87 research outputs found
The Cost Competitiveness of Manufacturing in China and India - An Industry and Regional Perspective
Get PDFThis paper focuses on comparisons of productivity, (unit) labor cost and industry level competitiveness for the manufacturing sector of China and India. We first provide a comparison between India and China using a broad international perspective. We find that China has increased its labor productivity to a level above that of India, but due to a somewhat higher compensation level, China is still somewhat at a disadvantage in terms of unit labor cost in manufacturing relative to India. In the second half of the paper, we make an analysis of industry level differences in productivity, labor compensation and unit labor costs at state and province level in the two countries from the mid 1990s to the early 2000s. We find rapid declines in unit labor cost across industries and provinces in China, but increases in many instances in India. This suggest that productivity and compensation growth have become much more aligned across regions in China whereas this is not (yet) the case in India. We relate these results to differences in the implementation of market reforms between the two countries and removal of barriers to resource mobility eradicating inefficient manufacturing activity.cost competitiveness, manufacturing, India, China, Labor Productivity
Capital aggregation and growth accounting: A sensitivity analysis
Get PDFWith the increasing importance of investment in Information Technology, methods for measuring the contribution of capital to growth have re-assumed centre-stage in recent growth accounting literature. The importance of using capital service growth rates rather than capital stock growth rates has long been advocated, and has become mainstream practice. However, the choice for a particular rate of return in the derivation of capital service prices is not straightforward and has barely been researched. Using four alternative rental price models – based on both external and internal rates of return models–this paper quantifies the differences in multifactor productivity growth rates (MFPG) under different model assumptions. The differences in MFPG are also examined in terms of the inclusion of taxes and subsidies in the calculation of rental prices. Empirical analysis, carried out for four EU countries and the US in 26 industries during 1979-2003 shows that the use of capital stock overestimates MFPG in most industries. Incorporation of taxes seems to have only modest effect. The magnitude of divergence generated by alternative rental price models-particularly between internal models- is quite low. The difference is seen to be relatively high between external rate of return models and internal rate of return models
Measurement and analysis of capital, productivity and economic growth
Get PDFUnderstanding the sources of economic growth has been a major subject in economics, as economic growth is essential to improve standards of living and to reduce global income inequality. Previous literature has clearly distinguished between the role of accumulation of resources through investment and that of assimilation which is related to the productive use of such resources, in attaining economic growth. Accumulation and assimilation may be measured as the contributions of capital and multifactor productivity (MFP) to economic growth. In order to accurately measure the relative importance of these factors, it is imperative to have accurate measures of capital input. Appropriate measures of capital should take account of the differences in the efficiency of various types and vintages of capital assets. However, when quantifying the contribution of capital and MFP, most studies use a crude measure of aggregate capital input which does not take this into account. This issue has gained renewed interest because of the increasing heterogeneity of capital assets, as newer forms of capital such as information and communication technology (ICT) equipments have been introduced into the production process. This thesis has attempted to examine important issues in the measurement of aggregate capital input for analyzing the sources of economic growth. In particular it examined the various ways of measuring aggregate capital input, and the sensitivity of measures of capital accumulation and MFP, to these alternative assumptions. The thesis also studies the sources of economic growth and cross-country differences in economic growth and technology adoption during the last three decades.
The sensitivity analysis suggests that the use of standard capital stock measures causes a downward (upward) bias in the contribution of capital (MFPG) when the share of equipment increases in capital stock. This would give the wrong impression that the country is doing well in terms of productivity, which need not be actually the case. The sensitivity analysis also suggests that the way one chooses to aggregate across various asset types in terms of capital composition and the choice of external versus internal rate of return models is of greater empirical importance than the inclusion or exclusion of corporate taxes and capital gain. We also examined the service lifetime of capital equipments which is an essential element in the measurement of capital input. We have estimated the average service lifetime of capital assets, through an analysis of firm level data for actually observed capital stock and discards by Dutch manufacturing firms. Our results indicate a notable variation in lifetimes of capital assets across industries. This cautions against the reliability of results on sources of economic growth if a common depreciation rate is assumed across industries. When our new estimates are compared with existing estimates for other countries, we also observed that the lifetime of capital assets vary across countries. This observation calls for better measures of cross-country asset lifetime and depreciation estimates. Given the differences in lifetimes of capital, we have examined the determinants of asset lifetime through an attempt to unearth the causes of firm’s decision to discard a capital asset. Our analysis shows that capital investment and discard decisions are endogenous decisions by firms, determined by innovation, technological specificities of firm and tear-and-wear.
The cross-country growth analysis strengthens the prevailing view that factor accumulation cannot explain much of the cross-country variation in economic growth for the 1970s and 1980s. This is also true for the 1990s, which is surprising given that the 1990s is a period of growing integration, globalization, international trade and increasing proliferation of ICT capital. Nevertheless, compared to the previous periods, the importance of capital accumulation has increased significantly in the 1990s, possibly due to the increasing share of ICT capital. MFPG is the major driver of economic growth in most of the world’s fast growing countries as well as during episodes of growth accelerations in individual countries. The results also suggest increasing joint variation of capital accumulation and MFPG. This may indicate the importance of technology embodied in capital, but could also be a reflection of disembodied knowledge creation by firms necessitated by accumulation of capital assets such as ICT. Increasing FDI flows that would bring managerial efficiency and advanced technology across national boundaries could also cause such growing co-variance. The results imply that poorer countries cannot achieve faster growth without adopting better technologies. But, as existing evidence suggests that frontier technologies are becoming highly capital-intensive, this covariance would also suggest the need for increasing capital accumulation in poor countries, in order to boost productivity and economic growth. Thus the research brought two major findings, namely (1) the importance of MFPG in driving growth divergence, and (2) the strengthened relationship between MPFG and capital accumulation.
Further, our analysis of cross-country differences in diffusion of technology suggests that technology spillovers do not automatically take place, depending only upon a country’s economic or educational capacity. Cultural ambience is important as well. This indicates that the cultural constraints on the adoption of better technologies may partly explain the productivity gap between countries, as it can affect the speed at which technology diffusion occur
Deconstructing the BRICs: Structural transformation and aggregate productivity growth
Get PDFde Vries, Gaaitzen J., Erumban, Abdul A., Timmer, Marcel P., Voskoboynikov, Ilya-Deconstructing the BRICs: Structural transformation and aggregate productivity growth This paper studies structural transformation and its implications for productivity growth in the BRIC countries (Brazil, Russia, India, and China) from the 1980s onwards. Based on a critical assessment of the reliability and consistency of various primary data sources, we bring together a new database that provides trends in value added and employment at a detailed 35-sector level. Structural decomposition analysis suggests that for China, India and Russia reallocation of labor across sectors is contributing to aggregate productivity growth, whereas in Brazil it is not. This confirms and strengthens the findings of McMillan and Rodrik [NBER Working Paper 17143, 2011]. However, this result is overturned when a distinction is made between formal and informal activities within sectors. Increasing formalization of the Brazilian economy since 2000 appears to be growth-enhancing, while in India the increase in informality after the reforms is growth-reducing. Journal of Comparative Economics 40 (2) (2012) 211-227. Groningen Growth and Development Centre, Faculty of Economics and Business, University of Groningen, The Netherlands; Institute of Economic Research, Hitotsubashi University, Tokyo, Japan; The Conference Board China Centre, Beijing, China; Laboratory for Inflation Problems and Economic Growth, Higher School of Economics, Moscow, Russia. (C) 2012 Association for Comparative Economic Studies Published by Elsevier Inc. All rights reserved
An Analysis of Global Value Chain Incomes in Indian Industries
No full textThe importance of using measures of global value chains to understand the participation of countries in global trade has increased in recent years, as the fragmentation of production accelerated globally. This paper provides estimates of foreign content in domestic production in Indian industries, Indian content in the production of global industries, and the reliance of income generated in Indian industries on foreign demand. In general, India’s participation in GVC is relatively lower than in many other countries, yet it is improving. We find that the expansion of India’s manufacturing, and to some extent, market services sectors increase demand for output from upstream sectors in foreign countries that produce intermediate inputs used in the downstream sectors in India. We also see that Indian content is relatively the highest in global textile production, but its contribution to India’s GDP by means of value chain income is not the highest and has declined over the years. We also provide some initial evidence that the relationship between India’s participation in the GVC and sectoral productivity level is positive, which suggests the importance of intensifying India’s participation in the GVC
Lifetimes of Machinery and Equipment. Evidence from Dutch Manufacturing
Get PDFThis paper estimates service lifetimes for capital assets in Dutch manufacturing industries, using information on asset retirement patterns. A Weibull distribution function is estimated using a nonlinear regression technique to derive service lifetimes for three selected asset types: transport equipment, machinery and computers. For this purpose the benchmark capital stock surveys for different two digit industries are linked to annual discard surveys. On average the estimated lifetimes are respectively 6, 9 and 26 years for transport equipments, computers and machinery. However, these estimates vary across industries. A comparison of our estimates with Canadian, US and Japanese estimates shows notable differences in the lifetimes of all the asset types, with machinery showing the largest difference
Rental Prices, Rates of Return, Capital Aggregation and Productivity: Evidence from EU and US
Get PDFWith the increasing importance of investment in information and communication technology, methods for measuring the contribution of capital to growth have re-assumed centre-stage in recent growth accounting literature. The importance of using capital service growth rates rather than capital stock growth rates has long been advocated, and has become mainstream practice. However, the choice for a particular rate of return in the derivation of capital service prices is not straightforward and has barely been researched. Using four alternative rental price models —based on both external and internal rates of return models—this article quantifies the differences in total factor productivity growth rates (TFPG) under different model assumptions. The differences in TFPG are also examined in terms of the inclusion of taxes and subsidies in the calculation of rental prices. Empirical analysis carried out for four EU countries and the US in 26 industries during 1979-2003 shows that the use of capital stock overestimates TFPG in most industries. Incorporation of taxes seems to have only modest effect. The magnitude of divergence generated by alternative rental price models-particularly between internal models- is quite low. The difference is seen to be relatively high between external rate of return models and internal rate of return models. (JEL codes: E01,O47) Copyright , Oxford University Press.
Replication Data for: Slicing up global value chains
No full textTimmer, M. P., Erumban, A. A., Los, B., Stehrer, R., & De Vries, G. J. (2014). Slicing up global value chains. Journal of economic perspectives, 28(2), 99-118, DOI: 10.1257/jep.28.2.99 Related websit
LIFETIMES OF MACHINERY AND EQUIPMENT: EVIDENCE FROM DUTCH MANUFACTURING
Get PDFThis paper estimates service lifetimes for capital assets in Dutch manufacturing industries, using information on asset retirement patterns. A Weibull distribution function is estimated using a non-linear regression technique to derive service lifetimes for three selected asset types: transport equipment, machinery and computers. For this purpose, benchmark capital stock surveys for different two-digit industries are linked to annual discard surveys. On average the estimated lifetimes are 6, 9 and 26 years for transport equipment, computers and machinery, respectively. However, these estimates vary across industries. A comparison of our estimates with Canadian, U.S. and Japanese estimates shows notable differences in the lifetimes of all the asset types, with machinery showing the largest difference. Copyright 2008 The Author. Journal compilation International Association for Research in Income and Wealth 2008.
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