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Structural Change and Its Impact on Productivity in Japan, Korea, and Singapore (1970-2000)

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This paper examines the impact of structural change on productivity through a decomposition of aggregate manufacturing productivity growth in Korea, Singapore, and Japan over the period 1970-2000. First, the shift-share analysis is utilized to
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  −35− 『国際開発研究フォーラム』28(2005. 3) Forum of International Development Studies, 28 ( Mar . 2005 ) Structural Change and its Impact on Productivity in Japan, Korea,and Singapore (1970-2000)* K. Ali AKKEMIK** Abstract  This paper examines the impact of structural change on productivity through adecomposition of aggregate manufacturing productivity growth in Korea, Singapore, and Japan over the period 1970-2000. First, the shift-share analysis is utilized to measure theimpact of the allocation of labor among manufacturing industries on aggregate laborproductivity. Next, the impact of the allocation of labor and capital on total factorproductivity (TFP) growth is analyzed. The findings show weak support for the positiveimpact on aggregate productivity of reallocation of factor inputs for Japan and Korea, and apositive impact for Singapore. I. Introduction Over the last three decades, East Asian economies went through a remarkable industrialtransformation. Korea, Singapore, and Taiwan, in particular, metamorphosed from producers of traditional light industry products to producers of heavy industry and technologically sophisticatedproducts. Subsequently economists started to debate on the sources of economic growth in East Asia.A large number of economists have been discussing whether it was due to the accumulation of physical and human capital and virtual insignificance of technological change or assimilation of newtechnologies that these countries maintained rapid growth rates. However, as pointed out by van Arkand Timmer (2003), there is another dimension of industrial development in these countries: “ ...therecent debate on the sources of growth in Asia has neglected the underlying dynamics of changes inproductivity growth within sectors and related to this, the shift of resources from low to high-productivity sectors. ”  The transformation in the industrial structure in East Asian countries came along with structuralchange, i.e. change in the composition of production and factor inputs (capital and labor) amongindustries. Structural changes coexisted with gains in manufacturing productivity. Some researchersrecognizing such coexistence pointed to structural change as a cause of aggregate productivitygrowth (e.g. Kaldor 1963, 1966, Chenery et al 1986, and Syrquin 1995). Among these, Kaldor (1963,1966) argues that there is often surplus labor in some industries in the manufacturing sector and laborsupply in the manufacturing sector is elastic. He asserts that a major source of labor supply in * Acknowledgements: I thank Professor H. Osada for his comments and help on earlier drafts and his continuous support,Prof. S. Itoh and Prof. T. Yanagihara for their comments during the presentation at the 14 th Meeting of the JapanAssociation of International Development in November 2003. Further thanks are for Y. Yasuba, two anonymous referees,and friends in Osada seminar for their helpful comments. **  The author is a PhD candidate at Graduate School of International Development in Nagoya University.Correspondence: m030102d@mbox.nagoya-u.ac.jp  manufacturing is the flow of labor from low-productivity to with high-productivity industries andassociates aggregate labor productivity growth in manufacturing sector with labor shifts. He alsoargues that labor shifts across industries increase average manufacturing productivity due to tworeasons. First, labor absorbing industry is growing with increasing returns. Second, in the industrythat is losing labor, productivity level rises with the withdrawal of labor. Kaldor emphasizes increasingreturns and externalities in manufacturing.Harberger (1998) provides a further insight into productivity and structural change. Hedifferentiates between what he calls a “ mushroom-process ” (i.e. innovative activities in a particularindustry improve productivity and cause a shift of resources from relatively low-productivity activitiesto itself), and a “ yeast-process ” (i.e. gains in productivity spreads across industries). 1 Long-run growthis a mix of these two processes.Most studies about industrial development in developing economies deal with structural changeand productivity separately. However, productivity comparisons across countries with catching-uprecently attracted attention of many researchers (see e.g. Choi 1990, Szirmai 1993, Wagner and vanArk 1996, and OECD 1996). It has been argued that the catch-up process of Asian economies stemmedfrom productivity growth of individual industries and the allocation of production factors from low-productivity industries to high-productivity industries (e.g., Pilat 1996 and van Ark 1996).There is aneed to examine the impact of structural changes in the manufacturing sectors of East Asianeconomies on partial and total factor productivity.In this study, I test the hypothesis that the shifts of production factors, i.e. structural change, havea positive effect on aggregate manufacturing productivity growth as supposed by Syrquin (1995). Thestudy covers Japan, Korea, and Singapore, and the period of analysis spans the years from 1970 to2000. The methodology is adopted from Timmer and Szirmai (2000). The structure of the study is as follows. In the second section, trends in productivity and structuralchange are briefly presented. The third section presents data and their sources. In the fourth section,an analysis of labor productivity is carried out for three countries. The fifth section extends thisanalysis to total factor productivity. Finally, the sixth section concludes with a wrap-up. II. Trends in Structural Change and Productivity Manufacturing sector is divided into 15 industries in this study as listed in Table 1. The changingshare of industries in manufacturing sector output and labor can be seen in Table 2. Output refers toreal value-added at 1995 prices normalized by relevant producers ’ price indices. Table 2 reveals thatthe importance of transport vehicles and electrical and electronic machinery industries in terms of output share in Japan increased and that of basic machinery industries was maintained during the last30 years. The corresponding industries are chemicals, basic machinery, electrical and electronicmachinery, and transport equipment in Korea and chemicals and electrical and electronic machineryStructural Change and Its Impact on Productivity in Japan, Korea, and Singapore (1970-2000) −36−  industries in Singapore. Oil refining and transport equipment industries declined dramatically overtime in Singapore. Overall, production in the three economies shifted to high value-added industries. Table 3 presents labor productivity growth rates for three periods. Labor productivity is measuredas real value-added per employee and the periodization is different for each country. For Japan theperiods are 1973-1984 (from oil shock to Plaza Accord that led to rapid appreciation of yen and arelocation of resources towards overseas production), 1985-1990 (bubble economy), and 1991-2000(recession). The periods for Korea are 1971-1979 (heavy and chemical industrialization drive where thegovernment undertook heavy investments nurture heavy and chemical industries), 1980-1988(structural adjustment), and 1989-1996 (technological sophistication). For Singapore the periods are1974-1979 (early post-oil-shock growth period), 1979-1985 (the period of corrective wage policy 2 ), and1986-1996 (emphasis on productivity and promotion of technology-intensive production). Table 3 presents productivity growth rates of each industry in manufacturing sectors. Aggregatelabor productivity growth was particularly very high during the bubble era (second period) in Japanand third period in Singapore due to high output growth and the technological sophistication period(third period) in Korea. Productivity growth in Japan slowed down drastically after the burst of thebubble in the early 1990s. Korea ’ s labor productivity performance was the most impressive.Productivity growth differentials across industry groups in Korea, where only three industriesexperienced annual average productivity growth rates below 8 percent, are smaller in comparison tothat of Japan and Singapore after 1980. Labor productivity growth rates in Singaporeanmanufacturing sector was influenced heavily by electrical and electronic machinery industry since itaccounted for half of the total manufacturing value-added and one third of labor force. The datademonstrate that high-productivity industries are also fastest growing industries. −37−  Table 1 Major industry groups Industry  Food Tex.WoodPap.Chem.Pet.Plas.Min.Bas.met.Met.pr.Mach.Elec. Tran.Prec.Others Corresponding ISIC categories  3100, 311, 312, 3130, 31403200, 3210, 3220, 3230, 32403300, 3310, 33203400, 3410, 34203500, 3510, 3520, 3521, 3522, 3523, 25293530, 35403550, 35603600, 3610, 3620, 36903700, 3710, 37203800, 38103820, 3821, 3822, 3823, 3824, 38293825, 3830, 3831, 3832, 3833, 38393840, 3841, 3842, 3843, 3844, 3845, 384938503900 Major industries included  Food, beverages, and tobacco manufactures  Textiles, wearing apparel, leather and products, and footwear Wood, wood products, furniture, and fixturesPaper, paper products, printing, and publishingIndustrial chemicals and other chemical productsPetroleum, petroleum refineries, coal productsRubber and plastic productsNon-metallic minerals, pottery, glass productsBasic metals, iron and steel, non-ferrous metals Fabricated metal products (except machinery and equipment) Non electrical (basic) machinery and equipment Electrical appliances, electronic machinery, office equipment  Transport equipment (transport vehicles, shipbuilding and repair, etc.) Professional equipment, optical equipment, precision equipment Other manufacturing  III. Description and Sources of Data Output: Output refers to value-added at 1995 prices. Value-added data are obtained from the Census of Manufactures  ( Kougyou Toukeihyou  ) for Japan, Yearbook of Statistics  for Singapore, and Major Statistics of Korean Economy  and the Report on Mining and Manufacturing Survey (Whole Country) for Korea. Value-added data are deflated by producer ’ s price indexes obtained from KoreaStatistical Yearbook, Singapore Yearbook of Statistics, and the Long-term Data Series  of the Bank of  Japan. Labor:  To calculate labor productivity, value-added figures are divided to total number of employees. Employment data are obtained from various issues of industrial census for Japan,Singapore Yearbook of Statistics, and Major Economic Statistics of Korean Economy. Labor inputemployed in total factor productivity (TFP) refers to total hours worked. These are calculated bymultiplying monthly working hours data by the factor 12 to obtain annual working hours peremployee, and then multiplying by number of workers. These data take into account only the actualworking hours of the employees, including overtime but excluding recess. The sources for the actualworking hours data are the Annual Report on the Monthly Labor Survey - National Survey  for Japan, Yearbook of Labor Statistics  for Korea, and the ILO Yearbook of Labor Statistics  for Singapore. To calculate labor shares for TFP, workers ’ remuneration data are obtained from the Census of Manufactures for Japan, Yearbook of Labor Statistics for Korea, and the ILO Yearbook of LaborStatistics for Singapore. These data include all payments made to employees including benefits. Totalremuneration per employee is multiplied by number of workers and divided to value-added tocalculate labor share in output. Subtracting this from unity, the share of capital is obtained. Capital: In this study, tangible and reproducible assets, i.e. nonresidential buildings and structures,plant, and equipments including office equipment, are included as part of the capital stock. Land,consumer durables, residential buildings and structures, and inventories, however, are excluded. Tocalculate capital stock, rather than depending on financial statement statistics, the cumulationtechnique named perpetual inventory method (PIM) is used, since the figures in the balance sheetsgenerally do not reflect the economic value of capital stock adequately since the book values recordedin the balance sheets are largely influenced by tax considerations. The basic formula for thecomputation of capital stock in this method is given as follows:(1)refers to the estimated level of capital stock at the end of the period t, to that of theprevious period, to addition to gross capital stock (investment), and to capital consumptionallowance. Three types capital assets are specified in estimations: (i) building and construction, (ii)plant and equipment, and (iii) transport equipment and others. It is assumed that the asset lives foreach type of asset are asset-wise the same across countries. The data on capital stock span enough  D t   I  t  K  t 1 − K  t  K K I D t t t t  = + − − 1 Structural Change and Its Impact on Productivity in Japan, Korea, and Singapore (1970-2000) −38−  number of years in order to cover the asset life of the longest-life asset.In order to estimate capital stock, we need to calculate the capital stock for a benchmark year andthen extend the series by adding net investment data using the equation (1). The benchmark yearsare selected as 1955 for Japan, 1968 for Korea and 1970 for Singapore. For Korea and Japan, thebenchmark years refer to years of national wealth surveys. For Singapore, a decomposition of grossfixed capital formation was not available. Hence, the method applied by Hsieh (1997) is employed tospecify the benchmark value of the capital stock: initial value of investment is divided to the sum of  −39−  Table 2 Shares of industries in manufacturing real value-added and labor OutputFood Tex.WoodPap.Chem.Pet.Plas.Min.Bas.metMet.pr.Mach.Elec. Tran.Prec.OthersLaborFood Tex.WoodPap.Chem.Pet.Plas.Min.Bas.metMet.pr.Mach.Elec. Tran.Prec.Others 1973-1984 12.26.64.88.98.21.64.24.88.67.411.28.39.01.82.310.413.36.27.23.90.44.44.85.97.49.912.78.42.42.7 1985-1990  10.85.33.48.69.50.94.84.55.77.311.414.010.01.92.011.011.14.57.43.60.35.34.24.77.410.417.28.42.32.3 1991-2000  10.53.92.68.610.00.95.04.24.86.510.817.710.91.61.812.38.74.07.93.80.35.84.14.27.810.917.19.02.02.1 1971-79  18.021.75.34.38.09.85.46.25.72.31.95.93.30.51.711.435.00.85.15.21.24.84.83.64.23.59.44.61.25.3 1980-1988  14.719.12.45.28.32.84.64.77.74.24.411.47.01.02.48.530.41.14.64.40.75.94.84.34.75.112.86.91.64.2 1989-1996  10.212.51.25.39.53.34.44.97.04.77.515.810.11.02.57.222.11.85.25.00.65.14.64.15.79.115.09.31.63.8 1974-1978  6.14.74.05.34.57.93.62.91.87.712.517.317.81.92.15.816.25.95.82.31.54.62.20.95.56.724.312.53.62.1 1979-1985  5.84.22.66.89.35.03.22.91.47.98.227.211.01.92.65.013.25.16.12.51.34.32.30.87.27.330.69.72.42.1 1986-1996  3.21.60.66.311.55.42.81.90.76.06.243.66.82.31.34.58.41.86.33.11.04.81.80.78.38.137.48.62.42.8 Japan JapanKoreaKoreaSingaporeSingaporeSource: Author ’ s calculations
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