Distr. GENERAL EESCWA/EAD/2005/9 16 December 2005 ORIGINAL: ENGLISH
ECONOMIC AND SOCIAL COMMISSION FOR WESTERN ASIA
ANALYSIS OF PERFORMANCE AND ASSESSMENT OF GROWTH AND PRODUCTIVITY IN THE ESCWA REGION Fourth Issue
United Nations New York, 2005
The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. References have, wherever possible, been verified. Symbols of United Nations documents are composed of capital letters combined with figures. Mention of such a symbol indicates a reference to a United Nations document. E/ESCWA/EAD/2005/9 ISSN 1727-5857 ISBN 92- 1-128300-0 05-065 1
UNITED NATIONS PUBLICATION Sales No. E.06.II.L.5
CONTENTS Abbreviations ........................................................................................................................................ Executive summary ............................................................................................................................... Introduction ...........................................................................................................................................
Page iv v 1
Chapter REVIEW OF DATA AND INDICATORS ..........................................................................
3
Construction of data set .................................................................................................... Review of labour productivity ......................................................................................... Review of capital deepening ............................................................................................ Concluding summary .......................................................................................................
5 5 7 9
ANALYSIS OF TOTAL FACTOR PRODUCTMTY: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS ..........................................................................
10
A . Methodology .................................................................................................................... B . Results .............................................................................................................................. C . Concluding summary .......................................................................................................
10 13 16
DECOMPOSITION ANALYSIS OF LABOUR PRODUCTMTY GROWTH.............
17
A . Methodology .................................................................................................................... B . Results .............................................................................................................................. C . Concluding summary .......................................................................................................
17 18 22
CONCLUSIONS ....................................................................................................................
23
A. B. C. D.
. .
LISTOF TABLES
Data set description ..................................................................................................................
3
Average annual change in TFP based on the Malmquist index. in technical efficiency and in technological progress. 1980-2000 ...............................................................................
14
Average annual change in TFP based on the Malmquist index. in technical efficiency and in technological progress. 1980-1990 ...............................................................................
15
Average annual change in TFP based on the Malmquist index. in technical efficiency and in technological progress. 1990-2000 ...............................................................................
16
Percentage change in tripartite decomposition indices. 1980-2000 ........................................
19
Percentage change in tripartite decomposition indices. 1980-1990 ........................................
20
Percentage change in tripartite decomposition indices. 1990-2000 ........................................
20
LISTOF FIGURES Non-oil sector as percentage of total GDP: Saudi Arabia and Oman ......................................
5
Labour productivity trends in the selected ESCWA member countries ..................................
6
Labour productivity in selected MDEs and emerging South-East Asian economies ..............
7
Capital stock per unit of labour in the selected ESCWA member countries ...........................
8
Capital stock per unit of labour in the selected MDEs and emerging South-East Asian economies ......................................................................................................................
9
References .............................................................................................................................................
24
ABBREVIATIONS APO CICUP DEA GCC GDP ESCWA FDI ICP MDEs OECD PPP TFP
Asian Productivity Organization Center for International Comparisons at the University of Pennsylvania data envelopment analysis Gulf Cooperation Council gross domestic product Economic and Social Commission for Western Asia foreign direct investment International Comparison Programme more diversified economies Organisation for Economic Co-operation and Development purchasing power parity total factor productivity
Executive summary
This fourth issue in the study series Analysis of Performance and Assessment of Growth and Productivity in the ESCWA region aims to assess the productivity performance of selected ESCWA member countries, applying recently introduced theoretical frameworks. The production frontier approach, based on data envelopment analysis, is used to analyse trends in total factor productivity. Moreover, the method is extended to a decomposition analysis of labour productivity. The study reviews these methodologies and the results obtained. Previous issues of the study series repeatedly emphasized that the region lacked physical investment activities on a scale sufficient to ensure a growth performance comparable to that in East Asia. The results of the present study support this well-established conclusion, but the importance of efficiency improvements is also stressed. As performance in terms of technological progress is found to be generally in line with international trends, the difference in labour productivity and total factor productivity performance may be ascribed to performance in terms of technical efficiency. More physical capital investment will increase the growth potential in under-capitalized countries such as Egypt. Consistent productivity growth, particularly in labour productivity, is discernible in Egypt but it is not yet on a sufficient scale to push the economy onto a rapid growth path. A sufficient level of capital deepening is necessary for the country to secure technical efficiency gains by improving labour and total factor productivity. More physical capital investment, with more up-to-date equipment, is needed in the nonoil sectors of Saudi Arabia and Oman. In spite of an impressive performance in productivity growth, capital deepening in the non-oil sector in Oman stagnated in the 1990s. This may lead to weaker productivity performance in the future. The capital intensity of the non-oil sector in Saudi Arabia was already high in 1980. As the process of depreciation of old equipment slowly nears completion, the country has an opportunity to revive its physical capital stock to produce more efficiency gains. In comparison with the emerging South-East Asian economies, the performance of labour productivity in Jordan and the Syrian Arab Republic is weak. A weak association between capital deepening and labour productivity is discernible. In those countries, the development of technical efficiency is crucial for productivity performance. Most ESCWA member countries have undertaken reforms in investment policies by setting up autonomous investment promotion agencies and reforming investment laws. However, with a view to pursuing a micro-based approach aimed at increasing physical investment with efficiency gains, the establishment of a productivity movement in the region is worth considering in view of its relatively successful record in East and South-East Asian countries.
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Introduction The United Nations Economic and Social Commission for Western Asia (ESCWA) has been producing a study series entitled Analysis of Performance and Assessment of Growth and Productivity in the ESCWA Region since 2003. The objective of the series is to develop policy prescriptions for the ESCWA region to ensure better economic growth performance and an improvement in productivity. When the research series was launched, it was generally accepted that growth performance in the ESCWA region and the Arab world in general was disappointing.' The region's weak performance is particularly noticeable when compared to rapidly growing East Asian economies. To achieve the United Nations Millennium Development Goals, especially goal 1, it is essential to direct economic activities towards overall growth through the improvement of productivity. Moreover, strong economic growth is considered to be a precondition for political and social stability in the region. The political instability and insecurity that have beset the region for several decades are a major factor impeding economic growth. However, in spite of the present unstable geopolitical setting, it is believed that active policy interventions and regional cooperation for economic growth can play an important role in bringing a degree of stability to the region. Hence, it is one of ESCWA's present priorities to investigate the issue of economic growth and productivity in order to generate a policy dialogue among the region's stakeholders. The first issue in the series2 focused on weak regional economic performance trends since the mid1980s. It concluded that the region was in a vicious circle stemming mainly from institutional barriers and political tensions and risks. Its lower investment rate and high unemployment rates showed that the region did not capitalize on its advantages in terms of natural, financial and human and other resources. Moreover, the volatile nature of the region's economic performance, measured in gross domestic product (GDP), reflected the poor state of economic integration within the region and in the global economy. The study concluded that strong regional economic integration would serve as an insurance mechanism for regional investors and would help to smooth out volatile economic performance through robust region-wide capital accumulation. The second issue in the series3 investigated policy conditions for regional economic integration. The study identified resource gaps relating to economic production in the region. Regional demographic trends reflected a rapid increase in a young labour force. However, the rate of physical investment was not growing fast enough to absorb those entering the labour market. Gaps between unemployed labour, physical capital stock and the region's financial resources hampered the potential for economic growth in the region. Estimates showed that there were potentially substantial benefits to be gained from active physical investment and full utilization of regional natural, human and financial resource advantages. However, the study also found that, under current conditions, it would still be difficult to achieve constructive regional integration. In a technical annex, it elaborated a new technique for measuring total factor productivity (TFP). The third issue in the series4 further investigated regional resource mobilization for robust regional economic growth. It identified the existence of investment-savings gaps at various country levels in the ESCWA region. Examining the factors affecting both investment and savings, the study concluded that an active regional anchor was needed to promote investment in both physical and human capital in order to bridge the gap. In the light of the findings of the previous issues, the present study focuses on productivity. Although the concept of productivity is as simple as a monotonic relationship between outputs and inputs, interpretation of productivity figures is difficult. An improvement in productivity at the micro level does not necessarily lead to improvements at the macro level. A structural change in an economy sometimes renders The word "disappointing" is used in the introduction to an influential paper: Xavier Sala-i-Martin and Elsa V. Artadi, "Economic Growth and Investment in the Arab World, October 2002, prepared for The Arab World Competitiveness Report published by the World Economic Forum. ESCWA, Analysis of Performance and Assessment of Growth and Productivity in the ESCWA Region, First Issue (E/ESCWA/EAD/2003/3). ESCWA, Analysis of Performance and Assessment of Growth and Productivity in the ESCWA Region, Second Issue (EIESC WA/EAD/2004/2). ESCWA, Analysis of Performance and Assessment of Growth and Productivity in the ESCWA Region, Third Issue (E/ESCWNEAD/2005/3).
such micro-level improvements invisible at the macro level. Moreover, a productivity improvement at the macro level does not necessarily indicate an improvement in general economic welfare, since such an improvement can be achieved by limiting employment. Furthermore, productivity statistics, if available, are only indicative, since precise measurement of various inputs and outputs using relevant prices is still impossible, even in advanced countries. However, careful estimation and analysis of productivity erformance are essential for determining policy priorities. For oil-exporting ESCWA member countries!establishing a highly productive private sector is the priority for economic diversification strategies. Given their already generally high aggregate income levels, an expansion of the non-oil sector with low productivity will not contribute to increased employment of their nationals in the non-oil private sector. Recognition of the present productivity structure is important for setting a priority area in their diversification strategy. For the ESCWA subregion of more diversified economies (MDEs), an improvement in productivity is essential to attract foreign direct investment (FDI) and to tackle chronic high unemployment. As repeatedly mentioned in the previous issues of this ESCWA study, the subregion of MDEs needs more physical investment. The present study seeks to identify other priorities, also pertaining to the improvement of productivity, as an additional precondition for economic growth in the subregion. A renewed interest in theoretical research on productivity measurement has recently produced useful methodologies. By introducing these methodologies, the present study also seeks to promote technical discussion among the region's experts in this field. Moreover, the study seeks to develop specific policy recommendations by applying the new methodologies to analysis of the productivity performance of selected ESCWA member countries. Chapter I reviews key data used in the analysis. The main data source for the analysis is the Penn World Table Version 6.1 .6 As this source covered only three ESCWA member countries (Egypt, Jordan and the Syrian Arab Republic), comparable data were estimated from national sources for the non-oil sectors of Oman and Saudi Arabia. Due to data constraints, particularly in respect of sector-specific gross fixed capital formation, the present study could not cover all ESCWA member countries. Chapter I1 comments on the pattern of TFP growth after briefly reviewing the use of nonparametric data envelopment analysis (DEA) to calculate the Malmquist index of total factor productivity. Chapter I11 analyses labour productivity, utilizing the tripartite decomposition method of Kumar and Russell (2002)~ The results show that efficiency performance is the factor that contributes most to determining the dynamics of labour productivity in the selected ESCWA member countries. This pattern is markedly different from East Asian countries, where capital deepening is the factor that has contributed most to their impressive labour productivity growth in the last two decades. Chapter IV concludes the study with policy recommendations.
As this group of countries usually coincides with the member countries of the Gulf Cooperation Council (GCC), it is henceforth defined as GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates). Non-GCC member countries of the ESCWA region are henceforth defined as more diversified economies (the MDEs: Egypt, Iraq, Jordan, Lebanon, Palestine, Syrian Arab Republic and Yemen). Although Egypt, Iraq, Syrian Arab Republic and Yemen are oil-exporting countries, they are included among the MDEs because their economic structure is more diversified than that of GCC member countries. Alan Heston, Robert Summers and Bettina Aten, Penn World Table Version 6.1, Center for International Comparisons at the University of Pennsylvania (CICUP), October 2002, available at: http://pwt.econ.upenn.edu. Subodh Kumar and R. Robert Russell, "Technological Change, Technological Catch-up, and Capital Deepening: Relative Contributions to Growth and Convergence", in American Economic Review, 2002, vol. 92, No. 3, pp. 527-548.
I. REVIEW OF DATA AND INDICATORS A. CONSTRUCTION OF DATA SET This chapter reviews the constructed core data as well as the methods used to construct the data set. Productivity is defined as a ratio of the value of outputs to the value of inputs. Various types of outputs are produced in economic activities using various types of inputs. Some outputs and inputs are measurable in terms of price and quantity, while others are just not measurable in such terms. For example, measurement of the productivity of the government sector is usually difficult. Moreover, there is no conclusive method of measuring the productivity of the services sector. Researchers and experts often rely on certain theoretical assumptions and use obtainable data to estimate productivity for various levels of aggregation. In making a macro-level productivity estimate, for instance, the assumption is that a country (or a sector) produces one value-added output, using human and non-human inputs. The human factor in the inputs is labelled labour, which is usually approximated by the size of the labour force employed in the country (or the sector). The non-human factor in the inputs is labelled capital, which is usually approximated by the value of physical capital stock in the country (or the sector). If the data are available, precision can be sought in the productivity estimate. Countries of the Organisation for Economic Co-operation and Development (OECD) use labour hours instead of the number of labourers for their inputs measure. Moreover, the utilization rate of physical capital must be considered. However, for non-OECD countries, the simplest set of necessary data is difficult to obtain. Official statistics on the value of capital stock and the utilization rate of physical capital are often not available. The results of labour-use surveys are available for a few countries only. ESCWA member countries are also prone to the data availability problem. This study constructs the best available data set to compare productivity internationally and with the estimated trend in the selected ESCWA member countries. The present analysis uses the most recent data set from the Penn World Table 6.1. This data set was chosen because it contains long-term time series data since the 1950s in respect of the data needed for productivity measurement. Moreover, as a product of the International Comparison Programme (ICP), the Penn World Table uses an exchange rate based on purchasing power parity (PPP) in 1996 for constant price figures. This is also known as the 1996 constant price international United States dollar. Recent arguments on productivity, particularly labour productivity, have interpreted productivity as an indicator of economic welfare. Adopting this line of argument, the present analysis seeks to undertake an international comparison of productivity based on PPP. The Penn World Table 6.1 covers three ESCWA member countries: Egypt, Jordan and the Syrian Arab Republic. In order to draw more ESCWA member countries into the analysis, a comparable data set was constructed for Oman and Saudi Arabia. The Penn World Table 6.1 provides a PPPbased 1996 exchange rate for both countries, which was used to link these data sets. A total of 16 countries were selected for comparison and analysis of productivity (see table 1). TABLE1. DATASET DESCRIPTION Grouping ESCWA member countries
Countries neighbouring the ESCWA region Emerging South-East Asian economies
Selected OECD countries
I
Country Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philitmines Thailand France Japan United Kingdom United States
Data source Penn World Table 6.1 Penn World Table 6.1 Processed from national sources Processed from national sources Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1 1 Penn World Table 6.1 Penn World Table 6.1 Penn World Table 6.1
Labour force size, gross fixed capital formation and GDP data are extracted for the analysis from the Penn World Table 6.1. Both gross fixed capital formation and GDP are calculated at the PPP-based 1996 United States dollar rate. The value of capital stock for each selected country is estimated by the perpetual inventory method. The initial value of capital stock, KO,is approximated by the formula:
where I. is the amount of investment in the first period, t=O, for which data are available, g is the average growth rate of investment over the subsequent five years and 6 is the annual depreciation rate. An annual depreciation rate of 4 per cent is assumed for the estimation. Physical capital stocks for subsequent years are calculated according to the equation:
Labour force size and the estimated value of capital stock are the input data. Constant-price GDP is used for the output data. The data set is constructed for the period 1979 to 2000. Several issues are taken into account in extending the coverage of the analysis to more ESCWA member countries. The first is data availability. To be included in the sample, the value of a country's capital stock must be estimated reasonably by the perpetual inventory method. However, destruction of a country's physical capital by war and other conflicts make the use of the perpetual inventory method impossible. For this reason, Iraq, Kuwait, Lebanon, Palestine and Yemen could not be included in the present analysis. The second issue is the treatment of the oil sector in oilexporting countries. Usually, the sector's productivity fluctuates and is dependent on oil prices. This factor should be excluded in international comparisons of productivity. Moreover, countries must have reasonably long time series data, at least from the mid-1970s. The availability of reasonably long time series for constant price GDP, gross fixed capital formation and labour force size in non-oil sectors is still limited. Nevertheless, the data set has been compiled for Saudi Arabia and Oman. Non-oil sectors have developed in both Saudi Arabia and Oman during the last two decades and stabilized at around 60 per cent of total GDP in recent years (see figure 1). The trends in the two countries have been converging since the early 1990s, after recording fluctuations due to the radical movement of oil prices. The ratio of the non-oil sector hit its lowest level in the early 1970s when oil prices surged, and reached its highest in Saudi Arabia when oil prices plunged during the late 1980s. The main data souree for Saudi Arabia is the Annual Report of the Saudi Arabian Monetary ~ ~ e n c ~ . ' Constant price GDP data for the non-oil sector with base year 1999 are available from 1968. Gross fixed capital formation data for the non-oil sector are available at current prices. The data were converted into 1999 constant price data, using a GDP deflator for the non-oil sector. The non-oil sector labour force was estimated. Several issues of the Statistical yearbook9 show labour numbers for the oil sector. It may be noted that oil-sector employment accounts on average for 1.2 per cent of the total labour force. The main data source for Oman is the Statistical earb book." Constant price GDP data for the non-oil sector with base year l988 are available from 1980. Using several issues of the Statistical Yearbook for the 1970s and 1%OS, the series was extended from 1975. Gross fixed capital formation data for the non-oil sector are available in l988 constant prices, and the series was likewise extended to 1975. The non-oil sector labour force is calculated by subtracting the oil sector employment data shown in each issue of the Statistical Yearbook from the total labour force. The initial values of capital stock for both countries are estimated by equation (l), and Saudi Arabian Monetary Agency, Fortieth Annual Report 1425H (2004G), August 2004. Ministry of Economy and Planning, Kingdom of Saudi Arabia, Statistical Yearbook, various issues. 'O
Ministry of National Economy, Sultanate of Oman, Statistical Yearbook, various issues.
subsequent values of capital stock are estimated by the perpetual inventory method. The series of data for the two countries were then rescaled to the base year 1996 and converted into 1996 international United States dollars using the PPP-based exchange rate published in Penn World Table 6.1. Figure 1. Non-oil sector as percentage of total GDP: Saudi Arabia and Oman
Source: ESCWA staff calculation, based on national sources.
B. REVIEWOF LABOUR PRODUCTIVITY From the data set constructed in the previous section, labour productivity is measured on the basis of constant price GDP in 1996 international United States dollars per employee. Figure 2 shows the trend of labour productivity in the selected ESCWA member countries. In this comparison, the data set is extended back to 1968 as data are available in Penn World Table 6.1 and compatible data are also available for Saudi Arabia. The converging trends of labour productivity for the non-oil sector in Saudi Arabia and Oman may be observed. After rapid growth in the mid-1970s, Saudi Arabia's non-oil sector labour productivity remained at a high level. In the mid-1980s, it was at the same level as that of the United States, at around US$ 50,000." The level of non-oil sector labour productivity in Saudi Arabia then began to decline towards the US$ 30,000 mark and stabilized during the 1990s. Oman's non-oil sector labour productivity grew more consistently, except for a period in the late 1980s, towards the US$30,000 mark. For selected ESCWA member countries belonging to the subregion of more diversified economies (MDEs), the trend of convergence is towards the US$ 15,000-mark. Jordan's labour productivity peaked in the late 1980s, then declined and stabilized at around US$ 16,000. The trend of labour productivity in the Syrian Arab Republic almost parallels that in Jordan, except for more moderate growth in the mid-1980s. Egypt has experienced a consistent, stable but moderate growth in labour productivity. The gap in the level ' l As may be seen from the PPP-based comparison in tables 5 and 6, labour productivity in Saudi Arabia (non-oil sector) was higher than in the United States in 1980. The implication is that the linkage of output prices in the non-oil sector to oil revenue was nevertheless strong due to the government sector and other public-sector activities.
of labour productivity between Jordan and Egypt was as large as US$ 10,000 in the mid-1980s, but it narrowed throughout the 1990s. Figure 2. Labour productivity trends in the selected ESCWA member countries (US dollar at l996 internationalprices)
Source: ESCWA staff calculation.
The trend in non-oil sector labour productivity in Saudi Arabia shows that the non-oil sector was heavily influenced by developments in the oil sector. The leap in the mid-1970s and the subsequent decline in the mid-1980s coincide with the trend in the country's oil revenue. The growth in the non-oil sector is due to an active development policy, with the expansion of public-sector and state-owned enterprises based on the use of oil revenue. The buoyant demand from increased income also contributed to the expansion of the services sector. However, a slow adjustment in the labour market is also discernible over the 20-year period.12The size of the labour force steadily increased despite the fluctuation in GDP performance during the period. Rapid population growth, the increase in the number of well-equipped nationals through better education and other improvements in social infrastructure, and the growth in inflows of foreign labour continued afier the initial leap in development of the non-oil sector in the mid-1970s. As the economy became less oil-dependent in the 1990s, the non-oil sector's absorption capacity for inflows into the labour force stabilized. Although Saudi Arabia has experienced major upward and downward adjustments, labour productivity in the non-oil sector has doubled since 1968. In comparison with emerging South-East Asian economies, the trend of labour productivity in Egypt, Jordan and the Syrian Arab Republic has been one of relative stagnation (see figure 3). With the exception of the Philippines, the South-East Asian economies experienced a high rate of growth in labour productivity until the Asian financial crisis of 1997. The labour productivity of Malaysia was marginally higher than that of the Syrian Arab Republic in the early 1980s. Its continuous and rapid growth from the late 1980s outperformed any sampled ESCWA member country. A clear positive trend is discernible for Thailand and l 2 Structural rigidity in the labour market was a common phenomenon in the 1980s in GCC member countries. For more details, see Maurice Girgis, "The GCC Factor in Future Arab Labour Migration", paper submitted to the Fourth Mediterranean Development Forum, Amman, Jordan, October 2002, pp. 29-3 1.
Indonesia. Thailand's labour productivity caught up with that of Egypt in the mid-1990s' and Indonesia's labour productivity doubled between 1979 and 1997. Figure 3. Labour productivity in selected MDEs and emerging South-East Asian economies (US dollar at l996 international prices)
Source: ESCWA staff calculation
C. REVIEW OF CAPITAL DEEPENING The data set can produce another crucial preliminary indicator, the value of physical capital per employee, which may be used to measure a country's stage of development. As more physical capital is associated with an employee, the more productive the employee can be. This process is called capital deepening. In neoclassical growth models, capital deepening is a crucial element for determining a country's income level. In more recent endogenous growth models, capital deepening is the process of determining a country's balanced growth rate. Moreover, capital deepening also indicates a structural change in an economy. With capital deepening, the economy's productive gravity moves from labour-intensive sectors (such as agriculture) to capital-intensive sectors (such as manufacturing and services). Figure 4 shows the estimated value of physical capital per employee in the selected ESCWA member countries. The estimate relates to the non-oil sectors in Oman and Saudi Arabia. Both Oman and Saudi Arabia were capital-intensive economies in 1980. The level of capital deepening continued to rise in both countries until the mid-1980s before experiencing downward adjustments. The estimated value of physical capital in the non-oil sector in Saudi Arabia stabilized in the mid-1 990s at around US$ 12,7000, while that of Oman remained at US$ 62,000. The level of capital deepening doubled in Jordan during the period from 1979 to 2000 owing to a relatively rapid accumulation of physical capital in the mid-1990s. In both Egypt and the Syrian Arab Republic, the process of capital deepening stagnated from the mid-1980s.
Figure 4. Capital stock per unit of labour in the selected ESCWA member countries (US dollar at 1 996 international prices)
Source: ESCWA staff estimation.
The trend towards stagnation of capital deepening in Egypt, Jordan and the Syrian Arab Republic became more pronounced in comparison with the trend in emerging South-East Asian economies (see figure 5). With the exception of the Philippines, the process of capital deepening proceeded at a fast pace in the latter economies. The trend had been similar, however, until 1990. The estimated value of physical capital per employee increased rapidly in Indonesia, Malaysia and Thailand. These three countries did not experience stagnation until the Asian financial crisis of 1997. Compared with the trend in labour productivity, Malaysia and Thailand show clear signs of a positive association between capital deepening and labour productivity. However, for the selected ESCWA member countries, the relationship is much weaker. For example, Jordan experienced a decline in labour productivity over two decades. Although the trend shows stagnation, Jordan also experienced positive capital deepening during the same period. The development of labour productivity in the non-oil sector in Saudi Arabia was weak, but its level of capital deepening stabilized at the highest level within the ESCWA region. Labour productivity in the non-oil sector in Oman increased although its capital deepening process came to a halt in the mid-1980s. Clearly, the growth performance and experiences of these selected ESCWA member countries are varied and they differ from the "East Asian miracle" of the emerging South-East Asian economies.
Figure 5. Capital stock per unit of labour in the selected MDEs and emerging South-East Asian economies ( US dollar at 1W 6 international prices)
Source: ESCWA staff estimation.
D. CONCLUDING SUMMARY This chapter reviews the data construction method and the constructed data in terms of two indicators: labour productivity and capital deepening. With regard to the five selected ESCWA member countries in the present analysis, Egypt, Jordan, Oman (non-oil sector), Saudi Arabia (non-oil sector) and Syrian Arab Republic, the following points may be made: (a) Labour productivity shows a trend of two-point convergence. Labour productivity in the non-oil sectors of Oman and Saudi Arabia converges at a higher level, while labour productivity in Egypt, Jordan and the Syrian Arab Republic converges at a lower level in the sample; (b) Despite abrupt upward and downward adjustments, labour productivity in the non-oil sector of both Oman and Saudi Arabia has grown considerably since the mid-1960s. Meanwhile, growth in labour productivity in Egypt, Jordan and the Syrian Arab Republic has been weak. This trend of stagnation is noticeable in comparison with the performance of Malaysia and Thailand; (c) The degree of capital deepening varies among the selected ESCWA member countries. When compared with the trend in labour productivity, a converging trend is not discernible; (d) The selected ESCWA member countries' growth performance and experience are very different from those in the emerging South-East Asian economies. A positive association between rapid growth in labour productivity and capital deepening is discernible in Malaysia and Thailand. This growth pattern does not match that of selected ESCWA member countries in the present analysis.
11. ANALYSIS OF TOTAL FACTOR PRODUCTIVITY: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS
Following the previous chapter's review of labour productivity in the selected ESCWA member countries, the present chapter proceeds to analyse TFP. In the framework of the growth accounting method developed by Solow (1957),13labour productivity is a partial picture, as the cost factor of non-human inputs is not considered. In the estimation and analysis of TFP, non-human inputs are usually approximated by the value of physical capital. The growth accounting method measures the contribution of growth in a country's input factors (such as the value of physical capital and the size of the labour force) to growth of GDP. The unaccounted part of residual part of GDP growth (the Solow residual) is interpreted as TFP growth. This traditional approach to TFP measurement is based on the assumption of a constant-returns-to-scaleversion of a Cobb-Douglas production function Y ( t )= ~ ( t ) ~ ~( (tt ) '~with - ~ Hicks-neutral productivity index, A(0; capital stock at time t, K(t); labour input at time t, L(0; gross domestic product at time t, Y(0; and the cost share of capital, b. Taking total differentiation with respect to time, the expression in percentage terms yields:
In this approach, TFP growth is always identified with shifts in the production function. Therefore, TFP growth is interpreted as technological progress. TFP growth is derived from the difference between output growth and share-weighted input growth. By assumption, the observed output is always at the frontier of the production set that is defined by the production function. In other words, the sampled country is assumed to have access to best-practice technology. This method cannot incorporate movements towards or away from the production frontier. An alternative method, the production frontier approach, has recently been proposed for the measurement of TFP growth and is increasingly used in empirical economic growth literature.14 The alternative approach assumes that not every country is producing its output at the frontier. Deviations from the frontier reflect technical inefficiency as the economy fails to produce the maximum possible output with given inputs and available technology. The TFP growth measure that allows for departures from the frontier can distinguish best practice from practices that are still inefficient. Change in best practice corresponds to the concept of technological progress. As emphasized in the traditional approach, TFP growth is associated with change in technology. Change in practices that are still inefficient is a measure of catch-up in the efficiency level, or change in technical efficiency. TFP growth is associated with improvements in efficiency in the use of inputs for production. The production frontier approach incorporates both aspects of TFP growth.
l 3 Robert M. Solow, "Technical change and aggregate production function", in Review of Economics and Statistics, 1957, vol. 39, pp. l 3 12-1320.
l4 Rolf Fare, Shawna Grosskopf, Mary Norris and Zhongyang Zhang, "Productivity growth, technical progress, and efficiency change in industrialized countries", in American Economic Review, 1994, vol. 84, pp. 66-83; Fatma Taskin and Osman Zaim, "Catching-up and innovation in high- and low-income countries", in Economic Letters, 1997, vol. 54, pp. 93-100; Joaquin Maudos, Jose Manuel Pastor and Lorenzo Serrano, "Total factor productivity measurement and human capital in OECD countries", in Economic Letters, 1999, vol. 63, pp. 39-44; Jens J. Kruger, "The global trends of total factor productivity: evidence from the nonparametric Malmquist index approach", in Oxford Economic Papers, 2003, vol. 55, pp. 265-286.
Moreover, the production frontier approach based on DEA has the advantage of measuring total factor productivity without the restriction of functional form. Even in cases in which the simplest Cobb-Douglas function is utilized, traditional growth accounting is reasonably sensitive to the assumption in the factor share. Productivity analysis based on DEA is adopted in the present analysis as a means of overcoming weaknesses in traditional TFP analysis. The essence of the production frontier approach consists in constructing a best-practice frontier using data on inputs and outputs of all sampled countries and then computing the distance of individual countries' production point from the best-practice frontier. The data requirement for this approach is therefore a data set of inputs (the value of physical capital and the size of the labour force) and outputs (real GDP) of a group of countries. The distance from the best-practice frontier is calculated as an output distance function. This function represents a country's technology at any given period. In line with the proposal by Fare et al. (1994),15the Malmquist index of the output distance function is calculated to measure and decompose TFP growth in the sampled countries. As explained below, DEA is used to estimate the production frontier and construct the Malmquist index. The assumption in constructing the Malmquist index is that for each time period, t=l, ...,T, there exists the production technology, S', which consists of the set of all feasible input vectors, X' E R : ,and output vectors, y' E : R such that: St={(xt,yt): X' can produce y t ~ Given this technology, the output distance function at time t, D,' ,is defined as:
The distance function is defined as the reciprocal of the "maximum" proportional expansion of the output vector, y', (at the proportion of O), given inputs xt in the feasible production set. D:(xt, y') is equal to or less than 1 if and only if the production is feasible in the set S' . It is equal to 1 if and only if (X', yt) is on the frontier of technology. In order to construct the Malmquist index of TFP growth, D,'+'(xt, y'), D,'(xt+', yt+l)and D,"'(xt+', y"') must also be calculated. D,'"(x', 9)is the distance function that measures the maximum proportional change in output required to make (X', y') feasible in relation to the technology at time t+l (i.e. St+l).D;(xt+', yt'l) is the distance function that measures the maximum proportional change in output required to make (X"', y'+l) feasible in relation to the technology at time t (i.e. S'). D;"(xttl, yt+') is the distance function that measures the maximum proportional change in output required to make (X"', yt+l)feasible in relation to the technology at time t+l (i.e. St+l). .
.
The (output-based) Malmquist total factor productivity index, M,, is defined as the geometric mean of two indices with different technologies at reference time t and t+l:
I5
countries".
Fare, Grosskopf, Norris and Zhang, "Productivity growth, technical progress, and efficiency change in industrialized
Equivalently, this index can be decomposed to give the expression:
In this equation, the first argument on the right-hand side of the equation represents the change in technical efficiency. This measures to what extent the country's production point moved tolfrom the production frontier over the period t to t+l. The bracketed argument on the right-hand side of the equation represents technological progress. This measures to what extent output (in terms of distance functions) changes only by virtue of change in production technology. In calculating the Malmquist index, the present text uses DEA, which is a mathematical linear programming model to envelop data in the smallest fitting convex cone. The upper bound of this enveloped set is interpreted as the best-practice production frontier. Through its optimization process, DEA simultaneously gives the efficiency level of production entities (countries in the present case) in terms of distance from the production frontier. The DEA technique does not require a functional form assumption. However, for the basic variant of DEA, it requires the assumption of constant returns to scale. Moreover, the main disadvantage of this method is that it does not account for statistical noise and that all departures from the frontier are counted as inefficiency.16 Suppose that the sample has K countries (i.e. H,.. ...j,. ..,K). The problem to yield D/(xq, yq) for a countryj for two inputs (physical capital and labour) and one output (real GDP) is:
max 8 ' S'
,;lk
subject to
Ak .p x k ~P ; I~x ~$ !~~ for ~ ~,capital ~ inputs, K
kP Ak p xibour I
for labour inputs, and
k=l
To construct the Malmquist index between t and t+l, it is necessary to solve four linear programming problems for (p, q)=(t, t); (p, q)=(t, t+l); (p, q)=(t+l, t) and (p, q)=(t+l, t+ l). In the optimization problem, the first constraint shows how much the output of country j in period q can be increased in order to reach a point on the frontier function. The second and third constraints are for inputs, capital and labour. Inputs are shown to be used most efficiently on the frontier, or less efficiently within the frontier. The frontier function l6
Stochastic frontier analysis is the alternative method used to overcome this drawback.
is constructed as a I-weighted (Lagrangian-weighted) linear combination of the inputs and outputs of all sampled countries in period p. The problem is solved for maximized 0' and the ks simultaneously. The reciprocal of the maximum proportional expansion (at the proportion of 0') for each country is calculated for the distance function. From the solution for the distance function, the Malmquist index for each country is constructed. Several software packages are available to apply DEA. For the present analysis, DEA Excel Solver (Zhu, 2003)'~was used to solve the linear programming problems.
The data set constructed in chapter I is used for the present TFP analysis using DEA. The output is real GDP and the inputs are the estimated value of physical capital and the size of the labour force. Selected OECD countries were included in this panel data set with the aim of covering a country that is likely to have best-practice technology. The Malmquist index is constructed for each year from 197911980, labelled as 1980, to 199912000, labelled as 2000. The results are presented in the form of annual average growth in terms of geometric means over the periods from 1980 to 2000, 1980 to 1990, and 1990 to 2000. They are calculated using the following formula, corresponding to equation (3). For a countryj,
b~
=
[[q [[=
P
[
=
-'l)
- l]
M!]
MF =
J
1 4'2
EF
'1
X
l00 (TFP growth based on Malmquist index),
1 4 ' 2 -'l)
]
- l) l00 (growth in technical efficiency),
1 4 ' 2 -'l)
P
J
- I)
X
100 (growth in technological proglmj,
where q + l
EF =
(Xt+l,
'+l)
D:(x',yt)
,and of equation (3).
Here EF stands for technical efficiency and TP for technological progress. The average annual growth rates are calculated between two points in time, t l and t2 . In the selected ESCWA member countries during the period from 1980 to 2000 (see table 2), the nonoil sector of Oman experienced the highest annual average TFP growth rate of 2.4 per cent. The annual average TFP growth rate in Egypt and the Syrian Arab Republic, at around 0.8 per cent, was relatively moderate but still higher than in the emerging South-East Asian countries and neighbouring ESCWA countries, with the exception of Tunisia. A considerable negative average TFP growth rate was recorded in Jordan and the non-oil sector of Saudi Arabia.
l7 Joe Zhu, Quantitative Modelsfor Performance Evahation and Benchmarking (Norwell, Massachusetts, Kluwer Academic Publishers, 2003).
TABLE2. AVERAGEANNUAL CHANGE IN TFP BASED ON THE MALMQUIST INDEX, IN TECHNICAL EFFICIENCY AND IN TECHNOLOGICAL PROGRESS, 1980-2000 (Percentages)
Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philippines Thailand France Japan United Kingdom United States
TFP growth (based on Malmquist index) 0.794 1 -1.7806 2.4424 -2.2906 0.787 1 0.4724 1.1386 -0.3392
Growth in technical efficiency 0.0000 -0.9227 3.2049 -1.7562 1.6642 0.9 l82 1.7479 0.4889
Growth in technological progress 0.794 1 -0.8659 -0.7388 -0.5439 -0.8627
Source: ESCWA staff calculation.
The decomposition of TFP growth into efficiency change and technological progress shows various patterns of growth within the selected ESCWA member countries. Egypt is at a lower point on the world production frontier, mainly due to under-capitalization. Its economy is bound by the physical capital constraint, and the source of TFP growth based on the Malmquist index is totally dependent on technological progress. This is in line with the neoclassical growth model, in which TFP growth is exogenous to the economy. However, it must be borne in mind that this characteristic stems from the continuously low level of capital deepening (see figure 4). TFP growth performance in Egypt is consistently positive but moderate. The level of labour productivity (see figure 2) remained the lowest in the sampled ESCWA member countries. In order to create the potential for growth, the country needs more physical investment for more capital deepening. Jordan experienced a negative development in both technical efficiency and technological progress. This is in line with the stagnation of labour productivity. Given the weak but ongoing capital deepening of the economy, careful consideration must be given to the enforcement of measures to promote efficiency and technological progress in order to regain productivity growth. TFP growth in Oman (non-oil sector) has been led by the growth in technical efficiency. The economy's rapid capital deepening was followed by this efficiency gain. It can be inferred that the country has experienced a "capital widening" stage for the last two decades. During the same period, however, the country experienced a regression in technological progress. Action aimed at further TFP growth in Oman (non-oil sector) must focus on this area. In contrast to Oman, Saudi Arabia (non-oil sector) recorded negative growth in TFP. This was mainly due to efficiency loss as well as negative growth in technological progress. The trend must be interpreted carefully as the country was already at a very high level of capital deepening. Over-investment during a short period in the mid-1970s led to a redundancy of physical capital and a lower level of TFP. In this sample period, the result strongly reflects the downward adjustment in productivity growth during the mid-1980s. The moderate TFP growth in the Syrian Arab Republic was led by growth in technical efficiency. The pattern is similar to Oman (non-oil sector) but more moderate in extent. Part of the country's efficiency gain was offset by a negative development in technological progress. With the exception of less-capitalized economies such as Egypt and Indonesia, negative growth in technological progress is shared with developing countries in the sample. The trend shows that it is the gain in technical efficiency that contributes to TFP growth. TFP growth in the selected ESCWA member countries, with the exception of Egypt, matches this pattern.
Table 3 shows results for the period 1980 to 1990. The trend in this period indicates more clearly the relationship between growth in technical efficiency and TFP growth. With the exception of Oman (non-oil sector), the sampled ESCWA member countries recorded negative growth in TFP. It may be observed that during the 1980s the ESCWA region was generally experiencing a period of downward adjustment in terms of TFP. The contrast becomes clear in a comparison with TFP growth performance in neighbouring countries of the ESCWA region. Morocco, Turkey and Tunisia experienced positive TFP growth led by the growth in technical efficiency. TABLE3 . AVERAGEANNUAL CHANGE IN TFP BASED ON THE MALMQUIST INDEX, IN TECHNICAL EFFICIENCY AND IN TECHNOLOGICAL PROGRESS, 1980-1990 (Percentages)
I Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philippines Thailand France Japan United Kingdom United States
TFP growth (based on Malrnquist index) -0.1435 -3.6270 2.6232 -4.2899 -0.6 171 0.9097 0.4363 0.1 195 -4.5496 0.1893 -1S883 1.3319
/
Growth in technical efficiency 0.0000 -0.9843 4.6303 -3.4015 2.2692 2.9778 2.5842 2.8085 -3.6505 2.2396 0.4728 4.0886
I
Growth in technological progress -0.1435 -2.6690 -1.9182 -0.9 196 -2.8223 -2.0084 -2.0938 -2.6 155 -0.9332 -2.0054 -2.05 14 -2.6485
Source: ESCWA staff calculation.
Table 4 shows the results for the period 1990 to 2000. In this period, the trend was reversed as technological progress became the factor contributing to TFP growth. With the exception of Saudi Arabia (non-oil sector) and the United Kingdom, all sampled countries experienced positive growth in technological progress. During this period, the sampled ESCWA member countries experienced an upward adjustment in TFP growth. TFP in Oman (non-oil sector) continued to grow steadily, and a recovery was observed in Egypt and the Syrian Arab Republic. The negative TFP growth rate in Jordan and Saudi Arabia (non-oil sector) declined considerably compared with the 1980s. Decomposition of TFP growth performance shows that technological progress reflected an international trend, whereas the growth in technical efficiency stemmed from national developments. The difference in TFP growth experience thus depended mainly on gains and losses in technical efficiency. For a resilient TFP growth performance that is less dependent on the international trend, enhancement of technical efficiency with relevant physical capital formation within countries would be crucial.
TABLE4. AVERAGEANNUAL CHANGE IN TFP BASED ON THE MALMQUIST INDEX, IN TECHNICAL EFFICIENCY AND IN TECHNOLOGICAL PROGRESS, 1990-2000 (Percentages)
Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philippines Thailand France Japan United Kingdom United States
TFP growth (based on Malmquist index) 1.9651 -0.4695 2.6786 -0.2446
Growth in technical efficiency
Growth in technological progress 1.g651 1.1951 0.4663 -0.2332 1.4078 1.3808 1.0948 1.2626
-
Source: ESCWA staff calculation
C. CONCLUDING SUMMARY This chapter analyses TFP based on the production frontier approach. The DEA method is used to estimate TFP growth in the 16-country sample for the period between 1980 and 2000. With regard to the five selected ESCWA member countries, the following points may be made: (a) Total factor productivity in the non-oil sector of Oman has consistently grown at a fast pace over this period. It recorded the highest growth rate in the sample, which includes OECD countries. This TFP growth was led by growth in technical efficiency; (b) In Egypt and the Syrian Arab Republic, negative average growth in total factor productivity was recorded in the 1980s, recovering to positive growth in the 1990s. While Egypt's TFP growth was dependent on technological progress, that of the Syrian Arab Republic related to both technical efficiency and technological progress; (c) This difference in the pattern of development between Egypt and the Syrian Arab Republic is due to the difference in the level of capital deepening. The Egyptian economy may be assumed to be under constraint at the production frontier on account of the low level of capital deepening. The economy of the Syrian Arab Republic, with its higher level of capital deepening, has had room for improvement in efficiency towards maximum production; (d) Jordan experienced a negative growth rate in total factor productivity over the whole period. Although the negative rate was less pronounced in the 1990s due to the reversed trend in technological progress, negative growth in technical efficiency continued; (e) Total factor productivity in the non-oil sector of Saudi Arabia continued to decline throughout the period. Although the rate of negative growth lessened in the 1990s, negative growth in technical efficiency and technological progress dragged on from the 1980s into the 1990s;
(f) Overall, with a few exceptional cases, the trend of technological progress was set internationally. In the 1980s, most of the sampled countries experienced negative growth in technological progress. The trend was reversed in the 1990s as most of the sampled countries experienced positive growth. Hence, the growth in total factor productivity nationally was largely determined by technical efficiency performance.
111. DECOMPOSITION ANALYSIS OF LABOUR PRODUCTIVITY GROWTH
In the previous chapters, two concepts of productivity, labour productivity and TFP, are introduced and their performance in the sampled countries reviewed. The performance of the two measures is often different and at times difficult to interpret. An improvement in labour productivity may often be observed concurrently with a deterioration in TFP, and vice versa. Recent research tends to place emphasis on the human factor (e.g. labour and human capital) as a basis for productivity evaluation. Empirical research shows that labour productivity is closely associated with a country's average income. Moreover, it is assumed that labour productivity is augmented by an accumulation of non-human factors such as physical capital. The logic may be reversed, but emphasis on the human factor may be justified in order to evaluate the link between productivity and economic welfare. In line with this research trend, Kumar and Russell (2002)18present an analysis of labour productivity. Their research decomposes the growth of labour productivity into three components: (1) technological progress; (2) growth in technical efficiency; and (3) capital accumulation. This is known as a tripartite decomposition of labour productivity growth. For the decomposition, DEA is used to measure technological progress and growth in technical efficiency. Theoretically, the decomposition method uses the assumption of constant returns to scale of a production function. The definition is that
where Y is real GDP, K is the value of physical capital, and L is the number of labour force participants. In short, y is labour productivity and k is the capital-labour ratio. An efficiency index is calculated through DEA. The efficiency index, e, is a reciprocal of the distance function discussed in the previous chapter. An economy's potential output can be reached when the economy is at the world production frontier where
When the economy is at the world production frontier, e is equal to 1. As the distance from the frontier increases, the efficiency index takes on a smaller value. Hence, the difference between the potential output and actual output increases. To compare the difference in labour productivity between the current period and the base period, a notification is made to describe the period in subscripts as c and b in the formula. Therefore,
Here a definition is used to describe potential labour productivity at current-period capital intensity using base-period technology, that is
18
Kumar and Russell, "Technological Change, Technological Catch-up, and Capital Deepening: Relative Contributions to Growth and Convergence".
Multiplying equation (4) by this potential labour productivity yields
Equation (5) decomposes the change in labour productivity between the current period and the base period into: (1) change in technical efficiency (first right-hand-side argument in the equation); (2) technological progress (second right-hand-side argument in the equation); and (3) change in capital intensity (third righthand-side argument in the equation). However, another possible measurement is to apply the potential labour productivity at base-period capital intensity using the current-period technology, that is
An equivalent modification of equation (4) yields
The Kumar and Russell decomposition takes the geometric average of the two measures, namely equation (5) and (6), as
On the right-hand side of equation (7), the first argument is the change in technical efficiency's contribution to labour productivity growth. The second argument is the contribution of technological progress, and the third argument is the contribution of capital deepening. The latter two are in the form of a geometric average consistent with the "Fisher Ideal Index". In the calculation of each argument by DEA, DEA Excel Solver (Zhu, 2003)'~is used.
The decomposition of labour productivity growth is undertaken for the period 1980 to 2000 as well as for the two sub-periods 1980 to 1990 and 1990 to 2000. The results are shown in tables 5, 6 and 7 for the respective periods. During the period 1980 to 2000, labour productivity increased by 54.4 per cent in Egypt, 70.9 per cent in the non-oil sector of Oman, and 30.8 per cent in the Syrian Arab Republic. In the same period, Jordan and the non-oil sector of Saudi Arabia experienced decreases in labour productivity of 12.0 per cent and 3 1.4 per cent respectively. As noted in chapter 1, performance in the ESCWA region, on average, was not in line with that in other regions, particularly in emerging South-East Asian economies. The labour productivity of Malaysia and Thailand more than doubled during the same period. The results for the period 1980 to 2000 indicate that capital deepening made a positive contribution to labour productivity during the period. There was a strong correlation between labour productivity and capital deepening in Egypt, Malaysia, Indonesia, Thailand, Turkey and the sampled OECD countries. However, in the selected ESCWA member countries, with the exception of Egypt, a positive effect from capital accumulation had a weak effect on the improvement of labour productivity. In Jordan and in the non-oil sector of Saudi Arabia, the positive effect from capital accumulation was offset by the deterioration in technical efficiency and technological progress. The contribution of capital deepening to labour productivity l9
Zhu, Quantitative Models for Performance Evaluation and Benchmarking.
18
performance was modest in the non-oil sector of Oman and in the Syrian Arab Republic. The positive growth in labour productivity in both countries was attributable to the improvement in technical efficiency. In other words, capital accumulation has been a weak anchor in labour productivity growth in the selected ESCWA member countries. Labour productivity performance is determined by efficiency gains or losses, mostly on existing physical capital pertaining to past investments. This is particularly true of the nonoil sectors of Oman and Saudi Arabia and of the Syrian Arab Republic. An extreme case is Jordan, where capital accumulation did not entail efficiency gains or technological progress. Egypt is a special case, in which capital accumulation is associated with positive labour productivity growth. However, despite the consistent growth in labour productivity and capital deepening, the level of both in Egypt is still the lowest in the sampled ESCWA member countries. The country is at the world production frontier, as its production is heavily constrained by its very low capital intensity. CHANGE IN TRIPARTITE DECOMPOSITION INDICES 1980-2000 TABLE5. PERCENTAGE (US dollar at 1996 internationalprices, percentage)
Country Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philippines Thailand France Japan United Kingdom United States
Labour Labour productivity productivity 1980 8 913 18 378 17 856 48 820 12 032
2000 13 765 16 178 30 524 33 497 15 732
Percentage change over the period 54.4 -12.0 70.9 -3 1.4 30.8
Contribution to the change in labour ~roductivitv Technical Technological Capital efficiency progress deepening 0.00 - 17.69 78.44 -3 1.07 33.32
11.71 -1 1.60 -12.25 -8.1 1 -9.43
38.24 20.98 9.17 8.33 8.28
Source: ESCWA staff calculation.
Table 6 shows the results of the tripartite decomposition analysis for the sub-period 1980 to 1990. During this period, the contribution of capital deepening to labour productivity was relatively moderate, with the exception of Indonesia. It may also be observed that most of the sampled countries experienced negative growth in technological progress. Thus, technical efficiency performance was the main determinant of the direction of labour productivity in most countries during this period. The sampled ESCWA member countries, with the exception of Egypt, are in line with this trend. Countries that recorded a loss in technical efficiency-Jordan and the non-oil sector of Saudi Arabiaexperienced a negative growth in labour productivity. Countries that recorded a gain in technical efficiency-the non-oil sector of Oman and the Syrian Arab Republic-experienced an improvement in labour productivity. The positive growth in labour productivity in Egypt was led by capital deepening during this sub-period.
TABLE6. PERCENTAGE CHANGE IN TRIPARTITE DECOMPOSITION INDICES 1980- 1990 (US dollar at l996 international prices, percentage) Contribution to the change in labour productivity Country Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Svrian Arab Re~ublic Morocco Tunisia Turkey Indonesia Malaysia Philippines Thailand France Japan United Kingdom United States
Labour Labour productivity productivity 1980 1990 8 913 11 689 18 378 14 972 17 856 27 416 48 820 31 221 12 032 12 684
Percentage change over the period 31.1 -18.5 53.5 -36.1 5.4
Technical Technological Capital efficiency progress deepening 0.00 -7.47 41.73 -10.31 -22.20 16.76 5 1.36 -17.50 22.96 -3 1.66 -1 1.23 5.42 20.66 -21.19 10.85
9 947 5 091
13 244 7 256
33.2 42.5
40.46 -26.78
- 19.96 -8.15
18.43 111.92
36 984 25 252 29 915 44 217
43 717 35 079 37 091 53 887
18.2 38.9 24.0 21.9
7.09 16.51 24.79 10.41
3 .08 -7.96 - 16.25 -2.16
7.09 29.55 18.63 12.82
Source: ESCWA staff calculation
Table 7 shows the results of the tripartite decomposition analysis for the sub-period 1990 to 2000. The trend in technological progress was reversed during this sub-period, as it mostly had a positive effect internationally. Although all sampled countries experienced positive growth in labour productivity during the sub-period, the pattern of growth became more diverse.
TABLE7. PERCENTAGE CHANGE IN TRIPARTITE DECOMPOSITION INDICES 1990-2000 (US dollar at 1W 6 international prices, percentage) Contribution to the change in labour ~roductivitv Country Egypt Jordan Oman (non-oil sector) Saudi Arabia (non-oil sector) Syrian Arab Republic Morocco Tunisia Turkey Indonesia Malaysia Philippines ~haiiind France Japan United Kingdom United States
Labour Labour productivity productivity 1990 2000 11 689 13 765 14 972 16 178 27 416 30 524 3 1 22 1 33 497 12 684 15 732 11 175 11 347 15 033 19 696 13 244 15 206 7 256 8 944 9 118 43 717 35 079 37 091 53 887
Source: ESCWA staff calculation.
12 702 49 136 38 737 44 649 64 537
Percentage change over the period 17.8 8.1 11.3 7.3 24.0 1.5 31.0 14.8 23.3 39.3 12.4 10.4 20.4 19.8
- --
Technical Technological Capital efficiency progress deepening 19.85 -1.75 0.00 12.02 5.1 1 -8.23 17.89 5.3 1 -10.32 0.86 -1 .OO 7.44 10.49 14.34 -1.82 -12.26 13.91 1.60 8.68 11.06 8.54 -1 8.3 1 11.99 25.50 -15.32 18.18 23.19 -9.97 -6.15 -14.35 0.40 0.00
10.66 11.56 8.08 -0.25 8.14
39.83 7.35 19.29 20.20 10.74
With regard to the sampled ESCWA member countries in this sub-period, capital deepening in Egypt, in the non-oil sector of Oman and in the Syrian Arab Republic stagnated as the value of capital stock per labour decreased. The growth in labour productivity in the non-oil sector of Oman and the Syrian Arab Republic was led by further efficiency gains and positive technological progress. In Egypt labour productivity growth was led by technological progress alone. Modest technological progress and capital deepening offset the efficiency loss in Jordan, resulting in positive labour productivity growth. Labour productivity growth in the non-oil sector of Saudi Arabia was led mainly by capital deepening during the sub-period. Comparing the results shown in tables 6 and 7, it may be noted that the source of labour productivity growth changed during the period from 1980 to 2000. The consistent labour productivity growth in Egypt was led by capital deepening in the 1980s, but resulted mainly from technological progress in the 1990s. Negative labour productivity growth in Jordan in the 1980s stemmed from the negative trend in technological progress, and the reversed trend in the 1990s pushed labour productivity growth into positive territory. Rapid labour productivity growth in the non-oil sector of Oman was led by a combination of improved technical efficiency and capital deepening in the 1980s. In the 1990s, the pattern changed, with growth in technical efficiency and technological progress contributing to labour productivity growth, compared with negative growth in capital deepening. To a lesser extent, the same pattern occurred in the Syrian Arab Republic. Labour productivity in the non-oil sector in Saudi Arabia recovered to record positive growth in the 1990s after a decline in the 1980s. While there continued to be a moderately positive growth in capital deepening, it was technical efficiency gains and technological progress that determined labour productivity during the two sub-periods. In the emerging South-East Asian economies, with the exception of the Philippines, capital deepening proceeded at a fast pace in both sub-periods. In Malaysia and Thailand, the growth in technical efficiency in the 1980s supported capital deepening in contributing to rapid growth in labour productivity. In the 1990s, it was technological progress that supported capital deepening in contributing to the growth in labour productivity. This pivotal role of capital deepening in the improvement of labour productivity is also discernible in OECD countries and Turkey. By contrast, the role of capital deepening is relatively weak in the sampled ESCWA member countries, with the exception of Egypt and the non-oil sector of Oman in the 1980s and the non-oil sector of Saudi Arabia in the 1990s. Why does capital deepening not result directly in improvements in efficiency and productivity? One explanation, particularly in the case of the non-oil sector of Saudi Arabia, is a downward adjustment in relation to past over-investment. Investment during the mid-1970s boom pushed up the value of capital stock and increased capital deepening. However, utilization of the physical capital stock remained low owing to absorptive capacity constraints. While absorptive capacity increased as additional labour with relevant expertise gradually became available from the early 1980s, part of the physical capital became obsolete. As oil revenue decreased from the mid-1980s, new investment moderated. Technical efficiency as well as technological progress experienced a negative development during this adjustment period before returning to a recovery path in the 1990s. Another explanation, particularly for the cases of Egypt, the non-oil sector of Oman and the Syrian Arab Republic, is the existence of a gestation period following the import of new technology embodied in new investment. It takes time for physical investment to have a positive productivity effect. Relatively rapid capital deepening in the 1980s spilled over positively into the 1990s when the capital deepening of those countries stagnated. This may suggest that labour productivity growth in the 1980s was affected by past capital deepening in the 1970s, and that poor performance in capital deepening in the 1990s may result in stagnation of labour productivity growth in the future. The case of Jordan is difficult to interpret. It's moderate process of capital deepening was not accompanied by technical efficiency gains, and labour productivity depends to a large extent on technological progress that appears rather as an external factor in the analysis. It has been noted that the trend in technical progress is internationally set. As Jordan was located between major conflict areas in the region,
its dependence on external factors in its productivity performance is understandable if this line of explanation is used.
C. CONCLUDING SUMMARY This chapter analyses labour productivity growth using the method of tripartite decomposition. The performance of labour productivity is decomposed into components attributable to the change in technical efficiency, technological progress and capital deepening. In line with the previous chapter, DEA is used for the decomposition. The method is applied to the sampled group of 16 countries for which a data set is constructed along the lines set out in chapter I. The following points may be made with regard to the five selected ESCWA member countries covered by the present analysis. (a) Overall, the contribution of capital deepening to the improvement of labour productivity is weak, particularly in comparison with Malaysia, Thailand, Turkey and the sampled OECD countries; (b) Although the consistent labour productivity growth in Egypt was led by capital deepening in the 1980s, the pattern changed in the 1990s as labour productivity growth became more associated with technological progress following the international trend; (c) Negative labour productivity growth in Jordan in the 1980s was caused by the negative development of technological progress. As the trend in technological progress changed in the 1990s, labour productivity began to grow again at a moderate rate, with continuous capital deepening from the 1990s; (d) The rapid labour productivity growth in the non-oil sector of Oman was due to a combination of improved technical efficiency and capital deepening in the 1980s. This pattern changed in the 1990s as the country experienced negative capital deepening. Labour productivity growth became more dependent on technical efficiency and technological progress performance. The Syrian Arab Republic shows a similar pattern of performance; (e) The non-oil sector of Saudi Arabia recovered from its negative labour productivity growth in the 1980s to record moderately positive growth in the 1990s. As it had already been capital-intensive, the effect of capital deepening during the period 1980 to 2000 was positive but modest. The performance of labour productivity growth was largely determined by developments in technical efficiency and technological progress;
(f) The weak association between capital deepening and labour productivity growth in the sampled ESCWA member countries is thought to be caused by: weak capital intensity (Egypt), lagged adjustment to past over-investment (non-oil sector of Saudi Arabia), the existence of a gestation period for investment (Egypt, non-oil sector of Oman, the Syrian Arab Republic) and external factors (Jordan).
IV. CONCLUSIONS The present study analyses the performance of labour productivity and TFP in five selected ESCWA member countries. In previous issues of this study series, attention was repeatedly drawn to the weakness of physical investment activities in the region. The results of the present study support this well-established conclusion, but also stress the importance of efficiency considerations. As the performance of technological progress is generally in line with international trends, it is the performance of technical efficiency that makes the difference in labour productivity as well as total factor productivity performance. More physical capital investment will increase growth potential in undercapitalized countries such as Egypt. Consistent productivity growth, particularly in terms of labour productivity, is discernible in Egypt but it is not sufficient yet to push the economy onto a rapid growth path. A sufficient level of capital deepening is necessary for the country to secure technical efficiency gains leading to an improvement in labour and total factor productivity. More physical capital investment, with more up-to-date equipment, is needed in the non-oil sectors of Saudi Arabia and Oman. In spite of the impressive performance in productivity growth, capital deepening in the non-oil sector of Oman stagnated in the 1990s. This may result in a lower productivity performance in the future. The capital intensity of the nonoil sector of Saudi Arabia was already high in 1980. As the process of depreciation of old equipment slowly nears completion, the country has an opportunity to revive its physical capital stock to produce more efficiency gains. In comparison with the emerging South-East Asian economies, the labour productivity performance of Jordan and the Syrian Arab Republic is weak, and there is only a weak association between capital deepening and labour productivity. In these two countries, the development of technical efficiency is of crucial importance in determining productivity performance. At the macro level, the formulation of investment strategies is crucial for the promotion of capital deepening with efficiency gains. This finding has already been acted on to varying degrees in the ESCWA region. Institutional development for the promotion of FDI has progressed, including the introduction of new investment laws and the establishment of autonomous investment promotion agencies. The private sector has also become more involved in infrastructure projects. Public-private partnerships have become a common policy recommendation in the area of investment promotion. With careful consideration of the role of the public sector in providing services, including for the poorer segments of society, public-private partnerships can be a way of promoting productivity growth through physical capital formation with efficiency gains. Another possible thrust for the ESCWA region is the launching of a productivity movement. The productivity movement had its origins in Europe in the 1950s, and sought to bridge the productivity gap between firms in Western Europe and the United States. The movement stressed cooperation between business, labour and government for the goal of productivity growth. The emphasis was on human resource effectiveness and efficiency improvement in quantity as well as quality at firm level. National productivity organizations served as national focal points for a Europe-wide productivity movement. The movement became active in East and South-East Asia with the establishment of the Asian Productivity Organization (APO) in 1961.20 APO is an international organization for the promotion of the productivity movement that serves 18 member states in East and South-East Asia. This style of regional cooperation can be transferred to the ESCWA region, where there has so far been no sign of a productivity movement. A bottom-up approach in line with the productivity movement is worth considering for the purpose of attaining efficiency gains. ESCWA member countries have active commercial and business organizations that also address the issue of productivity. However, specialized national productivity organizations and a regional network of organizations would be necessary to catch up with other regions, particularly East and South-East Asia, in order to pursue the goal of investment promotion with efficiency gains. Finally, it should be emphasized that statistical development in this area is crucial. In order to conduct a relevant and detailed analysis of productivity, data on labour and physical capital stock at the sector level are necessary. Yet such data are still difficult to find in the ESCWA region.
20
A description of its activities is available at: http://www.apo-tok~~o.ord.
23
REFERENCES ESCWA. Analysis of performance and assessment of growth and productivity in the ESCWA region, First issue, 2003 (EIESCWA/EAD/2003/3).
. Analysis of performance and assessment of growth and productivity in the ESCWA region, Second issue, 2004 (E/ESCWA/EAD/2004/2). . Analysis of performance and assessment of growth and productivity in the ESCWA region, Third issue, 2005 (E/ESCWA/EAD/2005/3). Fare, Rolf, Shawna Grosskopf, Mary Norris and Zhongyang Zhang. "Productivity growth, technical progress and efficiency change in industrialized countries", American Economic Review, vol. 84, pp. 66-83 (1994). Girgis, Maurice. "The GCC factor in future Arab labour migration", Paper submitted to the Fourth Mediterranean Development Forum, Amman, Jordan, 2002. Heston, Alan, Robert Summers and Bettina Aten. Penn World Table Version 6.1, Center for International Comparisons at the University of Pennsilvania (CICUP), October 2002, available at: Kumar, Subodh and R. Robert Russell. "Technological change, technological catch-up, and capital deepening: relative contribution to growth and convergence", American Economic Review, vol. 92, No. 3, pp. 527-548 (2002). Kruger, Jens J. "The global trends of total factor productivity: evidence from the nonparametric Malmquist index approach", Oxfrd Economic Papers, vol. 55, pp. 265-286 (2003). Maudos, Joaquin, Jose Manuel Pastor and Lorenzo Serrano. "Total factor productivity measurement and human capital in OECD countries", Economic Letters, vol. 63, pp. 39-44 (1999). Ministry of Economy and Planning, Kingdom of Saudi Arabia. Statistical Yearbook, various issues. Ministry of National Economy, Sultanate of Oman. Statistical Yearbook, various issues. Sala-i-Martin, Xavier and Elsa V. Artadi. "Economic growth and investment in the Arab world", Paper prepared for the Arab Competitiveness Report of the World Economic Forum, 2002. Saudi Arabian Monetary Agency. Fortieth Annual Report 14258 (2004G), 2004. Solow, Robert M. Technical change and aggregate production function. Review of Economics and Statistics, vol. 39, pp. 1312-1320 (1957). Taskin, Fatma and Osman Zaim. "Catching-up and innovation in high- and low-income countries", Economic Letters, vol. 54, pp. 93-100 (1997). Zhu, Joe. Quantitative Models for Performance Evaluation and Benchmarking. Kluwer Academic Publishers, Nonvell, Massachusetts, 2003.
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