 1994). Therefore, as the second hypothesis we anticipate that although religiosity is not a major determinant of political attitudes, we should be able to identify two correlations: one between religiosity and the political left–right divide, and another between religiosity and trust in governmental and political institutions. The possible correlation between religiosity and trust in institutions can be further argued for from the perspective of theories of social capital. These theories often emphasize the importance of social ties and shared norms for all types of civic values and engagement, not only for social trust. Most prominently, Putnam (2000) argues that in the United States, religious communities are the most important repository of social capital. Moreover, Putnam expects declining levels of civic engagement to be a

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consequence of secularization and decreasing connections between religious communities and the wider society. Norris and Inglehart (2004, p. 182) summarize Putnam’s thinking in a two-step model in which civic society first promotes social capital like social networks and cultural norms, which, in turn, facilitate political participation. Religion plays a pivotal role in this model by enhancing both networks and cultural norms. It is easy to expect certain country differences in the strength with which religiosity affects the way people think. As we saw above, the Protestant Nordic countries are among the most secularized countries. If, as discussed above, the strong tendency for secularization among Protestant countries is based on individualistic value orientation and the weaker tendency in Catholic countries is related to the Catholic religion, we might expect that for the same reason the association between religiosity and other values is less pronounced in the Nordic countries than in Central Europe and especially in the southern parts of Europe. In order to test these hypotheses, we take advantage of the richness of the ESS data, which contain measures on a large variety of values, attitudes and opinions. First, we concentrate on issues most clearly belonging to the public sphere of life, namely on items related to left–right divide and opinions about certain issues that are normally strongly related to the left–right scale, such as government intervention in the economy and income differences. Next, we turn to the issue of social trust. We use measures on both trust in institutions and generalized trust; that is, trust in other people. Finally we consider the most private issues. We test the effects of religiosity on attitudes that exemplify private issues, such as family values and more general moral values like the importance of general altruism and helping others, cheating on taxes and homosexuality. In order to test the effects of religiosity on these dependent variables we use two strategies. First, we divide the sample into two groups, the religious and the secular. The former group consists of those who attend religious services at least weekly or pray daily or identify themselves as religious (with the value of at least 8 on a scale from zero to ten). As religiosity itself and several of the dependent variables can be expected to correlate with various other variables, we also employ multiple linear regression analyses to control for the most important social background variables like gender, income, marital status, educational level, occupational status and age. Again, in this analysis we refer to the categorization of countries into three groups as described above. We start the analysis with values concerning the public sphere. Table 12.3 reports the effects of religiosity on selected left–right issues and certain measures of social trust.2 As explained above, we would expect religiosity to correlate negatively with support for leftist opinions, and as shown in

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Table 12.3, this hypothesis gains a degree of support. All over Europe religious persons identify themselves more with the political right than with the left. In Catholic countries the correlation between religiosity and the left–right scale is the highest. However, being religious does not necessarily make a person think in a more rightist way per se. As we control for the background variables, the effect of religiosity on two traditional left–right issues, government intervention in the economy and reducing income differences, turns positive. However, in Nordic countries we find no correlation at all between religiosity and these measures. The last four items in Table 12.3 refer to interpersonal trust and trust in two national institutions, the parliament and the legal system. We hypothesized above that religiosity stimulates both trust in social institutions and interpersonal trust. The hypothesis does not gain full support. First of all, country differences in generalized trust are notable. The publics of the most secular Nordic countries are the most trusting ones. In contrast Catholic nations show the least trust towards other people. Furthermore, the effects of religiosity vary from one group of countries to another in a way that does not entirely substantiate the expectations about positive correlation between the two variables. Only in Central European countries is there a positive correlation between religiosity and interpersonal trust. In Catholic countries, religious people appear to have less trust in other persons, and in the Nordic countries, again, there are no differences between the religious and the secular. We only find support for a positive correlation between trust and religiosity in relation to trust in the parliament and the legal system. Once more, however, the levels of trust are the highest in the Nordic countries. All in all, we find that public sphere issues undoubtedly correlate with religiosity in both Southern and Central European countries. In Nordic countries we find a correlation between religiosity and left–right scale, but otherwise there are no correlations between religiosity and public sphere issues at all. Neither do we find any support for the expectations about secularization stimulating a political backlash among the religious parts of the population. Even so, the comparatively weak association of these public and political concerns and religiosity is not surprising. It can be argued that churches and religion in general have lost substantial parts of their significance in public political issues. In most countries churches do not often interfere directly with politics. However, instead of participating in political debate, churches still argue for their views in more general moral issues. Therefore, we might expect a stronger association between religiosity and more personal, private and moral issues. In Table 12.4 we turn to more private issues such as general moral values and family values. We use altogether six items to tap moral issues like the

242 65.7 36.8 60.9 42.3 56.1 37.1 51.3

Sig.

B

72.6 36.7 56.1 38.7 53.4 34.3 48.8

Nonreligious (%)

B

*** .37 n.s. .08 *** .05 *** .23 ** .09 ** .38 ** .29

Sig.

72.5 *** .60 31.8 n.s. .05 68.6 *** .08 37.2 *** .09 49.7 *** .27 35.2 n.s. .00 45.7 n.s. .09 Continental mixed countries

Religious (%)

62.5 32.0 75.1 34.0 43.5 34.4 44.7

Nonreligious (%) 55.3 26.7 70.0 69.6 78.3 57.0 67.6

*** *** * *** * ** ***

61.8 29.9 81.5 28.6 36.3 31.9 40.3

Sig. Religious (%)

*** *** *** ** *** n.s. **

Sig. Religious (%)

Sig.

74.6 28.2 80.6 31.6 42.7 32.9 39.0

Nonreligious (%)

B

.41 .04 .08 .03 .01 .02 .01

B

*** .83 * .01 n.s. .06 *** .11 *** .23 n.s. .04 n.s. .23

Sig.

59.2 n.s. 23.1 n.s. 64.1 * 68.1 n.s. 76.8 n.s. 58.6 n.s. 68.9 n.s. Catholic countries

Nonreligious (%)

Nordic countries

Notes: Affirmative answers refer to ‘Agree strongly’ and ‘Agree’. On variables measured on an 11-point scale values greater or equal to 6 were categorized as affirmative. * p .05; ** p.01; *** p  .001.

Left–right scale Government intervention in economy Reduce income differences Most people can be trusted Most people try to be fair Trust in national parliament Trust in legal system

Left–right scale Government intervention in economy Reduce income differences Most people can be trusted Most people try to be fair Trust in national parliament Trust in legal system

Religious (%)

All countries

Table 12.3 Effects of religiosity on social trust and political attitudes by country group: percentages of affirmative answers and B coefficients produced by linear regressions (controlled for gender, income, marital status, educational level, occupational status and age)

*** n.s. *** ** *** n.s. ***

Sig.

*** n.s. n.s. n.s. n.s. n.s. n.s.

Sig.

243

Citizens should spend some free time helping others Citizens should not cheat on taxes Homosexuals should be free to live as they wish

Citizens should spend some free time helping others Citizens should not cheat on taxes Homosexuals should be free to live as they wish Women should be prepared to cut down paid work for the sake of family Men should have more right to jobs than women when jobs are scarce Children at home, parents should stay together 75.8 77.7 43.6 21.7 21.5

84.0 61.0 60.6 39.2 40.4

***

***

***

69.6 74.6 78.7

82.1 83.0 68.0

Religious Non(%) religious (%)

.21 ***

B

23.4

16.3

33.7

87.2 66.5

75.4

85.5 57.8

83.8

77.5 42.2

77.9

Sig. .21 ***

B

***

***

***

.09 ***

Sig.

*** .18 *** *** .47 ***

***

B

.29 ***

.23 ***

.27 ***

*** .25 *** *** .39 ***

***

Catholic countries

12.5

7.4

19.7

78.8 81.1

65.5

Sig. Religious NonSig. (%) religious (%)

.50 ***

*** .11 *** *** .25 ***

***

Sig.

***

.36 ***

36

Nordic countries Sig. Religious NonSig. (%) religious (%)

.16 ***

B

*** .16 *** *** .40 ***

***

Sig.

Continental mixed countries

71.9

82.8

Religious Non(%) religious (%)

All countries

Table 12.4 Effects of religiosity on moral values and family values: percentages of affirmative answers and B coefficients produced by linear regressions (controlled for gender, income, marital status, educational level, occupational status and age)

244

(continued)

45.4 19.1 86.5

60.7 32.7 90.3

Religious Non(%) religious (%)

***

***

***

Sig.

Catholic countries

.08 ***

.31 ***

93.3

46.0

65.0

80.8

27.6

47.8

***

***

***

Sig. Religious NonSig. (%) religious (%)

.30 ***

B

Continental mixed countries

Notes: Affirmative answers refer to ‘Agree strongly’ and ‘Agree’. * p .05; ** p .01; *** p .001.

Women should be prepared to cut down paid work for the sake of family Men should have more right to jobs than women when jobs are scarce Children at home, parents should stay together

Table 12.4

Sig.

.30 ***

.54 ***

.30 ***

B

The meaning and implications of religiosity

245

moral responsibilities of an individual towards other people and society at large (e.g. not cheating on taxes) and attitudes towards homosexuality.3 As expected, the correlations are stronger than in the previous analyses. This pattern also applies to the Nordic countries. There is a constant tendency for religious people to agree that citizens should spend some free time helping others, and this tendency, which is Europe-wide, is not as distinct with non-religious persons. Likewise, religious people despise cheating on taxes and breaking the law to a greater extent than do non-religious persons all over Europe. These differences remain substantial even when controlled for other background variables. Finally, the last three items focus on the effects of religiosity on attitudes to gender roles and family values. We find once more clear differences between religious and secular people across Europe. All over Europe religious people tend to support different gender and family roles in comparison to secular people. Religious persons support traditional gender roles according to which women should have a more limited role in the labour market than men. A part of traditional thinking is also reflected in the last item referring to divorce. Religious persons tend to reject divorce whenever there are children still living at home, no matter how the parents get along with each other. However, here one should note that only a minority of both religious and non-religious persons agree with the statement about divorce.

DISCUSSION In this analysis we have focused on religiosity in the Nordic countries in comparison with the rest of Europe. We started by having a look at the levels and social correlates of religiosity and then moved on to see how strongly religiosity still affects the way people think and behave in the Nordic countries as well as in other parts of the continent. So far the differences in religiosity between nations have been accounted for by two basically incompatible theories – secularization theory and religious markets theory. Secularization theory refers to the effects of general modernization and rising levels of affluence. Religious markets theory suggests that religious monopolies produce disappointment in religion, which leads to a decrease in the influence of religion in some countries, although not as a global trend. We find no direct evidence for the secularization theory or religious market theory. It would rather seem to be the case that the histories of various religious traditions in different parts of Europe are still reflected in current religious outlooks of European nations. However, this is not to say that either of these theories is wrong. It is not our aim to test

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the theories of historical religious change in Europe in this chapter. Instead, we use cross-sectional data to describe the current situation. The main finding of this analysis is that there are certain clear differences in religiosity and religious influence between European countries. In comparison with other European nations, the Nordic countries are among the least religious. However, the Nordic countries are not the only relatively secular region in Europe. The differences between the Nordic countries and the Central European mixed countries are not large. Even more notably, many of the post-socialist countries are highly secular. The most devout nations in Europe are Catholic Poland, Ireland and Italy and Orthodox Greece. We also find notable differences in the levels of religiosity between the Nordic countries. Finland and Iceland are an exception here. Although church attendance in these two countries is as low as in the other Nordic countries, it seems that Icelanders and Finns still hold personal religious beliefs more often than Swedes, Danes and Norwegians. However, taking the Nordic countries as a whole, we can conclude that despite the strong Lutheran tradition and persisting high levels of nominal church membership, church attendance, personal praying and identifying oneself as a religious person are clearly less common parts of the culture in the Nordic countries than in most other parts of Europe. In the case of individual determinants of religiosity, we find that religiosity in current Europe depends strongly on gender and age. A low socio-economic status and educational level are associated with religious orientation. These differences are quite similar across all ESS countries. Moreover, the influence of religion on other values is relatively modest in the Nordic countries. In relation to issues that are categorized as public concerns, such as politics and political engagement, we find almost no influence of religiosity at all. All in all, it can be concluded that religiosity, at least in its traditional forms, occupies a comparatively modest role in the Nordic countries. However, this conclusion should not be exaggerated; there are still certain issues that clearly differentiate believers from nonbelievers. Most notably issues that are categorized as private moral concerns like family values, are still determined by religiosity in the Nordic countries. Moreover, it has to be emphasized that this analysis concentrates on traditional forms of religiosity only. The possible religious change reflected in the obviously increasing levels of interest in various forms of New Age religiosity is outside the focus of this analysis.

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NOTES 1. Note that only 17 countries are included in the multilevel analysis in Table 12.2. Eight countries (Austria, Belgium, Czech Republic, Spain, France, Hungary, Luxembourg and Slovenia) were excluded from the analysis. All of these countries are predominantly Catholic, but much more secularized (see Table 12.1) than the Catholic countries that were included in the analysis in Table 12.2. Omitting the eight countries does not have an impact on the effects of individual level independent variables on religiosity, but makes the country difference more evident. In further multilevel analyses (not shown) controlling for the same individual level factors as used in Table 12.2 the country level differences in religiosity between the Nordic countries and the above mentioned eight Catholic countries were not statistically significant. 2. Left–right scale was measured on a scale from 0 to 10. Similarly, the items measuring social trust were on a scale from 0 to 10. About social trust, the respondents were asked whether or not most people can be trusted and whether they think that most people try to be fair to them or take advantage of them if they get the chance. About trust in institutions, the respondents were asked separately how much they personally trust in the national parliament and the legal system. Items about government intervention and income differences were on a 5-point scale from ‘agree strongly’ to ‘disagree strongly’. The exact wordings of these items were: ‘The less that government intervenes in the economy, the better it is for [country]’ and ‘The government should take measures to reduce differences in income levels’. 3. The respondents were asked whether they agree or disagree with the following statements: ‘Citizens should spend at least some of their free time helping others’; ‘Citizens should not cheat on their taxes’; ‘Gay men and lesbians should be free to live their own life as they wish’; ‘A woman should be prepared to cut down on her paid work for the sake of her family’; ‘When jobs are scarce, men should have more right to a job than women’; and ‘When there are children in the home, parents should stay together even if they don’t get along’. The answering options were on a 5-point scale from ‘agree strongly’ to ‘disagree strongly’.

REFERENCES Bäckström, Anders, Ninna Edgardh Beckman and Per Pettersson (eds) (2004), Religious Change in Northern Europe – the Swedish Case, Stockholm: Verbum. Berger, Peter (1969), The Sacred Canopy: Elements of a Sociological Theory of Religion, Garden City, NY: Doubleday. Bruce, Steve (2000), ‘The supply-side model of religion: The Nordic and Baltic states’, Journal for the Scientific Study of Religion, 39 (1), 32–46. Campbell, Robert A. and J.E. Curtis (1994), ‘Religious involvement across societies: Analyses for alternative measures in national surveys’, Journal for the Scientific Study of Religion, 33 (3), 217–230. Dobbelaere, Karel (1993), ‘Church involvement and secularization: Making sense of the European case’, in Ellen Barker, James A. Beckford and Karel Dobbelaere (eds), Secularization, Rationalism and Sectarianism, Oxford: Clarendon Press, pp. 19–36. Ester, Peter, Loek Halman and Ruud de Moor (eds), (1994), The Individualizing Society, Tilburg: Tilburg University Press. Gustafsson, Göran (1994), ‘Religious change in the five Scandinavian countries, 1930–1980’, in Thorleif Pettersson and Ole Riis (eds), Scandinavian Values. Religion and Morality in the Nordic Countries, Uppsala: Acta Universitatis Upsaliensis, pp. 11–58.

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Halman, Loek, T. Pettersson and J. Verweij (1999), ‘The religious factor in contemporary society. The differential impact of religion on the private and public sphere in comparative perspective’, International Journal of Comparative Sociology, 40 (1), 141–60. Hayes, Bernadette (1995), ‘The impact of religious identification on political attitudes: an international comparison’, Sociology of Religion, 56 (2), 177–94. Iannaccone, Laurence R., R. Stark and R. Finke (1998), ‘Rationality and the “religious mind” ’, Economic Inquiry, 36 (3), 373–89. Jagodzinski, Wolfgang and Karel Dobbelaere (eds) (1995), ‘Secularization and church religiosity’, in Jan van Deth and Eelinor Scarbrough (eds), The Impact of Values, Oxford: Oxford University Press, pp. 76–119. Kitschelt, Herbert (1994), The Transformation of European Social Democracy, Cambridge: Cambridge University Press. Lambert, Yves (2004), ‘A turning point in religious evolution in Europe’, Journal of Contemporary Religion, 19 (1), 29–45. Madeley, John (2001), ‘Reading the runes: The religious factor in Scandinavian electoral politics’, in David Broughton (ed.), Religion and Mass Electoral Behaviour in Europe, London: Routledge, pp. 28–43. Miller, Alan S. and R. Stark (2002), ‘Gender and religiousness: Can socialization explanations be saved?’, American Journal of Sociology, 107 (6), 1399–423. Norris, Pippa and Ronald Inglehart (eds) (2004), Sacred and Secular. Religion and Politics Worldwide, Cambridge: Cambridge University Press. Putnam, Robert (2000), Bowling Alone: The Collapse and Revival of American Community, New York: Simon & Schuster. Stark, Rodney (1999), ‘Secularization, RIP’, Sociology of Religion, 60 (3), 249–73. Stark, Rodney and Rofer Finke (2000), Acts of Faith: Explaining the Human Side of Religion, Berkeley: University of California Press. Stark, R. and L.R. Iannaccone (eds) (1994), ‘A supply-side reinterpretation of the “secularization” of Europe’, Journal for the Scientific Study of Religion, 33 (3), 230–52.

13.

Conclusions: Nordic uniqueness, reality or myth? Heikki Ervasti, Torben Fridberg, Mikael Hjerm and Kristen Ringdal

INTRODUCTION Geographically, the Nordic countries consist of Scandinavia (Denmark, Sweden and Norway) together with Finland and Iceland. From a European perspective the countries are located on the periphery of Europe. During the last century the Nordic countries transformed from predominantly agrarian countries with modest living conditions to industrial and postindustrial nations and achieved notably high standards of living. In the course of history the Nordic countries developed specific features that separated them from most other European countries in various respects. The most discernible characteristics are the tradition of the strong state based on long periods of social-democratic rule and the relatively strong position of the class of independent farmers. All in all, the countries formed a distinctive model of society that combined a specific model of the welfare state, politics and labour markets. With no exaggeration, the five countries analysed here stand out as a separate area of unique Nordic culture. Opinions about the Nordic countries in contemporary political debates have consistently oscillated between two extremes. These countries have served as ideal societies worth striving for, but they have also been seen as a warning example of societal development that should be avoided by all possible means. For those in favour of social equality in general, and especially equality of opportunities for education, health services and social services, such as daycare for children and care for the elderly, the Nordic countries look admirable. However, those in favour of more marketoriented policies may observe obstacles for private initiative: the welldeveloped and overly generous welfare state, high levels of taxation, rigid labour markets, compressed wage structures and excessively high levels of wages in relation to work productivity and so on. Some may also resent the massive role of the state that was previously dedicated to the family and individual citizens. 249

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It is not our task to become involved in this partly ideological debate about the society that best promotes the good life. Our task here is to analyse the effects of institutional settings typical to the Nordic countries on people’s attitudes and behaviour. We started the analyses of this volume with the assumption that different institutional settings are reflected in the ways people think and behave. This assumption is substantiated in our analyses. The uniqueness of the Nordic societies in a wider European comparison becomes especially clear in various fields of social life ranging from social exclusion and happiness to political behaviour and even to economic morality and religiosity. Our approach is decisively and consciously eclectic as our aim is to extend the analysis to a wide range of timely and critical issues that reflect the conditions of the Nordic countries as they face the pressures of a changing European context. Our analyses cover issues related to the welfare state, politics, family and work, and finally, cultural issues like economic morality and religiosity. Our empirical analyses are based on methodologically rigorous and strictly comparable surveys carried out in more than 20 countries across the European continent on two occasions, 2002 and 2004. Nevertheless, our analyses suffer from certain limitations and even shortcomings. At least four limitations can be identified. The first limitation of our study is the inability to measure changes in the examined attitudes and behaviour. We have only utilized cross-sectional data, which makes the study of individual change impossible. The short time span covered by the first two rounds of the European Social Survey (2002–04) also excludes analysis of aggregate change. This may not be a large problem in our case since we are mainly interested in differences between the countries at the present time. With the emergence of further rounds of the European Social Survey (ESS) studies of change in attitudes and behaviour will be feasible. The second limitation concerns the focus of the chapters in this volume. The main focus of all the chapters is on the Nordic countries in a comparative perspective and this severely confines our analysis of other countries. Further analyses concerning other European countries are beyond the scope of this book. With reference to our third limitation we want to emphasize that our aim has been to examine possible differences and similarities related to the different regimes while providing a number of examples of specific institutions that produce the depicted outcome. We are not able to account for the full complexity of causes. We do not claim to have explained why people are happy, xenophobic or hold egalitarian views on gender. Instead, we hope to have clarified how such things differ across countries in a somewhat ordered way. The task to fully account for the complexity in the examined phenomena would be impossible for any

Conclusions

251

book and even more so for a book that never set out to fulfil such a task in the first place. Finally, our fourth limitation is that we have not placed our focus on individual differences across countries. We have taken such differences into consideration, but have paid little attention to the fact that individual level differences are in some instances structured differently across countries. For example, the attitudes of the political left and right on xenophobia varies across countries (Chapter 10). The fact that various individual level stratifications have different meanings in different countries, and possibly related to different regimes, is in itself very important, but nonetheless is ignored to a large extent in this book. Notwithstanding the limitations, we believe that many of our findings offer new knowledge about the Nordic countries and serve as starting points for further empirical research about the complex meanings and implications of various institutional arrangements. We have divided our analyses broadly into four parts: the first part focuses on issues relating to the welfare state and living conditions, the second on political issues and the third on family and work-life, and the final part on moral, ethical and cultural issues. The exceptionalism of the Nordic countries becomes most obvious in issues related to the welfare state. As Fridberg and Kangas (Chapter 2) show in their analysis, the Nordic type of the welfare state has managed to decrease the amplitude of social problems in a comparatively efficient way. According to Fridberg and Kangas, Nordic poverty rates are the lowest of all countries and this is mainly the result of a combination of the universality and relative generosity of the social security benefits that is a distinctive feature of the Nordic model of the welfare state. Interestingly enough, indicators of social relations also suggest that the Nordic welfare state does not eat up and hollow-out such relations, such as meeting socially with friends and relatives on a daily basis/several times a week or the prevalence of having a close friend to talk to. Indeed, according to these data, Northerners are more sociable than other Europeans, which may come as a surprise to those who rely on national stereotyping. Also there is a positive impact of social spending and the Nordic welfare state on feeling safe walking alone in the local area after dark. Moreover, Fridberg and Kangas also show that traditional socioeconomic predictors like class and position in the labour market still explain the majority of the variance of social problems within each country. Also the Scandinavian poor and unemployed tend to suffer from ill-health and other related problems more than non-poor Scandinavians. Therefore, the analysis does not lend support to the recent claims about ‘democratization’ and the diffusion of social risks. In consequence,

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Fridberg and Kangas conclude that there are no reasons to expect that traditional social policies should become inefficient methods for combating social problems. Furthermore, the less conventional use of subjective indicators confirms the distinctive character of the Nordic countries. We are aware that all researchers do not agree that subjective well-being correlates with material living conditions. After all, it is not clear if the public goods of rich countries, such as health care, the welfare system and public schools, really make people healthier or happier at all. Nevertheless, Eikemo, Mastekaasa and Ringdal (Chapter 3) find there is a strong and positive correlation between health and happiness at the country level. Countries with a high percentage of people with poor health also have a high percentage of people who are unhappy. This is clearly related to the general living standard of the country as measured by the GDP per capita or the Human Development Index. This translates into differences between welfare regimes and more so for unhappiness than for poor health. As far as the latter is concerned, the Eastern European countries score the highest, while there are rather small differences among the remaining welfare regimes. For unhappiness, there are three different levels among the countries. Again, the East European countries fare the worst, and the Nordic countries are found in the most favourable position with the lowest percentage of unhappy people. The other West European countries are placed between the two extreme groups of countries. There are only minor differences in the levels of unhappiness and poor health among the Nordic countries. It is obvious that the welfare state and social policies have left traces in the whole society. One aspect of this becomes evident as Fridberg and Kangas (Chapter 4) move on to the analysis of social capital. The focus of this analysis is first on membership of and activity in voluntary organizations and second in generalized trust. All the Nordic countries score highly on membership of voluntary organizations. Norway and Sweden in particular score very highly on voluntary work in some voluntary organizations, followed by Denmark. Finland lags behind the Scandinavian countries, but still scores around the European average. Considering the other dimension of social capital, generalized trust, the Nordic countries form a clearly homogeneous group of countries with exceptionally high levels of trust. Indeed, in their conclusion, Fridberg and Kangas state that there seems to be a ‘virtuous circle’ between the encompassing and generous welfare state and social capital, and according to this analysis, the connection between the encompassing welfare state and non-governmental activities is positive, not negative as is sometimes argued. The second group of issues in our analyses relate to politics. One of the major changes in contemporary Europe is taking place in the political

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sphere. First, the levels of political decision making have been undergoing major change, undoubtedly, in several key areas of policy making, from national states up to European level institutions during the last few decades. At the same time, however, regional and local levels of decision making have also grown stronger. The nation states have ceased to be the main domains of power. Is this a distribution of political power that is supported by the majority of the people? As Berg and Hjerm (Chapter 5) show, there are differences in the preferred levels of decision making between European nations. In Finland, Norway and Sweden people show a notable level of criticism in relation to the European level of decision making. However, in Denmark, where people have had a longer experience of European level decision making, the attitudes are also clearly more positive. Both institutional relations to the EU as well as political articulation of Europe explains country differences in support for European level decision making, whereas sociotropic self-interests correlate only weakly with the preferred level of decision making. Whatever the level of political decision making, another important issue is to what extent people still get involved in politics and to what extent they still trust political institutions. Two chapters in this volume address these issues. Berglund, Kleven and Ringdal (Chapter 6) show that the levels of unconventional political activism (signed a petition, boycotted products) in Europe are in fact higher than the levels of conventional political activism (contacted politician, worked in a political party). The two types of political activism are positively correlated at the country level; that is, countries with high levels of conventional political activism also tend to have a high level of unconventional political activism. With the exception of participation in lawful public demonstrations, the levels of both conventional and unconventional political activism are higher in the Nordic countries than in other European countries. Both the detailed analysis of the indicators and the multilevel analysis confirm this. As far as conventional activism is concerned, the Nordic countries show the highest level followed by the old democracies in Western Europe, with the new democracies in Southern and Eastern Europe registering the lowest level. The new democracies in Eastern Europe have the lowest level of unconventional political activism, with the Nordic countries at the other end and the remaining West European countries in the middle. Among the Nordic countries, Iceland shows the highest level of political activism followed by Sweden and Norway and then, somewhat behind, come Denmark and Finland. Listhaug and Ringdal (Chapter 7) distinguish between three dimensions of political trust: trust in the electoral system, the legal system and the European Parliament. The Nordic countries, and other small rich

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countries, registered the highest level of trust in the two national political institutions. At the bottom were the East European countries. The pattern was quite different for trust in the European Parliament. On this dimension, the Nordic countries scored lower, whereas the South European countries registered the top scores. The multilevel analyses indicate that the country differences in political trust may be explained by a combination of compositional effects and macro-characteristics. The compositional effect seems to be the most important, as two thirds of the differences in trust in national political institutions between the countries are explained by individual differences in the attitudinal variables, especially the evaluations of political performance. The latter cannot explain the differences between the countries in trust in the European Parliament. However, quite a substantial part of the variation between the countries may be explained by macrocharacteristics, especially their score on the Human Development Index (HDI). Countries with good living conditions showed high trust in national political institutions, but lower trust in the European Parliament. Among the Nordic countries Denmark and Finland score highest on trust in national political institutions, but the differences are rather small. Concerning trust in the European Parliament, there are large differences among the Nordic countries. Iceland has one of the highest scores, whereas Sweden is found towards the other end. The third theme in our analyses concerns the everyday life of the Nordic nations in respect to family, gender issues and work. One of the most celebrated characteristics of the Nordic model is the high level of gender equality. Several recent accounts suggest that the family policies pursued in the Nordic countries help to find a balance between work and family life. The Nordic countries are normally classified as representing an egalitarian gender regime. The comprehensive family policy encourages female labour force participation and emphasizes gender equality and women’s independence from men. As is well known, labour force participation among women is almost as high as among men in the Nordic countries. Moreover, the evidence presented in this volume by Nordenmark (Chapter 8) suggests that gender equality is higher in the Nordic countries than elsewhere in Europe. People in the Nordic countries hold more equal attitudes towards gender roles. We find support once more for the idea that attitudes are reflected in the way people behave. As Nordenmark shows, the division of both domestic work and paid work is more equally divided between men and women in the Nordic countries than elsewhere in Europe. However, further research is needed. We cannot draw a general conclusion that gender conflict is less of a problem in the Nordic countries than in other European nations. On the contrary, Nordenmark’s analysis gives moderate support for the hypothesis that an egalitarian gender ideology

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and a comparatively egalitarian division of work, as in the Nordic countries, actually generates more, not less, disagreement among couples concerning division of work. Couples who live in countries with more traditional gender roles, such as Central and Southern European countries, tend to adjust to their roles and disagree less often than their counterparts in the Nordic countries. The gender ideology among people in different European states confirms that there seems to be a relationship between individual attitudes towards gender roles and the type of gender regime. People in the Nordic states have the most egalitarian gender ideology. People living in Southern Europe experience the lowest level of disagreement about the division of housework. They also have a very traditional gender ideology and division of labour. However, there are also large variations within each cluster of states. For instance, the scores are highest among Finnish men and women, but the mean scores among Swedes and Danes are, in general, around the total mean scores for all states. Another important part of everyday life concerns working life. The Nordic countries are well known for their model of labour market institutions and work relations, in which the labour unions have had a comparatively influential position. However, during the last decades working life has changed markedly in direction of less regulated and more flexible forms. One of the most notable implications of these changes has been the increase of the various forms of non-standard work, which may have a huge impact on the quality of working life. It is feared that in the increasingly deregulated and flexible labour market, employees end up in low quality jobs more frequently than before. Ervasti (Chapter 9) analyses employees’ subjective perceptions of the quality of their jobs in standard and non-standard positions in the labour markets in different countries that are grouped into a set of labour market regimes. Ervasti shows that with respect to the labour markets, differences between the regimes are not as clear-cut as is sometimes suggested. For example, criticism about the too rigid and inflexible Nordic labour markets does not sound so accurate if we take into account that the number of fixed-term employees is relatively high in all the Nordic countries. Danish labour market policies, especially, are among the most flexible in Europe. Moreover, the evidence suggests that only small differences in job quality can be found between the labour market regimes. Generally, wage-earners in the Nordic countries register a slightly higher level of job quality than their counterparts in other regimes, but on the measures of promotion opportunities and heavy work-load, for example, the Nordic countries score among the worst in Europe. Otherwise, the evidence supports earlier findings in that employees in non-standard work arrangements perceive the

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quality of their jobs to be in general poorer than their counterparts in standard work arrangements. This finding is universal across the regimes. Finally, our analyses were extended to cover moral and ethical issues. The three last chapters of this volume concern cultural and moral distinctions between the Nordic countries and the rest of the European countries. Chapter 10 deals with attitudes towards immigration, Chapter 11 focuses on economic values and behaviour and Chapter 12 with religious traditions in the Nordic countries. Prior to this book, a long tradition of analyses of individual determinants of negative or even xenophobic attitudes towards immigrants can be identified. In Chapter 10 Ervasti, Fridberg and Hjerm set out to analyse attitudes towards immigrants from quite a different point of view. Instead of individual level factors, they focus on macro-level determinants of xenophobia. The general finding is that the publics of the Nordic countries and especially the Swedes are relatively tolerant towards immigrants, but the multilevel analyses controlling for individual level factors suggest that the differences between European countries are not large. Statistically significant differences are found only between the Nordic countries and the Eastern European countries. Somewhat surprisingly most of the country level predictors of xenophobia prove to be statistically insignificant. However, the results of the analysis suggest that living conditions as measured by the UNDP Human Development Index are the main institutional predictors of xenophobia. In Chapter 11, Ringdal covered a number of aspects of economic morality, from values to behaviour: economic trust, economic norms, victimization, and committing offences, without finding any consistent pattern of country differences. On economic trust and values, the Nordic countries distinguish themselves from other European countries in a positive sense. In consumer victimization, however, the Nordic countries and the East European countries show quite similar levels. In committing minor offences, the Nordic countries score even higher than the East European countries. On bribery the relationship is quite different. Bribery is mainly a problem in the South and East European countries Minor economic offences are committed more often in the rich than in the poor countries of Europe. The picture tends to move in the opposite direction for the admittance of serious economic offences. We interpret these country differences to be a result of the complex interplay of several factors. The most obvious one is economic development and prosperity, which mainly distinguishes the North and West European countries from the countries in Eastern Europe (the Southern European countries are in between). The more advanced the economic development, the more economic transactions there are, and therefore the higher the risk of becoming a consumer victim.

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The second notable factor is the experience of a shadow economy. A third factor is economic norms, which explained large parts of the differences between the countries in offending behaviour. In economic morality there are both similarities and differences among the Nordic countries. Although they are pretty similar in terms of economic trust and values, economic practices do not follow the same pattern in all Nordic countries. This applies especially to Finland, which scores very low on consumer victimization, but high on admittance of minor economic offences. In relation to religion, the dominant role of Lutheranism is often mentioned as one of the many factors that still testify to similarities between the Nordic countries. However, it has been suggested that the Nordic countries are among the most secularized countries in the world. Indeed, according to secularization theory, the importance of traditional religiosity should continue to fade so that religion finally ceases to be an important factor in all personal, social and political life. According to Ervasti’s analysis (Chapter 12), there are clear differences in religiosity and religious influence between European countries. The analysis lends support to the suggestion that the Nordic countries are among the least religious countries in Europe. Furthermore, religiosity in its traditional forms occupies a comparatively modest role in the Nordic countries as a public issue, although religiosity is still reflected in the personal values of notable parts of the Nordic populations. Even though there are differences across the Nordic countries in some aspects that are examined in this book, it is obvious that the overall commonalities are profound in various areas. Looking into the differences we find that Finland differs a little in that relatively more Finns are suffering from economic hardship, and more Finns are not satisfied with their income than citizens in the other Nordic countries. Also participation in voluntary associations is a little lower and religiosity a little higher in Finland. When it comes to voluntary work, Norway and Sweden distinguish themselves with high levels and Denmark is lagging a little behind. This is also the case for the level of both conventional and unconventional political activism. The level of activism is very high in Iceland followed by Norway and Sweden, with Denmark and Finland lagging a little behind. Trust in politicians and in the political parties is a little lower in Sweden. Furthermore, Sweden is distinguished by having a very low level of xenophobia. Denmark is more pro-European than the other countries. But almost all of these differences are relatively small and do not disturb the impression of remarkable similarities between the Nordic countries. The similarities that we find are not only reserved for issues related to the welfare state, but also lie in areas that were less directly associated with the welfare state.

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IS THERE A FUTURE FOR THE NORDIC MODEL? This book has dealt explicitly with the attitudes and behaviour of the people in the Nordic countries in a European comparative context. We have shown that even though there are differences between the Nordic countries, the all-embracing impression is that the similarities between the people of the Nordic countries can be explained by similarities in institutional contexts. The existence of the institutional model and its existence in the minds and behaviour of the people at a specific moment in time does not guarantee its survival in times of dramatic change, like the expansion of the EU, pressure from the 1990s recession, the increasing heterogeneity of populations and economic globalization. It is logically impossible to counter the argument that future changes will thwart Nordic exceptionalism, but the combination of the specific institutional setting with its public support makes a strong argument against the disappearance of the model in the near future. The historical track record of the Nordic model and Nordic exceptionalism is of importance. Even though many political decisions and institutional developments may be a contingent result of specific actors, they tend to become stable over time. This path dependency of any political policy, institution and similar makes any decision making that challenges the current position extremely difficult to initiate. Pierson (2000) explains this in terms of increasing returns, or, in other words, that the probability of continuing on the same path increases over time as the relative costs of changing paths increases. It simply becomes too expensive to change to another path. The path dependency argument does, however, not imply that single institutions or the sum of institutions and their interactions are deterministic. One reason for changes to occur is as a result of exogenous shocks. Examples of exogenous shocks are environmental (in a broad sense) changes, balances of social power and unanticipated institutional effects (Pierson 2001). In spite of exogenous shocks like the pressures from a globalized economy and changes in the political decision-making process, the Nordic model has prevailed. The severe recession during the early 1990s placed tremendous pressure on the Nordic model, but did not cause it to wither away. Policies and institutions within the four examined countries have changed and continue to do so in an incremental way. An example of change resulting from exogenous shock is the change in pension systems in Sweden. Population changes, such as increasing life expectancy and declining birth rates, led to a situation where a declining number of employed people had to provide for an increasing number of retired people. This is an equation that could not be met within the existing retirement scheme

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and therefore it had to be substantially revised into a system that cost less but also became less beneficial for the individual. Notwithstanding such changes, the pillars of the Nordic model, like the universal welfare state, the centralized social models, active labour market policies and the collective agreements of social regulations, tend to remain intact. The exogenous shock argument should not be interpreted in such a way as to insinuate that all institutional changes happen in a revolutionary way wherein one institutional setting is replaced by another at a certain point in time. It should be interpreted to mean that external forces apply pressure on a particular institutional setting to change in an incremental way. Even though we are continuously witnessing such changes they have so far tended to follow the main path of the Nordic model rather than any substantial diversions from it. Pressure for institutional change is clearly not only a process of external pressure on existing institutions from above. It is highly dependent on benevolent public opinion, which has been shown, throughout this book, to be very persistent. The thermostatical model assumes that public opinion reacts to political policy changes in a predictable way; if the politicians spend more, the public want less spending and vice versa (Soroka and Wlezien 2005). Thinking in terms of this reciprocal model implies that any fundamental changes in the Nordic model or public opinion will not happen overnight as any changes are bound to be taken in small steps. The public support for the Nordic model makes it very resistant towards changes. It is not only the public support for the constituent parts of the model in itself that is of importance for its persistence, but also the multidimensionality of the Nordic exceptionalism that goes beyond the support for the welfare state, which makes the Nordic exceptionalism more resistant to changes as it has more anchor points to rest on. Changes in one area may spill over to other areas, but they can also work as protection against more profound changes. The scope of similarities across the Nordic countries and differences in relation to the rest of Europe in the multitude of areas covered in this book makes it obvious that the Nordic model has not disappeared in the minds of the people regardless of external and internal pressure. People continue to support the constituent parts of the model and are affected by the institutional contexts in which they live their lives. Thinking in terms of feedback effects where institutions affect public attitudes and behaviour, which, in turn, affects institutions, it becomes obvious that there are no immanent threats to the Nordic model of society at the present time. External pressure and the risks of exogenous shock clearly exist, but any change in the model has to be taken in incremental steps as long as the model continues to exist in the minds of the people.

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WHERE DOES THE ROAD END? A great deal of ink has been spilled on trying to cluster different welfare states into regime typologies. With their departure points in these regimes researchers have shown how institutional variation across these regimes structures people’s attitudes and behaviour as well as limiting their cognition. In many ways this book has followed this road, but with a difference: we have tried to expand the scope of the established regimes. We have tried to show that the institutional similarities within a certain regime stretch far beyond the limitations of the welfare state itself and that this has an impact not only on people’s attitudes and behaviour related to the welfare state, but also on various other areas of social life. The latter is one of the reasons why the regimes are so persistent regardless of external and internal threats in the form of changes in levels of decision making and increasing heterogeneity. We have only given an initial hint of the various impacts that the multidimensionality of the welfare state regimes have on social life for people in Europe. We can see three important areas in which future research can expand on what we have achieved. First, we clearly need, as has been tentatively shown in this book, to take a larger perspective on how a broad range of attitudes and behaviour are structured across various regimes. The welfare state and gender regimes structure attitudes and behaviour related to the welfare state and gender issues respectively, but they also structure other attitudes and behaviour that is not linked in a direct or explicit way to these regimes. The institutional setting of regimes does structure social life in a much more profound way. This is in no way a new discovery or insight, but much existing empirical research is limited by a too narrow scope on institutional effects on attitudes and behaviour. The second area, which is related to the first, involves the need for more complex models that can tie together institutional variation across policy areas in order to examine how they interact. At present much of the existing research tends to focus on one specific institutional setting, which may or may not vary across countries, in examining how this setting affects attitudes and behaviour. We need models that can go beyond this limitation in order to examine how different institutional settings in different areas interact in different countries to produce unexpected outcomes. Third, we need more longitudinal research in order to enable us to secure casual mechanisms between institutions on the one hand and attitudes and behaviour on the other. This is the key that enables the development of models that can, with improved accuracy, describe not only the relation between institutions and individual attitudes and behaviour, but can also predict the outcome of changing policies and contexts. Everyone

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acknowledges the feedback effects across levels, but we are, at the same time, still fumbling in the dark as we try to come to terms with such feedback effects. With the ever-expanding access to high quality individual data in combination with the harmonization of institutional data across countries, the future looks bright for an improved understanding of how multifaceted institutional settings affect the lives of people and how they in turn contribute to push institutional settings into new directions. We have only witnessed the beginning.

REFERENCES Pierson, Paul (2000), ‘Increasing returns, path dependence, and the study of politics’, American Political Science Review, 94 (2), 251–67. Pierson, Paul (2001), The New Politics of the Welfare State, Oxford and New York: Oxford University Press. Soroka, Stuart N. and C. Wlezien (2005), ‘Opinion–policy dynamics: Public preferences and public expenditure in the United Kingdom’, British Journal of Political Science, 35, 665–89.

Appendix: data source and statistical methods Mikael Hjerm and Kristen Ringdal The data source for this book is the European Social Survey (ESS). A short description of the ESS is given below. All empirical chapters employ a comparative perspective. There are a number of pitfalls in comparative research in general, and in comparative survey analysis in particular, which are reviewed below. The empirical analyses are based on a range of statistical techniques. The most common ones are briefly described here: factor analysis, multiple regression analysis, logistic regression analysis and multilevel analysis.

THE EUROPEAN SOCIAL SURVEY The European Social Survey (ESS) is a comparative attitude and behavioural survey conducted in more than 30 European countries. It is a new, conceptually well-anchored and methodologically rigorous survey that aims to pioneer a standard of methodology for cross-national attitude surveys that only the best national studies usually aspire to. The ESS intends to measure changing social attitudes and values in Europe. The survey consists of two parts: one core module that contains approximately 200 items and two rotating modules that contain about 50 items each. ESS is the result of a scientific mustering of strength unparalleled in the history of survey research. The development of the core module started four years before ESS1. Experts from various fields contributed with background reports within their various areas of expertise. These reports were evaluated by experts and the central project coordinators and formed the basis for the development of the test survey that was undertaken in Britain and The Netherlands during 2002. The fixed module was replicated in ESS2 and ESS3 and the intent is that this will continue every second year. The content of the fixed module is key repeated questions to measure change and persistence in a range of social and demographic characteristics, attitudes and behaviour patterns. The core contains questions on occupation 262

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and social structure, social exclusion, religious affiliation and identity, political trust, party affiliation, multilevel governance and voting behaviour, media consumption and value orientations. The rotating modules are developed by multinational research teams selected in a peer review process. The development of the rotating modules is continuously discussed with the national coordinators, expert committees and the central coordination team of ESS. These rotating modules are also pre-tested before becoming a part of an ESS survey. In 2002, these modules dealt with ‘citizenship, involvement and democracy’, and ‘immigration’. In 2004 three rotating modules covered family and work, health and medical services, and economic morality. In addition to the hour-long face-to-face interview questionnaire, a short self-completion questionnaire enables the inclusion of a scale on ‘basic human values’, plus a number of methodological test questions designed to quantify the reliability and validity of certain measures in the interview. An overview of the countries that have participated in the 2002 and 2004 European Social Survey is found in Table A1. The table also shows the net number of interviews in each country. ESS does set a new standard in producing high quality comparative survey data. This is achieved through a never-before witnessed level of standardization in all areas like translation of questionnaires, sampling and data collection. Combined with the development of new questionnaire items, quality checks and documentation, ESS is truly a pioneering project that will set the standard not only for comparative surveys but for all survey data collection for a long time to come. More thorough descriptions of the European Social Survey are found at the home page of the project: www.europeansocialsurvey.org/.

PITFALLS OF COMPARATIVE RESEARCH Comparative research based on surveys data encounters two sets of methodological problems. The first one is to develop measures that are strictly comparable so that observed country differences reflect real differences among the countries. The second is the problem of causal inferences from comparative research, where the small number of countries is one of the problems. Context Dependency and Comparability ESS suffers from problems that all comparative survey research suffers from. The most important problem is context dependency. Context dependency

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Table A1 The number of completed interviews in the countries participating in the European Social Survey, 2002 and 2004 Country

2002

2004

AT BE CH CZ DE DK EE ES FI FR GB GR HU IE IL IS IT LU NL NO PL PT SE SI SK UA

2257 1899 2040 1360 2919 1506 – 1729 2000 1503 2052 2566 1685 2046 2499 – 1207 1552 2364 2036 2110 1511 1999 1519 – –

2256 1778 2141 3026 2870 1487 1989 1663 2022 1806 1897 2406 1498 2286 – 579 – 1635 1881 1760 1716 2052 1948 1442 1512 2031

42359 22

45681 24

Austria Belgium Switzerland Czech Republic Germany Denmark Estonia Spain Finland France United Kingdom Greece Hungary Ireland Israela Iceland Italyb Luxembourg Netherlands Norway Poland Portugal Sweden Slovenia Slovakia Ukraine

Number of interviews Number of countries

Notes: a Israel is not included in the empirical chapters of this book. b The fieldwork in Italy started too late for inclusion in our analyses based on the 2004 survey.

problems do arise in national surveys too, where certain topics or phraseologies may be more relevant for certain parts of the population than for others, but are greatly magnified when contemplating a diverse multinational survey. Can the same question on, say, social exclusion be asked of a small farmer in a relatively poor country and of a stockbroker in a rich country? Do questions about confidence in multilevel governance have

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the same meaning for inhabitants of EU countries as for people from Switzerland, Hungary and Turkey? The task of the survey measurements is to discover and calibrate crosscultural and cross-national differences in people’s responses and to ensure that the content of the questions is kept as constant as possible between respondents. The problem, however, is that there is no easy way of guaranteeing such equivalence of meaning, especially in cross-national surveys where between-country variance is large. The word ‘especially’ in that sentence is important, because, as we have noted, these problems are by no means confined to cross-national surveys. Almost all surveys are, to varying degrees, cross-cultural; cross-national surveys tend merely to be more so. The conflict arises acutely when the ‘best’ cross-national measure nationally for a particular concept seems to be different from the ‘best’ national measure of the same concept. We are not here referring to the added problem of lexical equivalence between different languages, just to the problem of different cultural constructions of the same basic concept. Suffice it to say that the approach in the ESS is, wherever possible, to rely on the best cross-national measure we can come up with. A more thorough description of measurement problems in the ESS is found in a book edited by Jowell et al. (2007). In the ESS a set of common quality criteria have been introduced to maximize the comparability of the data. These criteria cover common specifications for translation, sampling, target response rate and fieldwork, and for variable definitions and data cleaning. Translation Translation is perhaps the most important key to comparability. The translation instructions require that the following five-step procedure (TRAPD) is followed: Translation, Review, Adjudication, Pre-testing and Documentation. The first step is two independent translations from the English source questionnaire. These translations are reviewed by a third person and adjudicated by the reviewer or a fourth person. The translation is then pre-tested in a pilot study before final adjustments are made. The final step is documentation of the translation process. Sampling The sample design for the ESS should be the best probability sample design that is possible in each country. It is essential to find a suitable, frequently updated frame for the selection of individuals, households or addresses, preferably a population register. All details of the design, such as number of primary sampling units, mean cluster size and stratification variables

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have to be approved by a sampling expert appointed by the ESS before the sampling process starts. The minimum effective sample size for most countries is 1500. All sampling procedures and sampling frames are specified in detail and monitored by the ESS central coordination team. Response rate The goal is a response rate of 70 per cent or more to minimize non-response bias. In practice, this goal is only reached for a few countries, but fieldwork procedures including following up non-respondents is developed to enhance the response rate. Moreover, response rates are high in the ESS compared with other similar national or international surveys. Fieldwork The mode is face-to-face interviews in all countries. The data collection is preceded by national test surveys in order to secure translations, questionnaires and programming. Factors like the amount and timing of contact attempts and strategies for refusal conversion are examples of standardized and documented issues within the ESS. Variable definitions and data cleaning Post-handling of data is done in each country in accordance with standardized modules. This includes, for example, the coding of occupations according to ISCO88 and standardizing levels of education in accordance with the ESS standard. The finalized data files are then quality controlled before delivery to Norsk Samfunnsvitenskapelig the Norwegian Social Sciences Data Services (NSD). NSD carries out the final quality control with specially designed software combined with manual checking before data are made public. The Problem of Causal Inferences The main problems in cross-national descriptions are cultural bias and translation problems. Causal inferences based on differences among the countries raise additional problems such as the comparability of countries, the small-N problem, and the endogeneity problem. The comparability of the countries First, we may ask whether the sample of countries, which includes Luxembourg and Iceland alongside Germany and France, is too heterogeneous for a meaningful statistical analysis. The answer to this question depends on the researcher’s perspective and no general answer may be given.

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A second problem with countries as units of analysis is within-country heterogeneity. Some countries are homogeneous, others are more heterogeneous. An example of the latter is the huge differences in standard of living between Northern and Southern regions in Italy. Therefore, characterizing Italy by one number on a variable such as the gross domestic product per capita may not adequately describe either part of Italy. A possible solution to this problem, which is not pursued in this book, is to disaggregate countries into regions. The small-N problem Although the ESS is a big survey with more than 40 000 interviews in each round, the small-N problem is still relevant because of the low number of countries, 20–25. The number of countries is critical in testing relationships involving country level variables. The low number of countries puts heavy restrictions on the number of country characteristics that may be used in the analyses. The low number of countries also makes it difficult to attain statistical significance for country level explanatory variables, especially if the effects are of medium or small strength. Another problem that stems from statistical analysis of small samples is the inability to test for causal mechanisms. The ESS may make precise inferences regarding country differences in levels of variables or correlations but the mechanisms creating these observed differences may be very difficult to establish in a quantitative analysis. The endogeneity problem: almost everything is related Many potential explanatory variables (X) at the country level are correlated. This makes it difficult to separate their effects. An example in this book is that our country classification in welfare regimes is correlated with economic development. In multiple regression analysis strong correlations among explanatory variables creates multicolinearity. The endogeneity problem makes causal inferences even more problematic as potential causes (X) and effects (Y) may show reverse causality; that is, Y may also affect X either simultaneously or in a process unfolding over time. Social capital may help to create well-functioning institutions and in turn the output from the institutions may increase trust and cooperation and thus further increase social capital. Welfare regimes may help to mould the attitudes of the people but these attitudes may also induce change in the welfare regimes. Such problems create difficult obstacles for causal analysis in comparative studies of countries (Franzese 2007; Przeworski 2007).

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STATISTICAL TECHNIQUES Factor Analysis (Explorative) Factor analysis is a statistical technique that aims to explain variability among observed random variables in terms of fewer observed random variables called factors. It is the orderly simplification of several interrelated measures. Factor analysis was developed by psychologists exploring different forms of intelligence and intellectual abilities. The main question was if there is one distinct form of intelligence or if there are more than one type. Say we have the test scores from an intelligence test for 1000 individuals. The test is divided into six parts so that we have scores for all parts for all individuals. If there is only one form of intelligence we would expect an individual to score similarly on all parts, but if we expect two different forms of intelligence (e.g. verbal and mathematical) we expect people to score differently on different parts of the test. One person can have a high score on the parts related to verbal intelligence but a low score on the parts that are related to mathematical intelligence. The aim of factor analysis (explorative) is to find such patterns.

MULTIPLE REGRESSION ANALYSIS The aim is to analyse the linear functional relationship between one continuous dependent variable (Y) and one or more explanatory variables (X). The multiple regression model for the population is expressed in the following equation where the subscripts for the individuals have been omitted: Yi  0  1X1i  2X2i  …  KXKi  ei The regression constant, 0 and the regression coefficients are estimated by means of ordinary least squares. This implies finding the values of the coefficients that minimize the error term e, which is the vertical distance from each y-value and the regression line. The regression constant may be interpreted as the predicted value of Y when all explanatory variables in the equation take the value of zero. The regression coefficient shows the change in Y resulting from a unit of measurement change in Xj controlling for the other x-variables in the equation. Logistic Regression Analysis Let Y be variable with the values 1 and 0 with the probabilities p and 1 p. The linear probability model may then be defined:

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Yi  0  1X1i  2X2i  …  KXKi  ei This model may have predicted probabilities outside the 0–1 limits and the dependent variable is clearly not continuous. To constrain the predictions to be within those limits, we first transform the probabilities into the odds that Y takes the value of 1 rather than 0: p Odds  1  p The log of the odds, the logit, is continuous with no lower or upper limits. This suggests a model that is linear in the logit:

 

pi logiti  log 1  p  0j  1 X1i  2X2i  ...  K Xki i This model is called the binary logit model, the binary logistic regression model, or just the binary regression model (Long and Freese 2006). The antilogarithm of the logistic regression coefficients may be interpreted as odds ratios (OR). For 0–1 variables, such as gender, the antilogarithm is the estimate of the odds ratio between men and women; that is, the odds for men divided by the odds for women (or vice versa). For continuous explanatory X, the antilogarithm is the odds ratio between persons with one unit of measurement difference on X. The estimated logistic regression equation may also be used to calculated predicted logits for specific groups, such as men and women, and transform the result back into the probability scale according to this formula: p

1 1  e  logit

Since the regression coefficients are hard to interpret except for their sign and statistical significance, interpretations are most often based on the estimates transformed into odds ratios and probabilities. Multilevel Models In several chapters the statistical analyses are based on multilevel models (Hox 2002; Raudenbush and Bryk 2002; Goldstein 2003). Several special purpose computer programs have been developed for multilevel analysis. The most familiar ones are MLwiN and HLM. Some multilevel models may also be estimated in standard statistical packages such as SAS, SPSS and

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STATA. In multilevel analysis the units of analysis at lower levels are nested within units at higher levels. In our case individuals (level 1) are nested within countries (level 2). Multilevel models enable us to split the variance in the dependent variables between levels, and to estimate effects of explanatory variables at all levels, with correct estimates of standard errors. The multilevel models used in this book are variance component models with random intercepts. The model may be expressed in two ways: with equations for each level or in one equation for both levels. Both ways of expressing the model are useful. Let us start with the separate equations for each level in a variance component model with only one explanatory variable. The level 1 model: Yij  0j  1 Xi  eij The level 2 model: 0j = 0  uoj The dependent variable in the first equation, Y, has two subscripts, i for individuals and j for countries. The j subscript on the regression constant indicates that it may vary among countries, whereas the regression coefficient is assumed to be common for all countries. The individual error term eij has subscripts for both levels. In the second, country level equations, the 20 or so countries are the units of analysis. The dependent variable is the regression constant for the level 1 equation. 0, the regression constant in the level 2 equation, is the weighted average regression constant among the countries, and uoj captures the deviation from the weighted average regression constant for country j. The two-level model may also be captured by one equation just by substituting 0j in the first equation with the right hand side of the second equation: Yij  0  1 Xi  uj eij The basic assumptions are: eij is N (0, 2e ), eij may be correlated u0j is N  (0, 2u0 ), COV (u0j, eij )  0 The variance in Y consists of two components: var(Yij)  2u0  2e The intra-class correlation, or the variance partition coefficient, measures the proportion of the variance in Y that is a result of between-country variation.

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2u0  2e

2u0

Computing the intra-class correlation is problematic in binary logistic multilevel models, because the level 1 variance cannot be estimated directly. The most common solution is to use the latent variable approach by assuming the observed values (0 and 1) as arising from an underlying continuous variable with logistic distribution. The variance of a standard logistic distribution is 2 / 33.29 is then used as the estimate of the level 1 variance (Snijders and Bosker 1999). The basic multilevel model may be expanded by adding more explanatory variables at the individual level and at the country level. The latter expansion changes the equation for level 2: 0j 0 0z Zj u0j The regression coefficient shows the effect of the country level explanatory variable Z on the intercept.

REFERENCES Franzese, Robert J.J. (2007), ‘Multicausality, context-conditionality, and endogeneity’, in Carles Boix and Susan Stokes (eds), Oxford Handbook of Comparative Politics, Oxford: Oxford University Press, pp. 27–72. Goldstein, Harvey (2003), Multilevel Statistical Models, London: Arnold. Hox, Joop (2002), Multilevel Analysis. Techniques and Applications, London: Lawrence Erlbaum. Jowell, Roger, Carolyn Roberts, Rory Fitzgerald and Eva Gillian (eds) (2007), Measuring Attitudes Cross-nationally: Lessons from the European Social Survey, London: Sage. Long, J. Scott and Jeremy Freese (2006), Regression Models for Categorical Dependent Variables using Stata, College Station, TX: Stata Press. Przeworski, A. (2007), ‘Is the science of comparative politics possible?’, in Carles Boix and Susan Stokes (eds), Oxford Handbook of Comparative Politics, Oxford: Oxford University Press, pp. 147–71. Raudenbush, Stephen W. and Anthony S. Bryk (2002), Hierarchical Linear Models: Applications and Data Analysis Methods, Thousand Oaks, CA: Sage. Snijders, Tom A.B. and Roel J. Bosker (1999), Multilevel Analysis, London: Sage.

Index Aardal, Bernt 133, 134 Åberg, Rune 23 Abromeit, Heidrun 88 AccountAbility index 15 age consumer victims 228 and health and happiness 60 and job satisfaction 181 and political activism 125–6, 128 and religiosity 236 and trust in political institutions 147 and xenophobia 195 Ala-Mursula, Leena 179 Alcock, Pete 32 Aldecoa, Fransisco 87 Alesina, Alberto 190, 192 Alestalo, Matti 3, 4 Allan, J. 26 Allardt, Erik 8, 23 Allport, Gordon W. 195 Almond, Gabriel A. 113 Altemeyer, Bob 195 Amin, Ash 87 Andersen, Jørgen Goul 172 Anderson, Christopher J. 91, 134, 135 Anderson, James 87 Andreß, Hans-Jürgen 22 Andrews, F.M. 48 Andvig, Jens Christopher 209 Anglo-Saxon/liberal regime/countries bribery 223 consumer victimization 221 corruption 211 definitions 192 division of work among couples 155–6 health and happiness 61 insecurity 40 trust in political institutions 149 voluntary organizations 79 xenophobia 197 see also Ireland; UK

Aristotle 22 Arthaud-Day, M.L. 48 Arts, W.A. 6, 50, 139, 210 Atkinson, Anthony 22 Austria personal safety 32 political activism 117 poor health and unhappiness 55 voluntary organizations’ membership 72 work arrangements 176 xenophobia 203 Bäckström, Anders 232 bad jobs, definitions of 178–9 Bahr, Stephen J. 153 Baldwin, Peter 5 Barbieri, Paolo 79 Barnes, Samuel H. 112, 113 Bartley, M. 49 Bauer, Thomas 190 Baxter, Janeen 153 Beck, Ulrich 42 Belgium level of last resort social benefits 27 political activism 117 preferred level of government 94 religiosity 233 work arrangements 176 ‘Beliefs in Government’ project (BIG) 133 Belous, Richard 172 Benyamini, Y. 52 Berg, Linda 89 Berger, Peter 238 Berglund, Frode 128 Bertola, Giuseppe 175 BIG (‘Beliefs in Government’ project) 133 Biswas-Diener, R. 48 Blair, Sampson L. 153, 154 Blais, André 110 273

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Blumer, Herbert 189 Bobo, Lawrence 189, 190 bonding (social capital) 66 Booth, Alison L. 173, 177 Bosker, Roel J. 97, 271 Bourdieu, Pierre 65 Braverman, Harry 173 Brehm, John 79 Brewer, Marilynn 196 bribery 218, 223 bridging (social capital) 66 Brinegar, Adam P. 89 Bruce, Steve 235 Bruter, Michael 90 Bryk, Anthony S. 269 Buch, R. 91 Budge, Ian 91, 96 Burton, J. 91 Campbell, A. 48 Campbell, Robert A. 235 Carey, Sean 89, 91 Cassel, J. 49 Castles, Francis G. 5 Catholicism 235 Catterberg, G. 110, 111, 112, 114 Caul, M. 110 causal inferences 266 cause-oriented repertoires 115 Cazes, Sandrine 176 Cebrian, Immalulada 176 childcare, and labour force participation 6–7 church attendance 233 citizen-oriented actions 115 Citrin, Jack 89, 190 Cobb, S. 49 Coenders, Marcel 194 Cohen, Lawrence E. 211, 212 Coleman, James 65 collectivist concepts 22–3 comparative research, pitfalls of 263–8 conservative regime 192, 202 consumer victimization country differences 210, 218, 227 data 213–15 definitions 207–8 individual differences 211–12 multilevel analysis 219–23 context dependency 263–5

Continental regime/countries bribery 223 corruption 211 division of work among couples 155 generalized trust 80 health and happiness 61 insecurity 42 trust in political institutions 149 voluntary organizations 79 Cook, Karen 67 corporatism 3, 9, 11 corruption country level studies 208–9 definitions 207 European country differences 210–11 individual differences 211–12, 215 within-country studies 209–10 Corruption Perception Index (CPI) 15 cultural threats, perceived, from immigration 189–90 Curtis, J.E. 235 customer victimization, see consumer victimization Czech Republic economic morality 218–19 religiosity 233 work arrangements 176 Dalton, Russell J. 92, 110, 111, 112, 133 data cleaning, in ESS 266 democratic crisis scenario 110–11 democratic participation 12 Dempsey, Kenneth C. 153 Denmark economic morality 218 immigration experiences 188 job quality 180 level of last resort social benefits 27 political activism 117–18, 120, 253, 257 political institutions, trust in 134, 140, 142, 254 poor health and unhappiness 56 preferred level of government 94–5 public social spending 26 relationship with EU 86, 132 religiosity 231

Index voluntary organizations’ membership 72, 257 xenophobia 203 Diener, E. 48, 50, 53 division of work among couples disagreements over 158–9 literature 152–6 Nordic countries 155, 159, 162, 254–5 overview 169–70 study method 156–8 study results 158–69 divorce, and religiosity 245 Dixon, Jeffrey C. 190 Dobbelaere, Karel 231, 235 Doeringer, Peter B. 178 Dollar, Davis 209 dual wage-earner model, and poverty 7 Dumont, Jean-Christophe 193 Duncan, Simon 155 Ease of Doing Business Index (World Bank) 14–15 Eastern European regime/countries bribery 223 consumer victimization 221 corruption 211 division of work among couples 155–6, 162 health and happiness 61 insecurity 40 job quality 180 political activism 128 political background 114 subjective poverty 42 trust in political institutions 149 voluntary organizations 79 work arrangements 176 xenophobia 197, 202–3 Easton, David 132 economic behaviour 207–8; see also consumer victimization economic hardship 31 economic morality country differences 215–19, 256 data 212–15 definitions 207 Nordic countries 211, 223–4, 227, 257 offenders 223–6

275

overview 207–8, 226–9 see also corruption economic norms 207, 227 economic offences 227 economic trust 227 education levels and health and happiness 60 and political activism 126, 128 and religiosity 237–8 and xenophobia 194 Eichenberg, Richard 92 Eisinga, Rob 195 endogeneity problem 267 Erikson, Robert 23, 31, 49, 53, 116, 215 Ervasti, Heikki 5, 66, 174 Espenshade, Thomas J. 189 Esping-Andersen, Gøsta 4, 5, 22, 90, 155, 173, 174, 175, 176 ESS (European Social Survey) 24–5, 262–3 Ester, Peter 233 Estonia political activism 117 poor health and unhappiness 56 religiosity 233 work arrangements 176 EU impact of 11, 43–4 see also MLG (multilevel governance), support for European level decision making study European Social Survey (ESS) 24–5, 262–3 EVS (European Values Study) 133 exclusive social capital 66 factor analysis 268 Felson, M. 211, 212 Ferrera, Maurizio 26 Fetzer, Joel S. 189 fieldwork, in ESS 266 Finke, Rofer 232 Finland division of work among couples 163 economic morality 218–19 generalized trust 80 immigration experiences 188

276 level of last resort social benefits 27 political activism 117–18, 120, 253, 257 political institutions, trust in 134, 136, 142, 254 preferred level of government 94, 253 public social spending 26 relationship with EU 86, 132 religiosity 231, 233–5, 246 voluntary organizations’ membership 72, 257 work arrangements 175, 177 xenophobia 203 Fisherl, Cynthia D. 179 flexible work arrangements, see non-standard employment Folk, K. 153 Fossett, Mark 190 Fouarge, D. 172, 173, 175 Fox, G.L. 153 France political activism 118, 120 religiosity 233 work arrangements 176 Franklin, Mark N. 110 Franzese, Robert J.J. 267 Freese, Jeremy 269 French, John R.P. 179 Fritzell, Johan 7, 22, 25, 32 Fuchs, Dieter 133 Fukuyama, Francis 79 Gabel, Matthew J. 88, 103 Gallie, Duncan 173 Gatti, Roberta 209 GDP per capita and health and happiness 50 and poverty 43 Gelissen, J. 6, 50, 139, 210 gender ideology 154–5, 164, 166–7 gender ideology index 157 generalized trust 79 generosity of welfare systems 25–6 Germany political activism 117, 120 preferred level of government 94 voluntary organizations’ membership 72 work arrangements 176

Index Ghent unemployment insurance system 67 Gilens, Martin 190 Giles, Michael 189 Glaeser, Edward L. 190, 192 Glaser, James M. 190 Glass, T.A. 49 global competition, and Nordic societies 13–15 Global Competitiveness Index (World Economic Forum) 14 Goldmann, Kjell 87 Goldstein, Harvey 269 Goldthorpe, John H. 49, 53, 116, 215 Gordon, David 23 Gordon, David M. 178 Granovetter, Mark 5, 49, 66 Gray, Anne 173 Gray, Mark 110 Greece division of work among couples 163 economic morality 218–19 generalized trust 79 political activism 117, 120 political background 113–14 poor health and unhappiness 56 religiosity 233, 246 voluntary organizations’ membership 72 work arrangements 176 Green, Francis 173, 174 Greenstein, Theodore N. 154 group threat theory 189–90 Guillory, C.A. 135 Gutiérrez, P. 90 Gustafsson, Göran 231 Guttman, Robert J. 88 Hall, Peter A. 89 Halman, Loek 233, 239 Hanifan, L.J. 65 Hansen, Kasper M. 91 happiness indicators 51–2 and marital status 49 self-rated happiness, validity as happiness indicator 53 Hay, Colin 91 Hayek, Friedrich 24 Hayes, Bernadette 235, 237, 239

Index HDI (Human Development Index) 14, 50, 61 health indicators 51–2 self-rated health, validity as health indicator 29, 52–3 health and happiness study cross-country differences 55–7 methods 51–4 multivariate analysis 57–61 overview 48–51, 61–2 Heistaro, S. 53 Held, David 87 Hello, Evelyn 194 Hempstead, K. 189 Hernes, Gudmund 194, 195 Hertz, K. 189 Hill, E. Jeffrey 172 Hjerm, Mikael 190, 194 Hochschild, Arlie 154 Holland, political activism 117 Holmberg, Sören 86 Hood, M.V. 190 Hooghe, Liesbet 89, 90, 91, 99, 104 household work, see division of work among couples Hox, Joop 269 Huber, Evelyn 9 Hughes, James 87 Human Development Index (HDI) 14, 50, 61 Hungary economic morality 218 generalized trust 79 political activism 117 poor health and unhappiness 56 preferred level of government 95 voluntary organizations’ membership 72 work arrangements 176 Huseby, Beate 135 Hyyppä, Markku 79 Iannaccone, L.R. 235, 238 Iceland economic morality 218 political activism 117–18, 120, 253, 257 political institutions, trust in 134, 142

277

poor health and unhappiness 56 relationship with EU 132 religiosity 231, 233–4, 246 work arrangements 177 Idler, E.L. 52 immigrants, see xenophobia inclusive social capital 66 individualistic concepts of state/individual relationship 23–4 Inglehart, Ronald 79, 110, 111, 112, 114, 195, 232, 235, 237, 239, 240 insecurity 35, 40, 42 institutions 1–2 Ireland economic morality 218 insecurity 35 loneliness and poverty 34 poor health and unhappiness 55 preferred level of government 95 religiosity 233, 246 work arrangements 175–6 Italy generalized trust 79 political activism 120 poor health and unhappiness 56 religiosity 233, 246 voluntary organizations’ membership 72 xenophobia 203 Jaakkola, Magdalena 195 Jackman, M.R. 194 Jackman, R.W. 208 Jagodzinski, Wolfgang 235 Jensen, Anders Todal 91 Jensen, J.B. 172 Jessor, T. 190 job quality, country differences in 178–80 Johansson, Sten 23 Johnson, M.P. 153, 154 Jolly, S.K. 89 Jowell, Roger 265 Jylhä, M. 53 Kalleberg, Arne L. 172, 177, 178, 181 Kane, E. 153 Kangas, Olli 5, 22, 25, 42, 66, 67 Karasek, Robert A. 178

278 Katzenstein, Peter J. 3 Keating, M. 87 Keefer, P. 79 Khagram, S. 208 Kiecolt, J.K. 190 Kitschelt, Herbert 239 Klingemann, Hans-Dieter 133, 193 Knack, Stephen 79 Knudsen, K. 194, 195 Korpi, Walter 25, 44, 67 Kuhnle, Stein 3, 4 Kumlin, Staffan 68 Kunst, A.E. 48 Kuus, Merje 91 Kvist, Jon 26 Kymlicka, Will 24 Lahelma, E. 29 Lambert, Yves 232 Larsen, Christian A. 68 Lehto, Juhani 7 Lemaitre, Georges 193 Lennon, Clare M. 153 Lewis, Jane 155 liberal regime/countries, see AngloSaxon/liberal regime/countries lifestyle theory 210 Listhaug, Ola 133, 134, 135, 140 Liu, Cong 179 Lodovici, Manuel S. 174, 175 logistic regression analysis 268–9 loneliness 34 Long, J. Scott 269 Loughlin, John 87 Lundberg, Olle 29 Lutheranism 231, 234, 246, 257 Luttmer, Erzo 190 Luxembourg economic morality 219 political activism 117, 120 preferred level of government 94 religiosity 233 voluntary organizations’ membership 72 xenophobia 203 Madeley, John 231 Maître, B. 22, 32 Mäki, J. 79 male breadwinner model 155

Index marital status and happiness 49 as indicator of social support 50, 54 as predictor of religiosity 236 Marks, G. 89, 90, 91, 99, 104 Martinussen, Willy 114 McGovern, Patrick 178, 181 McIntosh, S. 173 McLaren, Lauren M. 89, 190 Mediterranean regime 192; see also Greece; Portugal; Spain Medrano, Juan Díez 90 Meier, Robert F. 211 Melamed, S. 179 men consumer victims 220, 228 generalized trust 81 health and happiness 50, 60–61 political activism 124, 127–8 religiosity 236 trust in political institutions 147 see also division of work among couples; xenophobia, gender Miethe, T.D. 211 Miller, Alan S. 236 Miller, Arthur H. 135 Miller, Norman 196 MLG (multilevel governance) questions posed by 86–8 support for European level decision making study method 92–3 overview 102–3 relevance of contextual effects 96–101 research questions 88–92 results 93–5 Moen, Phyllis 153 Moene, K.O. 209 Montinola, Gabriella R. 208 Morris, I.L. 190 Muffels, R. 172, 173, 175, 176 Muha, M.J. 194 multilevel governance, see MLG multilevel models 269–71 multiple regression analysis 268–71 national identity, and Euro scepticism 89 Near, J.P. 48

Index Nelson, Kenneth 26 Nesporova, Alena 176 Netherlands preferred level of government 94 voluntary organizations’ membership 72 work arrangements 176 New Public Management 11 Newman, Peter 87 Nie, Norman H. 113 Nieuwbeerta, Paul 210, 211 non-standard employment advantages 173 adverse effects 173 country differences in job quality 178–80 country differences in work arrangements 175–7 definitions 172 historical perspective 174 individual work experience 181–4 Nordic countries 255 overview 184–5 perceived job quality 255–6 Nordenmark, M. 154, 156 Nordic model definition 2 effects compared to other regimes 38–44 future of 10–13, 258–9 generalized trust 79 and health and happiness 61, 252 social trust 82–3 uniqueness of 249–57 voluntary organizations’ membership 72, 79 Nordic model welfare state generosity 26 history 5–8 level of last resort social benefits 26–8 universalism 12, 25 Nordic societies consumer victimization 221 division of work among couples 155, 159, 162, 254–5 economic hardship 31 economic morality 211, 223–4, 227, 257 and global competition 13–15

279

insecurity 35 job quality 179–80 non-standard employment 255 overview 3 personal safety 31–2 political background 3–5, 113 poverty 34, 251 preferred level of government 90–91, 94, 103 relationships with EU 86 religiosity 231–3, 257 self-rated health 29 sickness 35 social capital 252 social exclusion 32–4 social interaction 31 trust in political institutions 148–9 welfare state, see Nordic model welfare state work arrangements 175–7 work relations 9–10 xenophobia 197, 202–4, 256 Norris, Pippa 110, 112, 113, 115, 132, 133, 232, 235, 237, 239, 240 Norway economic morality 207, 218 immigration experiences 188 level of last resort social benefits 27 political activism 117–18, 120, 253, 257 political institutions, trust in 134–6, 140, 142 poor health and unhappiness 55 preferred level of government 94, 253 public social spending 26 relationship with EU 86, 132 religiosity 231 voluntary organizations’ membership 72, 257 xenophobia 203 Nozick, Robert 24 Nyman, C. 154 Olesen, Thorsten B. 86 Olsen, Johan P. 132 Olsen, K.M. 172, 177 Olson, Mancur 67 opportunity structure theory 210 opportunity theories 212

280 Orenstein, Mitchell A. 209 Oscarsson, Henrik 86 Østerud, Øyvind 131 Palme, J. 5, 25, 44 pension policies, and poverty 42 Perry-Jenkins, Maureen 153 personal safety 31–2 Peters, Guy B. 87 Pierre, Jon 87 Pierson, Paul 258 Pinquart, M. 49 Piore, Michael J. 178 Poland generalized trust 79 political activism 117, 120 poor health and unhappiness 56 preferred level of government 95 religiosity 233, 246 voluntary organizations’ membership 72 work arrangements 176 political activism and age 125–6, 128 conventional and unconventional 117–21, 124 and economic development 114 education level 126, 128 explanations 113–14 explanatory variables, country level 117, 127, 129 explanatory variables, individual level 116 interpretations of current trends 111–13 measures 115–17 multilevel analysis 121–7 overview 127–9 political articulation, and preferred level of government 90–91, 96–9, 103 political distance 135 political institutions and preferred level of government 89–90, 96, 102–3 trust in and age 147 definitions 132 explanatory variables, country level 139–43, 148–9

Index explanatory variables, individual level 137–9 importance 131 indicators 137 model 135–6 multilevel analysis 143–9 recent research 133–5 political trust 131–2 Portugal economic morality 218–19 political activism 117, 120 political background 113–14 preferred level of government 95 religiosity 233 voluntary organizations’ membership 72 work arrangements 176 post-materialist political activism 111–12 poverty definitions of 22–4 and dual wage-earner model 7 and GDP per capita 43 levels in Europe 34 and pension policies 42 and social exclusion 24 subjectivity 42 Protestantism 208, 231, 235, 240 Przeworski, A. 267 public service provision 7 public social spending 26 public spending 26 public sphere issues, influence of religiosity 239, 241 Putnam, Robert 5, 65, 66, 67, 110, 239 Quality of Life Index (The Economist) 14 Quillian, Lincoln 189, 190 racism 189–90; see also xenophobia Rahn, W. 79 Rasbash, Jon 121 Raudenbush, Stephen W. 269 recommodification 11–12 Regini, M. 173, 174 relative deprivation, theory of 194–5 religiosity consumer victims 220, 228 and corruption 209

Index influence on political/social/moral values 238–45 Nordic countries 231–3, 257 overview 231–3, 245–6 social determinants 233–8 and xenophobia 195 religious markets theory 235, 245 research directions 260–61 research limitations 250–51 response rates, in ESS 266 Ringen, Stein 23 Ritakallio, V.-M. 7, 22, 25, 32, 42 Ritter, Gerhard A. 67 Rose-Ackerman, Susan 208 Rose, Richard 209 Rosenbaum, M. 190 Rosenfield, S. 153 Ross, M.J. 195 Rothstein, B. 67, 68, 89, 90, 190, 191 routine activity theory 211–12 Rydgren, Jens 190 Salomon, J.A. 53 sample design for the ESS 265–6 Sanchez, Laura 153 Scandinavian welfare state, universalism 25–6 Scanzoni, John 153 Scarrow, Susan 110 Scharpf, Fritz 88 Scheepers, P. 68, 189, 190, 194 Schwarz, N. 53 Scruggs, Lyle 26 Sears, David O. 190, 195 secularization theory 232, 235, 238, 245, 257 self-interest, and preferred level of government 91–2 self-rated health, validity as health indicator 29, 52–3 Sen, Amartya 23, 39 shadow economies 209 Sherif, C. 189 Sherif, Muzafer 189 Sides, J. 89 Siune, Karen 86 Skandia 207 Slovakia division of work among couples 163

281

economic morality 218–19 work arrangements 176 Slovenia generalized trust 79 political activism 117 work arrangements 176 small-N problem 267 Smith, A. Wade 190, 194 Smith, Adam 22 Smith, N.J. 91 Snijders, Tom A.B. 97, 271 social capital concept of 65–6 Nordic countries 252 and welfare regimes study data 68–9 generalized trust 79–81 overview 66–8, 81–3 voluntary organizations’ activities analysis 73–9 voluntary organizations’ membership 69–72 social class definitions 49 and health and happiness 60 social exclusion determinants 35–8 in Europe 32–4 and poverty 24 social interaction 31 social status and health and happiness 49 and religiosity 238 social support and health and happiness 60 and well-being 49 sociotropic self-interest, and preferred level of government 91–2, 97, 99, 103 Sorensen, S. 49 Soroka, Stuart N. 259 Southern European regime/countries bribery 223 consumer victimization 221–2 corruption 211 division of work among couples 155, 162–3 generalized trust 79 health and happiness 61 insecurity 40

282

Index

trust in political institutions 149 voluntary organizations 72, 79 Spain division of work among couples 163 political activism 118, 120 political background 113–14 voluntary organizations’ membership 72 work arrangements 176 Spoonley, Paul 173 Stark, R. 232, 235, 236 state, perceptions of 4 Statoil 207 Stephens, John D. 9 Strack, F. 53 Strandh, Mattias 154, 156 strong ties 49 Subramanian, S.V. 49, 50, 51, 52, 58, 62 Svallfors, Stefan 1, 26, 66, 89 Svensson, Jakob 208 Svensson, P. 86 Swamy, Anand 209 Sweden economic morality 207, 218 immigration experiences 188 level of last resort social benefits 27 political activism 117–18, 120, 253, 257 political institutions, trust in 134, 136, 140 preferred level of government 94, 253 public social spending 26 relationship with EU 86, 132 religiosity 231 voluntary organizations’ membership 72, 257 work arrangements 175 xenophobia 202–3, 256–7 Switzerland economic morality 218 political activism 118 poor health and unhappiness 55 work arrangements 176 xenophobia 203 Szreter, Simon 67, 68 taxation, individual rather than family 6

Taylor, Marylee C. 190 Taylor, R.C.R. 89 Thackray, Richard I. 179 Thorsrud, Einar 10 Titmuss, Richard 23 Townsend, Peter 23 translation process 265 Translation, Review, Adjudication, Pre-testing and Documentation (TRAPD procedure) 265 TRAPD procedure (Translation, Review, Adjudication, Pre-testing and Documentation) 265 Treisman, Daniel 208 Treu, T. 174 Triandafyllidou, Anna 91 UK division of work among couples 155 economic morality 218 insecurity 35 loneliness and poverty 34 personal safety 32 political activism 118 preferred level of government 94, 100–101 voluntary organizations’ membership 72 work arrangements 175–6 see also Anglo-Saxon/liberal regime/countries Ukraine economic morality 218–19 political activism 117–18, 120 political institutions, trust in 133 poor health and unhappiness 56–7 work arrangements 176 universalism of welfare systems 25–6 Uusitalo, H. 23, 31 Van der Brug, Wouter 189 Verba, Sidney 113, 114 voluntary organizations activities around 73–9 membership 69–72 Walby, Sylvia 155 Wallace, Claire 176, 177 weak ties 49 Welch, Susan 196

Index welfare 8 welfare state, Nordic societies, see Nordic model welfare state welfare state typology 192 well-being components 23 dimensions 29 and material living conditions 48 measurement 47 and social support 49 Whelan, Christopher 22, 32 Whiteley, Paul 79 Wiberg, M. 134 Wilkie, Jane R. 153 Withey, S.B. 48 Wlezien, C. 259 women consumer victims 220 corruption 209 generalized trust 81 health and happiness 50, 60–61 labour force participation 7, 17, 19, 254 political activism 124, 127–8 religiosity 236 trust in political institutions 147

283

see also division of work among couples; xenophobia, gender work arrangements, country differences in 175–7 work relations, Nordic societies 9–10 World Values Survey (WVS) 133 WVS (World Values Survey) 133 xenophobia age 195 country level determinants 191–3 cultural threats 193 education levels 194 ethnic propinquity 196 gender 194–5 individual level determinants 194–6 overview 188–91, 202–4 political conservatism 195 political orientation 195 religiosity 195 socio-economic threats 192–3 study results 196–202 You, Jong-sung 208 Yu, Y. 153