Skilled Immigrant and Native Workers in the United States: The Economic Competition Debate and Beyond (The New Americans) (Criminal Justice)

The New Americans Recent Immigration and American Society

Edited by Steven J. Gold and Rubén G. Rumbaut

A Series from LFB Scholarly

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Skilled Immigrant and Native Workers in the United States The Economic Competition Debate and Beyond

Jeanne Batalova

LFB Scholarly Publishing LLC New York 2006

Copyright © 2006 by LFB Scholarly Publishing LLC All rights reserved. Library of Congress Cataloging-in-Publication Data Batalova, Jeanne, 1974Skilled immigrant and native workers in the United States : the economic competition debate and beyond / Jeanne Batalova. p. cm. -- (The new Americans) Includes bibliographical references and index. ISBN 1-59332-136-8 (alk. paper) 1. United States--Emigration and immigration--Economic aspects. 2. Immigrants--United States. 3. Skilled labor--United States. 4. Women immigrants--United States. 5. Professional employees. I. Title. HD8081.A5B38 2006 331.6'20973--dc22 2006021761

ISBN 1-59332-136-8 Printed on acid-free 250-year-life paper. Manufactured in the United States of America.

Table of Contents

Acknowledgements

vii

1. “Brain Gain” What’s in the Name? Opportunities and Challenges of Highly Skilled Immigration

1

2. The Historical Treatment of Skilled Immigrants in US Immigration Legislation

9

3. Definitions and Demographics: Highly Skilled Workers in the United States

37

4. The Tipping Point of the Brain Gain: Job Context and Earnings Competition with Natives

65

5. Looking Through the Nativity-Gender Lenses: Earnings of Immigrant and Native Women in Highly Skilled Jobs

95

6. “End Restriction! Recruit!” or “End Recruitment! Restrict!” Further Thoughts on Highly Skilled Immigration in the 21st Century United States

121

Appendices

129

Notes

147

References

151

Index

175 v

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Acknowledgements

I would like to express my immense gratitude to Frank D. Bean, Judith Treas, Philip Cohen, and Rubén G. Rumbaut who provided me with their invaluable guidance and great mentorship during the conception, development, and implementation, and writing of this book. I also want to thank other members of the Sociology Department at UC Irvine who read and commented on my work along the way. I am grateful to UC Irvine’s School of Social Sciences and Sociology Department and the National Science Foundation, which provided me with grants and research fellowships. My thanks go to Rubén G. Rumbaut for encouraging me to publish in this series, Leo F. Balk for his graciousness and patience, and Aaron Erlich for his great help with editing. Finally, I would like to thank my family, friends, and colleagues at the Migration Policy Institute for their support and encouragement.

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CHAPTER 1

“Brain Gain” What’s in the Name? Opportunities and Challenges of Highly Skilled Immigration

Globalization not only intensifies cross-national movement of goods and financial capital but also accelerates international migration of a large number of people. According to United Nations (UN) estimates, more than 175 million people – who constitute about three percent of the world’s population – are living outside their country of birth (United Nations 2002). This number includes both temporary and permanent migrants, of which professional and skilled workers constitute a significant portion. The United States has long been regarded as a magnet for foreign talent, and this remains true today. In 2000, of all skilled immigrants living within the thirty member countries of the Organization for Economic Co-operation and Development (OECD), about half lived in the United States (Docquier and Rapoport 2004). Similarly, 30 percent of the 2.1 million foreign students who studied in OECD countries in 2003 chose to attend university in the United States (OECD 2005). It is certain that the United States is not the only country in the world seeking to attract the best and the brightest. Australia, Canada, South Korea, and many European countries have also been actively recruiting foreign talent in order to alleviate labor shortages in skill-intensive sectors of their economies, stimulate research and development, and expand business into foreign markets (Mclaughlan and Salt 2002; OECD 2002; Smith and Favell 2006). 1

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These aggressive recruitment efforts, however, have provoked criticism both at home and abroad. The increased emigration of science and technology workers, health practitioners, and educators from Africa, Asia, and Latin America to developed countries in the 1970s sparked debates about “brain drain” – the loss of skilled workers as a result of emigration – and its impacts on growth and development in developing and underdeveloped countries.1 In turn, this led government officials in developing countries as well as some policy experts and academics in the West to question the sensitivity of rich countries’ policies that encouraged highly skilled emigration (Docquier and Rapoport 2004; Kapur and McHale 2005; Lowell 2002; Lowell, Findlay, and Stewart 2004). Since the early 1990s, however, the scope of this debate has expanded beyond countries of the Global South. Developed countries such as Canada, the United Kingdom, Ireland, and Germany are facing the potential loss of their own talented workers and students to other countries, most notably to the United States (Hansen 2004; Iqbal 2001; Mahroum 1998). Within the United States, the issue of “brain gain” – a permanent or temporary acquisition of skilled foreigners – has been far from uncontroversial. Some researchers and professional science and engineering organizations object strongly to the increase in permanent and, especially, temporary skilled migration on the grounds that these immigrants foster unfavorable competition with domestic skilled and professional workers (Borjas 2003; Institute for Electrical and Electronics Engineers 2003; Lowell 1999; North 1995). Whereas efforts to explain the effects brought by low-skilled foreign-born workers have generated ample research (Bean and BellRose 1999; Borjas 1990; Borjas 1994; Catanzarite 1998; Hamermesh and Bean 1998; Ong and Valenzuela 1996), the impact of highly skilled foreign born, who constitute about a third of the immigrants coming to the United States, has garnered relatively little attention (Cornelius, Espenshade, and Salehyan 2001; Lowell 1999). This study adds to the burgeoning literature on highly skilled and professional immigrants by focusing on their economic impacts in the context of the US labor market. In this research, I addresses concerns that skilled immigration measures passed by Congress since 1990 have had a negative impact on earnings of US-born skilled workers and professionals. While the

“Brain Gain” What’s in the Name?

3

Bureau of Labor Statistics (BLS) projects that demand for an educated and skilled workforce in the US economy will increase over the next ten to twenty years, the country’s education system is lagging behind in terms of producing a sufficient number of native specialists (Hecker 2001; Horrigan 2004; Lopez 2003). Given these trends, the need for foreign talent by the knowledge-based American economy will only continue to grow and is likely to intensify heated debates among businesses, government, and labor regarding the necessity of skilled foreigners (Ellwood 2001). Policymakers, therefore, must understand the impact of skilled immigration on labor market outcomes of all American workers in order to design effective immigration and labor market policies. Global competition for skilled workers makes this need for effective policies even more urgent. My study expands upon past research in a number of ways. First, I use the most recent US Census data, which take into account changes that have occurred after the 1990 Immigration Act and the economic boom of the 1990s. Second, I provide a detailed demographic, social, and economic profile of the highly skilled labor force describing similarities and differences among native, early immigrant, and recent immigrant workers. Unlike previous studies, I distinguish between immigrants by the amount of time they have spent in the United States. I analytically separate earlier and new arrivals because they differ on a number of accounts, and treating all foreign born as one group masks diversity in immigrants’ experiences and outcomes. Third, I employ hierarchical linear modeling (HLM) to examine the relationship between the greater presence of skilled foreign born and the earnings of native and immigrant workers in skilled jobs. The HLM multi-level methodology provides a more robust test of such relationships as it simultaneously allows me to account for individual and job-level characteristics, as well as their interaction effect on the earnings of workers in skilled jobs (Raudenbush and Bryk 2002). Finally, I pay special attention to the question of gender with regards to earnings of skilled native and immigrant men and women. As numerous studies of labor market segmentation and occupational segregation suggest, opportunities in the labor market are not the same for men and women. The case of skilled immigrant women provides an interesting analytical window to test theories of gender and nativity inequality in the workplace. I recognize the difficulty in estimating the effects of immigration (whether skilled or unskilled), as immigration has multi-dimensional –

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long-term versus short-term and macro versus micro – implications (see Figure 1.1). Changes in global and national economic structures, in immigration, education, and labor policies, as well as the success of assimilation of immigrants and their children will ultimately determine the long-run implications of today’s immigration (Poot and Cochrane 2004). In this study, however, I focus on more immediate impacts of skilled immigrants on labor market outcomes of native and immigrant workers (in bold in Figure 1.1). Organization of the Book The book is divided into four substantive chapters. Chapter 2 provides a historical overview of US legislation that addresses skilled and professional immigration. This history shows that the migration of highly educated and skilled persons is not an invention of contemporary globalization and knowledge-based economies. For many decades, skilled immigrants have been moving across borders in search of better wages, career prospects, and more advanced educational and research opportunities. They have also fled persecution (e.g., German Jews in the period before and during World War II). Unlike their poorly educated and low-skilled compatriots, skilled and professional immigrants have enjoyed a favorable reception in the United States even during the most restrictive times. This trend is currently under strain; therefore, the second half of Chapter 2 discusses five key domestic and international issues with respect to skilled immigration that have to be on the agenda of US policy makers. While there is a consensus on the importance of studying highly skilled immigration, there is little agreement on how to define or measure it (Batalova and Lowell 2006). Chapter 3 addresses this deficit by discussing different definitions used by researchers to operationalize the highly skilled. Chapter 3 also provides a detailed and comparative sociodemographic and economic profile of native and immigrant workers in skilled jobs in the United States. Chapter 4 explores the core implications of skilled immigration on the US labor market by addressing the following questions: Who loses and who gains from highly skilled immigration? What effect does the greater presence of highly skilled foreign born have on the earnings of skilled US-born workers? How do immigrants themselves fare in jobs

Figure 1.1 Some Dimensions of Economic Impacts of Immigration Short-term

Macro Level

Micro Level

Long-term

* Prices of goods and services * Population composition and size * Income inequality * Interest rates and inflation * Aggregate level of wages and rate of unemployment

* International competitiveness * International trade and new markets * Industrial/occupational composition * Public and private infrastructure * Technological change and productivity

* Wages of local native and immigrant workers * Relative wages between and within workers’ groups * Taxes and Social Security payments * Social, health, and fiscal resources

* Innovation and entrepreneurship * Labor market flexibility * Economic and social mobility across generations * Net fiscal balance over migrants’ lifecycles

Source: Adapted from Poot, Jacques, and Bill Cochrane. 2004. “Measuring the Economic Impact of Immigration: A Scoping Paper” (Table 1). New Zealand Immigration Service and Department of Labour.

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with higher concentrations of foreign-born workers? Sociological theories recognize the importance of workers’ characteristics as well as characteristics of the workplace on the degree of complementarity and competition between immigrant and native groups. Following this tradition, in Chapter 4, I apply a multi-level methodology to analyze the 2000 US Census data and to examine individual and structural determinants of earnings of native-born, earlier immigrant, and recent immigrant skilled workers. Extensive research indicates that immigrant workers are disadvantaged (at least initially) in the labor market due to the complex interplay between the structure of employment, the demand for certain kinds of workers, and immigrants’ conditions upon arrival to the United States (Massey, Durand, and Malone 2002). Similarly, female workers are found to be in less-privileged economic positions than their male counterparts due to traditional gender norms that prioritize a woman’s role as wife and mother over her status as a worker. To shed light on gender and native earnings differences, Chapter 5 focuses on highly skilled women. I test a double disadvantage hypothesis that suggests that women who are immigrants will be worse off in terms of their economic outcomes than their male compatriots, as well as worse off than native-born women. Using the case of immigrant women employed in skilled jobs, I demonstrate the ways in which gender and nativity affect one’s earnings potential in the increasingly segmented and segregated US labor market. Finally, Chapter 6 highlights my major findings and discusses their broader implications and policy considerations. Understanding the implications of yesterday’s and today’s immigration policies on social and economic outcomes is imperative in order to establish proactive policies with regard to immigration, labor, education, and national security. Our ability to understand and explain the potential positive and negative effects of highly skilled immigrant workers across diverse occupations and industries is important in responding to questions regarding the economic integration and contribution of immigrants.

“Brain Gain” What’s in the Name?

7

Main Findings The main findings of this research include the following: 1.

For the overwhelming majority of native workers, the higher presence of immigrants in skilled jobs is not associated with a decline in earnings. The fear of highly skilled immigrants depressing earnings or increasing competition is overstated. Only those natives who work in jobs where more than 35 percent of the workforce is foreign born experience a decline in earnings (about 5 to 7 percent of natives work in such jobs). Recent immigrants are most affected by this decline in earnings, as they are more likely to work with other immigrants.

2.

The earnings of native, earlier, and recent immigrant workers respond in a similar fashion to the changing job nativity composition. All workers experience increased earnings when employed in jobs in which immigrants constitute up to 35 percent of the workforce. Thirty-five percent is a tipping point after which earnings of all workers begin to decline. In other words, when a job becomes an “immigrant” job, earnings of all workers decline.

3.

Regardless of their nativity, women working in skilled jobs earn less than men with similar human capital and demographic characteristics. The double disadvantage hypothesis, which posits that immigrant women’s gender and nativity negatively influence their earnings, is not supported for skilled immigrant women. The conclusion is that gender has a greater debilitating effect on the earnings of women in skilled jobs than nativity. Moreover, all workers employed in female-dominated jobs experience a decline in earnings, although men are more sheltered from this negative impact than women.

4.

The pay penalty associated with working in “immigrant” or “female” jobs raises the importance of considering the economic impacts of skilled immigration not in a vacuum but in the context of deepening labor market segmentation and occupational segregation that are taking place in the United States.

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5.

The immigrant admission system can be a potent tool to bring needed labor to help power the American economy. For the system to be effective in alleviating labor shortages on the one hand and protecting the interests of domestic workers on the other hand, it should have three major features: Flexibility to respond to market labor demands, enforcement of wage and work condition standards, and integration of immigrant workers.

CHAPTER 2

The Historical Treatment of Skilled Immigrants in US Immigration Legislation

Introduction Unlike many European nations that only recently have transitioned from being countries of emigration to being countries of immigration, the United States has always received immigrants. Historian Oscar Handlin captured this dynamic when he wrote, "Once I thought to write a history of the immigrants in America. Then I discovered that the immigrants were American history" (Handlin 1973: 3). However, the 300-year history of movement of people to the United States across the Atlantic and the Pacific is a story of increasing regulation and restriction of immigration flows. The US government first restricted immigration by setting quotas on “undesirable” would-be immigrants, and then by defining who, when, and under what conditions immigrants would be allowed to come (Martin and Houstoun 1984; Massey 1999). Immigration, with its profound influences on American society, economy, and national identity, has been one of the most enduring leitmotivs in political and public debates. These debates often focus on whether immigration adversely affects labor market outcomes of US workers and drains fiscal and public resources. They are furthermore complicated by non-economic factors. Recent polls of the American public about their attitudes toward immigration and immigrants show the continuing ambivalence about the prospects of integrating today’s immigrants as well as concerns about lack of efforts by the federal 9

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government to deal with unauthorized immigration (National Public Radio 2004; Pew Hispanic Center 2006). The public perception that America is in a state of economic and cultural decline contributes to anxiety about newcomers and generates anti-immigrant feelings that are translated into direct political action (Bean and Stevens 2003; Bianchi 1997). The provisions of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), which restricted access of legal immigrants to public assistance programs, could be viewed as an attempt by politicians to stop such a decline. Two propositions passed in California (the home of almost 30 percent of the nation’s immigrants) in 1994 and 1998 denied public benefits to undocumented migrants (prop. 187) and reduced assistance for limited English proficiency students (prop. 227). These propositions were a political response at the state level to fears that immigrants take advantage of the generous US social system. “Protect Arizona Now” Prop 200, which was passed by voters in Arizona (a state with a fast growing immigrant population) in 2004, requires state residents to prove their US citizenship before registering to vote or applying for government services. More recently, the attack on unauthorized immigration has been fueled by post-September 11th fears that undocumented immigration constitutes a breach in national security. As the line between immigration (unauthorized or not) and terrorism is blurred, politicians attach immigration-related provisions to immigration-unrelated bills in order to hasten their passage. For example, the REAL ID Act, which included provisions to bar undocumented migrants from receiving federally recognized drivers’ licenses, finish a border fence between California and Mexico, and make asylum application more difficult, was passed as part of a 2005 supplemental military spending bill called ‘‘Emergency Supplemental Appropriations Act for Defense, the Global War on Terror, and Tsunami Relief, 2005’’ (Yau 2005). These restrictive policies, partly with a goal to further militarize the border, are a response to the demands of the domestic constituencies that the country’s land and resources have to be reclaimed and protected (Massey 1999; Massey, Durand, and Malone 2002). Even a cursory examination of the history of immigration to the United States reveals that nativist sentiments have ebbed and flowed

The Historical Treatment of Skilled Immigrants

11

over time in synchronization with economic and political upheavals both at home and abroad. Naturally, these sentiments find their reflection in immigration policies and legislation. However, often the United States has provided exceptions for highly skilled or well-off immigrants. For example, the main targets of restrictive immigration policies since the mid-19th century were low-skilled immigrants and their families. In contrast, openness to the immigration of skilled workers has withstood many legislative initiatives intended to halt the flows of migrants from abroad. I, therefore, begin this chapter with an overview of the evolution of US labor migration legislation, focusing on the treatment of skilled and professional migrants arriving and settling in the United States. Then, I describe major contemporary trends and debates concerning permanent and temporary skilled migration to the United States. I argue that foreigners, who possessed skills and other resources that were of economic interests to the United States, have always been an “exception-to-the-rule” group afforded favorable treatment in immigration legislation even during the most restrictive times. Moreover, the current interest in skilled immigrants spurred by the demands of the American knowledge-based economy represents a continuation of the US immigrant tradition rather than a unique reflection of today’s realities. Since the privileging of skilled and professional immigrants is a long-term phenomenon, I predict that the focus on the supply of foreign talent and the ways in which this talent affects the American polity will persist in the future. This will occur despite the current trend to reduce immigration more generally. Thus, in conclusion, I discuss five issues pertinent to skilled immigration with which American policy makers will have to grapple in the years to come. Skilled Immigration in Historical Perspective Labor Immigration in the 19th Century: Contesting the Open-Door Policy From the birth of the country well until the 1880s, there were no major attempts at the federal level to regulate or restrict immigration.2 Between 1820 and 1900, nearly 20 million people moved to the United States to flee from poverty and destitution caused by famines and wars, find harbor from religious and political persecution, or respond to the

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aggressive recruitment efforts on the part of American employers (US Department of Homeland Security 2005a: Table 1). Voluntary immigrants, the majority of whom were from Europe, sojourners from China, Japan, and Mexico, as well as involuntary migrants such as slaves from Africa and indentured servants from Europe became the source of cheap and docile labor vital for the rapidly developing industrial economy in the United States. Nevertheless, the open-door policy was vociferously but mostly unsuccessfully challenged by the American labor movement and various nativist organizations (Calavita 1984). Labor unions have often opposed immigration throughout history on the grounds that immigrants take away jobs, depress wages, and jeopardize the working conditions of American workers (Goldin 1994). As Calavita (1984) argues, historically, immigrant labor served a number of goals. First, it supplied people willing to work hard for little money. Second, it relieved labor shortages created by industrial expansion and the resistance of US-born workers to difficult work conditions. Finally, it served as a weapon of economic control over the American labor. Most labor organizations, therefore, viewed immigrant workers, particularly Asian workers, as competitors, who wreaked havoc on their attempts to unionize the labor force. As a result, immigrant labor was ostracized, resented, and often described in pejorative racial terms. Moreover, the American Federation of Labor – one of the most prominent protectionist organizations that lobbied Congress to restrict immigration – excluded immigrants already in the country from its membership altogether. There were other opponents to the open-door immigration policy on the American political scene. Nativist organizations demanded restriction on immigration on the premise that immigrants represented a threat to the nation’s political institutions, social welfare system, and cultural cohesion (Tichenor 2002). A number of nativist organizations such as the Know-Nothing Party enjoyed enormous popular support and rose to prominence on the waves of anti-Catholic and anti-Asian hysteria spurred by low-skilled immigration from Ireland and China. Cycles of economic depression between 1873 and 1878 coupled with mounting protests from the labor movement and nativist organizations, created the conditions that led to major shifts in the political debates about how many and what kinds of immigrants should

The Historical Treatment of Skilled Immigrants

13

be allowed to enter the United States (Tichenor 2002). The Chinese Exclusion Act of 1882, notably the first major piece of legislation aimed to exclude a particular immigrant group, was passed under pressure from American labor lobbyists, who were mainly from California. The Exclusion Act and its further amendment in 1884 prohibited Chinese laborers from coming to the United States and denied Chinese-born persons already in the country the right to become citizens. Initially enacted for a period of ten years, the Act was extended and stayed in effect until 1943 (Usdansky and Espenshade 2001). However, the fact that not all Chinese-born persons were treated (or rather mistreated) equally is often overlooked. The members of the Chinese upper class as well as teachers, students, and merchants were exempt from the immigration restrictions and could come to the United States freely, provided they could demonstrate evidence of their skills or social position. Such an exemption was neither the first nor the last example in US immigration history of preferential treatment afforded to better-off or higher-skilled foreigners. Skilled foreign workers recruited under contract also became the target of legislative restriction. Although unskilled laborers alone or with their families dominated the immigration flows, American industrialists recognized the importance of skilled workers. Owners of fledging American industries were particularly interested in capitalizing on the knowledge and experience of skilled British workers who already worked in industrialized sectors in Britain. Such workers were able to get favorable contracts (including payment for transportation, profit-sharing provisions, and higher salaries) to come and manage workers in American factories, mills, and construction sites (Erickson 1957 in Calavita 1984: 21). Over time, greater mechanization significantly decreased the need for skilled workers. To appease American workers, the popular method of bringing overseas workers to the United State on contract was stopped as a result of the Contract Labor Law of 1885 and the subsequent amendment in 1887. However, policy makers protected the interests of big business by writing legislation with numerous loopholes that allowed industry employers to continue bringing in contract labor (Calavita 1984). For example, a large group of foreigners (professional entertainers and skilled workers in unspecified industries, domestic and personal servants, artists, and lecturers) were excluded from the provisions of the Contract Labor Law. Furthermore, in 1891 another

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group of foreigners – ministers, professors, and “persons belonging to any recognized profession” – was added to the list of exemptions. Twenty years later, another wave of protests from domestic workers and anti-immigrant organizations against a “yellow peril” – Japanese immigrants – led to the “Gentlemen’s Agreement” (1907). According to this agreement between the governments of the two countries, Japan stopped issuing passports to Japanese laborers while the US government permitted the immigration of spouses of Japanese workers already present in the United States. In the same year, President Roosevelt issued an executive order to stop admission (direct or through a third country) of Japanese or Korean male workers, regardless of their skill level. Labor Immigration between 1900 and 1950: The Closed-Door Approach Whereas the majority of 19th century immigrants were from Northern and Western Europe (plus sojourners from China, Japan, and Mexico), immigration in the early 20th century was dominated by Southern and Eastern Europeans. Southern, Central, and Eastern-European migrants constituted almost two-thirds of the 14.5 million immigrants admitted to the United States in the first two decades of the 20th century (US Department of Homeland Security 2005a: Table 2). This new wave of immigration spurred a major restructuring in US immigration law. Pseudo-scientific discoveries from eugenicists supported what Benjamin Franklin had said in the mid-18th century about arriving immigrants, “Those who come hither are generally the most stupid of their own nation…Not being used to liberty, they know not how to make a modest use of it…even our government will become precarious” (cited in Shanks 2001: 33). A law of 1917 instituted a literacy test as a way to restrict the arrival of illiterate, low-skilled, and low-wage immigrant labor from Southern and Eastern Europe (Goldin 1994).3 The law also created an “Asiatic barred zone,” which lead to the exclusion of immigration from most Asian countries. Again, the focus of these restrictions was mainly on low-skilled foreigners, while professionals, religious workers, and merchants as well as students and tourists were exempt.

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15

A combination of factors prompted the era of harsher restrictions. These included the usual suspects: Bitter and well-organized protests by American labor unions and vigorous lobbying by nativist organizations such as the Immigration Restriction League. Although the restrictionist camp faced daunting opposition from ethnic lobbying groups such as the German American Alliance, scholars such as Harvard president Charles Eliot, and business groups such as the National Association of Manufactures (Tichenor 2002), the “stopimmigration now” lobbyists prevailed. The new insights into the relationship between one’s intelligence and country of origin and race (that placed Northern and Western European-origin persons on the top, followed by Eastern and Southern Europeans, then by Asians, and lastly by Blacks) were not in favor of new immigrants either (Tichenor 2002). Finally, fears of overwhelming immigration from Europe as a result of World War I and a civil war in Russia solidified the foundation and justification for new restrictions on immigration. In parallel to the debates today, worries that the days of plenty had ended, the American democratic system was doomed to collapse, and assimilation of immigrants had become an impossible mission colored concerns about immigration in the 1920s. As populist-nationalist explanations, which stressed the low value of Southern and EasternEuropean immigrants and their poor integration prospects, came to dominate public and political thinking, politicians responded by enacting the national origins and race-based quota laws in 1921 and 1924. The 1921 Quota Law set a numerical cap (357,000) on total immigration from the Eastern Hemisphere and limited the annual number of immigrants of any nationality (from the Eastern Hemisphere) to 3 percent of the foreign-born persons of that nationality who lived in the United States in 1910. The quota law in effect favored immigrants of Western and Northern-European stock whose conationals were more numerous than their counterparts from other parts of Europe as of 1910. The 1921 law did not restrict immigration from the Western Hemisphere but did nothing to amend the exclusion of Asian immigration. Yet again, not all foreigners were treated equally under the quota laws. Following the tradition of the previous legislation, certain groups of immigrants were exempt from the quota restrictions. The exempt mainly included a variety of professionals, professors and lecturers, medical personnel, religious workers, and entertainers and domestic servants. However, the Act of 1924 tightened

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further the national origins restrictions and granted the extension of privileged status to only two groups of skilled workers – ministers and college professors and their immediate family members (Usdansky and Espenshade 2001). The significance of the 1921 and 1924 Acts lies in their implications for the future of the US immigration system. That is, the 1921 Act allowed the entrance of relatives of immigrants already present in the United States. The 1924 Act allocated up to half of all visas under national origins quotas to skilled agricultural workers, their families, and to the immediate relatives of US citizens. These allocations in effect became the foundation of the contemporary immigration preference system, which contains both family- and employment-based categories. Also, the 1924 Act distinguished between permanent immigrants and temporary visitors (nonimmigrants); the latter became the prototype for today’s temporary skilled and agricultural worker visa categories (Usdansky and Espenshade 2001). As this brief overview of pre-WWII immigrant legislation indicates, with almost no exception, the legislation provided a clear preferential treatment to foreigners who possessed occupational credentials, skills, and other economic resources. Post-WWII: The Emergence of the Employment-Based Immigration and Non-Immigrant Systems The restrictions put in place by the new laws coupled with Great Depression and World War II halted substantial immigration for the next thirty years.4 As Figure 2.1 shows, immigration took a nose-dive from four million in the 1920s to 528,000 in the 1930s, which in turn led to a dramatic decline in the share of foreign born in the US population: From a historical high (14.7 percent in 1910) to a historical low (4.7 percent in 1970). The post-WWII events ushered in new challenges for immigration policy making. Economists reached a consensus that immigration contributed to the country’s economic growth and did not adversely impact income distribution (Carter and Sutch 1999). Additionally, foreign policy experts argued that preventing the spread of communist ideas in the newly independent countries of Africa and Asia was central to US security during the Cold War (Tichenor 2002). Fighting

Figure 2.1 Number of Legal Immigrants (in thousands) Arriving by Decade and Percent Foreign Born in Total US Population, 1901 to 2000 N

10,000 9,000

Number of legal immigrants Percent foreign born

8,000

16

%

14 12

7,000 6,000

10

5,000

8

4,000

6

3,000

4

2,000

2

1,000 -

0 1901-10 1911-20 1921-30 1931-40 1941-50 1951-60 1961-70 1971-80 1981-90 1991-00

Sources: Derived from Statistical Yearbook of the Immigration and Naturalization Service, 2000 (Table 1). Washington, DC: US Government Printing Office, and Campbell J. Gibson and Emily Lennon (1999) Report 29. "Historical Census Statistics on the ForeignBorn Population of the US: 1850-1990." Washington, DC: US Census.

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communism prompted the US Congress to drop the racial-based national origins quotas as inconsistent with a notion that the United States was a free, open, and just society that could serve as a model to follow. Similarly, the quickly intensifying Cold War put pressure on America to engage in rapid scientific and military research, which required a large pool of qualified labor (Ong and Liu 1994). Finally, the Civil Rights movement of the 1950s and 60s pushed for equality and fairness in immigration policy (Massey 1999; Zolberg 2006). The Immigration and Nationality Act (INA), also known as the McCarran-Walter Act, was passed by the US Congress in 1952 and became the foundation of US immigration law. The INA collected and codified prior provisions and statues into one place. Most immigrationrelated legislation passed since 1952 amended various sections of the INA. Although the original INA did not drop the national origins quotas, it canceled immigration and citizenship eligibility restrictions based on race set forth by the Act of 1924. The INA established a preference-based immigration system by assigning the slots for permanent immigrant visas to those with relatives in the United States (family-sponsored immigrants) and to employment-qualified persons (employer-sponsored immigrants) within the national origins quota system. Moreover, spouses, minor children, and parents of US citizens were exempt from numeric limitations altogether. With regard to skilled labor, the McCarran-Walter Act was significant in two ways. First, it stipulated that up to 50 percent of the quotas for the Eastern Hemisphere had to be allocated to immigrants “whose services are determined by the Attorney General to be needed urgently in the United States because of high education, technical training, specialty expertise, or exceptional ability of such immigrants” (INA, 66 Statutes-at-Large 163 cited in Usdansky and Espenshade 2001: 35). Second, it not only reauthorized the admission of temporary workers (barred by the Contract Labor Law of 1885) but also began to distinguish between skilled and unskilled temporary workers by creating an H-1 visa program. The H-1 visas allowed foreign nationals of distinguished merit and ability to work in the United States temporarily in occupations that required their qualifications. The original provisions of the INA placed no numerical limitations or provisions for protection of US workers in the H-1 temporary visa program (Meyers 2006).

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Contrary to expectations, the Act did not promote a great inflow of skilled and talented foreigners. On the one hand, Western Europeans chose not to take advantage of new immigration opportunities but rather stayed put in a Europe that was quickly rebuilding after the war. This differed from Eastern Europeans who were not allowed to leave by their Communist governments except under exceptional circumstances. On the other hand, because the INA maintained the national origins quotas, non-Europeans could not easily immigrate. The significant increases in immigration in general and of educated and skilled persons in particular came as a result of the INA Amendments passed in 1965. The key feature of the 1965 Hart-Celler Immigration Act was the elimination of the national origins quota system. In its place, the 1965 Act established a seven-category preference system with the allocation of 170,000 and 120,000 visas annually for immigrants from the Eastern and Western Hemispheres, respectively. The 290,000-person limit did not include immediate relatives of US citizens – spouses, minor children, and parents – who as before were exempt from numerical limitations. An annual quota of 20,000 immigrants was established for each country from the Eastern Hemisphere while no per-country quotas were set for countries from the Western Hemisphere. The lion’s share of all visas (80 percent) were allocated to familypreference immigrants in an unspoken effort to continue European migration and preserve European-origin dominance in the racial and ethnic composition of the American population (Usdansky and Espenshade 2001). The other 20 percent of the 290,000 visas were divided between two employment preferences: Members of the professions or persons of exceptional ability in the sciences and arts (3rd preference) and needed skilled or unskilled workers (6th preference). To appease labor unions’ opposition to employment-based immigration, Congress also stipulated that US employers wishing to sponsor a permanent immigrant worker had to obtain a labor certification from the Department of Labor. The purpose of this certification was to ensure that immigrant workers would not negatively affect the employment opportunities and earnings of US workers, as the employers had to certify that they searched and found no American worker available to fill the position.5 The Hart-Celler Act was quickly followed up by more legislation. The Immigration Act of 1970 focused mainly on temporary foreign workers. First, the Act permitted H-1 visa workers to bring their

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immediate family members along. Second, a new non-immigrant visa – L-1 intra-company transferees – was created to allow US companies engaged in international business to bring their current employees from overseas without long waits for permanent employment visas. Third, both H-1 and L-1 workers were allowed to stay longer, work in permanent positions, and adjust to lawful permanent resident status from within the United States if they met eligibility requirements (Meyers 2006). As knowledge about the American immigration system spread around the world and the need for skilled workers increased in the growing American economy, more immigrants entered under the permanent and temporary employment-based visas. By the early 1980s the entire employment-based immigration quota was reached every year (Usdansky and Espenshade 2001). The number of temporary H workers was on the rise as well. The H-1 visas issued by the Department of State to foreign temporary workers more than doubled from 14,573 in 1969 to 31,117 in 1979 and then increased further to 48,820 in 1989 (US Department of State 1971, 1980). The Immigration Act of 1990 Whereas unauthorized immigration to the United States was a bone of contention in the late 1970s and 1980s (reflected in the Immigration Reform and Control Act of 1986), skilled immigration captured the spotlight between the mid-1980s and 1990s. Despite greater inflows of skilled and educated foreigners to the country, the proportion of employment-based immigrants (principal applicants and their spouses and children) was less than 10 percent of total immigration in the 1980s. The second half of the 1980s was a period of escalating debates over the future of the American workforce with representatives of business and labor as well as pro-immigration and anti-immigration non-profit organizations forcefully lobbying Congress for their respective cause (Subcommittee Hearings in the Senate and House of Representatives 1989a; 1989b). A highly influential report from the Hudson Institute entitled “Workforce 2000” argued that if nothing was done, the American economy would face a severe skill shortage in the near future (Espenshade 2001). The question in the air was: Given the potential for a mismatch between the supply of and the demand for

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college-educated and skilled workers, would the United States be able to compete successfully in the global marketplace? Representatives of the business community argued that the 54,000 permanent immigrant visas allotted to skilled workers did not suffice to meet demand (of these visas, at least half went to the immediate family members of employment-based immigrants because family members were counted against the 54,000 visa cap). They also complained about the long and tedious process required in order to hire foreign skilled labor, caused by the backlogs in the processing of applications in the Department of Labor (DOL) and in the Immigration and Naturalization Service (INS). For example, an employer who applied for a visa for a prospective immigrant worker under the 3rd preference immigrant visa on August 14, 1984 had to wait no fewer than ten months for the visa to become available. The waiting time for the 6th preference visa was even longer: The applications submitted on August 31, 1983 were still pending as of June 1985 (US Department of State 1985). The waiting time for the employment-based visas extended even further by the end of the 1980s (US Department of State 1991). As employers correctly pointed out, such processing times were significantly longer than their hiring cycles. For different reasons, labor unions and professional organizations were not content with the current state of affairs either. They argued that the temporary H-1 visa program was flawed because it placed American skilled workers and professionals at an economic disadvantage. To address these concerns, INS commissioned a study, which found that a significant portion of H-1 temporary workers were indeed hired in entry and middle-level positions, which contradicted the requirement for this visa. The study, however, found little support for the unfavorable competition argument (Lowell 2001a). The Immigration Act of 1990 (IMMACT90), which came as a result of heavy lobbying and negotiations, significantly affected both the permanent and temporary immigration of foreign workers.6 First, IMMACT90 created an annual flexible cap on total immigration of 700,000 visas in fiscal years 1992 to 1994 and 675,000 visas thereafter (US Immigration and Naturalization Service 2003). Second, the new law more than doubled employment-based immigrant visas from 54,000 to 140,000 visas per year and placed more emphasis on skilled migrants within this category (Martin, Chen, and Madamba 2000). Third, the Act increased the number of employment-related preferences from two to five, allocating no more than 10,000 visas to unskilled

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workers. IMMACT90 retained the labor-market testing required for sponsorship of certain employment-based immigrants (2nd and 3rd preference categories). Appendix A shows the five employment-based preferences along with the number of annual visas allocated to them and visa eligibility requirements. Besides affecting permanent employment-based immigration flows, IMMACT90 profoundly changed the kind and number of foreign workers admitted to the United States on a temporary basis. The new law affected both skilled and unskilled temporary labor inflows. In 1989, the H-1 visa program for workers of distinguished merit and ability was split into H-1A visas for registered nurses and H-1B visas for other persons of distinguished merit and ability.7 IMMACT90 separated certain occupations from H-1 visas into their own visa categories: the O visa for scientists, educators, and artists with extraordinary abilities; the P visa for entertainers and athletes who are either internationally recognized or will perform under a reciprocal cultural exchange; and the R visa for religious workers. Spouses and children of H-1B, O, P, and R workers were allowed to follow principal applicants, but they had no permission to engage in employment in the United States unless they had their own work visas. IMMACT90 also established the H-1B visa program as it is known today by limiting it to foreign workers who are admitted to the United States to perform work temporarily in “specialty occupations” (fashion models of distinguished merit and ability also qualified for H-1B visas). The law defined “specialty occupation” as an occupation that requires, “first, a theoretical and practical application of a body of highly specialized knowledge, and, second, an attainment of a Bachelor's or higher degree in the specific specialty (or its equivalent) as a minimum for entry into the occupation in the United States” (US Citizenship and Immigration Services 2005: INA §214(i)(1)). In addition to setting a more precise definition of education and skill level required to obtain an H-1B visa, Congress, upon the insistence of labor unions and professional organizations, placed an annual limit of 65,000 visas on the newly established H-1B category (prior to 1990 there was no numeric limitation on H-1 visas). This cap proved to be insufficient in meeting the demand for temporary foreign workers even within the first couple of years after IMMACT90. As former Representative Bruce Morrison (D-CT.), the chairman of the

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House Subcommittee on Immigration, Refugees, and International Law explains, a 25,000 H-1B visa limit based on INS data on the usage of H-1 visas was initially set in the House bill. Since some of occupations eligible for the former H-1 visa were given their own categories (O, P, and R), the revised 65,000 visa cap seemed high enough to accommodate the current as well as potentially expanding demand. The problem was that the INS had underestimated the usage data; the technology boom that started in the mid-1990s exacerbated the situation (Morrison 2006). IMMACT90 maintained that US employers could hire H-1B temporary workers initially for three years with a possibility to extend their permission to work for another three years. To prevent the misuse of the H-1B visa program, the employers were required to file a Labor Condition Application (LCA) with DOL attesting that they would pay the prevailing wage and provide work conditions similar to US workers. The employers also had to attest that they were not involved in a labor dispute or lockout (US Department of Labor 2005). Recognizing the fact that many temporary workers were hired to work in permanent rather than temporary jobs and that eventually it would be in the interest of both the employer and employee if these temporary foreign workers could adjust their status to that of lawful permanent resident, IMMACT90 allowed for dual intent by H-1B, L-1, and O-1 visa holders.8 To sum up, IMMACT90 modified existing and introduced new temporary work-related programs designed to promote a variety of US political, economic, and cultural exchange goals as well as to meet US bilateral and multilateral trade and commerce obligations (Papademetriou and Yale-Loehr 1996). Appendix B provides a description of visas available for hiring skilled and unskilled temporary workers and shows length of stay, the numerical limitation, and applicable US worker protection requirements for each of these visas. What is important about the majority of these classes of foreign workers is that, unlike in the case of H-1B visas, IMMACT90 neither placed a cap on them, nor included any domestic worker protection provisions. Besides these explicit work-related temporary visas, there were a few visas for which work was permitted under certain conditions. The primary example of this type of visa is the F-1 student visa. Students are allowed to work on campus part-time while school is in session, full time when school is not in session, and have the option of working for one year in their field of study after graduation.

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The H-1B Debate Continues Between 1991 and 1998, nearly half a million H-1B visas were issued by the Department of State (US Department of State 1998). The number of H-1B admissions (admission numbers refer to the number of border crossings, not people) more than doubled – from 114,000 in 1991 to 241,000 in 1998 (US Department of Homeland Security 2005a, Table 24).9 The majority of the H-1B visas went to foreign workers hired in information technology and health care industries (Lowell 2001a). More than two-thirds of all H-1B visas were issued to foreign workers from Asia and Europe. During the late 1990s, India alone accounted for nearly half of all issued H-1B visas. To provide a representative example, in fiscal year (FY) 1998 about 44 percent of H-1B visas were issued to citizens of India, followed by 7 percent to nationals of the United Kingdom, and 4 percent to nationals of mainland China (US Department of State 1998). While the H-1B initiative was applauded by the business community, it was opposed by professional science and engineering organizations such as the Institute of Electrical and Electronics Engineers (IEEE). For the next ten years after IMMACT90, the H-1B visa program was a subject of rapt national attention and heated battles. On the one hand, the US business community, particularly the IT industry, complained about a serious shortage of qualified domestic workers, which was inhibiting the industry’s growth. Moreover, the slow processing of applications for workers under the permanent immigration system by US government agencies (application processing backlogs were over one year) made the supply of permanent immigrant skilled workers unreliable (Lowell 2005). Therefore, US employers argued that the fastest way to deal with the labor shortage was to hire temporary foreign workers. The problem for employers, however, was that the annual cap of 65,000 H-1B visas was reached within first six to seven months of each fiscal year, resulting in backlogs when thousands of foreign workers with job offers had to wait until the next year to apply for a visa. On the other hand, some academics and professional science and engineering organizations argued that the shortage of skilled labor was a myth altogether and highly skilled temporary labor undercut domestic opportunities by driving down wages and worsening working

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conditions for native workers (Espenshade 2001; Lowell 2001a; Matloff 2001). Academic research and government investigations found many instances of H-1B exploitation with adverse effects on USborn and foreign workers alike (General Accounting Office 2000; Hagan and McCollom 1999). As shown in my historical overview, the confrontation between the labor and the business community of the late 1990s was nothing new, as the two groups have been traditionally on the opposite sides of the immigrant labor barricade. During the 1990s, industry representatives lobbied Congress for the open-door approach while labor lobbied for the close-door approach regarding temporary skilled foreign workers. Congress responded to employers’ claims of shortages of skilled workers and to employees’ demands to protect native workers with two acts. First, the American Competitiveness and Workforce Improvement Act (ACWIA) signed into law by President Clinton in 1998 increased the number of H-1B visas from 65,000 to 115,000 for two years, 1999 and 2000; but then the cap on H-1Bs was to revert to the original 65,000-visa level in 2001. The number of H-1Bs allotted did not return to 65,000, however. In October 2000, Congress passed the American Competitiveness in the 21st Century Act (AC-21) that raised the annual cap even further to 195,000 for each of the next three years (2001, 2002, and 2003), but mandated that the number of visas return back to its original 65,000 by 2004. Non-profit or government research organizations, institutions of higher education, and other non-profit entities were exempted from the visa caps altogether. As part of the worker protection provisions, AC-21 doubled the fee companies had to pay for each foreign worker they hired on an H-1B visa (the original fee of $500 was set by ACWIA). The receipts from this fee went into a fund so that US citizens, lawful permanent residents, and other US workers could attend job training and receive low-income scholarships or grants for mathematics, engineering, or science enrichment courses administered by the National Science Foundation and the Department of Labor (US Department of Homeland Security 2004). Additionally, employers whose workforce was composed of 15 percent or more of H-1B workers had to certify that they did not lay off US workers to hire H-1B workers. Moreover, in efforts to prevent continued abuse of the H-1B program and to protect the rights of temporary workers, AC-21 allowed for visa portability; that is, an H-1B visa holder could switch jobs provided that the new

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employer was willing to file a new H-1B petition on the worker’s behalf. The economic slowdown and the concomitant burst in the hightech bubble in the early years of the 21st century dampened the demand for highly skilled foreign workers. The cap of 195,000 H-1B visas was not reached in 2001, 2002, or 2003. The cap, however, was reached in 2004, when it returned to 65,000 visas as required by AC-21. Since 2004, the 65,000-visa cap has been reached well before the filing deadline. For example, in August 2005, US Citizenship and Immigration Services (USCIS) reported that it had already received enough H-1B applicants to fill the cap for FY 2006 (US Department of Homeland Security 2005b). This situation propelled the H-1B issue onto the center stage of the political debate yet again (Wall Street Journal 2005). The most recent change in the H-1B program came as a result of the H-1B Visa Reform Act of 2004. The Act increased the fees associated with applying for an H-1B visa from $1,000 to $1,500 ($750 for employers with fewer than twenty-five full-time workers). In addition to the $1,500 fee, the Act established a Fraud Prevention and Detection Fee of $500 for all H-1B and L-1 applications. Moreover, beginning May 2005, 20,000 additional H-1B visas became available to H-1B applicants holding advanced degrees from US institutions. However, the Act did not revise the 65,000 cap itself (US Department of Homeland Security 2004). The debates over both permanent and temporary skilled immigration show no signs of abatement (Interpreter Releases 2006b; Interpreter Releases 2006c). The next section discusses five policy considerations with regard to skilled immigration that will have to be addressed in the near future. Skilled Immigration Policy Considerations of Tomorrow 1. The Economic Impact of Skilled Foreign Workers As discussed earlier, one of the most long-standing controversies in immigration debates is whether the presence of foreign workers depresses wages and diminishes employment opportunities for nativeborn workers. Evaluation of the economic impacts of immigrants is a complex enterprise since immigrants affect the US economy in ways

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that reach beyond labor market outcomes of native workers (see Figure 1.1). For decades, sociologists and economists have attempted to tackle the question of economic competition between native and foreign workers (Bean, Gonzalez-Baker, and Capps 2001; Borjas 2003). However, as a recent review of the literature on the economic impacts indicates, the direction and magnitude of the effects has become an increasingly contested ground, which in turn makes it difficult to devise sound policy based on the research findings (Murray, Batalova, and Fix 2006). Moreover, until recently, skilled immigrants and their labor market experiences and impacts were not analyzed separately from those of unskilled workers. The few studies that examine the consequences of skilled permanent and temporary immigrants arrive at no consensus on whether native skilled workers (and native workers in general) gain or lose from the skilled immigration (Murray, Batalova, and Fix 2006). Since the economic impact question is bound to stay on the policy agenda, the need for more research has acquired unprecedented urgency (Interpreter Releases 2006b). The next two chapters address the competition issue between native and immigrant workers (Chapter 4) and competition within native and immigrant worker groups exploring the nativity-gender interaction (Chapter 5). The rest of this chapter is devoted to the discussion of four other important issues. 2. The Brain Gain Race: International Competition for Foreign Skilled Workers and Foreign Students The United States is considered to be a magnet for foreign talent. The fact that more than one-third of Nobel laureates from the United States are immigrants (National Academies 2005a) and that there are sixtytwo patent applications for every 100 foreign students enrolled in sciences and engineering doctoral programs (Anderson 2005) are just two reasons for the United States to continue to allow access to talented people from across the globe. However, as the global competition for professionals, IT workers and researchers, doctors and nurses, and university students intensifies, the question arises: Will the United States have unchallenged access to the best and brightest? Identified by the Migration Policy Institute (MPI) as one of the top ten issues of 2005, challenges to US preeminence posed by increasing global

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competition for foreign workers, researchers, and students received considerable attention in the academic and policy community as well as in the American media (Florida 2005; MPI 2005; National Academies 2005a; National Academies 2005b; UC Irvine and The Merage Foundation 2005). 2.1 Foreign Workers In the last decade, there was a proliferation of programs and initiatives developed and implemented in the United States, Canada, Australia, New Zealand, the United Kingdom, Germany, France, Ireland, South Korea, and Taiwan, to attract, retain, and/or repatriate highly skilled individuals. “We are in an international competition for the best workers,” the chair of Germany’s Independent Commission on Migration Rita Süssmuth said after presenting the commission’s recommendations to increase the immigration of skilled foreign workers to Germany (New York Times On-line 2001). Germany launched a so-called “Green-Card” scheme to bring in 20,000 IT specialists from non-EU countries (Mclaughlan and Salt 2002).10 Unlike its American version, Germany’s “Green Card” does not lead to permanent residency but allows non-EU high-tech specialists to work for up to five years in Germany (Martin 2003). Canada and Australia rely on their point systems for permanent immigration, under which about two-thirds of arriving immigrants are skilled and educated. Non-Western countries also use aggressive recruiting programs and have liberalized their immigration policies to stimulate the inflow of skilled persons from abroad. For example, Singapore, in efforts to supply the power for its expanding information technology, aims to develop the country into a “‘Brains Service Node’, ‘An Oasis of Talent,’ and ultimately, the ‘Talent Capital of the New Economy, where local and foreign talent combine their strengths, ideas, and creativity to drive the economy and rise above global competition” (Yeoh 2006: 31). Countries like India, China, Taiwan, Ireland, Germany, and Sweden among others have adopted policies to create incentives for their emigrants to return. These include creating business and investment opportunities, allowing emigrants to possess dual citizenship, and providing tax incentives (Martin 2003; Mclaughlan and

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Salt 2002; OECD 2002; O'Neil 2003). At the same time, these countries’ governments have attempted to formalize their relationships with immigrant and diasporic networks in order to establish ties between scientific and business communities at home and abroad (Chakravartty 2001). In 2000, the British government and the Wolfson Foundation allocated ₤20 million to an initiative to find ways to encourage repatriation of British scientists as well as to stimulate the immigration to the United Kingdom of young scholars from abroad. In 2005, New Zealand launched a website that aimed to bring back some of its approximately 500,000 citizens residing abroad and to connect New Zealand employers with skilled workers looking for jobs in the country (MPI 2005). 2.2 Foreign Students Foreign students enrich the cultural diversity and educational experience for US-born students, enhance the reputation of American universities as world-class learning and research institutions, and make the country one of the most profitable educational destinations (Wasem 2003). For example, in 2004, foreign students contributed $12.9 billion in tuition and living expenses (NAFSA 2004). Graduate and undergraduate students have been coming to the United States to study science and medicine since the mid-1960s. Later these students were joined by those interested in studying, researching, and getting practical training in computer and telecommunication sciences, business, education, law, social sciences, and the humanities. The number of international students has increased from 82,000 in 1964-1965 to more than 500,000 in 2003-2004. The share of foreign students as a percentage of the total student population rose as well, from 1.5 percent of total enrollment in 1964-1965 to 4.3 percent in 2003-2004 (Institute of International Education 2004). On the global education market, the United States has long been a major destination for many undergraduate and graduate students. The United States accounts for 28 percent of all foreign students studying in OECD countries at the tertiary level, but its share has declined recently compared to Australia and Canada (OECD 2005). Moreover, while the percentage of foreign students in the US total enrollment barely changed between 1998 and 2003, it grew from 12.7 to 18.7 percent in Australia, more than tripled (from 3.7 to 13.5 percent) in New Zealand,

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and nearly doubled (from 4.5 to 8.0 percent) in Sweden (OECD 2005). There is also evidence that students from the Gulf region, North Africa, and Southeast Asia are increasingly choosing to study in Europe, the Middle East, Asia, and Oceania rather than in the United States (Brown 2005; OECD 2005). Given the recent drop in the enrollment of foreign students – a reversal of the thirty-year upward trend – has the United States already lost its competitive edge in attracting students and scholars? Clearly not, but several trends pose a serious challenge to America’s leadership. First, tightened visa procedures and entry conditions for international students (especially for those from the Middle East) implemented in the aftermath of the terrorist attacks of September 11th, 2001, dampened the demand for visas. For example, the annual number of F-1 student applications submitted between 2001 and 2004 dropped by nearly 100,000 (Yale-Loehr, Papademetriou, and Cooper 2005).11 Second, and perhaps more important, the aggressive recruitment efforts by Australia, New Zealand, Canada, France, and Sweden among others resulted in the expansion of foreign student populations in those countries. These countries use a combination of American-style programs taught in English, free or subsidized tuitions for foreign students (OECD 2005), and eased routes for permanent immigration after graduation in efforts to secure their share of the foreign student market (Citizenship and Immigration Canada 2005; Hawthorne 2005). Finally, traditional sources of foreign students in the United States – China and India – now commit significant resources boosting their own innovation and educational capacities, with the Indian Institute of Technology and the University of Beijing leading the way. China, India, Taiwan, South Korea, and Singapore aim not only to keep their own students but also to encourage students from Asia and the Middle East to come to study. As The Economist’s Special Issue on Higher Education argues, although the United States still has a monopoly on the world’s top universities (seventeen out of the top twenty), its dominance has been undeniably challenged by new educational destinations (The Economist 2005). Recognizing the fact that today’s international students and postdoctoral scholars are the entrepreneurs and workers of tomorrow, representatives of US colleges and universities, academics, and US

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employers intend to keep the topic of foreign students fresh in the minds of the public and policy makers (Anderson 2005; Grimes and Alden 2004). A number of recent reports point to the same recommendation: To maintain its leadership in technological and scientific innovation, the United States’ main goal should be to attract the best graduate students and workers regardless of their national origin (Bean and Brown 2005; National Academies 2005a; National Academies 2005b). However, in the race for foreign talent, the United States should not overlook its own students and workers and their stakes in the future, the issue discussed next. 3. Skilled Foreign Workers and Education and Labor Policies Benefits derived from the “brain gain” are many (Mclaughlan and Salt 2002). The gaining countries increase their research and development (R&D) and economic activities thanks to intellectual and entrepreneurial capacities of foreign skilled workers, build and strengthen ties with foreign universities and research organizations, stimulate foreign investments, and alleviate labor shortages in fields that cannot or do not attract enough domestic workers (Regets 2001). A country’s ability to attract foreign talent is an important economic and political advantage; however, heavy reliance on foreign workers and students is a double-edged sword with respect to the future supply of skilled workers. At least initially, immigrants tend to accept lower wages and poorer working conditions either due to unfamiliarity with local labor market conditions or discrimination. Some argue that over time, occupations that rely on foreign workers may lose their attractiveness to the native born population. A popular opinion is that US-born students are not interested in pursuing degrees in sciences and engineering (S&E) not only because these are difficult fields to study, but also because these majors promise lower pay than those of business, law, and medicine (North 1995). Furthermore, those natives who do go after S&E degrees may find themselves crowded out from the top schools by highly competitive foreign students (Regets 2001). Betts (1999) and North (1999) argue that this is especially relevant for minority students such as African Americans and Hispanics as well as women, who may face unfavorable competition with foreign students first when being considered by admissions committees and then for

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funding resources (for a critique of this view, see Bean and Brown 2005). Therefore, one policy goal should be to pursue comprehensive policies to enhance the education and training of native students, particularly minorities, in the majors that will be in demand in the future (Papademetriou 1999). The National Academies report recommends focusing closely on the “pull factors” – time required to obtain the degree, availability of fellowships, research assistantships, or teaching assistantships, and the prospects of attractive employment opportunities – in efforts to promote the interest of domestic students in S&E fields (National Academies 2005a). Another possible negative implication of the “brain gain” is that it frees the business community from finding ways to adjust to tighter supplies of skilled workers by retraining their existing labor force (Papademetriou 1999). Thus, governments have to recognize the interdependency between educational, labor, and migration policies. Some countries (for example, Germany, the Netherlands, and Denmark) have already made this realization and make training and retraining of domestic workers explicit long-term goals stated in their migration policies (Mclaughlan and Salt 2002). Although a complete moratorium on skilled immigration would be extremely detrimental to the country’s economic and technological global competitiveness, the United States needs to seek long-term solutions to persistent labor shortages through education and labor policies (Interpreter Releases 2006b; Papademetriou and Yale-Loehr 1996). 4. Skilled Foreigners and National Security In the aftermath of September 11th, 2001, national security is on the minds of politicians, academics, and the public alike. While some see skilled immigrants as powerful collaborators in strengthening the United States’ ability to fight terrorism and espionage, others assert exactly the opposite (for further discussion of the debate, see Rosenblum 2001; Wasem 2003). Although the excessive focus on foreign students and workers as the main security and terrorist risk is misplaced and overshadows real gaps in the current security system (see Yale-Loehr, Papademetriou, and Cooper 2005 for a comprehensive evaluation of post-9/11 visa and admission procedures), it is true that

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some foreigners have taken advantage of the relative openness of US immigration channels to inflict harm on the country. First, hiring foreign workers to research and develop new technologies in sciences, medicine, and IT sectors may lead to charges of espionage (of course, this applies to foreign companies that hire USborn workers as well). The case of a Taiwanese-born scientist Wen Ho Lee illustrates the point. Dr. Lee was accused and placed in prison (with a subsequent exoneration) for allegedly copying top-secret nuclear bomb codes and sharing them with China (Tucker 2004). His trial for espionage and treason stirred fears of foreigners being disloyal to their new country (Smith 2000). Another possible threat is the transfer of cutting-edge technologies to US economic, intellectual, and military competitors when foreign workers involved in the development of these technologies at the American universities or companies return home or emigrate to a third country. Taiwan’s Hsinchu Science Park (HSP) is one example of the high-tech enclaves developed to invest in the knowledge that Taiwanese and other scientists and engineers have gained while living abroad. According to the HSP website, the Taiwanese government has invested over $1 million in the last two decades developing a national high-tech industry and making the HSP a global manufacturing and R&D center for high-end products (Hsinchu Science Park 2004; Woo 2000). Similar centers are operating or in the process of opening in Hong Kong, South Korea, India, and China (Woo 2000). While important for the development of their own countries, such centers may pose a challenge to others. As highly trained foreign workers move to another country or go back home, they carry with them not only financial resources but also skills and knowledge of technologies that could potentially be used against the countries where these technologies were originally developed (Regets 2001). 5. Economic Integration of Skilled Immigrants As discussed earlier, much of the advanced industrial world has invested significant time, energy, and resources to attract and retain highly skilled foreigners. These aggressive recruitment efforts, however, have taken place with little consideration from policy makers and researchers about what would happen to these immigrants once they arrived in their host country. Using the data from the New Immigrant Survey Pilot (1996), Redstone Akresh finds that, within one

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year of receiving work authorization, 52 percent of newly admitted immigrant workers experienced occupational downward mobility with their first American job (Redstone Akresh 2006). The author further shows that human capital acquired in Latin America and the Caribbean is valued less than that from Europe, Australia, and Canada in the American labor market. Often, skilled immigrant workers from nonWestern countries have to start at the bottom not because there are no jobs or because they do not qualify for them, but because their foreign credentials, licenses, and work experience are not recognized by the US employers or state professional licensing and occupational certification agencies (Newman 2006). To benefit from the skills and training of foreign workers, cases of Tunisian-born lawyers working as doormen and Pakistani engineers driving cabs – notorious examples of human capital waste – have to be recognized as such and minimized. The United States needs to develop and implement policies to ensure successful integration of these immigrants into the American labor market by addressing the issues surrounding the validation and recognition of academic, professional and work-related competencies and credentials of foreign educated or trained workers. Is it possible to capitalize successfully on skilled immigration while minimizing the negative implications for the country’s national security? Papademetriou and Yale-Loehr (1999) and Rosenblum (2001) think so because skilled immigrants powerfully contribute to the strength of national security through their research and collaboration in security-related fields. These authors assert that in the context of the information revolution and increasing competition for foreign students and workers, it is imperative for US employers to have access to talented people regardless of their nationality and for foreign workers to feel welcomed in the United States. In other words, it is essential to make sure that the best and brightest workers become “permanent” in the United States, both in terms of residence, attachment to the labor force, and national allegiance. Thus, the future well-being and national security of country depends not only on successful recruitment of foreign talent but also on their subsequent integration.

The Historical Treatment of Skilled Immigrants

35

Conclusion Countries have historically benefited from immigrant talent and labor. Although migration has always been a part of human history, what distinguishes today’s migration trends is the volume and intensification of movement across borders, its importance to domestic and foreign policies, and its enormous social, political, and economic consequences for sending and receiving societies (Castles and Miller 1998). As my review of the evolution of US legislation regarding skilled workers in the United States indicates, migration of skilled foreigners is an issue that is politically highly charged, complicated in design and implementation, and full of challenges and opportunities. Do the current work-related permanent and temporary admission systems well serve the interests of the country – access to needed talented foreigners and protection of its domestic skilled workers? Many experts argue that they do not (Martin 2006; Papademetriou and Yale-Loehr 1996). The permanent immigration system falls short of achieving these two goals for a number of reasons. Since the INA amendments in 1965, the United States has undergone significant economic, demographic, and social changes, yet the policies toward employment-based immigration has been revised only once in 1990. During the 1990s, the American economy went through a new economic transformation with no adjustment in the immigration system either. In other words, the current employment-based immigration system is completely unresponsive to changing market needs. Furthermore, processing delays, backlogs in labor certification and visa issuance, and percountry limits (it takes more than a year in general and three-four years in cases of India and China to bring a permanent immigrant worker to the United States) make both employers and foreign employees extremely frustrated with the system to say the least. Furthermore, the system also lacks effective employment enforcement mechanisms to protect the rights of domestic or foreign workers and effective sanctions against employers who do not follow the rules. Is the temporary admission system a solution? It certainly is a better and more flexible market-based mechanism, under which US employers have a chance to test the economic contribution of their foreign workers while these workers gain local experience and professional and social networks (Batalova 2006). Acting as a

36

Skilled Immigrant and Native Workers

transmission belt, the temporary system delivers already integrated immigrants. The problem is that the temporary system is complicated in design and implementation (having a lawyer is a must to navigate it) and does not discourage hiring foreigners as a way to cut down on costs (rather than out of a genuine need). Although it is a challenging enterprise to devise and implement a straightforward system to handle work-based immigration in the United States, the current permanent system is not delivering on its promise. Employing a temporary system as a crutch is not a long-term solution. Many alternatives have been offered to resolve this puzzle – expand permanent immigration and cut down the processing time, or use a feebased or auction-like system for permanent and temporary visas to name just two (Martin 2006; Morrison 2006) – but Congress too often relies on band-aid solutions rather than making substantial changes. The growing need for foreign labor (skilled and unskilled) and increasing competition for foreign workers and international students, perhaps, would make the time ripe for thinking hard and acting promptly if the goals of country’s well-being and national security are to be achieved in the 21st century.

CHAPTER 3

Definitions and Demographics: Highly Skilled Workers in the United States

Introduction I begin this chapter with a discussion of how researchers conceptualize the “highly skilled” and provide my own definition of this concept. I then present a demographic and socio-economic profile of highly skilled workers between ages 25 and 64 in the United States using data from the 5 percent Public Use Microdata Samples (PUMS) 2000 Census and the Bureau of Labor Statistics. Defining the “Highly Skilled”: Conceptual and Data Issues Scholars and politicians alike have repeatedly used the phrase “the best and the brightest” in relation to highly skilled immigrants. However, as a review of the international academic and policy literature reveals, no consistent definition or measurement of “highly skilled” exists (OECD 1995). The lack of consensus in the literature can be attributed to the difficulty in conceptualizing “highly skilled” and data scarcity to capture it. Researchers who study highly skilled workers (especially from a cross-country perspective) face a number of conceptual issues. First, it is difficult to define what makes a person highly skilled and then to operationalize this definition with the available data. Second, the recognition of skilled workers’ qualifications varies across countries. 37

38

Skilled Immigrant and Native Workers

That is, different policy and philosophical approaches to managing migration make it unclear who the highly skilled are in various countryspecific contexts (Mclaughlan and Salt 2002; OECD 2002; Solimano and Pollack 2004). The varying definitions make sound comparative research using international migration statistics challenging. Finally, the definitions of what characteristics make a worker “skilled” have also varied over time, reflecting changes in economic and labor market structures of national and global economies. The absence of appropriate data presents its own challenges to researchers of skilled and professional migration and its impacts. In the case of the United States, population censuses and labor force surveys such as the Decennial Census, Current Population Survey (CPS), and American Community Survey (ACS) provide the most readily available data on the US resident population. Although these sources have large sample sizes and are conducted using standard international classifications, they are cross-sectional. That is, they only present snapshots of peoples’ social and economic characteristics and experiences rather than a dynamic picture (for a critical review of available cross-sectional data, see Lowell 2004). In addition, the data sources often lack crucial information about immigrants such as their legal status (permanent resident, temporary migrant, or unauthorized), mode of admission (family, employment, or humanitarian-based), the percent of those who return home, or country of education. Researchers also lack data on the characteristics of the employers that hire immigrants (Lowell 2001b). The data limitations do not only impinge on academic scholarly debate, but also severely hamper informed policy making. For instance, whether the current US immigration system, with its greater emphasis on family reunification over employment-based immigration, has resulted in a higher inflow of low-skilled and poorly educated people is hotly debated. Some have argued that the United States’ emphasis on family reunification undermines the international competitiveness of the United States and imposes higher costs on the welfare system (Borjas 1999b). If one considers administrative data collected by the Immigration and Naturalization Service on the characteristics of admitted legal permanent immigrants, there appears to be some support for this view. Table 3.1 demonstrates not only that

Table 3.1 Legal Immigrants between Ages 18 and 64 by Class of Admission and Occupation, 1996 and 2000 Relatives of US citizens 1996 Number of immigrants Broad occupation (percent): Professional, technical, and kindred Executive and managerial Other occupations No occupation 2000 Number of immigrants Broad occupation (percent): Professional, technical, and kindred Executive and managerial Other occupations No occupation

Family preference

Employment preference

Diversity

Refugee/Asylee status adjusters

219,433

180,311

89,054

43,491

88,342

7.8 3.4 30.3 58.6

7.4 4.2 35.5 52.9

33.0 14.0 22.0 31.0

24.9 5.7 34.6 34.8

3.6 0.9 40.0 55.6

249,479

152,911

85,308

37,675

45,553

3.5 1.6 10.4 84.4

5.9 3.0 25.4 65.7

35.1 10.7 9.7 44.5

23.5 5.0 39.0 32.5

2.3 0.5 24.8 72.4

Note: Numbers reflect both new admissions and adjustments. The number of legal immigrants includes principal applicants and their dependents. Source: US Department of Justice, Immigration and Naturalization Service, Immigrants Admitted to the United States, 1996 and 2000 [producer]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor].

40

Skilled Immigrant and Native Workers

family-based immigrants (such as relatives of US citizens and permanent residents) are less likely to be in professional and management occupations than employment-sponsored immigrants, but also that their share in these occupations declined between 1996 and 2000. The problem is that administrative data give information about characteristics of admitted immigrants upon arrival but provide no insight into how these different categories of immigrants adjust after their arrival to the United States. Only a handful of studies (with special data access authorization from the immigration authorities) have been able to combine information on immigrant admission with Census data. These studies indicate that over time the main two groups of immigrants to the United States, family and employment-based, converge towards similar socioeconomic status and labor market outcomes (Lowell 1996; Sorensen, Bean, Ku, and Zimmermann 1992). The newly collected New Immigrant Survey – a nationally representative sample of new legal immigrants to the United States – promises to overcome some of the drawbacks of the Census and CPS data by including pre-migration and life course information. However, many skilled foreigners arrive to the United States on temporary visas, and currently there is no data that would permit analysis of labor market outcomes and impacts of these workers. As these examples illustrate, the lack of solid, high quality data sets, which incorporate admission statuses and economic and social characteristics and outcomes, hinders our understanding of the realities of immigration and, therefore, undermines the foundation of solid policy making. Defining the “Highly Skilled”: Practical Approaches Scholars address these conceptual and data problems using a variety of techniques. The two most often used definitions of what makes workers “highly skilled” are either “education-based” (otherwise known as “supply-based”) definitions and “occupation-based” (otherwise known as “demand-based”) definitions (Xie and Shauman 2003). Although using either higher education or occupation as a benchmark is convenient – both pieces of information are usually available in any survey – there are problems with each. In the case of “education-based” definitions favored by economists, not everyone with a college or higher degree does skilled work, especially in the case of immigrants. Often, college-educated foreign born, because of the non-transferability

Definitions and Demographics

41

of their credentials or limited English proficiency, may end up working in less skilled occupations. The opposite problem occurs with “demand-based” definitions of highly skilled, which demographers and sociologists often employ: Not everyone working in skilled and professional occupations possesses formal training and education. For example, Bouvier and Simcox (1994) found that 31 percent of nativeborn engineers and 39 percent of mathematicians and computer scientists did not have a university degree in 1990. Though the corresponding numbers for foreign born were smaller, they were still significant: 15 percent of foreign-born engineers and 23 percent of mathematicians did not possess a university degree in 1990. One attempt to streamline the definition of highly skilled workers across various national contexts is the Canberra Manual definition of Human Resources in Science and Technology (HRST) (OECD 1995). This measure, collaboratively constructed by the OECD and European Commission/Eurostat, is based on two conditions: Qualification (tertiary level of educational achievement or higher) and occupation (training/employment in a science and technology (S&T) field) (Auriol and Sexton 2002; OECD 1995). HRST are those who satisfy one of two conditions: “1) successfully completed education at the third level in a Science & Technology (S&T) field of study; and/or 2) not formally qualified as above, but [currently] employed in a S&T occupation where the above qualifications are normally required” (OECD 1995: 16). Although it is one of the most detailed definitional guidelines for comparative international statistics, the Canberra Manual definition has its limitations. If relevance to policy is important, one needs to emphasize that governments typically define “highly skilled” immigrants, not in terms of either education or occupation, but in terms of both education and occupation (Mclaughlan and Salt 2002). For example, the United States’ well-known specialty worker H-1B visa program is based on specialty occupations, which have a minimum degree requirement of a baccalaureate. Occupation is important not only because by its nature it excludes workers with little education, but also because it targets specific skills that are desired. The S&T occupations in the Canberra Manual definition can be seen as uniquely embodying technical skills that drive knowledge-based economies. However, restricting the meaning of “highly skilled” to S&T occupations makes the Canberra Manual definition too narrow as it disregards other highly skilled categories – managers, educators, and

42

Skilled Immigrant and Native Workers

healthcare providers – that are in equal demand by knowledge-based economies. Defining Highly Skilled for the Purposes of This Research I follow the approach offered by Lofstrom (2001), who combines both education and occupation in his definition of highly skilled, in an attempt to tap into both “supply” and “demand” dimensions of highly skilled workers. Lofstrom identifies people who are currently employed in occupations for which a college education is normally required as “highly skilled.” Therefore, I define skilled occupations as occupations where at least 55 percent of workers have a Bachelor’s degree or higher. Although the occupation “registered nurse (RN)” does not technically fit the above definition of highly skilled occupation, as only 52 percent of nurses have a college education, I include it in the analysis because of its theoretical importance. RNs comprise the most educated group among health care personnel besides doctors. Furthermore, a large proportion of RNs are immigrant women, a population of interest in this study. Using my definition of highly skilled, the data yield 93 highly skilled occupations which, for purposes of my analysis, I further sort into sixteen groups using the Standard Occupational Classification Manual (SOC) 2000 (for detailed composition of each group, refer to Appendix C). Given that the 2000 Census is not a random sample of the US population, I use sampling weights in producing population estimates. Applying weights to the Census data, I find that there are 23.3 million skilled workers in the United States. The next section discusses the projections of future needs and supplies of educated and skilled labor, followed by a demographic and socioeconomic profile of the highly skilled workers between ages 25 and 64 in the United States (unless otherwise stated, all tables are based on the 2000 Census data). Demand for and Supply of Highly Skilled Workers Since the 1970s, changes in the American economy, namely the decline of manufacturing and the dramatic increase in demand for high- and low-end services, has resulted in a U-shaped structure of job opportunities. Jobs in professional and technical sectors receive high remuneration, while manual-level jobs in agriculture, construction,

Definitions and Demographics

43

personal services, and the food industry are poorly paid (Bean, Lee, Batalova, and Leach 2004). This bi-modal pattern of job distribution seems likely to continue in the future. For example, according to the Bureau of Labor Statistics (BLS), for the next ten years the two fastestgrowing groups of occupations will be professional occupations and low-end service occupations; indeed, BLS projects that these two occupational groups will account for more than half of total job growth between 2002 and 2012 (Bureau of Labor Statistics 2004a). Immigrants are disproportionately represented in these two fast growing occupational groups. In order to better understand what role immigrants will play in the future of the bi-modal American economy, a closer examination of projected labor demand is warranted. Overall, BLS projects continuing job growth in the American economy and expects total employment to grow by 22.2 million jobs between 2000 and 2010. Such growth would mean that by 2010, 167.8 million individuals would be employed in the United States. On average, growth rates are projected to be faster for occupations that rely on an educated workforce (an associate degree or higher) than for occupations that require no education or training (Hecker 2001). According to BLS projections, six out of ten of the fastest growing occupations projected for the period between 2002 and 2012 rely on workers with at least an associate or Bachelor’s degree (Bureau of Labor Statistics 2004b). Nine out of ten of these jobs are health care or computer-related. In addition, as never before, persons with greater levels of education are handsomely rewarded by the labor market: College graduates are paid almost twice as much as those with only a high school diploma who otherwise have similar characteristics (i.e., race, sex, age, industry, place of residence, etc.) (Horrigan 2004). While the demand for skilled labor will only continue its upward trend, there are concerns whether there will be an adequate supply of workers (due to a smaller size of the pre-working age cohorts) and the types of skills needed in the labor market (due to inability of the US educational system to produce a sufficient number of educated workers) (Ellwood 2001). As Chapter 2 on the history of labor migration policies indicates, immigration has been a popular and successful method for addressing labor shortages for decades. This has especially been the case for occupations in which it is difficult to find domestic qualified workers. But what do we know of the current skilled workforce? I turn next to the discussion of the demographic and socioeconomic characteristics of immigrant and native highly skilled.

44

Skilled Immigrant and Native Workers

Highly Skilled Workers in the United States: Demographic Characteristics On average, one out five members of the US civilian labor force is a worker in a highly skilled occupation.12 Of the 23.3 million workers in highly skilled occupations, more than three-quarters have a college education. The foreign born constitute 11.9 percent of all workers in skilled occupations compared to 13.5 percent among the general labor force. However, as Map 3.1 indicates, the highly skilled are geographically concentrated. Highly skilled workers as a percent of the total civilian labor force range from 14.2 percent in Nevada to more than a third in Washington DC. Half of the US states, mainly from the North Central, Central, and South East regions, are similar to Nevada in that skilled workers represent well below 20 percent of all state workers. In contrast, in Connecticut, Massachusetts, Maryland, and New Jersey, more than one quarter of the state’s civilian labor force is highly skilled, at least in part owing to their historical positions as industrial centers and educational hubs. Map 3.2 focuses on the immigrant component of the skilled workforce. It shows that the geographic concentration of foreign born among highly skilled is also far from equal. In fact, the share of skilled foreign-born workers varies even more significantly across states, from only 2.0 percent in Wyoming to 23.5 percent in California. The patterns of geographic concentration of the overall foreign-born population and the highly skilled foreign born are largely correlated with one another. The top immigrant receiving states (California, New York, Florida, and New Jersey) are also states that have the highest percentage of foreigners among the skilled labor force. For the last thirty-forty years, these states have received the lion’s share of all immigrants arriving to the United States, many of whom were highly educated and skilled (Bean, Lee, Batalova, and Leach 2004). This uneven geographical distribution reflects the fact that immigrants, regardless of their skill level, respond to the economic and social attractiveness of certain states and cities.

Map 3.1 Highly Skilled Workers in Civilian Labor Force by State (%), 2000

Map 3.2 Foreign Born in Highly Skilled Labor Force by State (%), 2000

Definitions and Demographics

47

Table 3.2 switches the focus from the geographic distribution to the demographic portrait of the highly skilled workers. As a way to capture the labor market experiences and outcomes of immigrants who came in the aftermath of the Immigration Act of 1990, I distinguish between two groups of foreign born, recently arrived and earlier immigrants. Recent immigrants are defined as those foreign born who arrived in the United States between 1990 and 2000, while earlier immigrants are defined as persons who arrived before 1990. Table 3.2 Selected Social and Demographic Characteristics of Native and Immigrant Workers Recent Earlier Native immigrants immigrants born Population estimates (thousands) 957.0 1,817.0 20,567.0 Mean age (years) 35.2 43.4 42.4 Currently married (%) 68.7 72.6 69.4 Women (%) 39.1 46.4 51.6 Race and ethnicity (%) Non-Latino white 33.7 30.9 87.5 Non-Latino black 6.2 9.5 7.1 Non-Latino Asian 48.2 40.3 1.4 Non-Latino other race 1.6 1.3 1.0 Latino 10.4 17.9 3.0 The majority of workers in skilled occupations, 20.6 million or 88.9 percent, are native born. Among the foreign born, earlier immigrants comprise 1.8 million or 7.5 percent and recent immigrants comprise almost one million or 3.7 percent. The recent immigrants are the youngest group; on average they are seven years younger than either earlier immigrants or native born. Men outnumber women among recent immigrant workers, suggesting that, at least among skilled persons, immigration is a young men’s game. The highest proportion of currently married persons is among earlier immigrants. The overwhelming majority of native-born professionals are nonLatino whites (87.5 percent), while racial/ethnic minorities are underrepresented: Blacks comprise 7.1 percent of native-born skilled workers, followed by Latinos (3.0 percent) and Asians (1.4 percent).13 In contrast, among foreign-born highly skilled workers, Asians and

48

Skilled Immigrant and Native Workers

whites make up about three-quarters. The proportion of whites and Asians among recent immigrants is higher than among earlier immigrants, whereas the proportion of blacks and Latinos is lower. However, compared to the native highly skilled, foreign-born Asians and Latinos stand out; their shares among both recent and earlier immigrants are much higher. In addition, the shares of Asians and whites among the highly skilled immigrant workforce is disproportionately higher compared to those among the total civilian labor force. Table 3.3 shows the place of origin of skilled immigrants by period of arrival, illustrating changes in US policies toward total and skilled immigration over time. Thanks to the national origins quota legislation that virtually barred migration from Asia, before 1965 the overwhelming majority of immigrants in general and 44.8 percent of skilled immigrants came from Europe. In fact, 17.1 percent of all skilled immigrants arrived from one country – Germany. Prior to 1965, Latin America was the second most important source of skilled foreigners; a quarter of all skilled immigrants arrived from Central and South America. Pre-1965, Cuba was the largest single-country source of skilled immigrants from the region. This was a result of the mass exodus of the highly educated Cuban professionals and elites who fled from the Cuban Revolution of 1959-1962 and found a warm reception in the United States, which opposed Cuba’s new communist regime (Rumbaut 1996). Prior to 1965, Asian countries accounted for 17.3 percent of highly skilled immigrants. However, when the restrictive national origins quotas were abolished, Asia quickly became a major source of skilled immigrants. Philippines, China, and India accounted for a quarter of all skilled immigrants who arrived between 1965 and 1979. This was more than all European countries combined, and equaled the share of skilled immigrants from Latin and Central America. The predominance of Asian highly skilled migration continued to even a greater degree after 1980. The share of skilled foreigners from Africa also increased after 1980, although to this day it stays fairly small. During the 1990s, almost a million skilled workers, more than in any previous decade, arrived to the United States. Half of them came from Asia, with China and India being the leading countries of origin. With 23.3 percent, Europe overtook Latin America (13.8 percent) in the percent of skilled newcomers.

Definitions and Demographics

49

Table 3.3 Highly Skilled Immigrants by Country/Region of Birth and Period of Arrival Country/Region of Birth Number (thousands) Total percent Europe UK and Ireland Germany Other Northern and Western Europe Former Soviet Union Southern and Central Europe Asia Philippines China and Taiwan Vietnam India Korea Japan Middle East Other Asia Northern America Latin America Cuba Other Caribbean Mexico Other Central and South America Africa Oceania Elsewhere/at sea

Pre- 1965- 1980- 19901965 1979 1989 2000 346.3 881.2 786.0 974.6 100.0 44.8 8.7 17.1

100.0 18.8 5.0 4.4

100.0 15.6 4.4 1.7

100.0 23.3 5.1 2.6

8.9 1.2 8.8 17.3 2.4 3.7 0.1 1.5 1.0 4.6 3.1 1.1 9.3 25.7 6.9 6.8 5.1

3.7 1.5 4.2 46.4 9.3 7.9 4.6 7.7 4.5 2.1 7.3 3.1 4.1 24.9 2.6 9.3 5.1

2.9 2.6 4.0 51.1 9.1 13.3 4.4 9.2 3.5 1.2 6.4 4.0 3.1 23.0 1.1 9.0 4.1

4.4 6.8 4.4 50.2 6.0 13.1 1.7 16.6 2.7 2.8 4.4 2.9 6.1 13.8 0.7 4.2 2.9

6.9 1.7 0.7 0.5

7.9 4.5 0.8 0.4

8.9 6.2 0.7 0.3

6.0 5.4 1.1 0.2

Note: Asia includes all countries of the Middle East except Egypt, which is part of Africa; Northern America includes Canada, Bermuda, and Greenland.

50

Skilled Immigrant and Native Workers

Increased immigration from Europe was partly due to the end of the Cold War. The percentage of skilled foreigners arriving to the United States from the former Soviet Union rose from 2.6 percent in the 1980s to 6.8 percent in the 1990s. Foreign and Native Born Compared: Human Capital and Economic Characteristics How do skilled immigrants and natives compare in terms of education and occupations? The overall immigrant population in the United States exhibits an educational distribution that is very different from that of natives. On average, the native-born population is more educated: Only 17 percent have no high school diploma compared to 38 percent among foreign born (Bean, Lee, Batalova, and Leach 2004). The situation is different on the upper end of the educational continuum, where immigrants are as likely to be college educated as their native counterparts. Moreover, as Table 3.4 shows, among skilled workers, recent immigrants are more educated than either native born or earlier immigrants: Almost half of recent skilled immigrants hold a higher level degree (i.e., Master’s, Doctorate, or Professional) compared to 43.8 percent among earlier skilled immigrants and 36.1 percent among skilled native-born workers. This finding is not surprising since many recent immigrants join the labor force either right after completing their graduate studies in the United States or arrive under the temporary or permanent employment visas that require a high level of education and training. Despite their high levels of formal education, workers not born in the United States lag behind in their knowledge of English. Not surprisingly, more recently arrived workers have a poorer command of the language: 5.8 percent of them self-report that they speak little or no English. This is compared to only 2.4 percent among earlier immigrants and less than 0.3 percent among natives. Increased immigration from non-English speaking countries (mostly from Asia and Latin America) and shorter time spent by recent immigrants in the United States are two possible explanations for this difference. Additionally, since earlier immigrants tend to have come to the United States at younger ages, they have had more time to assimilate and learn English. Another factor that may contribute to the differences in language proficiency between the two groups of foreign born is that many recent immigrants are employed in science and engineering rather than in

Definitions and Demographics

51

education, humanities, law, or business. Since science and engineering rely on the language of numbers and formulas much more than on spoken English, employers in these fields may put much less of a premium on a high degree of English fluency. Table 3.4 Educational Attainment, English Fluency, and Age of Arrival by Nativity of Highly Skilled Workers (%), 2000 Recent Earlier Native immigrants immigrants born Degree (%) No college Bachelor's Master's Doctoral/Professional

13.0 37.1 29.1 20.8

19.9 36.3 22.6 21.2

23.7 40.2 23.1 13.0

Self-reported spoken English fluency (%) Not at all Not well Well Very well Only English

0.9 4.9 22.0 53.4 18.8

0.3 1.9 12.7 57.1 28.0

0.0 0.3 0.5 4.9 94.3

Age at arrival (years)

31.0

20.1

-

Table 3.5 takes a closer look at the occupational distribution of skilled workers by nativity. Almost one in two recent highly skilled immigrants is either in information technology (IT), sciences, or engineering, compared to a third among earlier immigrants and less than a fifth among the native born. In contrast, the skilled native born are more likely to be in management or business occupations, followed by earlier skilled immigrants, and then by recent skilled immigrants. The native born are also more likely to be in education than either of the two immigrant groups. Earlier skilled immigrants tend to be more present in health care occupations. For example, 6.8 percent of earlier skilled immigrants are physicians and surgeons compared to 5.4 percent of recent skilled immigrants and 2.4 percent of skilled native workers. Similarly, earlier skilled immigrants are more likely to be registered nurses.

52

Skilled Immigrant and Native Workers

Table 3.5 Percent Distribution of Occupations by Nativity, 2000 Recent immigrants

Earlier immigrants

Native born

Number (thousands)

957.3

1,816.9

20,567.4

Total percent

100.0

100.0

100.0

9.9

12.9

15.6

9.0 5.3

11.8 3.0

10.3 2.5

17.8 0.7

7.8 0.4

4.6 0.3

0.6 10.1 7.6

0.6 11.3 3.5

0.6 7.4 2.0

Management Business and financial operations Computer scientists Computer programmers and engineers Computer technical support Math scientists and engineers Architects and engineers Life sciences: researchers

Social sciences: researchers 1.2 1.1 1.4 Physicians and surgeons 5.4 6.8 2.4 Registered nurses 7.5 10.3 9.2 Other health practitioners 3.4 4.3 4.2 Healthcare technicians 1.5 1.9 1.3 Education and training 12.2 13.2 21.4 Other professionals 6.5 9.5 14.6 Non-professional occupations 1.4 1.7 2.2 Note: For a detailed list of occupations within the above occupational groups, refer to Appendix C.

The next two tables explore occupational distribution by gender (Table 3.6) and race and ethnicity (Table 3.7). Regardless of nativity, men are more likely to work in managerial, IT, and engineering occupations as well as practice medicine (see Table 3.6).

Table 3.6 Percent Skilled Workers by Occupation, Nativity, and Gender, 2000

Number (thousands) Total percent Management Business and financial operations Computer scientists Computer programmers and engineers Computer technical support Math scientists and engineers Architects and engineers Life sciences: researchers Social sciences: researchers Physicians and surgeons Registered nurses Other health practitioners Healthcare technicians Education and training Other professionals Non-professional occupations

Recent immigrants Earlier immigrants Male Female Male Female 583.1 374.1 974.7 842.2 100.0 100.0 100.0 100.0 11.8 6.8 16.2 9.2 7.2 11.7 10.0 13.9 6.7 3.0 3.8 2.1 21.9 11.5 10.1 5.1 0.8 0.5 0.4 0.3 0.6 0.6 0.7 0.6 13.9 4.3 18.6 2.9 7.8 7.3 4.1 2.8 1.1 1.3 1.0 1.3 5.9 4.8 8.9 4.3 1.8 16.3 1.7 20.3 2.3 5.1 3.5 5.2 0.9 2.4 1.2 2.7 10.1 15.5 9.5 17.5 5.5 8.0 8.2 10.9 1.7 0.9 2.3 1.0

Native born Male Female 9,947.0 10,620.5 100.0 100.0 19.8 11.7 10.5 10.0 3.4 1.7 7.0 2.4 0.3 0.3 0.7 0.5 13.6 1.6 2.8 1.2 1.3 1.5 3.7 1.2 1.4 16.6 3.7 4.7 0.9 1.8 13.0 29.3 14.5 14.7 3.5 1.0

Table 3.7 Percent Skilled Workers by Occupation, Nativity, and Race and Ethnicity, 2000 Recent immigrants Early immigrants White Black Asian Latino White Black Asian Latino

Number (thousands) Total percent Management Business operations Computer scientists Computer programmers Computer technical support Math scientists and engineers Architects and engineers Life sciences: researchers Social sciences: researchers Physicians and surgeons Registered nurses Other health practitioners Healthcare technicians Education and training Other professionals Non-professional occupations

322.4 100.0 14.6 8.6 4.1 13.8 0.4 0.6 10.6 8.4 1.7 5.0 5.9 3.3 1.1 12.8 7.1 2.0

59.0 461.6 100.0 100.0 5.6 6.6 12.2 8.5 3.4 6.9 5.6 24.9 0.5 1.0 0.8 0.7 6.3 10.4 2.7 8.5 1.1 0.8 5.5 5.5 20.9 7.6 4.2 3.2 2.7 1.6 13.8 9.7 13.1 3.4 1.8 0.8

99.2 100.0 12.1 10.4 3.2 6.4 0.3 0.3 9.3 3.9 1.5 6.2 4.3 3.7 1.7 20.8 13.9 2.1

561.4 100.0 17.4 9.5 2.4 6.5 0.3 0.4 11.7 3.3 1.6 6.0 7.2 4.3 1.2 16.1 10.0 2.3

172.6 733.0 100.0 100.0 8.6 9.5 13.4 13.4 2.7 3.8 3.9 11.2 0.2 0.5 0.9 0.8 5.7 13.8 1.9 4.8 0.9 0.8 4.0 8.9 22.6 11.5 4.2 4.7 2.1 2.4 13.8 7.4 13.7 5.3 1.5 1.3

White

Native born Black Asian Latino

325.3 18,001.8 1,466.0 278.5 100.0 100.0 100.0 100.0 15.2 16.0 12.9 11.8 11.3 10.2 10.6 12.4 2.5 2.5 3.1 3.3 4.2 4.7 4.0 7.5 0.2 0.3 0.4 0.3 0.6 0.6 0.7 0.8 7.7 7.7 4.0 10.3 1.9 2.1 1.0 3.0 1.2 1.4 0.9 1.3 4.8 2.4 1.6 6.5 6.5 9.3 9.8 5.5 3.5 4.3 3.0 6.3 1.8 1.2 2.2 1.6 21.0 21.1 24.1 15.7 15.8 14.0 20.7 12.1 1.8 2.3 1.2 1.7

616.0 100.0 14.7 10.3 2.8 3.8 0.3 0.7 6.3 1.4 1.1 2.0 7.2 3.6 1.7 24.8 17.4 1.9

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By contrast, women are more likely to be teachers, registered nurses, health practitioners, or therapists. A combination of nativity and gender does play a role in the choice of professions. For example, although recent skilled immigrant women are half as likely to be employed in IT occupations as recent skilled immigrant men, they are more likely to be employed in IT occupations than native-born or earlier immigrant workers of either gender. Skilled native men have the highest propensity of all groups to be in managerial and business/financial operations occupations (30 percent), while half of all skilled American-born women are in teaching or health care (Table 3.6). In contrast, half of all skilled recent immigrant women are in management, business, IT, or sciences. Earlier skilled immigrant men are the most likely to be physicians and surgeons, while women have the highest likelihood of being nurses. Table 3.7 tells an interesting story about the interplay between nativity and race and ethnicity. Asians are clearly more likely to be in IT, sciences or engineering: 53 percent of recent skilled Asian immigrants, 36 percent of earlier skilled Asian immigrants, and 26 percent of skilled native Asians are in these occupations. Native black and Latino skilled workers tend to occupy much different professions. They are more likely to be educators, social workers, or librarians. Regardless of nativity, whites are more likely to be managers while blacks are more likely to be in nursing (the majority of whom are women). Table 3.8 shows in which industries each of the three groups of highly skilled is likely to be employed (for more detailed data on industry distribution by nativity see Appendix D). Skilled workers are much more likely to work in professional service industry, regardless of nativity. In general, women have a greater tendency to be employed in professional services (especially in the educational, health, and social science fields) compared to men. In contrast, men are much more likely to be engaged in manufacturing work, construction, trade, and transportation. Recent immigrants are largely underrepresented in public administration, as jobs in this sector often require US citizenship. The above tables illustrate substantial variations among native and immigrant skilled workers in geographical concentration, human capital characteristics, and occupational and industry distribution. How do these variations translate into workers’ economic experiences and outcomes?

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Table 3.8 Percent Distribution of Immigrant and Native Skilled Men and Women by Industry, 2000

Recent immigrants Manufacturing Professional services FIRE* Public administration Other industries Total percent

Total 14.1 60.2 6.4 2.0 17.4 100.0

Male 17.8 54.5 6.7 1.7 19.2 100.0

Female 8.1 69.0 6.1 2.2 15.7 100.0

Earlier immigrants Manufacturing Professional services FIRE* Public administration Other industries Total percent

Total 12.2 59.1 7.3 4.5 16.8 100.0

Male 17.4 49.8 7.7 4.1 20.3 100.0

Female 6.2 69.9 6.9 3.9 12.8 100.0

Native born Manufacturing Professional services FIRE* Public administration Other industries Total percent

Total 9.2 62.1 6.7 5.3 16.9 100.0

Male 14.6 49.7 8.2 5.6 21.9 100.0

Female 4.1 73.7 5.2 5.0 12.1 100.0

Note: *FIRE includes finance, insurance, and real estate.

Table 3.9 gives some preliminary answers.14 According to the table, native skilled workers are more likely to work full time, work longer hours, and have more work experience. Additionally, native skilled workers are less likely to be unemployed or enrolled in college and university than recent immigrants. Earlier immigrants are similar to native born in terms of their potential work experience as well as working patterns (e.g., average hour and weeks worked in 1999, likelihood of working full time). The higher education of recent immigrants does not necessarily translate into better achievement in the

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labor market at all levels. Recent immigrants are significantly more likely to be unemployed and less likely to be working full time compared to other workers. In addition, recent skilled immigrants work three fewer weeks on average than the other two groups. Table 3.9 Economic Characteristics of Skilled Workers by Nativity, 2000 Recent Earlier Native immigrants immigrants born Working full time (%) 85.8 88.6 87.8 Currently enrolled in school (%) 15.7 9.7 8.4 Average potential experience 12.2 20.6 20.0 Median potential experience 10.0 20.0 20.0 Self-employed (%) 4.2 11.0 9.5 Unemployed (%) 2.6 2.1 1.5 Average hours worked in 1999 40.8 42.3 42.5 Average weeks worked in 1999 44.8 47.8 47.8 Note: Full time refers to working more than 35 hours in a week; enrolled in school refers to being currently in college or university; potential experience is defined as worker’s age minus years of education minus six; persons were classified as unemployed if at the time of Census they were neither ‘‘at work’’ nor ‘‘with a job but not at work’’ during the reference week, but were looking for work during the last four weeks, and were available to start a job.

The average potential experience of recent immigrants is lower as well. Compared to the other two groups, 50 percent of recent immigrants have ten or fewer years of potential experience compared to almost twenty years for other foreign and native-born skilled workers. The potential experience numbers have to be interpreted with caution, however. Due to the nature of available data, it is impossible to capture one’s work experience perfectly. A widely used approximation is calculated as a “person’s age minus years of education minus six.” However, recent immigrants are younger on average than the other two groups and have more years of education. Therefore, it makes sense that their potential work experience is lower. As Lopez (2003) points out, the information technology industry lobbied for an increase in the number of H-1B workers (a large proportion of recent immigrants) by claiming that they needed workers with up-to-date and often highly

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specialized training and experience. Many of the new H-1B workers were recent graduates of US universities. Table 3.9 indicates that both earlier and recent immigrants are more likely to be unemployed. However, the likelihood of being out of work depends on one’s occupation. Table 3.10 reports the number of workers in the civilian labor force and the unemployment rate by nativity and occupation. Among US-born skilled workers, the highest number of unemployed is among managers and workers of other professions. However, it is computer scientists/programmers and engineers who have the highest likelihood of being unemployed: 2.3 and 2.1 percent are unemployed, respectively. Although earlier immigrants are more likely to report being physicians and surgeons than natives, the unemployment rate among earlier immigrant doctors (0.9 percent) is almost twice as high as that of native doctors (0.5 percent), but the unemployment rate for doctors is the lowest unemployment rate of any occupation for earlier immigrants. Earlier immigrants who are social scientists have the highest rate of unemployment (3.0 percent), closely followed by those who are computer scientists (2.9 percent), then by computer programmers and other professionals (2.7 percent each). Compared to the other two groups, recent immigrants have the highest unemployment rates in all occupations, with exception of computer, math, and life sciences. The above tables demonstrate substantial nativity differences in the characteristics of the workers and in their labor market experiences. How do the immigrant and native workers compare in their economic outcomes? Previous studies indicate that foreign-born professionals are better paid, on average, than their native-born counterparts (Bouvier and Simcox 1994). Table 3.11, which shows how well workers in skilled occupations are remunerated for their work, seems to support this overall finding. However, again one has to pay attention to the differences in labor market outcomes between earlier and recent immigrants. The table shows that earlier immigrants are doing the best in terms of annual earnings. Their average and median annual earnings, regardless of how many weeks and hours they worked in 1999, are higher than those of recent immigrants and natives. Recent skilled immigrants who are employed make $10,000 less per year than earlier immigrants and about $1,700 less per year than native workers. Once the sample is restricted to full-time full-year workers (i.e., those working at least 35 hours a week and 50 or more weeks a year),

Table 3.10 Number of Workers in Civilian Labor Force (in thousands) and Rate of Unemployment (percent) by Nativity and Occupation, 2000 Occupation Management Business and financial operations Computer scientists Computer programmers and engineers Computer technical support Math scientists and engineers Architects and engineers Life sciences: researchers Social sciences: researchers Physicians and surgeons Registered nurses Other health practitioners Healthcare technicians Education and training Other professionals Non-professional occupations

Recent immigrants Earlier immigrants Native born Number Rate Number Rate Number Rate 94.3 2.7 234.7 2.1 3,214.3 1.7 85.7 3.4 214.1 2.5 2,107.5 1.8 50.3 1.7 54.3 2.9 520.7 2.3 170.8 2.1 140.8 2.7 949.3 2.1 6.6 3.8 6.3 1.5 59.8 1.7 6.0 11.4 2.4 125.2 1.6 0.7 97.1 2.2 205.2 2.1 1,516.9 1.5 72.7 1.4 63.4 1.9 405.7 1.8 11.5 3.3 20.8 285.9 1.5 3.0 51.9 2.7 122.7 495.0 0.9 0.5 71.3 2.3 186.9 1.5 1,900.4 1.3 32.5 2.7 78.1 1.1 862.7 1.0 14.3 3.1 34.2 2.1 273.0 1.8 116.9 3.4 240.1 1.9 4,397.7 0.9 62.2 172.3 2.7 3,006.4 1.7 4.0 13.3 3.5 31.5 2.8 447.1 1.7

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the average earnings of recent immigrants are the same as natives and about $6,000 less than earlier immigrants. Table 3.11 Average and Median Annual Earnings of Highly Skilled Workers, 2000

Recent Earlier immigrants immigrants

Native born

Employed workers Number of workers (thousands) Median earnings ($) Average earnings ($)

869.3 42,800 53,562

1,566.2 18,222.0 50,000 42,700 63,144 55,317

Full-time, full-year, employed workers Number of workers (thousands) Median earnings ($) Average earnings ($)

577.6 50,000 63,070

1,165.2 12,900.3 55,000 48,600 69,902 63,224

Note: The figures shown in this table are for workers who were not selfemployed and reported positive earnings in 1999.

Figures 3.1 to 3.3 return us to the original question motivating this study: Does the greater presence of immigrants in skilled occupations negatively affect the earnings of native highly skilled workers? These scatterplots (for the data behind these scaterplotts, see Appendix E) show the average earnings for the three groups of skilled workers by occupation and percent foreign born in occupations (the average earnings are calculated for full-time workers who worked for 50 or more weeks in 1999, earned positive income, and were not selfemployed). The preliminary answer to the negative impact question is “no.” For example, native-born physicians report higher earnings ($150,300) than their immigrant counterparts, despite the fact that the percent of foreign born among physicians and surgeons is the highest (26 percent) among all highly skilled occupations. In contrast, US-born teachers and educators make about $39,000 per year working in jobs with less than 10 percent foreign born. I have to point out that these scatterplots do not control for any other factors known to affect one’s

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earnings (i.e., individual and job characteristics). I will discuss these factors and control for them in the Hierarchical Linear Modeling analysis presented and discussed in the next two chapters. Conclusion My profile of foreign-born skilled workers leaves little doubt that these individuals are indeed among the best and the brightest. First, the foreign born in skilled occupations are better educated and are more likely to possess higher degrees than their native counterparts. Second, immigrants are much more likely to be in the most competitive occupations, being three times as likely as natives to be among hightech workers, twice as likely to be physicians and surgeons, and four times as likely to be life scientists. Little is known, however, how these patterns of education, occupation, and geographical distribution translate into labor market outcomes of immigrants and their native-born colleagues. Within certain occupations, the reliance on immigrants raises questions about their impact on earnings of native workers. Does the abundant supply of foreign talent depress wages of native and foreign-born workers? In order for policymakers to adequately understand and design immigration and labor market policies, they must have convincing answers about possible implications of skilled immigration. The empirical findings of the next two chapters shed light on the labor market effects of skilled immigration and point to areas for future research.

Figure 3.1 Average Earnings (in thousands of dollars) of Native-born Skilled Workers by Occupation 160

Physicians

140

Earnings ('000)

120 100 80

Computer scientists

Managers

Computer programmers

60

IT support 40

Life scientists

Nurses Educators

20 0 6

9

12

15

18

Percent foreign born in occupations

21

24

27

Figure 3.2 Average Earnings (in thousands of dollars) of Earlier Immigrant Skilled Workers by Occupation 160 140

Physicians

Earnings ('000)

120

Managers

100

Computer programmers

IT support

80 60

Life scientists Computer scientists

Educators

40

Nurses

20 0 6

9

12

15

18

Percent foreign born in occupations

21

24

27

Figure 3.3 Average Earnings (in thousands of dollars) of Recent Immigrant Skilled Workers by Occupation 120

Managers 100

Computer scientists

Earnings ('000)

80

Physicians IT support Computer programmers

60

Life scientists

40

Educators Nurses

20

0 6

9

12

15

18

Percent foreign born in occupations

21

24

27

CHAPTER 4

The Tipping Point of the Brain Gain: Job Context and Earnings Competition with Natives

Introduction The impact of immigrants on American society has long occupied a central position in public policy debates about immigration (Bean and Bell-Rose 1999; Bean and Stevens 2003). Recent emphasis on the importance of knowledge and skills in post-industrial economies has generated greater scrutiny of the highly skilled component of US immigration flows. In developed economies, proponents of an increase in the flow of highly skilled immigrants – a “brain gain” – point to domestic labor shortages and the significant economic and social contributions made by skilled and educated workers who are immigrants. Opponents argue that highly skilled immigrant labor undercuts opportunities for the domestic workforce by displacing natives from jobs, driving down wages, and undermining working conditions. Both sides discuss these impacts of skilled immigrants in the context of higher education, science, labor, and national security priorities (Lowell 1999; North 1999; UC Irvine and The Merage Foundation 2005). Research Agenda College-educated immigrants constituted about one-third of all US immigrants who arrived in the 1990s, up from one-quarter of those who 65

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arrived in the prior decade (Kaushal and Fix 2006). A small but growing number of studies attempt to explain the composition, contributions, and impacts of these skilled immigrants (Borjas 2005; Cornelius, Espenshade, and Salehyan 2001; Smith and Favell 2006). In this chapter, I examine individual and structural determinants of earnings among three groups of skilled workers: Native born, earlier immigrants, and recent immigrants. While I recognize that the impacts of immigration might be different in the short versus long run as illustrated in Figure 1.1, this chapter is limited to the immediate impact of skilled immigrants on native earnings. I focus on native earnings because the “competition question” raises important social equity issues and continues to be a central political and public preoccupation with regard to immigration. Understanding Labor Market Impacts of Immigrants Theoretical Explanations Economists and sociologists use different lenses to analyze immigrants’ impacts on labor market outcomes of native workers. The former mainly focus on whether the foreign born serve as complements to or substitutes for native workers (Borjas 1999a). The latter consider the complementarity-substitution dynamics in the socioeconomic structural context that affects the nature and magnitude of the economic influences of immigrant labor (Bean, Gonzalez-Baker, and Capps 2001). Economists tend to provide two main answers to the economic competition question. Classical economic theory suggests that immigrants depress wages and take jobs away from native workers because the immigrant workers entering the labor market cause a supply shock, namely, a sudden decrease in wages of existing workers due to an arrival of new (immigrant) workers. Two main assumptions underline the classical explanation: Perfect substitutability of immigrant for native workers and a limited number of positions available to workers in a given labor market. A more contemporary line of economic thinking recognizes that immigrants are often not perfect substitutes for native workers because they may not have the adequate skills, education, English language capabilities, or legal status. This

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new line of economic reasoning also takes into consideration the fact that labor markets are not closed; rather it understands labor markets as dynamic entities, which respond to changes in the workforce composition either through creating more jobs or by encouraging some workers to seek out more suitable labor markets (e.g., move to another city or state) (Borjas 1999a; Smith and Edmonston 1997). Economists typically ignore the fact that economic competition does not take place in a vacuum. Sociologists, however, pay close attention to the context of changing economic and social realities. Thus, Piore, who developed the segmented labor market theory, argues that the structure of the labor market itself influences the demand for and the impacts of immigrants. He maintains that migrants – immigrants and natives from rural areas who migrated to cities – “appear to be coming to take a distinct set of jobs, jobs that the native labor force refuses to accept” because of low pay and poor working conditions (Piore 1979: 33). Piore defines the jobs, which are rejected by the native population and in which migrants tend to work, as the secondary sector. In contrast, he defines higher skilled and more prestigious jobs, in which the native population is concentrated, as the primary sector. According to Massey, Durand, and Malone (2002), the labor market segmentation between primary and secondary sectors described by Piore occurs for three reasons: 1.

Structural inflation causes wages to reflect not only labor supply and demand but also a job’s status and prestige. An increase in wages at the bottom of the occupational hierarchy, implemented in order to attract workers, eventually leads to an increase in wages in occupations at the higher levels. To keep the labor costs down, employers rely on cheaper solutions. One common solution is to hire immigrants who for a variety of reasons are willing to accept lower wages.

2.

Social constraints on motivation make native workers resistant to poorly paid and demeaning secondary-sector positions. In contrast, immigrants’ social standing is often determined by families and friends in their countries of origin who view these immigrants’ ability to earn money and send it home as more valuable than the

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Skilled Immigrant and Native Workers prestige of jobs immigrants hold in the host country (a so-called dual frame of reference).

3.

Due to their formal education and institutional experience and training, workers in the capital-intensive primary sector are valuable to employers and are offered stable and well-paid jobs. Such workers become substantial investments – similar to capital – in employers’ eyes. On the other hand, it is easier for employers to lay off secondary-sector workers whose labor is more replaceable. The duality of labor and capital makes it difficult to attract natives to such jobs; the solution is to hire immigrants.

The rough division of the labor market into primary and secondary sectors does not account for finer distinctions within any given labor market. In fact, the same labor market segmentation logic can be applied within the primary sector. The existence of corporate “glass ceilings,” which impede the upward mobility of some workers, suggests that a form of segmentation exists within the highly skilled labor market as well (Woo 2000). Indeed, it has been argued that foreign skilled workers provide the perfect labor pool for the lower rungs of the occupational ladder within the primary sector: They are qualified to perform complex tasks but for a variety of legal, social, and economic reasons employers can pay them less and promote them at much slower rates (Fernandez 1998; Tang 1993; Woo 2000). Hagan and McCollom’s ethnographic research (1999) in Texas illustrates this point empirically. The study describes a case of twenty H-1B Filipino programmers working in a small “underground, hightech sweatshop” supervised by three white natives. Despite poor working conditions, including no overtime pay, arbitrary promotions, and underutilization of the workers’ previous experience, these H-1B temporary workers were willing to continue their work. From their study, the authors conclude that the existence of high-skilled sweatshops not only depresses wages of native workers and displaces them from jobs, but also leads to the abuse of immigrant workers. Moreover, as a status composition theoretical perspective argues, occupations – which employ a disproportionate share of workers whose labor employers devalue – also become devalued (England 1992; England, Reid, and Kilbourne 1996; Huffman and Velasco 1997). For

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example, Tomaskovic-Devey (1993) finds that the gender composition of an occupation accounts for 55 percent of the difference between men and women’s hourly wages. Similarly, Catanzarite finds a wage penalty for US-born and earlier Latino immigrant workers who are employed in so-called “brown-collar” occupations (i.e., with a large share of recent Latino immigrants) (Catanzarite 1998; Catanzarite 2003b). The differences in pay stem from the bias (gender, racial, or nativity) in the way wages are set beyond the effect of other characteristics (England 1992). Furthermore, studies of gender inequality show that, regardless of gender, men and women alike earn less if they work in occupations with a high proportion of women (Baron and Newman 1990; England 1992), although within such workplaces men are likely to earn more and hold positions of authority (Cohen and Huffman 2003a). These findings call for research to analyze earnings not only in terms of workers’ human capital and other individual characteristics but also in terms of characteristics of the jobs in which skilled workers are employed. The segmented labor market and status composition perspectives are especially relevant to the study of the economic impacts of immigration at a time when the US economy is characterized by increasing segmentation across and within sectors and occupations, including high-status ones (Leicht and Fennell 1997; Waddoups and Assane 1993). The next section presents a brief overview of recent findings on the effects of skilled immigrants. Empirical Findings When it was published in 1997, an oft-cited, comprehensive National Academies study of immigrants’ economic, fiscal, and demographic impacts and contributions confirmed the existing consensus among US researchers. These researchers believed that in the 1980s and early 1990s immigration had only a small negative effect on the wages of native workers (Smith and Edmonston 1997). The authors of the study cited evidence that immigrants reduced the wages of competing natives by only 1 or 2 percent. The authors also found that natives in skilled occupations, owners of capital, and consumers who purchased immigrant-produced goods and services benefited from immigration. However, natives at the lower end of the occupational distribution

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competed with immigrants for the same jobs. Neither the 1997 report nor the majority of researchers until recently addressed the question of competition among skilled native and foreign workers. Since this comprehensive review in 1997, researchers have diverged in their opinions on immigrants’ economic impacts. New studies report results ranging from large negative to strong positive impacts of immigrants on labor market outcomes of native workers such as wages and employment (for a review, see Murray, Batalova, and Fix 2006). Meanwhile, highly skilled immigrants and their impacts and contributions have also become a focus of mainstream research, although researchers have not reached any consensus on the impacts of highly skilled immigrants either. Borjas (2003) estimates that immigration during the last two decades depressed wages by 4.9 percent for native college graduates. His empirical analysis of foreign-born doctorates finds that a 10 percent increase in the doctorate supply as a result of immigrants causes a wage reduction of about 3 percent for competing new doctorates (Borjas 2005). In sharp contrast, other researchers find that highly skilled immigrants actually raise native wages. One study finds that a 10 percent increase in the share of highly skilled immigrants in an occupation group raises native skilled workers’ earnings by 2.6 percent (Lopez 2003). Similarly, Ottaviano and Peri (2006) demonstrate that college-educated native workers experienced an increase of 1.5 percent in their wages (in real terms) thanks to immigration of the 1990s. Orrenius and Zavodny (2003) further suggest that highly skilled immigrants may uniquely complement similarly skilled natives rather than pose a competitive threat. Research Hypotheses Guided by both the theoretical and empirical literature reviewed in this chapter, I propose to test four hypotheses to shed further light on the possible impacts of skilled immigrants on the earnings of native and immigrant workers. I start by considering the role of workers’ individual characteristics as determinants of their earnings. In the United States, both skilled and unskilled immigrants are underpaid compared to their native-born counterparts (Catanzarite 2003b; Fernandez 1998; Woo 2000). Foreign-born physicians and

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nurses are not only more likely to work in rural and urban ghetto areas, but also are paid, on average, less than their native-born counterparts. Shin and Chang (1988) find that Korean-born physicians in the United States are much more likely to practice in rural areas than either their fellow physicians who stayed in Korea or US-born physicians. Native skilled workers have fluency in language, American education/training, and knowledge of American culture that give them certain advantages in the job market (Espenshade, Usdansky, and Chung 2001; Wilson and Jaynes 2000). Immigrants may experience (at least initially) downward mobility because their schooling and skills are not necessarily transferable to the labor market of the host country. In addition to education and experience, English language ability is also an important determinant of occupational mobility and earnings opportunities (Kossoudji 1988; Portes and Rumbaut 1996). Thus, my first hypothesis (testing a human capital model) states that earnings are a reflection of one’s human capital (e.g., education, skills, and experience): Hypothesis 1: Controlling for other characteristics, nativeborn skilled workers earn the most, followed by early, and then by recent immigrants. Research finds that not only are individual factors at work in determining one’s earnings. Structural factors such as the composition of workers in occupations, industries, and/or labor markets affect earnings. Studies document long-term patterns of negative relationships between the proportion of women and racial-ethnic minorities in the workplace and the earnings of workers in such jobs and occupations (Cohen and Huffman 2003b; Cotter, Hermsen, and Vanneman 1999; England, Reid, and Kilbourne 1996). In female or racial/ethnic minority-dominated workplaces, earnings are lower for all workers compared to more diverse workplaces. In addition, female and racial/ethnic minority workers are paid less than their male and white counterparts, controlling for other factors (Cohen and Huffman 2003a; England 1992; Huffman and Cohen 2004; Reskin and Padavic 1994; Reskin and Roos 1990). Catanzarite (2003) finds that greater employment of immigrants in low-skilled occupations adversely affects the earnings of native workers. Similarly, in his preliminary analysis, Lowell (2003) finds that, as the share of H-1B visa holders increases in

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the information technology labor force, the earnings of native workers go down. Therefore, my second hypothesis postulates that the average earnings of native workers will be lower in jobs with a higher percentage of immigrants: Hypothesis 2: There is a negative relationship between the earnings of native skilled workers and the percent of immigrants in location-specific jobs.15 In contrast, if immigrants and natives are not in direct competition (i.e., immigrants who occupy the bottom positions in the job hierarchy push up natives), earnings of the native-born workers will be lower in jobs with a small proportion of foreign born. Moreover, if the demand for highly skilled labor continues to grow with the expansion of the knowledge-based economy, skilled immigrants may be absorbed by the market with no negative consequences for prior workers. Thus, the second and third hypotheses predict opposite results: Hypothesis 3: There is a positive relationship between the earnings of native workers and the percent of immigrants in location-specific jobs. One can extend the idea of immigrant-native competition beyond the impact on wages of native workers. Certain groups of immigrants, for example, recent versus earlier immigrants, may compete with each other rather than with native workers. If this is the case, one could expect that the more skilled foreign born there are in a given job, the greater the competition between them, and the lower the earnings and the poorer the employment opportunities they face as compared to natives. Therefore, my last hypothesis states that: Hypothesis 4: The average earnings of earlier immigrants will be lower in jobs with a higher percent of immigrants.

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Data and Methodology Definitions Researchers rely on a number of definitions of highly skilled workers. As discussed in detail in Chapter 3, for the purposes of my analysis, I combine both education and occupation in defining highly skilled. Thus, a highly skilled worker is defined as a person who is employed in a skilled occupation, which, in turn, is defined as an occupation in which at least 55 percent of workers possess a Bachelor’s degree or higher. According to this definition, a worker may or may not be a college graduate but must work in an occupation where the majority of workers have at least a Bachelor’s degree. There are also different ways to conceptualize the “workplace” where immigrant-native competition or complementarity takes place (for a review see Lopez 2003: 26). Following the approach by Cohen and Huffman (2003a), I use a location-specific job as a place where I examine the immediate economic impacts of immigrants on native workers. I define a location-specific job as the intersection of skilled occupation, industry, and metropolitan area. Occupation and industry contexts are important as both vary in their institutional practices, barriers to entrance, professional licenses and exams, earnings and career opportunities, and union presence. The geographical component is important as well since highly skilled workers, and particularly immigrant highly skilled workers, are not equally distributed geographically across the nation. Additionally, metropolitan areas vary significantly in terms of labor market opportunities and population composition, which, in turn, affect labor market outcomes. This is pertinent both for some occupations such as computer engineer and some industries such as professional/science services that tend to concentrate in large metropolitan areas within certain regions of the United States such as West and Northeast. Data To test my hypotheses, I analyze data both at the individual and the job levels. Data for individuals (micro level) are from the 2000 Census 5 Percent Public Use Microdata Samples (PUMS) file (US Census 2003).

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My population of interest is restricted to metropolitan area workers between the ages of 25 and 64, who worked full time (35 hours or more in the average week) for at least 40 weeks in 1999, earned 1,000 dollars or more, and were not in the military or self-employed. Data for the macro-level characteristics of location-specific jobs are also derived from the 5 Percent PUMS file. As discussed above, I define location-specific jobs as the intersection of skilled occupation, industry, and metropolitan area. Thus, I started with a set of ninetythree skilled occupations (see Chapter 3) in eighteen industries located in 241 Metropolitan Statistical Areas (MSA) or Consolidated Metropolitan Statistical Areas (CMSA). To construct the macro-level file, I draw upon the information from individuals 16 years and older, living in metro areas, who are not in the military or self-employed. This limited the number of location-specific jobs to 73,507. I further excluded jobs with fewer than twenty unweighted cases, which yielded 7,537 distinct location-specific jobs (e.g., a computer programmer in professional/scientific industry in Los Angeles-Riverside-Orange County, CA CMSA or a management analyst in durable manufacturing in Atlanta, GA MSA). Dependent and Independent Variables The dependent variable is the natural logarithm of annual earnings, where earnings refer to earnings before taxes and other deductions that a worker received in 1999. The explanatory variables include a number of individual- and job-level variables. The main individual-level independent variables are nativity status (earlier immigrants, recent immigrants, and native born as an excluded category), female, race/ethnicity (non-Latino black, non-Latino Asian, Latino, and nonLatino white as an excluded category). I also include a number of variables typically used as controls in the studies of earnings determinants: Marital status (not currently married=1), degree (Master’s and Doctoral/Professional degrees compared to Bachelor’s degree or below as an excluded category), potential work experience (calculated as age minus years of education minus six), potential work experience squared (to account for non-linearity), disability status, being currently enrolled in college/university, self-reported knowledge of English (ranging from “not at all”=0 to “very well/native”=4),

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presence of own children under 5 years old in the household, the natural logarithm of weekly hours and the natural logarithm of weeks worked in 1999. I did not include age variable in my analysis because of its high correlation with work experience and degree. The primary job-level independent variable is Percent Foreign Born among the Highly Skilled Workforce (PFBHS). For comparative purposes, a variable Percent Recent Immigrants among the Highly Skilled Workforce (PRIHS) is used in a separate analysis. These variables are calculated from the information for the workers in each job. The squared terms of PFBHS and PRIHS are included to address possible non-linear effects of these two variables. Other job-level variables are also derived from the 5 percent PUMS data. To control for the ethnic composition of a job, I include percent Latino and percent black. For gender composition, I include percent female. I do not include percent Asian because of its high correlation with the PFBHS and PRIHS. I also control for whether the job employs high-tech workers. This variable is based on three occupations: Computer scientists and engineers, computer programmers, and information technology support personnel. Three dummy variables represent the variable region (West, Northeast, and Midwest with South being an excluded category). Multi-Level Modeling To investigate the effect of the percentage of immigrants in locationspecific jobs on the earnings of native and foreign-born workers, I use hierarchical linear models (HLM) (Raudenbush and Bryk 2002). HLM has advantages over an Ordinary Least Squares (OLS) regression because HLM allows for the examination of how differences in location-specific jobs interact with individual human and social capital characteristics to influence workers’ earnings outcomes. Furthermore, HLM improves the confidence of predictions by applying controls at the micro-level separately from those at the macro-level, thus allowing more accurate measurement of effects and errors at both levels. To investigate the direct effects of individual and job variables as well as the impact of their interaction, I use HLM to estimate a series of two-level models. The HLM strategy allows for the differentiation between earnings variability among individual workers within location-

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specific jobs and earnings variability across these jobs. At the individual level, I test the effect of human and social capital on earnings. The equation for the individual-level model is: Yij = β0 + β1jEIij + β2jRIij + ΣβkjXikj + Rij

(1)

where Yij equals the log annual earnings for person i in job j, and β0 is the individual-level intercept; β1j and β2j are coefficients for the difference between earlier immigrants (EI), recent immigrants (RI) and native-born workers. Xikj is the set of human and social capital control variables that are centered at their grand means and βkj is the vector of the coefficients associated with these control variables. The centering of the control variables means that the intercept, β0, is the log annual earnings of a native worker with average characteristics on all the control variables. β1j and β2j are the differences for immigrant workers at the same levels of the control variables. Finally, Rij is the level-1 error term, assumed to be normally distributed with a zero mean and constant variance. These individual-level coefficients become the dependent variables at the job level (a similar analysis was conducted using PRIHS variable): β0j β1j β2j βkj

= = = =

γ00 + γ01(PFBHSj) + γ02(PFBHSsqj) + Σγ0M(JOB varj) + U0j γ10 + γ11(PFBHSj) + γ12(PFBHSsqj) + Σγ1Μ(JOB varj) + U1j γ20 + γ21(PFBHSj) + γ22(PFBHSsqj) + Σγ2M(JOB varj) + U2j γk

(2) (3) (4) (5)

In equation 2, γ00 is the intercept for the job-level model of native workers’ predicted log annual earnings β0j; γ01 is the effect of percent of the highly skilled workforce who are foreign born in a job (PFBHS) on β0j; and Σγ0M is the effect of other job variables (grand-centered) on β0j. Similarly, in equations 3 and 4, γ10 and γ20 are the intercepts for the job-level models on β1j and β2j (the native-immigrant differences in the log annual earnings); γ11 and γ21 are the effect of PFBHS on β1j and β2j respectively. Σγ0-2M is the effect of other job-level variables (grandcentered). Finally, U0-2j are the error terms at the job level, and γk is the

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constant coefficient βk across all jobs. The centering of job-level control variables means the individual-level intercept represents log earnings for native workers at average levels of the individual controls in jobs with average values on the job controls and no foreign born among the highly skilled workforce in that job. I run a series of models to analyze the impact of key individual and location-specific job variables separately and together with controls. This analysis is based on equations 1 through 5. Results Descriptive Statistics Descriptive statistics for the individual level of the analysis are presented in Table 4.1.1. The table shows that, on average, workers in skilled location-specific jobs earn about $52,000 per year, although there is a large range of earnings. For example, the sample includes both a market and survey researcher in San Francisco-Oakland-San Jose, CA CMSA who earned $2,500 in 1999 and a chief executive in finances in Washington-Baltimore, DC-MD-VA-WV CMSA who earned $680,000 in the same year. Table 4.1.2 presents descriptive statistics of the jobs’ characteristics. It indicates that location-specific jobs vary significantly in terms of their nativity composition. There are jobs with no foreigners at all. For example, there is not a single immigrant real estate lawyer in Allentown-Bethlehem-Easton, PA MSA or elementary/middle school teacher in Alexandria, LA MSA. In contrast, the foreign born are significantly represented in other jobs such as accountants in the transportation industry in Miami-Fort Lauderdale, FL CMSA. Table 4.2 focuses on where, in terms of nativity composition, workers tend to be employed. As shown in Table 4.2, the distribution of the PFBHS is skewed. Approximately half of all workers (including native born, earlier, and recent immigrants) are in jobs where foreign born make up 12 percent or less of the workforce. Both the earlier and recent immigrants are much more likely to work in jobs with a higher percentage of foreigners: 50 percent of early and recent immigrants work in jobs where 25 percent or less of workers are born outside of the United States. There are a few jobs (1.5 percent of all jobs) in which

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Table 4.1.1 Descriptive Statistics for Individual-Level Variables Variable Dependent variable Annual earnings (ln) Earnings (thousand $) Independent variables Nativity status Native born Early immigrants Recent immigrants Race and ethnicity White Black Asian Latino Female Not married Have a child under age 5

Mean

Std

Min

Max

10.9 52.4

0.6 1.9

7.8 2.5

13.4 680.0

0.9 0.1 0.0

0.4 0.3 0.2

0.0 0.0 0.0

1.0 1.0 1.0

0.8 0.1 0.1 0.1

0.4 0.3 0.3 0.2

0.0 0.0 0.0 0.0

1.0 1.0 1.0 1.0

0.5 0.3 0.1

0.5 0.5 0.3

0.0 0.0 0.0

1.0 1.0 1.0

0.2 0.4 0.3 0.1

0.4 0.5 0.4 0.3

0.0 0.0 0.0 0.0

1.0 1.0 1.0 1.0

3.8

0.5

0.0

4.0

0.1 19.3 0.1 3.9 3.8

0.3 10.0 0.3 0.1 0.2

0.0 0.0 0.0 3.7 3.6

1.0 58.0 1.0 4.0 4.6

Degree No college Bachelor’s Master’s Doctoral/Professional Assimilation English fluency Economic characteristics Currently enrolled in school Potential work experience Disability Weeks worked (ln) Hours worked (ln)

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Table 4.1.2 Descriptive Statistics for Job-Level Variables Variable Percent female Percent black Percent Latino Region West Midwest South Northeast Percent high tech

Mean 46.2 7.5 4.9 0.2 0.2 0.4 0.2 0.1

Std Min 26.2 0.0 9.0 0.0 8.0 0.0 0.4 0.4 0.5 0.4 0.3

0.0 0.0 0.0 0.0 0.0

Max 100.0 78.3 89.1 1.0 1.0 1.0 1.0 1.0

Table 4.2 Distribution of Workers in Jobs by Job's Nativity Composition (PFBHS)

Quintile Min 1% 5% 10% 25% Median 75% 90% 95% 99% Max Mean

All workers

0.0 0.0 1.3 2.6 5.6 12.3 22.0 35.2 41.8 56.4 76.6 15.7

Native born 0.0 0.0 1.0 2.3 4.9 10.7 19.2 30.0 37.0 50.3 76.6 13.7

Earlier Recent immigrants immigrants 0.2 2.8 5.6 8.3 14.5 24.4 36.6 45.7 52.7 60.5 76.6 26.1

0.5 3.6 7.1 9.9 16.7 26.7 39.5 52.7 58.5 62.7 76.6 28.8

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more than 50 percent of the workforce is foreign born, although in some jobs (e.g., civil engineers in transportation in San FranciscoOakland-San Jose, CA CMSA and accountants in transportation in Miami-Fort Lauderdale, FL CMSA) more than three-quarters of workers are foreign born. Multivariate Model Results Table 4.3 turns to the results of the multivariate analyses. An intra-class correlation coefficient (ICC) shows the percent of variance in the log annual earnings between jobs (Raudenbush and Bryk 2002: 36). The ICC is derived from a random-intercept model (i.e., Model 1 that has no independent variables at either individual or job level) and based on the following formula: ICC= τ00/(σ2 + τ00) Or in my case: ICC=0.1261/(0.2965+0.1261)=0.298 or 29.8 percent That is, about 30 percent of the total variability in the log earnings is attributable to differences across location-specific jobs, while the remaining 70 percent is due to differences at the individual level. Model 2 examines the effect of nativity alone on the annual earnings of highly skilled workers. To make the results more meaningful, I take the exponential of the log coefficients for the intercept and slope of each of three groups of workers. Without controlling for either individual or job characteristics, native-born persons earn $51,860 (=exp(10.8563)) annually while earlier immigrants earn $50,445 (=exp(10.8563-0.0277)). Recent immigrants earn the least, $43,562 (=exp(10.8563-0.1744)), which is 16 percent less than natives and 14 percent less than earlier immigrants. Model 3 adds individual level controls, which explain about 17 percent of earnings variability within jobs and 33 percent between jobs. All individual-level control variables are centered at their grand means with effects fixed across all jobs. With no job-level variables included, Model 3 is similar to an OLS regression with the exception that the intercept and nativity coefficients are set to vary across jobs. In this case, the intercept (10.8454 or $51,385) is the predicted earnings for

Table 4.3 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native-Born, Early Immigrant, and Recent Immigrant Workers in Skilled Jobs

Native born Intercept PFBHS PFBHS squared Earlier immigrants Intercept PFBHS PFBHS squared Recent immigrants Intercept PFBHS PFBHS squared Controls at level 1 Demographic characteristics Female Black Asian Latino

Model 1

Model 2

Model 3

Model 4

10.8471***

10.8563***

10.8454 ***

10.7140*** 0.0162*** -0.0002***

Model 5

10.7570*** 0.0110*** -0.0002***

-0.0277***

0.0079+

0.0080 -0.0004 0.0000

0.0015 0.0005 0.0000

-0.1744***

-0.0603***

-0.0299 -0.0011 0.0000

0.0006 -0.0047** 0.0000+

-0.1756*** -0.0943*** -0.0032 -0.0784***

-0.1751*** -0.0945*** -0.0038 -0.0797***

-0.1671*** -0.0908*** -0.0077 -0.0750***

Table 4.3 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native-Born, Early Immigrant, and Recent Immigrant Workers in Skilled Jobs (Continued) Model 1

Disabled Not married Have own child under age 5 Human capital and economic characteristics Potential experience Potential experience squared Master’s degree Doctoral/Professional degree Weeks worked in 1999 (ln) Hours workers (ln) Enrolled in classes Assimilation English

Model 2

Model 3 -0.0682*** -0.0758*** 0.0389***

Model 4 -0.0663*** -0.0775*** 0.0387***

Model 5 -0.0677*** -0.0755*** 0.0386***

0.0377*** -0.0006*** 0.1977*** 0.2947*** 0.4311*** 0.4868*** -0.0713***

0.0377*** -0.0007*** 0.1978*** 0.2942*** 0.4292*** 0.4874*** -0.0716***

0.0378*** -0.0007*** 0.1978*** 0.2907*** 0.4232*** 0.4831*** -0.0716***

0.0536***

0.0536***

0.0406***

Table 4.3 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native-Born, Early Immigrant, and Recent Immigrant Workers in Skilled Jobs (Continued) Model 1 Controls at level 2 Native-born % women Ethnic composition % black % Latino High tech Region: West Region: Midwest Region: Northeast Early immigrants % women Ethnic composition % black % Latino High tech Region: West Region: Midwest Region: Northeast

Model 2

Model 3

Model 4

Model 5

-0.0048*** -0.0049*** -0.0031*** 0.0037 -0.0128 -0.0214* -0.0054 0.0005** -0.0006 -0.0018*** 0.0260* -0.0118 0.0132 -0.0209*

Table 4.3 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native-Born, Early Immigrant, and Recent Immigrant Workers in Skilled Jobs (Continued) Model 1

Model 2

Model 3

Model 4

Recent immigrants % women Ethnic composition % black % Latino High tech Region: West Region: Midwest Region: Northeast Variance components Individual level Percent explained JOB level Intercept Percent explained Earlier Immigrants Slope Recent Immigrants Slope Note: +p <0.1, *p<0.05, ** p<0.01, ***p<0.001

Model 5

0.0000 0.0005 -0.0001 0.1759*** 0.0115 -0.0312+ -0.0157

0.2965***

0.2924*** 1.4

0.2438*** 16.6

0.2438*** 0.0

0.2438*** 0.0

0.1261***

0.1283*** 0.0 0.0119*** 0.0367***

0.0853*** 33.5 0.0083*** 0.0321***

0.0772*** 9.5 0.0079*** 0.0310***

0.0568*** 26.5 0.0072*** 0.0250***

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native workers with average characteristics in jobs with no foreign born. Model 3 shows the reversal in the direction of the effects of being an earlier immigrant (from slope=-0.0277 to slope=0.0079) and the significant reduction of the negative effect (from -0.1744 to -0.06) in the case of recent immigrants. Thus, controlling for individual human capital and economic characteristics slightly increases the annual earnings for earlier immigrants (from $50,445 to $51,706) and recent immigrants (from $43,562 to $48,299) but decreases the earnings of natives (from $51,860 to $51,299). All control variables have effects in the expected directions and are statistically significant, except for the effect of being Asian. Women earn less than men. Blacks, Asians, and Latinos earn less than whites. Respondents with limited knowledge of English, with some form of disability, formerly married or never married, and currently enrolled in school are predicted to have lower annual earnings than their respective comparison groups. Those working more weeks per year as well as longer hours per week also earn more. The impact of greater potential work experience is positive and statistically significant although nonlinear. The coefficients for these control variables at the individual level do not change substantially in the next two models. Model 4 adds the main explanatory variable, PFBHS, at the macro level. The inclusion of this variable further reduces earnings variability across jobs by 10 percent. The model shows that the earnings of all three groups are lower than those in Model 3. The negative intercept coefficient for recent immigrants declines and so does the native-recent immigrant gap in earnings. According to this model, native workers make $44,979 per year, earlier immigrants make $45,340, and recent immigrants earn $43,653. While there is a positive correlation between earnings of native born and greater PFBHS (the slope coefficient, 0.0162, is positive and significant), both early and recent immigrants experience relative earnings disadvantages if they work in jobs with more immigrants (their slope coefficients, -0.0004 and -0.0011, are negative although not significant). The significant squared term (PFBHSsq) indicates that the association between PFBHS and earnings of natives has an inverse-U shape, not simply a linear positive effect. Model 5 includes key individual and job variables as well as controls at both levels. The results from this model (expressed as annual earnings in dollars) are presented graphically in Figure 4.1.

Figure 4.1 Effect of Skilled Job’s Percent Foreign Born on Annual Earnings by Workers’ Nativity, Ages 25 to 64 Annual Earnings ($)

Native born

61,000

Earlier immigrants

Recent immigrants

56,000

51,000

46,000

41,000

36,000 0

5

15

25

35

45

Percent foreign born in skilled jobs (PFBHS)

55

65

76

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Since job-level variables are grand centered in this analysis, these lines reflect predicted earnings in skilled jobs with average values on the control variables as the PFBHS variable increases from 0 to 76 percent. In jobs with an insignificant presence of foreign skilled workers, earlier immigrants are predicted to receive the highest annual earnings ($47,028), closely followed by the other two groups. However, as the percent of foreign born increases in skilled jobs, the situation changes dramatically. The slopes for native and earlier immigrant workers follow each other closely and are steep and positive until the PFBHS reaches 35 percent. This is the inflection point where the slope changes its direction. It is calculated based on the following formula: Inflection point = ((-1)*coefficient of PFBHS) / (2*coefficient of PFBHSsq) After this tipping point, the earnings of natives and earlier immigrants decline sharply from about $57,000 to $44,000. But as Table 4.2 shows, about 95 percent of native workers and 75 percent of earlier immigrant workers work in jobs with 35 percent or less foreign born. In other words, for the overwhelming majority of natives and earlier immigrants, there is a strong and positive association between their earnings and PFBHS. The recent immigrants slope is also positive (although not as steep) until it reaches its tipping point (26 percent). This tipping point equals the median value of the distribution of PFBHS for recent immigrants (see Table 4.2). That is, for half of recent immigrants, working with other immigrants brings financial benefits. However, for the other half of immigrants, the presence of fellow immigrants is detrimental to their earnings. The figure also shows that as PFBSH goes up, the earnings gap between recent immigrants and the other two groups increases. A Special Case: Recent Immigrant Workers Temporary workers on H-1B visas constitute a significant portion of recent immigrants. The increasing presence of H-1B temporary workers remains a bone of contention between those who employ these workers and organizations representing the interests of US skilled workers. While the former argue that existing shortages of qualified workers could be ameliorated by hiring temporary skilled foreigners, the latter

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Skilled Immigrant and Native Workers

deny the very existence of a skill shortage and point out the adverse labor market effects of foreigners on the US highly skilled workforce. Since H-1B workers depend on their employers for their legal work status in the United States and are often promised green card sponsorship (i.e., sponsorship for legal permanent residence), they are more likely to comply with employers’ demands for longer working hours and less pay (Smith 1999). Some observers argue that such dependency is the main reason why businesses are interested in hiring and keeping temporary workers over both US-born and more established immigrant workers (DeFreitas 1999). To gauge whether native and immigrant workers are particularly disadvantaged when they work in jobs with a high percent of recent immigrants, I examine the relationships between the share of recent immigrants (a portion of whom are H-1B visa holders) and earnings of skilled workers.16 The main independent job-level variable is the percent of recent immigrants in a skilled job or PRIHS. Table 4.4 shows where, in terms of nativity composition, skilled workers tend to work. Table 4.4 Distribution of Workers in Jobs by Job's Nativity Composition (PRIHS) Quintile Min 1% 5% 10% 25% Median 75% 90% 95% 99% Max Mean

All workers 0.0 0.0 0.0 0.0 1.4 3.5 7.7 13.0 18.2 33.6 61.5 5.6

Native born 0.0 0.0 0.0 0.0 1.2 3.2 6.5 11.5 15.2 25.5 61.5 4.8

Earlier Recent immigrants immigrants 0.0 0.0 0.2 1.6 3.4 6.9 11.2 17.9 23.2 36.8 53.7 8.5

0.1 1.1 2.3 3.2 5.9 10.4 18.0 27.5 35.3 42.8 61.5 13.3

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Table 4.4 indicates that the distribution of PRIHS is skewed. Ten percent of workers are in jobs with no recent immigrants at all. As the median value indicates, half of all workers are in jobs with 3.5 percent or less recent immigrants, although immigrants (especially recent ones) are more likely to work with other recent immigrants. Jobs in which recent immigrants make up more than 50 percent tend to be in physical and medical science or IT occupations, in education/training and professional/scientific/technical industries, and in large metropolitan areas (e.g., Boston, Chicago, Dallas, Miami, Los Angeles, New York, San Diego, and San Francisco). Figure 4.2 illustrates the results of the final model with PRIHS as the main job-level explanatory variable. It demonstrates that as the PRIHS goes up, the earnings of earlier immigrant and natives workers increase; the annual earnings of recent immigrants also increase, although at a slower pace. However, once the percent of recent immigrants in a job reaches about 15 percent, the earnings drop for earlier immigrant and US-born workers. About 95 percent of native workers and 75 percent of earlier immigrants are in jobs in which recent immigrants constitute 15 or less percent. In other words, the negative relationship between the percent of recent immigrants and earnings is applicable only to a small proportion (5 percent) of native workers. The tipping percentage point for recent immigrants is 11 percent, which is almost the same as the median value of the PRIHS distribution. Again, the association between greater immigrant presence and lower earnings is applicable to half of the recent immigrant workers. Figure 4.2 also demonstrates that as PRIHS goes up, the earnings gap between recent immigrants and the other two groups increases (although to a much smaller extent than in Figure 4.1) and then gets even smaller at higher PRIHS values. In terms of the four hypotheses stated above, the results of the HLM models (either with PFBHS or PRIHS) support only one. The first hypothesis states that native born would earn the most of all three groups, followed by earlier and then by recent immigrants. The HLM results indicate that earlier immigrants earn the most of all three groups, although the differences between native and earlier immigrant workers are small and not statistically significant.

Figure 4.2 Effect of Skilled Job’s Percent Recent Immigrants on Annual Earnings by Workers’ Nativity, Ages 25 to 64 Annual earnings ($)

Native born

60,000

Earlier immigrants

55,000 50,000

Recent immigrants

45,000 40,000 35,000 30,000 25,000 20,000 15,000 0

5

15

25

35

45

Percent recent immigrants in skilled jobs (PRIHS)

55

61

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The second hypothesis postulates that native workers would earn less in jobs with a greater presence of immigrant workers (testing the idea of competition). The results do not support this statement for the overwhelming majority of native workers. This also means that the third hypothesis is supported; that is, there is a positive relationship between the earnings and the percent of immigrants in the job, albeit only to a certain tipping point. These findings are in line with research carried out by Lopez (2003), who uses different data and methodology to address the same question. The last hypothesis tests the idea of competition between different cohorts of immigrants. For the majority of earlier immigrants, their earnings are not affected negatively by the greater presence of other immigrants. Both figures show that recent immigrants pay an assimilation price. Perhaps intangible capital that recent immigrants do not possess, gives natives and earlier immigrants an earnings advantage that goes beyond social and human capital and workplace characteristics. Alternately, the difference in pay may be due to discrimination against recent immigrants as well as against jobs defined as “immigrant.” Although jobs with some immigrants pay better than those with no immigrants, the slopes for all workers reverse direction at some point. As the share of foreign born in a job reaches 30 to 35 percent, they may be defined as “immigrant” jobs and thus pay less. A vast literature on inequality in the workplace suggests that female-dominated as well as “brown-collar jobs” pay less just because their workers (women and low-skilled immigrants) are undervalued by the employers (Catanzarite 1998; Catanzarite 2003b; Cohen and Huffman 2003a; England 1992). Conclusion In a world of competitive, fast-moving, and internationally oriented business, employers rely on highly educated and skilled workers to meet the challenges of a global economy. Both traditional immigration countries such as Australia, Canada, and the United States and new immigration countries of Europe and Asia have been actively promoting an increase in skilled workers from abroad. Foreign talent helps to meet the demands of their economies by stimulating R&D, expanding foreign markets, and offsetting the adverse consequences of aging populations.

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Skilled Immigrant and Native Workers

Most of the current US immigration legislation was formulated in the mid-1960s when immigrant admissions were divided into family and employment-based preference categories with numerical limits. The largest group of preferences continues to go to family-based immigration, while a smaller portion goes to work-related immigration. Critics of the 1965 amendments to the INA maintain that too many family-based immigrants, who tend to be low-skilled and poorly educated, are allowed to come to the United States (Borjas 1995; Borjas 1999b; Briggs and Moore 1994). They argue that, in contrast, the increased admission of employment-based immigrants would increase international competitiveness, boost the domestic economy, and decrease welfare expenditures (Interpreter Releases 2006b). In the 1990s, calls for greater skill-based immigration coincided with pressures from IT companies whose representatives insisted that skilled immigrants were a key factor in the industry’s impressive growth. These employers complained about a serious shortage of qualified workers that inhibited the industry’s further growth. In the last decade, the US Congress has significantly increased the annual quotas for H-1B temporary worker visas, which led to an exponential increase in the number of such workers in the country (Usdansky and Espenshade 2001). Such developments provoked strong criticism from professional science and engineering organizations such as the Institute for Electrical and Electronics Engineers, which contended that increased numbers of skilled immigrant workers, especially temporary H-1B visa holders, led to adverse competition with US-born workers (Institute for Electrical and Electronics Engineers 2003; North 1995). The increase in skilled-based immigration, and the H-1B program in particular, raised heated debates about the benefits and costs of such workers for the labor market and the national economy in general (Lowell 1999). My research addresses some of these concerns by examining the nature and strength of the relationship between highly skilled immigration and the earnings of native and foreign-born workers across skilled jobs. Sociological theories recognize the importance of workers’ characteristics as well as characteristics of the workplace on the degree of complementarity and competition between immigrant and native groups. Following this tradition, I use a multi-level methodology that distinguishes the effects of individual social and human capital

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characteristics (e.g., gender, race/ethnicity, education, work experience) on workers’ earnings from the effects of location-specific job characteristics (e.g., presence of highly skilled foreigners in a job). I find that the earnings of native and earlier immigrant workers are similar and higher than those of recent immigrants after controlling for individual and job characteristics. Moreover, as the percent of foreigners in skilled jobs goes up, so do the earnings of native and earlier immigrants, albeit only up until a certain tipping point. Additionally, I find that the earnings nativity gap increases for recent immigrants in jobs with more skilled immigrants. These results support the idea that recent immigrant skilled workers are not substitutes for the majority of native workers but may be in competition with other immigrants, mainly with other recent immigrants. The results described above lead to three important conclusions. First, highly skilled immigrants have not been found to produce negative impacts on the earnings of all native workers. To the contrary, there is a positive (although non-linear) relationship between the presence of foreigners in a skilled job and the earnings of the overwhelming majority of native-born men and women. These findings may alleviate concerns about increases in skilled immigration. While there might be other problems with the current employment-based immigration system (Papademetriou and Yale-Loehr 1996), the presence of highly skilled immigrants seems not to lead to major adverse impacts on native earnings. Second, I find no substantial differences in earnings between earlier immigrants and native born, regardless of the level of immigrants in their jobs. In contrast, newcomers (those who arrived after 1990) seem to pay an assimilation price: Even controlling for individual and structural factors, their earnings are lower than those of native and earlier immigrant workers with similar characteristics. Newcomers are also more likely to be in jobs characterized by a higher presence of immigrants, which in turn are paid less. Perhaps, similar to their Canadian counterparts (Boyd 2000), these newly arrived immigrants are also underemployed because of their experience-skill mismatches (see also Woo 2000 on Asian-born highly skilled in the United States). Possible explanations for the labor market mismatches include difficulties in obtaining professional credentials, discrimination in promotion to managerial positions with high salaries and benefits,

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and lack of knowledge of corporate culture and access to informal networks. These findings point to the importance of recognizing the diversity in labor market experiences and outcomes within the immigrant population. Third, my analysis emphasizes the need to consider the structural features of employment of skilled workers. The multi-level models show that in jobs with few immigrants, no significant differences in earnings among native and immigrant groups exist. In contrast, as the percent of immigrants reaches a certain tipping point, these jobs become “immigrant,” and earnings begin to decrease for all workers. The literatures on labor market segmentation and occupational segregation suggest that occupations and sectors dominated by a minority group (i.e., women, low-skilled Latino immigrants, blacks) tend to be devalued by employers. My analysis suggests a similar process might occur at the highly skilled level. As the job composition tilts toward a higher percent of immigrants, whose labor is more dispensable (Massey, Durand, and Malone 2002), every worker starts paying earnings penalties. As the US economy increasingly demands a skilled and educated labor force and relies on immigration as a method to expand this labor force (Bureau of Labor Statistics 2004b; Horrigan 2004), questions regarding the economic impact of immigrants will continue to dominate public and political discourse. My findings challenge the exclusive focus on immigrants as individual workers in discussions of their economic impacts. Instead, I suggest placing such discussions in the larger context of the American economy, which is characterized by labor market segmentation and occupational segregation as well as gender and racial inequality.

CHAPTER 5

Looking Through the NativityGender Lenses: Earnings of Immigrant and Native Women in Highly Skilled Jobs

Introduction The comparative economic performance of men and women – both natives and immigrants – has long interested scholars, activists, and policy makers (Cotter, Hermsen, and Vanneman 1999; Cotter, Hermsen, and Vanneman 2003; National Science Foundation 2002; Xie and Shauman 2003). Extensive research demonstrates that female workers tend to have fewer opportunities to gain access to jobs they qualify for (Altonji and Blanck 1999; Reskin and Roos 1990), experience higher levels of unemployment and job-skills mismatch (De Jong and Madamba 2001), and are paid less than their male counterparts with similar education and training (Baron and Newman 1989; Cohen and Huffman 2003a; National Science Foundation 2002). Immigrants, especially newly arrived, face similar barriers in the labor market (Boyd 2000; Duvander 2001; Fernandez 1998; Man 2004). A variety of theories from economics and sociology have been proposed to explain the gender and nativity pay gaps (England 1992; Marini 1989; Waldinger and Lichter 2003). These theories cite both individual and structural determinants of workplace inequalities, such as family roles and responsibilities, geographic mobility constraints, social capital, and the structure of opportunities within the labor market 95

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Skilled Immigrant and Native Workers

(Catanzarite 2003a; Catanzarite 2003b; Cohen and Huffman 2003a; Cohen and Huffman 2003b; McBrier 2003; Shauman and Xie 1996). Research Agenda The labor market experiences and outcomes of skilled immigrant women bear consideration for three reasons as identified by Xie and Shauman (2003). First, women represent about 40 percent of highly skilled immigrants. Second, the presence of highly skilled immigrant women may affect women’s overall economic and social position in US society and their representation in the skilled labor force. Third, since their economic characteristics and outcomes may differ from those of immigrant men and native-born women, research on immigrant women professionals is likely to generate new insights into the determinants and manifestations of economic inequality. Thus, in this chapter, I bring together different theoretical threads to explain the earnings gap in the case of native and immigrant women employed in highly skilled jobs. My goal is to explore how the intersection of nativity and gender affects one’s earnings potential in the context of the US skilled labor market. Women in the Highly Skilled Labor Market Studies of gender inequality in the workplace show that women earn less than men, even after adjusting for human capital and work-related characteristics (Cohen and Huffman 2003a; Cotter, Hermsen, and Vanneman 1999; Reskin and Padavic 1994; Reskin and Roos 1990). Although over time there has been some improvement in the position of women in the labor market, gender equality in the workplace is still an ideal. Certain characteristics such as age, race, and nativity tend to aggravate the situation as older women, racial minority women, and immigrant women are known to be more disadvantaged than their younger, white, and native-born counterparts. Highly educated women are no exception to this trend despite the significant inroads that they have made in formerly male bastions such as law, academia, medicine, sciences, and engineering (American Bar Association 1996; American Medical Association 1994; Xie and Shauman 2003). Nevertheless, women in academia earn less and are

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less likely to receive tenure than their male counterparts (McBrier 2003; National Science Foundation 2003). Similarly, compared to men with similar characteristics, women working in science and engineering occupations are more likely to receive lower salaries and be offered part-time work (National Science Foundation 2002; Zuckerman 1987). Immigration to a new country creates its own opportunities and challenges for women. These challenges are related to the new social and cultural positions in which immigrant women find themselves in a new host society (Pedraza 1991). On the one hand, many women gain greater personal autonomy and access to social and economic resources, which were beyond their reach back home (HondagneuSotelo 1994). On the other hand, immigrant women often get caught in gendered and racialized institutional practices of their host countries that marginalize them to lower positions than immigrant men (with comparable skills) occupy (Man 2004; Raijman and Semyonov 1997; Xie and Shauman 2003). The disadvantages immigrant women experience in the skilled labor force compared to native men, native women, and immigrant men may stem from both individual-related (“supply”) and structure-related (“demand”) factors. What follows next is a brief overview of various theoretical perspectives developed to explain the gender and nativity gap in labor market outcomes and opportunities. The “supply-side” perspectives focus on the characteristics and decisions of the individual workers. In contrast, the “demand-side” perspectives pay more attention to the characteristics of the workplace and the actors within it. Supply-Side Barriers Human Capital Proponents of the human capital theory maintain that labor markets operate in a nondiscriminatory fashion. They explain gaps in earnings in terms of groups’ differences in human capital, such as education, training, and work experience (Becker 1964). With regard to the gender gap, human capital scholars believe that women do not invest as much in their human capital as men. Women invest less because they know that they will only participate in the labor market intermittently since they plan to exit the labor market in order to fulfill their social roles as

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wives and mothers (Becker 1985). Studies analyzing the labor market partially support this thesis. These studies find that, although women and men have the same amount of education, women have less job experience and on-site training (England 1992; Reskin and Roos 1990). Nevertheless, as Corcoran and Duncan (1979) show, differences in human capital cannot be the primary factor, as human capital differences account for less than 50 percent of the gender gap in pay. In the case of immigrants, the human capital theory predicts that upon arrival in a new country, immigrants possess lower levels of human capital and country-specific skills than native workers. Limited English abilities, lack of knowledge of the labor market, poor transferability of skills and training, and difficulties in obtaining professional credentials are possible factors that negatively affect the earnings of immigrants. The most serious challenge to the human capital theory is that it exclusively focuses on workers’ personal characteristics. No consideration is given to the impacts of the structural conditions of employment and the worker-job matching process nor to institutional inertia that carries over from past discriminatory practices (Duvander 2001; Fernandez 1998; Granovetter 1981; Marini 1989). To cite just one example, labor market-related barriers and not individual choices led Jewish, Korean, and Middle Eastern immigrants to pursue upward mobility through self-employment rather than through employment in the mainstream labor market (Lee 2000). Assimilation Those who immigrate voluntarily tend to be more ambitious, risktolerant, and educated than those who stay put in their home countries (Chiswick 2000). Nevertheless, immigrants are likely to experience difficulties in the labor market upon arrival. Despite these initial difficulties, assimilation theory predicts that over time immigrants will catch up with native workers in terms of their labor market performance and outcomes as they become assimilated culturally, linguistically, and economically (Bean, Lee, Batalova, and Leach 2004; Chiswick 1978; Richard and Nee 2003; Smith and Edmonston 1997). For example, Tang (1993) finds that among engineers in the United

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States there is a similarity in earnings between white native-born, Asian native-born, and Asian long-term immigrants. In contrast, Fernandez (1998) argues that neither human capital nor assimilation perspectives provide a full explanation of the earnings gap between Indian immigrant and native-born white workers. In her study, a large portion of variation in the probability of being a manager, as well as in the earnings of managers, is left unexplained after controlling for human capital and assimilation characteristics. To my knowledge, no extensive research has been done to examine a gender dimension in the experiences of highly skilled immigrants. Studies on economically active immigrant women in general demonstrate, however, that female immigrant workers face blocked mobility in the labor market to a greater degree than immigrant men, regardless of their tenure in the country (Boyd 1984; Raijman and Semyonov 1997). Double Disadvantage The double disadvantage perspective takes into account the interaction of workers’ characteristics such as nativity and gender (Boyd 1984; Husted, Nielsen, Rosholm, and Smith 2000; Raijman and Semyonov 1997). Its proponents argue that because of both their gender and nativity status, immigrant women will find it especially difficult to compete successfully in the labor market of their host countries. Therefore, the double disadvantage perspective would expect that being a female and being an immigrant are significant determinants of lower earnings net of other individual and structural factors. In other words, immigrant women are expected to earn less than their US-born female counterparts and less than their immigrant male counterparts. Demand-Side Barriers Dissatisfied with individual-level explanations provided by the supplyside barriers perspectives, students of economic inequality give more weight to structural aspects of the labor market. These approaches are briefly discussed below (for more see Chapter 4).

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Segmented Labor Market Researchers who use the segmented labor market theory to explain workers’ economic performance and outcomes argue that certain workers are disproportionately located in the lower segments of the labor market, which are characterized by low status, lack of job security, and poor mobility opportunities. Furthermore, the work of such workers is devalued by employers (Catanzarite 2003a; McBrier 2003; Reskin and Roos 1990; Waddoups and Assane 1993; Woo 2000). The operation of segmented labor markets is relevant to the study of women’s and immigrants’ economic performance and outcomes because these groups of workers, regardless of their skill level, are disproportionately located in the lower segments of the labor market (McBrier 2003; Reskin and Roos 1990; Waddoups and Assane 1993). Status Composition The proponents of the status composition perspective argue that occupations or jobs characterized by a high percent of women, racial minorities, or immigrants often become stereotyped and devalued (Catanzarite 2003b; Catanzarite 2004; England, Reid, and Kilbourne 1996; Huffman and Velasco 1997). The bias against such occupations adversely affects all workers employed there. Thus, using this perspective one may argue that persons working as registered nurses – an occupation with a high share of immigrant women – will pay an earnings penalty regardless of their nativity or gender. The same logic can be applied to workers in low-end computer occupations that are known for a high proportion of workers who are Indian and Chinese temporary immigrant workers. Thus, both segmented labor market and status composition perspectives focus on labor market discrimination against sectors and occupations in addition to discrimination against individual workers (Cohen and Huffman 2003b). Hypotheses As the above theoretical overview suggests, earnings differentials could be influenced by a number of individual and labor market factors. My first hypothesis addresses the double disadvantage argument:

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Hypothesis 1: Earnings of immigrant women in skilled jobs are lower than those of native-born women and those of their immigrant male counterparts after controlling for human capital, demographic, and assimilation variables as well as for job composition differences. The composition of jobs held by native and immigrant men and women determines one’s earnings as well. Students of skilled migration and its labor market impacts raise concerns that native women have little chance to obtain prestigious and well-paid jobs because they face unfavorable competition from the “best and the brightest” workers from abroad (North 1995). From their side, researchers of gender segregation in the workplace argue that female-dominated jobs are paid less because women’s work is devalued by society and employers (England, Herbert, Kilbourne, Reid, and Megdal 1994). Moreover, women working in female-dominated jobs earn less and have fewer chances for career mobility than men (Cohen and Huffman 2003a). To test these arguments on the case of skilled workers, I propose the following two hypotheses: Hypothesis 2: Earnings of native and immigrant women in skilled jobs are lower in jobs with a higher percentage of foreign born net of other personal and job characteristics. Hypothesis 3: Earnings of native and immigrant female and male workers are lower in jobs with a higher percentage of women net of other personal and job characteristics. Data and Methods To test my hypotheses, I employ multi-level modeling to analyze earnings determinants for native and immigrant male and female workers in location-specific skilled jobs as a function of individual and job characteristics. For my analysis, I use data drawn from the 5 percent 2000 Census PUMS file (for a detailed description of data and methodology, see Chapter 4).

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The dependent variable is earnings (the natural logarithm of annual earnings in 1999). The main independent variables are five dummy variables: Earlier immigrant male, earlier immigrant female, recent immigrant male, recent immigrant female, and native female (native-born male is the excluded category). To examine the influence of structural factors, I control for characteristics of location-specific skilled jobs defined in detail in the previous chapter. The main job-level explanatory variables in this analysis are Percent Foreign Born among the Highly Skilled Workforce (from now on, PFBHS) and its squared term and Percent Female among the Highly Skilled Workforce (PFEM) and its squared term. The squared terms are introduced to account for non-linearity. The individual and job-level control variables are the same as used in the analysis in Chapter 4. At the individual level, I test the interaction effect of nativity and gender on workers’ earnings. The equation for the individual-level model is: Yij = β0 + β1jEIMij + β2jRIMij + β3jEIWij + β4jRIWij + β5jNBWij + + ΣβkjXikj + Rij

(1)

Where Yij is the logarithm of annual earnings for person i in job j, and β0 is the individual-level intercept for US-born men; β1j to β5j are coefficients for the difference between earlier immigrant men (EIM), recent immigrant men (RIM), earlier immigrant women (EIW), recent immigrant women (RIW), native women (NBW), and the intercept (native men). Xikj is the set of human-capital, demographic, economic, and assimilation control variables that are centered at their grand means and βkj is the vector of coefficients associated with these control variables. The centering of the control variables means that the intercept, β0, is the log annual earnings for a native male worker with average characteristics on all the control variables. Finally, Rij is the level-1 error term, assumed to be normally distributed with a zero mean and constant variance. These individual-level coefficients become the dependent variables at the job level:

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β0j = γ00 + γ01(PFBHSj) + γ02(PFBHSsqj) + γ03(PFEMj) + + γ04(PFEMsqj) + Σγ0M(JOB varj) + U0j

(2)

β1j = γ10 + γ11(PFBHSj) + γ12(PFBHSsqj) + γ13(PFEMj) + + γ14(PFEMsqj) + U1j

(3)

β2j = γ20 + γ21(PFBHSj) + γ22(PFBHSsqj) + γ23(PFEMj) + + γ24(PFEMsqj) + U2j

(4)

β3j = γ30 + γ31(PFBHSj) + γ32(PFBHSsqj) + γ33(PFEMj) + + γ34(PFEMsqj) + U3j

(5)

β4j = γ40 + γ41(PFBHSj) + γ42(PFBHSsqj) + γ43(PFEMj) + + γ44(PFEMsqj) + U4j

(6)

β5j = γ50 + γ51(PFBHSj) + γ52(PFBHSsqj) + γ53(PFEMj) + + γ54(PFEMsqj) + U5j

(7)

βkj = γk

(8)

In equation 2, γ00 is the intercept for the job-level model of native male workers’ predicted log annual earnings β0j, and γ01 is the effect of PFBHS on β0j; Σγ0M is the effect of other job variables (grand-centered) on β0j. In this case, the intercept shows the log annual earnings of USborn men (the reference group), with average individual-level characteristics, employed in jobs with no significant presence of foreign born or women, and otherwise average job-level characteristics. In equations 3 to 7, γ10 to γ50 are the intercepts for the job-level models on β1j to β5j (the differences in the log annual earnings from native male workers); γ11 and γ51 are the effect of PFBHS and γ13 and γ53 are the effect of PFEM on β1j and β5j respectively. U0-5,j are the error terms at the job level and γk is the constant coefficient βk across all jobs.

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Results Descriptive Statistics Table 5.1.1 provides descriptive statistics at the individual level. It indicates that immigrant and native women earn less than their male counterparts. Regardless of gender, earlier immigrants have the highest annual earnings while recent immigrants have the lowest. Furthermore, earnings differences are smaller among women than among men. Earlier immigrant men earn the most, whereas recent immigrant women earn the least. Table 5.1.2 presents descriptive statistics for the job-level control variables. Table 5.2 and 5.3 show where, in terms of nativity and gender composition, skilled native and immigrant men and women tend to work. According to Table 5.2, the percent of foreign born in locationspecific skilled jobs ranges from 0 (e.g., education administrators in education in the Washington-Baltimore, DC-MD-VA-WV CMSA or lawyers in professional/scientific/technical industry in the Anchorage, AK MSA) to 76.6 (e.g., accountants and auditors in transportation in the Miami-Fort Lauderdale, FL CMSA). The variable’s distribution is skewed with a mean of 15.7 and median of 12.3. Native workers are much less likely to work with immigrants, while recent immigrants are more likely to work with other foreign born. Men, regardless of their nativity, are more likely than women to work in jobs with foreign born. Table 5.3 indicates that the percentage of females in locationspecific skilled jobs averages 51.7 percent and ranges from 0 (e.g., civil engineers in construction in the Las Vegas, NV-AZ MSA or aircraft pilots in transportation in the Colorado Springs, CO MSA) to 100 (nurses in education in Chicago-Gary-Kenosha, IL-IN-WI CMSA or speech language pathologists in health and social services in the Houston-Galveston-Brazoria, TX CMSA). Regardless of nativity, women are more likely to work with other women than are men. However, native women are much more likely to be in female-dominated jobs than either earlier or recent immigrant women.

Table 5.1.1 Descriptive Statistics for Individual-Level Variables

Variable

Dependent variable Annual earnings (ln) Earnings (thousand $) Independent variables Race and ethnicity White Black Asian Latino Disabled Not married

Native-born men

Native-born women

Earlier immigrant men

Earlier immigrant women

Recent immigrant men

Recent immigrant women

Mean

Mean

Mean Std

Mean Std

Mean

Mean Std

Std

Std

Std

11.1 64.6

0.7 2.0

10.7 42.4

0.5 1.7

11.1 65.5

0.7 2.0

10.7 46.0

0.6 1.7

11.0 57.0

0.7 2.0

10.6 40.8

0.6 1.7

0.9 0.1 0.0 0.0 0.1 0.3

0.3 0.2 0.1 0.2 0.3 0.4

0.8 0.1 0.0 0.0 0.1 0.4

0.4 0.3 0.1 0.2 0.3 0.5

0.3 0.1 0.4 0.2 0.1 0.2

0.5 0.3 0.5 0.4 0.3 0.4

0.2 0.1 0.4 0.2 0.1 0.3

0.4 0.3 0.5 0.4 0.3 0.5

0.4 0.0 0.5 0.1 0.1 0.3

0.5 0.2 0.5 0.3 0.3 0.4

0.3 0.1 0.5 0.1 0.1 0.3

0.5 0.3 0.5 0.3 0.3 0.5

Table 5.1.1 Descriptive Statistics for Individual-Level Variables (Continued)

Variable

Have a child under age 5 Degree No college Bachelor’s Master’s Doctoral/Professional Currently enrolled (%) Potential work experience

Native-born men Mean Std

Native-born women Mean Std

0.1

0.3

0.1

0.2 0.4 0.2 0.2 0.1 19.7

0.4 0.5 0.4 0.4 0.3 9.9

3.9

0.3

3.9

0.3

3.9 3.8

0.1 0.2

3.9 3.8

0.1 0.2

0.3

0.2 0.4 0.4 0.5 0.3 0.4 0.1 0.3 0.1 0.3 19.5 10.0

Earlier immigrant men Mean Std 0.1 0.3

Earlier immigrant women Mean Std

Recent immigrant women Mean Std

0.2

0.4

0.4 0.5 0.4 0.3 0.3 9.9

0.1 0.4 0.3 0.2 0.1 12.3

0.3 0.5 0.5 0.4 0.3 8.0

3.1 0.7

3.1 0.7

2.9

0.8

2.9 0.8

3.9 0.1 3.8 0.2

3.9 0.1 3.7 0.2

3.9 3.8

0.1 0.2

3.9 0.1 3.8 0.2

0.1 0.4 0.3 0.2 0.1 20.3

0.4 0.5 0.4 0.4 0.3 9.7

0.1 0.3

Recent immigrant men Mean Std

0.2 0.4 0.2 0.1 0.1 20.5

0.2 0.4 0.2 0.4 0.2 0.2 0.1 12.7

0.4 0.5 0.4 0.4 0.3 8.1

Assimilation English fluency Economic characteristics Weeks worked (ln) Hours worked (ln)

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Table 5.1.2 Descriptive Statistics for Job-Level Control Variables Variable Percent black Percent Latino Percent in high tech Region West Midwest Northeast South

Mean Std 7.5 9.0 4.9 8.0 0.1 0.3 0.2 0.2 0.2 0.4

0.4 0.4 0.4 0.5

Min Max 0.0 78.3 0.0 89.1 0.0 1.0 0.0 0.0 0.0 0.0

1.0 1.0 1.0 1.0

Table 5.2 Distribution of Workers in Location-Specific Skilled Jobs by Job's Nativity Composition All workers Quintile Min 1% 5% 10% 25% Median 75% 90% 95% 99% Max Mean

0.0 0.0 1.3 2.6 5.6 12.3 22.0 35.2 41.8 56.4 76.6 15.7

Native born

Earlier immigrant

Recent immigrant

Men Women Men Women Men Women 0.0 0.0 0.2 0.2 0.5 0.5 0.0 0.0 3.2 2.5 3.9 3.0 1.2 0.8 6.7 4.9 7.9 5.8 2.9 1.9 9.4 7.2 11.0 8.6 6.3 4.2 16.0 13.4 17.7 15.0 12.8 8.8 25.1 23.0 27.8 25.1 21.6 16.3 36.6 36.6 40.1 37.8 32.6 26.9 46.5 44.9 54.5 49.7 39.6 36.6 55.0 49.7 58.5 56.5 55.0 47.0 61.0 60.5 62.7 62.7 76.6 76.6 76.6 76.6 75.2 76.6 15.5 12.0 27.0 25.0 29.7 27.4

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Table 5.3 Distribution of Workers in Location-Specific Skilled Jobs by Job's Gender Composition All workers Quintile Min 1% 5% 10% 25% Median 75% 90% 95% 99% Max Mean

0.0 3.9 9.8 15.9 28.4 50.6 77.8 90.0 93.4 95.8 100.0 51.7

Native born

Earlier immigrant

Recent immigrant

Men Women Men Women Men Women 0.0 0.4 0.0 3.4 0.0 2.6 2.4 12.2 3.2 10.2 3.4 8.7 6.9 24.5 7.0 22.1 8.0 18.6 10.1 31.3 9.6 26.9 10.7 22.9 20.9 50.0 17.8 42.6 20.8 31.8 33.4 73.4 30.3 65.3 27.3 51.5 54.5 84.7 48.7 86.2 41.3 80.9 75.7 93.3 66.7 93.4 58.1 93.3 81.0 94.2 78.3 93.4 73.3 93.4 92.3 97.3 92.3 95.6 92.6 94.8 99.4 100.0 99.4 100.0 96.1 100.0 38.4 66.6 34.6 62.3 32.3 55.4

Multi-Level Modeling Results Table 5.4 presents four models. In each model, additional variables are included in the analysis. The analysis of the variance model (Model 1) indicates that with no controls at individual and job levels, 30 percent of the variance in the log annual earnings is attributable to the differences between location-specific skilled jobs. Differences between individual workers account for the remaining 70 percent (Raudenbush and Bryk 2002).17 Model 2 shows the effects of belonging to each of the six worker groups in jobs with insignificant foreign-born presence. Native-born men’s coefficient is a baseline; the coefficients for other groups represent differences in earnings from the baseline. With no individual or job controls, native-born men show the highest earnings ($57,500), followed closely by earlier immigrant men ($55,157) (the earnings values in dollars are derived by taking the exponential of the respective log value of the coefficient). Recent immigrant men are predicted to

Table 5.4 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native and Immigrant Men and Women in Skilled Jobs

Intercept (native-born men) Intercept PFBHS PFBHS squared PFEM PFEM squared Earlier immigrant men Intercept PFBHS PFBHS squared PFEM PFEM squared Recent immigrant men Intercept PFBHS PFBHS squared PFEM PFEM squared

Model 1

Model 2

Model 3

Model 4

10.84706***

10.95954***

10.93146***

11.06922*** 0.00914*** -0.00014*** -0.00274*** -0.00003***

-0.04161***

-0.01084*

0.02408 -0.00184+ 0.00002 -0.00029 0.00000

-0.20068***

-0.08253***

0.05193+ -0.00226 0.00001 -0.00340** 0.00003*

Table 5.4 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native and Immigrant Men and Women in Skilled Jobs (Continued) Model 1 Earlier immigrant women Intercept PFBHS PFBHS squared PFEM PFEM squared Recent immigrant women Intercept PFBHS PFBHS squared PFEM PFEM squared Native-born women Intercept PFBHS PFBHS squared PFEM PFEM squared

Model 2

Model 3

Model 4

-0.26344***

-0.15570***

-0.14641*** 0.00336*** -0.00004* -0.00478*** 0.00007***

-0.41380***

-0.22663***

-0.12593** 0.00206 -0.00003 -0.00812*** 0.00010***

-0.25197***

-0.17254***

-0.17963*** 0.00320*** -0.00003*** -0.00285*** 0.00004***

Table 5.4 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native and Immigrant Men and Women in Skilled Jobs (Continued) Model 1 Controls at level 1 Demographic characteristics Black Asian Latino Disabled Not married Have own child under age 5 Human capital Potential experience Potential experience squared Master’s Doctoral/Professional degree Enrolled in classes

Model 2

Model 3

Model 4

-0.07200*** -0.01567** -0.04861*** -0.05507*** -0.07065*** 0.04203***

-0.06878*** -0.01730** -0.04670*** -0.06754*** -0.07328*** 0.03920***

0.03895*** -0.00064*** 0.38227*** 0.47767*** -0.06299***

0.03897*** -0.00064*** 0.38223*** 0.47453*** -0.06358***

Table 5.4 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native and Immigrant Men and Women in Skilled Jobs (Continued) Model 1 Controls at level 1 (continued) Assimilation English fluency Labor market characteristics Weeks worked in 1999 (ln) Hours worked (ln) Controls at level 2 Intercept Ethnic composition % black % Latino High tech Region: West Region: Midwest Region: Northeast

Model 2

Model 3

Model 4

0.05273***

0.05277***

0.45819*** 0.45333***

0.45078*** 0.44974***

-0.00373*** -0.00295*** 0.06174*** 0.00784 -0.01139 0.01066

Table 5.4 Hierarchical Linear Model Results Predicting the Log Annual Earnings of Native and Immigrant Men and Women in Skilled Jobs (Continued)

Variance Components Individual Level Percent explained Job level Intercept Percent explained Earlier immigrant men's slope Recent immigrant men's slope Earlier immigrant women's slope Recent immigrant women's slope Native-born women's slope

Model 1

Model 2

Model 3

Model 4

0.29647

0.27961 5.69

0.23444 16.15

0.23440 0.02

0.12608***

0.12823*** -1.71 0.01960*** 0.05153*** 0.02590*** 0.04451** 0.01806***

0.10311*** 19.59 0.01437*** 0.04141*** 0.01426*** 0.03413** 0.00893***

0.06968*** 32.42 0.01421*** 0.03948*** 0.01254*** 0.03101** 0.00833***

Total variance 0.42255 0.56744 0.45065 0.40965 +p <0.1, *p<0.05, ** p<0.01, ***p<0.001 Note: Coefficients for other groups represent differences in earnings from native men with average characteristics. Omitted categories are white, not disabled, married, no own children under 5 years, college education or less, and South region;

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earn $47,045 per year, followed by US-born women ($44,693), then by earlier immigrant women ($44,183), and, after a big gap, by recent immigrant women ($38,015). Adding individual demographic, human capital, and assimilation variables (Model 3) reduces earnings variance by 16 percent at the individual level. The addition of these variables reduces the earnings differences from native male workers for each of the five groups, suggesting that differences in human capital, demographic, and economic characteristics provide some explanation for earnings differentials. Both immigrant and gender earnings disadvantages are evident (Model 2 and 3), but the adjusted coefficients show much smaller immigrant disadvantages than gender disadvantages (Model 3). Earlier immigrant men make almost the same as their native male counterparts; so do earlier immigrant women compared to their native counterparts. Recent immigrant men earn slightly less than other men while recent immigrant women make slightly less than other women. So far, the double hypothesis is supported for recent immigrant women but not for earlier immigrant women. That is, recent immigrant women earn about $7,000 less than recent immigrant men and about $2,500 less than native women. All control variables have effects in the expected direction and are statistically significant. Blacks, Asians, and Latinos earn less than whites. Respondents with limited knowledge of English, with some form of disability, the formerly married or never married, and those currently enrolled in school have lower annual earnings on average than their respective control groups. Workers with advanced degrees are paid significantly more than those with a college degree or less. Those working more weeks per year and longer hours per week also earn more. The impact of greater potential work experience is positive and statistically significant, although non-linear. The coefficients for these control variables at the individual level do not change substantially in the next model. It is interesting to note that the addition of individual controls reduces variation in earnings at the job level by almost 20 percent. This suggests that a significant portion of the earnings difference is explained by the kinds of workers who are employed in those jobs. Model 4 adds job-level main and control variables. According to the full model, the difference in earnings between native and immigrant men is not statistically significant. Model 4 indicates that controlling for all other factors, men earn more than women, with recent immigrant

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115

men earning the most and recent immigrant women earning the least. Model 4 demonstrates how the gender and nativity compositions of jobs affect one’s earnings. It indicates that there is a negative and significant effect of PFEM on all groups. In contrast, the results indicate positive and significant effects of PFBHS on native men and all women (coefficients of PFBHS for immigrant men are not significantly different from those of native men). The positive effects of PFBHS are greater for women than for men (i.e., PFBHS slopes for women are steeper than those of men). However, the effects for all workers are not linear. This means that women and men, regardless of their nativity, benefit from working in skilled jobs with a certain percentage of foreign born, after which more immigrants result in a decline in earnings. The tipping point, however, is different for the six groups of workers. The results are translated from logs to dollar values and graphically presented in Figure 5.1, which depicts the earnings of the six groups in jobs that vary in their nativity composition, and in Figure 5.2, which shows workers’ earnings by jobs that vary in their gender composition. Figure 5.1 demonstrates that as the percentage of foreign born in location-specific skilled jobs increases, the earnings of all groups go up until PFBHS reaches the 30-percent mark, at which point earnings take a downturn. The more precise value (indicated by the inflection point) is as follows: 33 percent for native men, 31 percent for earlier immigrant men, and 26 percent for recent immigrant men; 36 for earlier immigrant women, 33 percent for recent immigrant women, and 36 percent for native women. Keeping in mind the distribution of workers in location-specific skilled jobs shown in Table 5.2 and the inflection points of the six groups, the positive association between higher PFBHS and earnings holds for 90 percent of native men, slightly less than 95 percent of native women, about 60 percent of earlier immigrant men and women, less than 50 percent of recent immigrant men, and about 60 percent of recent immigrant women. A completely different picture is evident in Figure 5.2. Regardless of nativity or gender, all workers experience a substantial penalty if they work in female-dominated jobs. That is, those employed in location-specific skilled jobs with a higher percentage of women earn

Figure 5.1 Effect of Skilled Job’s Percent Foreign Born on Annual Earnings by Workers’ Nativity and Gender, Ages 25 to 64 Annual earnings ($)

NB men

8 0 ,0 0 0

75,0 0 0

EI men 70 ,0 0 0

6 5,0 0 0

RI men

6 0 ,0 0 0

EI women 55,0 0 0

50 ,0 0 0

RI women

4 5,0 0 0

NB women

4 0 ,0 0 0 0

10

20

30

40

50

P ercent foreign born in s killed jobs (P FBHS)

60

76

Figure 5.2 Effect of Skilled Job’s Percent Female on Annual Earnings by Workers’ Nativity and Gender, Ages 25 to 64 Annual earnings ($)

NB men

70,000 65,000

EI men 60,000 55,000

RI men

50,000

EI women

45,000 40,000

RI women 35,000 30,000

NB women 0

10

20

30

40

50

60

70

Percent female in skilled jobs (PFEM)

80

90

100

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Skilled Immigrant and Native Workers

less than workers with similar characteristics who work in more maledominated jobs. In addition, as shown before, men are less likely to work in female-dominated jobs. Thus, women experience two sets of disadvantages: First, because they are women, they are paid less than their male counterparts with similar characteristics; second, because women are more likely to work in female-dominated jobs, which pay less, female workers earn even less. Conclusion This chapter contributes to the limited literature on highly skilled workforce in the United States as well as to the literature on the influences of gender, nativity, and their interactions on economic inequality. In this chapter, I attempted to identify the presence and extent of a negative impact of dual status for immigrant women (Bean and Lowell 2003; Boyd 1984; Xie and Shauman 2003). I also examined the influence of structural factors such as the composition of locationspecific jobs on the gender and nativity pay gap. Workers in skilled jobs and occupations provide an interesting analytical case, as they work in environments where the norm of universalism is assumed to operate. Thus, it is expected that education and skills override considerations such as being female and foreign born. The analysis demonstrates that native and immigrant women and men with similar individual characteristics and in similar jobs are paid differently – with differences being more pronounced along gender than nativity lines. I find that in the case of skilled immigrant women, the double disadvantage hypothesis is not supported. Thus, while skilled immigrant women make less than their male counterparts, their earnings are not statistically different from those of US-born women, regardless of the job characteristics.18 In addition, what matters for workers’ earnings is the composition of skilled jobs. For the majority (more than 90 percent) of native male and female workers, it is to their financial advantage to work with foreign-born colleagues, although the effect is not linear. This advantage is applicable to a smaller percentage of immigrant workers (50 to 70 percent). My findings help alleviate the concern that recent policies that increased skilled immigration to the United States adversely affect native women (and men). In addition, I maintain that the debates about the possible negative labor market impacts of immigrants on

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opportunities for women professionals miss the point that employment of immigrant women may reduce gender imbalance in the traditionally male-dominated worlds of academia, law, science and engineering, and medicine (Xie and Shauman 2003). On the other hand, I find that all workers regardless of nativity, pay earnings penalties for working in female-dominated jobs. This is a hardly surprising result given numerous studies of female-dominated work, which report similar findings (England 1992; Tomaskovic-Devey 1993). However, the focus on skilled workers suggests that even women professionals, as a group, do not escape gender inequality in the workplace. Once again, workers’ gender is important, as male workers are sheltered from the most severe earnings disadvantages. I conclude that the earnings difference story for skilled native and immigrant men and women is a gender story. In the primary sectors, deepening labor market segmentation coupled with women’s recent inroads and the increased employment of foreign born may lead to stereotyping the lower strata of primary sector jobs as “women’s work” or “immigrants’ work” (Reskin and Roos 1990). The unfortunate consequence of such trends is that these jobs and occupations become less prestigious and less remunerated. This turns male and native workers away from such jobs, thereby perpetuating occupational segregation along gender and nativity lines. Even those women and immigrants who make it to the upper echelons of the primary sectors are likely to hit institutional barriers such as a glass ceiling, lack of access to informal networks, and absence of outreach and recruitment programs (Glass Ceiling Commission 1995; Woo 2000). My research again stresses the importance of structural conditions of inequality and biases against jobs filled by certain groups of workers. At least in the case of the earnings of skilled workers, gender is a more salient factor than nativity in determining one’s position and outcomes in the labor market. These findings strengthen the hypothesis that the underlying factor of earnings differentials is the devaluation by employers of the work done by women (Cohen and Huffman 2003b; England et al. 1994). My finding of a gender gap in pay, even after controlling for individual and job characteristics for skilled workers, is consistent with a national pattern of gender inequality in the labor market. Thus, there is a need to view my results in the context of

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gender inequality in general. Given the persistent devaluation of female-dominated jobs and pay penalties associated with them, it is essential to enforce anti-discrimination laws and initiatives to combat occupational segregation as a way to promote equality along gender and nativity lines.

CHAPTER 6

“End Restriction! Recruit!” or “End Recruitment! Restrict!” Further Thoughts on Highly Skilled Immigration in the 21st Century United States

In this study, I examined the economic implications of highly skilled immigration in the United States. More specifically, I applied a multilevel methodology to explore whether and to what extent a greater presence of skilled immigrants in a job is associated with a change in native earnings. The research contributes to the heated debates about whether or not skilled immigrants pose a competitive threat to nativeborn professionals. Empirical Contributions I find that the relationship between the share of foreign born in skilled jobs and natives’ and immigrants’ earnings is positive, albeit only up to a certain tipping point, after which the earnings decline for native and immigrant groups. For about 5 to 7 percent of native workers who are employed in skilled jobs with 35 percent (the tipping point) or more foreign born, a decline in earnings is associated with a greater percent of immigrants. However, for the overwhelming majority of native workers employed in skilled jobs, working with foreign-born colleagues is associated with an increase in earnings. 121

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Skilled Immigrant and Native Workers

As recent literature reviews on the impact of immigration on host labor markets indicate, no consensus on the direction or magnitude of the economic impact of immigration on either skilled or low-skilled workers currently exists among researchers (Congressional Budget Office 2005; Longhi, Nijkamp, and Poot 2005; Murray, Batalova, and Fix 2006). Therefore, my results shed further light on the issue and may alleviate the fears that skilled immigration is necessarily detrimental to all native highly skilled workers. Although the protection of native-born workers from unfavorable immigrant competition is the central theme in the debates over highly skilled immigration, I also find it instructive to examine the impact of immigrants (especially the recent ones) on the earnings of fellow immigrants. My analysis indicates that immigrants who arrived in the United States before 1990 are more similar to native workers than to recent immigrants in terms of their demographic, human capital, and economic characteristics. I also find no substantial differences in earnings between earlier immigrant and native-born workers, regardless of the proportion of immigrants in the jobs they held. In contrast, newcomers (those who arrived after 1990) seem to pay an assimilation price: Even controlling for individual and structural factors, their earnings are lower than those of both native-born and earlier immigrant workers in location-specific skilled jobs. They are also more likely to be in jobs characterized by a higher percentage of immigrants; these jobs, in turn, are less well remunerated. What is often lost in the analyses of economic impacts and integration of skilled (and unskilled) immigrants is that these immigrants are not a monolithic group that shares similar backgrounds, resources, and interests. My findings point to the importance of recognizing the diversity in the labor market experiences and outcomes of various immigrant populations. To address the concerns that the effects of skilled immigration might be particularly adverse for native women, I examined the determinants of earnings by gender. Three findings emerge from this analysis. First, native and foreign-born skilled women receive similar earnings and their earnings are lower than those of men. Second, for the overwhelming majority of US-born and earlier immigrant women, there is a positive relationship between higher concentrations of immigrants in skilled jobs and earnings. Third, employment in jobs with a greater presence of women has a negative impact on the earnings of all

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workers in that job. Nevertheless, men seem to be sheltered from the pay penalty associated with female-dominated work as they are less likely to be employed there in the first place. My results suggest that in the US skilled labor market, which is characterized by gender occupational segregation, gender matters more than nativity. These findings unambiguously highlight the importance of gender in the analysis of economic outcomes, which plays itself out both at the individual and structural levels. Theoretical Contributions One of the core tenets of the segmentation labor market theory is the importance of structural features of employment in explaining workers’ labor market outcomes. To date, the theory has been mainly used to analyze the determinants of earnings and employment of low-skilled native and immigrant workforce. My study extends the theory to the case of highly skilled workers. The results of the multi-level models indicate a positive but nonlinear relationship between nativity composition of skilled jobs and the earnings of workers in these jobs. I find that in jobs with a lower percentage (less than 2 percent) of immigrants, there are no significant differences in earnings among native and immigrant groups. In contrast, after the percent of immigrants reaches a certain tipping point – about 35 percent – a higher presence of immigrants results in a decline in earnings for native and earlier immigrant workers (the tipping point for recent immigrants is lower, about 26 percent). It suggests that these jobs might become defined as “immigrant” jobs. The literatures on labor market segmentation and occupational segregation argue that work is devalued in occupations and sectors that are dominated by certain groups of workers – women, low-skilled Latino immigrants, and blacks. And, as a result, everyone in such workplaces suffers earnings penalties (Catanzarite 1998; Cohen and Huffman 2003a; England 1992; England et al. 1994). My analysis shows that a similar process might take place at the highly skilled level as well. Jobs with a high percentage of immigrants tend to be in hightech and science occupations and concentrated in education and professional/science industries. As the US economy increasingly demands a skilled and educated labor force in high-tech, science,

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Skilled Immigrant and Native Workers

medicine, and education and relies on immigration as a method to expand it, the questions of economic impacts of immigrants have to be considered in the context of deepening labor market segmentation and occupational segregation. Avenues for Future Research My research suggests several avenues for further investigation. First, although I control for various individual and structural characteristics, it is possible that due to limitations in the data, there are important factors that were not accounted for. For example, controlling for economic conditions such as demand for skilled labor would reflect more precisely the relationship between earnings and nativity job composition in the data analysis. Second, although I do not find that the presence of immigrants had a negative effect on the earnings of the majority of native workers, questions of implications of skilled immigration on other kinds of labor market outcomes (e.g., likelihood of unemployment, underemployment, or permanent switch to another occupation/job type) leave fertile ground for future empirical investigations. For example, Ong and Valenzuela (1996) find that while the low-skilled Latino immigrants in Los Angeles slightly boost the wages of native-born African Americans, their presence also increases joblessness of native workers. In other words, it is possible that skilled immigrants “help” the earnings of those natives who keep their jobs but decrease their employment prospects. As critics of temporary skilled worker programs point out, the immigrant impact on employment may be particularly adverse for certain groups of native workers – recent PhD graduates or older native workers (Borjas 2005; Matloff 2001). Therefore, researchers need to pay more attention to these possibly disadvantaged groups of native workers. Third, important information is missing from the Census data, which could be helpful in explaining economic impacts of skilled immigration as well as earnings differences across groups. For example, admission and visa status of immigrant workers (i.e., whether the person is on an H-1B visa), where workers received their education (i.e., in the United States or abroad), and employers’ characteristics are absent in the Census data. My multi-level analysis indicates that

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125

individual characteristics explain a considerable portion in earnings variation among native and immigrant workers. Nevertheless, even controlling for individual factors, recent immigrants are still predicted to earn significantly less than native and earlier immigrant workers. Since many of these recent immigrants are on temporary visas working in high-tech, science, and engineering occupations, a dependency on their employer for legal status most likely has a crippling effect on their earnings. For the same reason, individuals, regardless of nativity, who are working in jobs with a large number of H-1B holders, might pay an earnings penalty compared to other workers with similar characteristics who are in jobs with fewer immigrants. These questions could be better answered with data sets that combine admission and visa status with economic characteristics and outcomes. However, to this date, with few exceptions, such data sets are not available despite a great need for the analyses. Policy Considerations In political and public debates in the United States and other countries that rely on foreign labor, both economic impacts and the integration of immigrants are hot-button issues. Nevertheless, until recently, skilled foreign workers have attracted much less attention than low-skilled immigrants and refugees. They tend to be perceived as individuals who are beneficial (and necessary) to the country’s economic and social well-being in an increasingly competitive global economy. Skilled foreigners are said to be “good” immigrants because they join the labor market without significant investment on the part of the receiving country, earn higher wages, pay higher taxes, and are unlikely to be in need of social assistance. However, some observers do not share the idea that the impacts of highly skilled immigrants are only positive. As my historical overview indicates, like the labor unions who represented miners and factory workers and fought against increasing immigration in the end of the 19th century and the early 20th century, researchers along with professional organizations today cite examples of native skilled workers losing their employment, receiving lower payment for their work, and otherwise being adversely affected by the greater presence of skilled foreigners (Interpreter Releases 2006c).

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Skilled Immigrant and Native Workers

Therefore, policy makers in the United States face the challenge of achieving two, somewhat contradictory, goals: Expand skilled immigration to address labor needs and protect domestic highly skilled workers from unfavorable competition (Papademetriou 1999; Papademetriou and Yale-Loehr 1996; Usdansky and Espenshade 2001). The multifaceted nature of skilled immigration makes it difficult to offer easy policy solutions. Global competition for foreign talent, the mismatch between supply of the domestic workforce (higher education policy) and demand for it (labor policy), and national security considerations all have to be taken into account in devising and implementing a successful system of skilled admission. However, one thing is clear: Rhetorical arguments such as blaming immigrants for economic competition with highly skilled natives or shutting the doors as the only way to protect US workers would cause more harm than good to the country in the long run. Such an approach overlooks the benefits the country gains from having such immigrants and ignores the deepening segmentation of US labor market that affects the earnings structure and opportunities of all workers. I argue that the current visa regime for highly skilled foreigners is too rigid and not set to adapt quickly to the changing realities of the labor market. Indeed, the structure of permanent immigration system has been revised only twice in the last forty years! Some of the proposals currently pending in Congress (as of spring 2006) would amend the visa caps for permanent and temporary employment-based visas, but only as a one-time deal (Rosenblum 2006). Instead, a more flexible system of visa allocation is needed. Moreover, the current admission system enforces entry heavily but does virtually nothing to regulate labor practices at the workplace. Employers with good intentions are forced to go through a burdensome and lengthy process of labor certification. Unscrupulous employers, on the other hand, take advantage of a complicated and lengthy process of labor certification to their own financial benefit. For example, some employers sell or trade approved labor certifications to the highest bidder, as reported by a recent study by the Department of Labor (Interpreter Releases 2006a). For these and other reasons, many experts consider labor certifications to be a feeble way to protect domestic workers, rather stressing the need to establish effective mechanisms to monitor post-

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127

hiring practices such as universal enforcement of wage and labor standards (Martin 2006). Again, the current proposals discussed in Congress would not do enough to change the focus on regulation, even though many have persuasively argued for more workplace scrutiny (Rosenblum 2006). Finally, as my review of policy challenges indicates, increasing global competition for foreign students and skilled and educated foreign workers as well as national security concerns associated with the work of skilled foreigners highlight the need to incorporate immigrant workers into the economic and social life of the United States sooner rather than later. Today, having favorable admission policies only is simply not enough. The United States needs to employ strategies to ensure successful integration of these immigrants in the American labor market and American society. Early integration will provide all the benefits of having loyal residents who support the interests of the United States. Therefore, for the immigration system to be effective in achieving the long-term goals of economic well-being of workers and of national security, I argue that it needs to have three features: Flexibility in the issuance of permanent and temporary visas that would be responsive to genuine labor market needs; Enforcement of labor practices to ensure that immigrant workers are brought to fill real needs and are treated fairly at the workplace; and Integration of immigrants so they are invested in the well-being of the United States.

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Appendices

129

Appendix A. Types and Limits of Employment-Based Immigrant Visas* Preference

Type of worker

Numerical limit

Permanent Labor Certification required?

1st preference (EB-1)

"Priority workers": Persons of extraordinary ability in the arts, science, education, business, or athletics; outstanding professors and researchers; and certain multinational executives and managers

28.6 percent of worldwide limit plus unused 4th and 5th preferences

No

2nd preference (EB-2)

Members of professions holding advanced degrees or persons of exceptional abilities in the sciences, art, or business

28.6 percent of worldwide limit plus unused 1st preference

Yes (except national interest waivers)

3rd preference (EB-3)

"Skilled": Skilled shortage workers with at least two years training or experience, professionals with Bachelor's degrees

28.6 percent of worldwide limit plus unused 1st or 2nd preferences, of which not more than 10,000 numbers are available for unskilled workers**

Yes

and “Other": Unskilled shortage workers

Appendix A. Types and Limits of Employment-Based Immigrant Visas (Continued)* Preference

Type of worker

4th preference (EB-4)

"Special immigrants": Ministers of religion, religious workers other than ministers, certain employees of the US government abroad, and others

5th preference (EB-5)

Employment creation investors whose investments will create employment for at least ten US citizens or lawful permanent residents (LPR)

Numerical limit 7.1 percent of worldwide limit; religious workers limited to 5,000

Permanent Labor Certification required? No

7.1 percent of No worldwide limit; 3,000 minimum reserved for investors in rural or high unemployment areas Note: *The total annual number of visas allocated for employment-based immigration 140,000. **Although the limit under the statue is set at 10,000 visas for unskilled workers, beginning in Fiscal Year 2002, 5,000 visas are taken away temporarily by the Nicaraguan Adjustment and Central American Relief Act (NACARA), until all NACARA applicants are processed. Sources: US Department of State. Appendix A “Provisions of the Law and Numerical Limitations on Immigrant Visas”; Brian Christian. 2000. “Facilitating High-Skilled Migration to Advanced Industrial Countries: Comparative Policies,” Table 17, p. 74. Washington, DC: Georgetown University, Institute for the Study of International Migration.

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas Class

Visa name

Workers E-1 Treaty traders E-2 Treaty investors E-3 Treaty aliens in specialty occupations*

Initial stay

Cap on the number of annual petitions

Maximum stay

Domestic worker protection requirements

Variable, up None (E-1, E-2); to 2 years 10,500 for E-3 principal applicants

Up to 2 years per extension. No maximum number of extensions, with some exceptions

H-1A Registered Nurses

Variable, up The H-1A program to 3 years ended in 1995

Up to 3 years per extension. Labor attestation Total stay limited to 5 years required,** employers must pay prevailing wage

H-1B Temporary workers in specialty occupations

Variable, up 65,000 (first time to 3 years applications; no limit on extensions)***

Up to 3 years per extension; Stay limited to 6 years, with further 1-year extensions for those who have adjustment of status applications pending

None

Labor Condition Application submitted to DOL: employers must attest to lack of strike, payment of prevailing wage, and proper working conditions

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Class

Visa name

Initial stay

Cap on the number of annual petitions

H-1C Nurses in shortage areas

Variable, up to 3 years

The H-1C program ended in September 2004

H-2A Temporary agricultural workers

H-2B Temporary workers (skilled/unskilled)

Maximum stay

Domestic worker protection requirements

Total stay limited to 3 years

Labor attestation required

Variable, up None to 1 year (same as validity of labor certification)

Up to 1 year extension increments to a total of 3 years

Employers must apply for temporary labor certification,**** offer housing, transportation, and meals or cooking facilities, and prescribed wages and working conditions

Variable, up 66,000 to 1 year (same as labor certification)

Up to 1 year per extension

Employers must apply for temporary labor certification, offer prevailing wages

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Class

Visa name

Initial stay

H-3 Industrial trainees

Special education training, up to 18 months; other trainee, up to 2 years

I-1

Duration of employment

Journalists and foreign media

Cap on the number of annual petitions None

None

Maximum stay Special education trainee, total stay limited to 18 months. Other trainee, total stay limited to 2 years

Duration of employment

Domestic worker protection requirements The employer must demonstrate: 1) the training is not available in the foreign national’s home country; 2) the trainee will not be placed in a position ordinarily filled by a US worker None

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Class

L-1

Visa name

Executive/managerial and specialized knowledge intracompany transferees

O-1 Temporary workers with extraordinary ability/achievement O-2 Temporary workers accompanying and assisting in performance of O-1 workers

Initial stay

Cap on the number of annual petitions

Maximum stay

Domestic worker protection requirements

Variable, up to 3 years

None

Up to 2 years per extension. Those with specialized knowledge limited to 1 extension. Total limitation is 7 years for managers and executives and 5 years for those with specialized knowledge

None

Variable, up to 3 years

None

Up to 1 year per extension. No maximum number of extensions

Advisory opinion from worker organizations (to obtain views from potentially affected worker organizations)

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Class P-1

P-2

P-3

Visa name Temporary workers – internationally recognized athletes or entertainers Temporary workers – artists or entertainers (reciprocal exchange programs) Temporary workers – artists or entertainers (culturally unique programs)

Q-1 International cultural exchange visitor Q-2 Irish peace process cultural and training program aliens

Initial stay Athletic and entertainment groups, up to 1 year; Individual athletes, up to 5 years

Variable, up to 15 months Variable, up to 3 years

Cap on the number of annual petitions None

None None

Maximum stay Athletic and entertainment groups, up to 1 year per extension, with some exceptions; Individual athletes, up to 5 years per extension, total stay limited to 10 years

Total stay limited to 15 months Total stay limited to 3 years

Domestic worker protection requirements Advisory opinion from worker organizations (to obtain views from potentially affected worker organizations)

None None

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Visa name

Initial stay

R-1

Religious workers

TN

North American Free Trade Agreement (NAFTA) professional workers

Variable, up to 3 years Variable, up to 1 year

Class

Cap on the number of annual petitions None

Maximum stay

Domestic worker protection requirements None

None

Up to 2 years per extension. Total stay limited to 5 years Up to 1 year per extension. No maximum number of extensions

Duration of status

None

Duration of status

N/A

Variable, up to 1 year

None

Up to 1 year per extension. No maximum number of extensions

N/A

None; professionals applying must prove proper credentials and existing job offer

Students and Exchange Visitors F-1

Students – academic institutions

M-1 Students – nonacademic institutions

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) Class

J-1

Visa name

Exchange visitors (include students, research scholars, au pairs, government visitors, camp counselors, etc.)

Initial stay

Duration of status

Cap on the number of annual petitions None

Maximum stay

Duration of status

Domestic worker protection requirements N/A

Notes: *For Australian citizens only. Modeled after H-1B visa with some elements of E treaty visa (see INA Section 101(a)(15)(E)(iii)). **Labor attestation requires employers to attest to the Department of Labor that they will provide working conditions consistent with those of similarly employed workers and pay prevailing wages, that there is no strike or lockout, and that they have posted the job application at the work site. ***Nonprofit organizations and institutes of higher education are exempt from the cap. As of 2003, 6,800 visas are set aside from the annual 65,000 cap for the H-1B1 program under terms of the US-Chile (1,400 visas) and US-Singapore (5,400 visas) Free Trade Agreements. As of May 2005, 20,000 more H-1B visas became available for foreign nationals who received their Master's or higher degrees in the United States.

Appendix B. Class of Admission, Time Limits, Visa Caps, and Domestic Worker Protection Requirements Associated with Work-Related Nonimmigrant Visas (Continued) **** Labor Department certification requires that employers prove an inability to find US workers to fill the job, and that the employment of temporary workers will not adversely affect the wages or working conditions of native workers. Sources: The table was adapted from Jeanne Batalova (2006) "The Growing Connection between Temporary and Permanent Immigration Systems." Appendix 2. Policy Insight #14. Washington, DC: Migration Policy Institute; Deborah W. Meyers (2006) "Temporary Worker Programs: A Patchwork Policy Response." Policy Insight #12. Washington, DC: Migration Policy Institute.

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Appendices

Appendix C. Occupational Groups and Detailed Occupations Defined as Highly Skilled Occupational Group Management

Detailed Occupations based on SOC 2000 • • • • •

Business & Financial Operations

• • •

Chief executives Legislators Advertising and promotions managers Marketing and sales managers Public relations managers

•

Management analysts Accountants and auditors Budget analysts

• •

Computer Scientists

•

Computer scientists and systems analysts

Computer Programmers & Engineers

•

Computer programmers

Computer Technical Support

•

Database administrators

Math Scientists & Engineers

• •

Actuaries Operations research analysts

• • • •

•

Computer and Information Systems managers Education administrators Engineering managers Natural sciences managers Social and community service managers Financial analysts Personal financial advisors Financial examiners

•

Computer software engineers

•

Miscellaneous math science occupations (including mathematicians and statisticians)

Appendices

141

Appendix C. Occupational Groups and Detailed Occupations Defined as Highly Skilled (Continued) Occupational Group

Architects & Engineers

Detailed Occupations based on SOC 2000

• • • • • • •

Architects, except naval Surveyors, cartographers, and photogrammetrists Aerospace engineers Chemical engineers Civil engineers Computer hardware engineers Electrical and electronics engineers

• • • • • • • •

Life Sciences: Researchers

• • • • •

Social Sciences: Researchers

• • •

Agricultural and food scientists Biological scientists Conservation scientists and foresters Medical scientists Astronomers and physicists

•

Economists Market and survey researchers Psychologists

•

Physicians & Surgeons

•

Physicians & Surgeons

Registered Nurses

•

Registered Nurses

• • •

•

Environmental engineers Industrial engineers, including health and safety Marine engineers and naval architects Materials engineers Mechanical engineers Nuclear engineers Petroleum, mining, geological engineers Engineers, including agricultural & biomedical Atmospheric and space scientists Chemists and materials scientists Environmental scientists and geoscientists Physical scientists, all other Urban and regional planners Miscellaneous social scientists, including sociologists

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Appendices

Appendix C. Occupational Groups and Detailed Occupations Defined as Highly Skilled (Continued) Occupational Group Other Health Practitioners

Detailed Occupations based on SOC 2000 • • • • • • •

Chiropractors Dentists Dietitians and nutritionists Optometrists Pharmacists Physician assistants Podiatrists

• • • • • • • •

Audiologists Occupational therapists Physical therapists Recreational therapists Speech-language pathologists Therapists, all other Veterinarians Health diagnosing and treating practitioners, all other

Healthcare Technicians

•

Clinical laboratory technologists and technicians

•

Other healthcare practitioners and technical occupations

Education & Training

• •

Postsecondary teachers Elementary and middle school teachers

•

Secondary school teachers Special education teachers

• • • •

Counselors Social workers Clergy Directors, religious activities and education Lawyers Judges, magistrates, and other judicial workers Archivists, curators, and museum technicians

• •

Other Professionals: Legal, Community Service, Entertainment

• • •

•

• • • • •

Librarians Other education, training, and library workers Producers and directors News analysts, reporters and correspondents Public relations specialists Editors Writers and authors

Appendices

143

Appendix C. Occupational Groups and Detailed Occupations Defined as Highly Skilled (Continued) Occupational Group Nonprofessional occupations (as defined by the SOC-based Census 2000 classification)

Detailed Occupations based on SOC 2000 • •

Securities and financial services sales agents Sales engineers

•

Aircraft pilots and flight engineers

Source: US Census. 2003. Technical Documentation: Public Use Microdata Sample, 2000. Appendix G. Occupation Code List for the 5Percent PUMS Files. Washington DC.

Appendix D. Number of Skilled Workers by Nativity and Industry Recent immigrants

Earlier immigrants

Native born

Total

Manufacturing Manufacturing: nondurable

30.1

52.6

496.1

578.8

104.0

169.0

1,390.5

1,663.5

Professional, scientific, technical Management, administrative, and waste management services

206.2

267.6

2,854.0

3,327.8

12.1

23.7

240.3

276.1

Educational

172.8

322.1

5,658.1

6,152.9

Health and social services

185.4

461.0

4,013.6

4,660.0

57.1

122.6

1,244.7

1,424.5

4.4

10.9

122.0

137.3

Manufacturing durable Professional services

FIRE Finance, insurance Real estate, rental and leasing

Appendix D. Number of Skilled Workers by Nativity and Industry (Continued) Recent immigrants Public administration

Earlier immigrants

Native born

Total

18.7

81.5

1,082.8

1,183.0

Agriculture, forestry, fishing and hunting, and mining

4.1

4.9

97.9

106.9

Construction

8.4

24.7

274.1

307.2

Wholesale trade

22.8

38.7

296.9

358.4

Retail trade

34.5

57.8

578.1

670.5

Transportation and warehousing

9.2

23.4

240.1

272.7

Utilities

3.4

12.2

155.9

171.5

52.2

76.6

867.6

996.4

8.8

20.2

275.0

304.0

23.0

47.4

679.7

750.1

957.3

1,816.9

20,567.4

23,341.6

Other industries

Information Arts, entertainment, recreation, and food services Other services (except public administration) Total number

Appendix E. Average Earnings of Native and Immigrant Skilled Workers and Percent Foreign Born in Occupation

Management Business and financial operations Computer scientists Computer programmers/engineers Computer technical support Math scientists and engineers Architects and engineers Life sciences: researchers Social sciences: researchers Physicians and surgeons Registered nurses Other health practitioners Healthcare technicians Education and training Other professionals Non-professional occupations

Average earnings (in thousands of dollars) Percent workers in occupation who are Earlier Recent foreign born Native-born immigrants immigrants 84.7 95.1 98.4 9.3 60.6 56.5 57.6 12.5 59.9 63.8 66.2 16.7 64.3 72.5 66.4 24.7 57.7 68.5 71.6 17.8 63.5 67.3 63.3 12.2 63.7 70.3 60.7 16.6 57.1 62.0 44.0 25.1 59.0 75.5 69.6 10.1 150.3 148.3 84.4 26.1 45.2 53.9 48.3 12.0 58.3 62.7 54.8 11.4 39.1 43.0 36.8 15.1 43.0 54.2 38.6 7.5 55.5 50.2 47.3 7.2 96.4 85.1 103.2 9.1

Notes

1

Ironically, the term “brain drain” was first used not to describe the emigration of skilled persons from less developed countries but the outflow of British scientists and technologists to the United States and Canada. The term was coined by the Royal Society of London in the 1950s. Today, it is used more generally and it refers to the loss of scientists, researchers, top business executives, and other highly skilled and highly educated persons. 2 Prior to the American Civil War (1861–1865), for the most part, it was not the federal government but port states that had control over who disembarked on their shores (Zolberg 2006). 3 Presidents Cleveland, Taft, and Wilson vetoed prior attempts to introduce literacy measures (which required that an immigrant must be able to read in at least one language as a condition of entry) in 1896, 1913, and 1915. President Wilson again objected to this clause in the 1917 Immigration Act but it was still passed by Congress over his veto. 4 These laws limited immigration mostly from the Eastern Hemisphere. At the same time, legal and unauthorized immigrants from Mexico and other countries of the Western Hemisphere were arriving both to stay permanently and to work on a temporary basis in great numbers. About 4.5 million Mexican guest workers were hosted under the two “Bracero” Programs between 1942 and 1964. Another 66,000 workers were employed through the British West Indies program between 1943 and 1947 (Meyers 2006). The United States implemented these temporary labor programs in response to domestic labor shortages in agriculture, railroads, and assembly operations that appeared during World War II. 5 The process of obtaining a permanent labor certification had been criticized as being complicated, time consuming, and requiring the expenditure of considerable resources by employers, State Workforce Agencies, and the Federal government. For a critical review of the labor certification and other

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Notes

domestic worker protection programs, refer to Papademetriou and Yale-Loehr 1996: Chapter 3. 6 Although it maintained the basic goals and principles of the 1952 INA and 1965 INA Amendments (i.e., family reunification being the core of US immigration), IMMACT90 represented the most comprehensive restructuring of legal permanent and temporary immigration since 1965. The discussion of its implications on non-employment-related immigration is beyond the scope of this chapter. 7 The split came as a result of the Immigration Nursing Relief Act of 1989. The H-1A visa program was small in scale (about 7,000 visas per year) and ended in 1995. 8 Under the INA, foreign nationals applying for a non-immigrant visa (e.g., tourist, student, or temporary worker visa) must demonstrate that they have foreign residence, which they have no intention to abandon. The IMMACT90 waived this requirement for H-1B, L-1, and O-1 applicants, thus making these visas “a natural funnel into permanent immigration” (Papademetriou and O'Neil 2004: 18). 9 US Immigration Services does not track the number of people arriving on non-immigrant visas but the number of admissions. Thus, for example, if a non-immigrant enters the United States three times within the same fiscal year (on the same or different non-immigrant visa), three admission entries will be recorded. 10 The program was folded into the general immigration law in 2005 and no longer exists in its original form. 11 In response to the criticism from American universities (about the unreasonable security checks and delays in visa processing that also send a message to the world that the United States no longer welcomes foreign students and exchange visitors), the Department of State made a number of steps to improve the reality and perception of the student visa issuance process (Yale-Loehr, Papademetriou, and Cooper, 2005, see Appendix E). 12 The civilian labor force is defined as persons between 25 and 64 years of age, employed or unemployed, who are neither in military service nor residing in group quarters. The nativity variable is based on the Census “citizenship status” variable: Native born are defined as individuals who were born in the United States or abroad to American parents; foreign born are defined as individuals who were born outside of the United States, in Puerto Rico, and other US territories. In this book, the terms foreign born and immigrant are used interchangeably.

Notes 13

149

Following Bean et al. (2004), I consider four racial-ethnic categories, Non-Latino whites, Non-Latino blacks, Non-Latino Asians, and Latinos. My definition of these categories combines race and ethnicity information and forces mutual exclusivity. First, I group all Latinos regardless of their race into one group. To control for the multiple-race identification available in the 2000 Census, I categorize hierarchically the remaining non-Latinos into the largest racial minority with which they identified. For example, a person who identified as ‘black only’ or as ‘black with other race combinations’ was classified as non-Latino black. From the remaining group, Asians were classified as non-Latino Asians in a similar fashion. The last category is the non-Latino whites. For simplicity, I label these groups as whites, blacks, Asians and Latinos. 14 A word of caution has to be made about the unemployment rate. In the 2000 Census, the unemployment rate is derived from the “Employment Status” question and shows the percent of people who answered “unemployed” as of the entire civilian labor force. However, there are concerns about the overestimation of the numbers of unemployed in Census 2000 because of the changed question on employment status. In 1990, the question read “Did you work at any time last week?” while in 2000 the employment question read “Last week, did you do any work for either pay or profit?” According to a Census report that compared 2000 Census and 2000 CPS estimates of the employed and unemployed, the census unemployment rate was 2.1 percentage points higher than the Current Population Survey rate. The reported differences between the two data sets persist across sex, age, and race/ethnicity (US Census. Housing and Household Economic Statistics Division 2003). Unfortunately, there is no way to fix the problem at this point. 15 As will be discussed later in greater detail, I use the information on occupation, industry, and metropolitan area to define a workplace (i.e., a location-specific skilled job) where skilled workers work. 16 Since the visa status information is not available in the PUMS file, there is no way to identify precisely who H-1B visa holders are. My definition of recent immigrants captures H-1B current and former workers as well as other immigrants who arrived to the United States after 1990 and were employed in 1999. Recent immigrants, who tend to be worse off in their labor market experiences and outcomes compared to earlier immigrants and natives, might be disadvantaged more in jobs with higher presence of other newcomers. 17 Model 1 is a baseline model with no variables but an intercept that varies by level-2 units. The data in the variance component panel allows calculation of an intraclass correlation coefficient (ICC), which shows the

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Notes

percent of the variance in the log annual earnings explained by the variance between level-2 units. From Model 1, ICC=0.12608/(0.12608+0.29647)=29.8% (Raudenbush and Bryk 2002: 36). 18 The earnings differences reflected in the coefficients in Table 5.5 are in relationship to native-born men. I ran a similar analysis using native-born women as the omitted category to find out whether the earnings of immigrant women are statistically different from those of native women. The results of this analysis indicate that the differences are not statistically significant at alpha level of 0.01.

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Index

A American Competitiveness and Workforce Improvement Act (ACWIA), 25 American Competitiveness in the 21st Century Act (AC-21), 25-26 American Federation of Labor, 12. See also labor unions American universities, 1, 30, 58 reputation of, 29 Arizona prop. 200, 10 Asian immigrants, 12, 14, 24, 4748, 55 Asian immigration, 15 “Asiatic barred zone,” 14 assimilation, 15, 101, 102, 114 price, 91, 93, 122 theory, 98-99 Australia, 34 foreign students in, 29, 30 point system, 28 recruitment of foreign talent, 1, 28, 91

Batalova, Jeanne, 4, 27, 35, 43, 44, 50, 70, 98, 122 Bean, Frank D., 2, 10, 27, 31, 32, 40, 43, 44, 65, 66, 98, 118 “the best and the brightest,” 1, 37, 61, 101 Borjas, George, 2, 27, 38, 66, 67, 70, 92, 124 Boyd, Monica, 93, 95, 99, 118 “Bracero Program,” 147 brain drain, 2, 147 brain gain, 2, 27, 31-32, 65 Brown, Susan K., 31, 32 “brown-collar” occupations, 69, 91 Bureau of Labor Statistics (BLS), 37, 94 projections, 3, 43 C Calavita, Kitty, 12, 13 California, 10, 44 Chinese Exclusion Act, 13 prop. 187, 10 prop. 227, 10 Canada, 34 foreign students in, 29, 30 loss of own talent, 2

B backlogs, 21, 24, 35 175

176

Index

point system, 28 recruitment of foreign talent, 1, 28, 91 Canberra Manual, 41 Catanzarite, Lisa, 2, 69-71, 91, 96, 100, 123 Census data, 3, 6, 37, 40, 42, 124 China, 28, 33, 35, 48 boosting own education capacities, 30 Chinese Exclusion Act, 13 Chinese laborers, 12, 14 H-1B workers from, 24 classical economic theory, 66 Cohen, Philip, 69, 71, 73, 91, 95, 96, 100, 101, 119, 123 Cold War, 16, 18, 50 complementarity, 6, 66, 70, 73, 92 Congress, 2, 12, 18, 19, 20, 22, 25, 36, 92, 126, 127 and H-1B, 22, 25 Contract Labor Law of 1885, 13, 18 Cuba, 48

E economic impacts, 2, 5, 7, 26, 27, 69, 70, 73, 94, 122, 124, 125 of highly skilled immigrants, 2, 7, 27, 122, 124 The Economist, 30 employment enforcement mechanisms, 35 employment-based immigration, 16, 19, 20, 22, 35, 38, 93 employment-based preferences. See employment-based immigration enforcement feature, 8, 127 England, Paula, 68, 69, 71, 91, 95, 98, 100, 101, 119, 123 Espenshade, Thomas J., 2, 13, 16, 18, 20, 25, 66, 71, 92, 126 eugenicists, 14 European immigration, 14, 15, 19, 48 and literacy test, 14 statistics on, 14

D Department of Labor (DOL), 19, 21, 23, 25, 126 Department of State (DOS), 20, 21, 24 discrimination, 31, 91, 93, 97, 100, 120 double disadvantage hypothesis, 6, 7, 99, 101, 118 dual intent, 23 Durand, Jorge, 6, 10, 67, 94

F family-based immigration, 16, 18, 19, 40, 92 family-based preference. See family-based immigration family reunification, 38 Favell, Adrian, 1, 66 “female” job. See femaledominated job female-dominated job, 7, 91, 101, 104, 115, 118, 119, 120, 123 Fix, Michael, 27, 66, 70, 122 flexibility feature, 8, 127

Index foreign students, 1, 27, 29-32, 34, 127 statistics on, 29-30 foreign talent, 1, 3, 11, 27, 28, 31, 34, 61, 91, 126. See also skilled immigrants France, 28, 30 Fraud Prevention and Detection Fee, 26 G German American Alliance, 15 Germany, 28, 32, 48 “Green Card” scheme, 28 loss of own talent, 2 globalization, 1, 4 H H-1 visas, 18-22 qualifications for, 19 numerical limit, 19 statistics on, 20 H-1A visas for registered nurses, 22 H-1B visas, 22-26, 40, 57, 58, 68, 87, 88, 92, 124, 125 annual cap, 22, 26 criticisms of, 24, 26, 87 IMMACT90 and, 22-23 requirements for, 22 workers vs. American workers, 24, 26, 68, 71 Hagan, Jacqueline, 25, 68 Handlin, Oscar, 9 Hart-Celler Act (1965). See Immigration and Nationality Act (INA) Amendments of 1965

177 Hierarchical Linear Models (HLM), 3, 61, 75 higher education, 40, 65, 126 highly skilled, 37-42 conceptualizing, 37-38 defining for this analysis, 42 highly skilled immigrants, 6, 7, 37, 48, 51, 65, 70, 93, 96, 99, 125. See also skilled immigrants impacts, 2, 4, 7, 25, 93, 122 highly skilled immigration. See skilled immigration history of immigration, 10 Hudson Institute, 20 Huffman, Matt, 69, 71, 73, 91, 95, 96, 100, 101, 119, 123 human capital, 34 characteristics, 7, 50, 55, 69, 71, 84, 91, 92, 96-99, 101, 114, 122 theory, 71,97-98 I unauthorized immigration, 10, 20 immediate relatives of US citizens, 16, 19, 40 “immigrant” job, 7, 91, 94, 119, 123 immigrants, 4, 9, 11, 14, 19, 26, 31, 38, 40, 43, 61, 65, 95, 98, 123, 124 as economic competitors, 2, 6, 12, 27, 66, 67, 6973, 91, 101, 121, 122, 126 as source of labor, 12, 35

178 employment-based, 20-22, 40, 92 family-based, 40, 92 permanent, 16, 18, 19, 24, 35, 38 immigration economic effects. See economic impacts restriction on, 12 Immigration Act of 1970, 19 Immigration Act of 1990 (IMMACT90), 20-23, 24 Immigration and Nationality Act (INA), 18-19, 22, 92 Immigration and Nationality Act (INA) Amendments of 1965, 19, 35, 92 Immigration and Naturalization Service (INS), 21, 23 immigration policy, 6, 11, 12, 18, 26-34 Immigration Restriction League, 15. See also nativist organizations immigration system, 16, 18, 20, 24, 35, 38, 93, 126, 127 India, 28, 33, 35, 48 H-1B workers from, 24 boosting own education capacities, 30 inequality, 3, 91 economic, 96, 99, 118, 119 gender, 3, 69, 91, 94, 96, 119 Information Technology, 24, 28, 51, 57 workers, 72, 75 Institute for Electrical and Electronics Engineers (IEEE), 2, 24, 92

Index integration, 6, 15, 33-34, 122, 125, 127 integration feature, 8, 127 international students. See foreign students Ireland, 12, 28 loss of own talent, 2 J Japan, 12, 14 “Gentlemen’s Agreement,” 14 K Know-Nothing Party, 12. See also nativist organizations knowledge-based economy, 4, 11, 41, 42, 72 L L-1 visas, 20, 23, 26 labor certification, 19, 35, 126 Labor Condition Application (LCA), 23 labor market outcomes, 3, 4, 9, 27, 40, 58, 61, 66, 70, 73, 97, 123, 124 labor market segmentation, 3, 7, 67, 68, 94, 119, 123, 124. See also segmented labor market theory labor-market testing, 22 labor shortage myth, 24 labor unions, 12, 15, 19, 21, 125 opposition to employmentbased immigration, 19 lawful permanent residents (LPR), 20, 23, 25 legal status, 38, 66, 125 literacy test, 14

Index location-specific jobs, 72, 73, 74, 75, 76, 77, 80, 93, 101, 102, 104, 108, 115, 118, 122 definition, 73 Lofstrom, Magnus, 42 Lopez, Mary, 3, 57, 70, 73, 91 Lowell, Lindsay B., 2, 4, 21, 25, 38, 40, 65, 71, 92, 118 M Malone, Nolan, 6, 10, 67, 94 Martin, Philip, 9, 21, 28 Martin, Susan, 35, 36, 127 Massey, Douglas, 6, 9, 10, 18, 67, 94 McCarran-Walter Act (1952). See Immigration and Nationality Act (INA) McCollom, Susan, 25, 68 Meyers, Deborah, 18, 20 mode of admission, 38 Morrison, Bruce, 22, 23, 36 Murray, Julie, 27, 70, 122 N National Academies, 27, 28, 31, 32, 69 National Association of Manufactures, 15 national origins quotas, 16, 18, 19, 48 national origins quota system, 18, 19 National Science Foundation, 25, 95, 97 national security, 6, 10, 32, 34, 36, 65, 126, 127 native earnings, 6, 66, 93, 121 nativist organizations, 12, 15 nativist sentiments, 10

179 New Immigrant Survey, 33, 40 New Zealand, 28, 29 foreign students in, 29 non-immigrant system, 16-20 non-immigrant visa, 20 non-immigrants, 16 North, David, 2, 31, 65, 92, 101 O O visas, 22, 23 occupational segregation, 3, 7, 94, 119, 120, 123, 124 Organization for Economic Cooperation and Development (OECD), 1, 29, 30, 37, 38, 41 organized labor. See labor unions P P visas, 22, 23 Papademetriou, Demetrios, 23, 30, 32, 34, 35, 93, 126 permanent immigrant visas, 18, 21 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), 10 Piore, Michael, 67 polls of public opinion, 9 preference system, 16, 19 preferences employment, 19, 21, 22, 92 family, 19 primary sector, 67-68, 119 Q Quota Laws, 15-16

180 R R visas, 22, 23 REAL ID Act, 10 registered nurses, 22, 42, 51, 55, 100 Rosenblum, Mark, 32, 34, 126, 127 Rumbaut, Ruben, 48, 71 S secondary sector, 67-68 segmented labor market theory, 67-68, 69, 100 September 11th, 2001, 10, 30, 32 Singapore, 28, 30 skill shortage, 20, 88 skilled immigrants, 1, 4, 11, 27, 28, 32-34, 47, 48, 50, 51, 55, 57, 58, 65, 66, 69, 92, 93, 121, 125. See also highly skilled immigrants impacts, 4, 7, 38, 40, 60, 65, 66, 69, 70, 73, 88, 94, 118, 122, 12 recent vs. earlier, 3, 47 women, 3, 6, 7, 55, 96, 100, 101, 118 skilled immigration, 2, 3, 4, 7, 11, 20, 26, 27, 32, 35, 48, 61, 92, 93, 118, 121, 122, 124, 126 Smith, Michael Peter, 1, 33, 66 South Korea, 1, 28, 30, 33 “Specialty occupation.” See H-1B visas Standard Occupational Classification Manual (SOC), 42

Index status composition theory, 68-69, 100 substitution, 66 sweatshop labor, 68 Sweden, 28, 30 T Taiwan, 28, 30, 343 temporary admission system, 35 temporary visa, 18, 23, 36, 40, 125, 127 temporary visitors, 16 temporary worker, 18, 20, 21, 23, 25, 68, 87, 88, 92 terrorism, 10, 32 Tichenor, Daniel, 12, 13, 15, 16 tipping point, 7, 87, 91, 93, 94, 115, 121, 123 U United Nations (UN), 1 United Kingdom, 24, 29 loss of own talent, 2 United States immigration policy. See immigration policy US immigration law, 14, 18 Usdansky, Margaret, 13, 16, 18, 19, 20, 71, 92, 126 V visa portability, 25 Visa Reform Act of 2004, 26 Y Yale-Loehr, Stephen, 23, 30, 32, 34, 35, 93, 126