Globalization, Structural Change, and Interregional Productivity Growth in the Emerging Countries (original) (raw)
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STRUCTURAL CHANGE AND PRODUCTIVITY GROWTH IN INDIA AND THE PEOPLE'S REPUBLIC OF CHINA
Globalization has significantly changed the composition and structure of emerging economies, which has in turn reallocated factors across various economic activities. In this context, this study examines the sources of labor reallocation or structural change, and measures and empirically evaluates the contribution of structural change to labor productivitygrowth (LPG) by controlling for indicators of economic globalization and types of human capital. The study also evaluates the relative contributions of human and physical capital to LPG. The study found that changing final demand is the most crucial factor in labor reallocation in India. In the PRC, this and changes in technology are factors of labor allocation. The regression analysis confirmed that structural change, globalization, and human capital significantly contribute to LPG. Due to its prevailing structure, India is capable of leading global economic growth in the future, provided that certain necessary policies on human capital development, outward-oriented policies, and other conducive economic reform measures are taken.
Globalization, Structural Change and Productivity Growth in the Emerging Countries
The paper examines the sources of labor reallocation or structural change, and measures and empirically evaluates the contribution of structural change to labor productivity growth (LPG). The paper also evaluates the relative contributions of human and physical capital to LPG. The paper found that changing final demand is the most crucial factor in labor reallocation in India. In the PRC, this and changes in technology are factors of labor allocation. The regression analysis confirmed that structural change, globalization, and human capital significantly contribute to LPG. Due to its prevailing structure, India is capable of leading global economic growth in the future, provided that certain necessary policies on human capital development, outward-oriented policies, and other conducive economic reform measures are taken. There is enough room for India to use manufacturing as a growth escalator, and for China to tap into services as a growth escalator to avoid the middle income trap.
Government College University, Lahore., 2020
Shifts in the sectoral employment and output (commonly referred to as structural change) are essential conditions as well as a connected phenomenon of economic growth. Despite the importance of structural changes for economic development, for a long time, this body of work was dormant. In recent times, the curiosity about alternative viewpoints to understand growth process and outcomes has also increased. Furthermore, it is also acknowledged in literature that empirical studies about developing countries in this domain are limited. Accordingly, this study addresses these gaps in literature. For this purpose, a sample consisting of 24 developing countries of Asia is studied for the period 1992-2016 as a case in example. In contrast with several studies found in literature related with the topic, this study deploys modern macro-panel data econometric techniques that generate more robust and reliable estimates, and are more appropriate empirically while dealing with macropanels. Therefore this study is updated, timely and more robust. After careful examination of alternatives, this study uses the 'sectoral labor relocation' as a proxy of structural change that is constructed through the application of Shiftshare analysis (SSA). A unique feature of this study is that it includes structural change (labor relocation) as a predictor of economic progress, along with other growth related variables such as capital stock, institutions, human capital and trade openness. The choice of these variables is based on theoretical as well as empirical literature. Twostep analytical strategy is used in this study; firstly, the SSA is applied using sectoral labor and value added data for each country and change in labor productivity is decomposed into three components i.e. 'within effect', 'between-static effect', and 'between-dynamic effect'. The last two effects are used for assessing the 'structural bonus' and 'structural burden hypotheses' in relevant literature, and collectively these two are referred to as 'structural change effect'. In the second analytical step, the calculated 'structural-change effect' is used in econometric modelling. The parameters are estimated, after necessary pre-and-post estimation requirements, through Common Correlated Effects Mean Group, and the Augmented Mean Group estimators. These estimators show empirical superiority over other older techniques in the presence of cross-sectional dependence and other issues. Overall results suggest that there is a positive significant relationship between structural change (measured as labor relocation) and economic progress (except in the case of AMG estimation without trend). Capital accumulation is also a positive significant explanatory variable of the economic progress in this empirical setting and this in in line with the standard growth theory. Both these finding support the conceptualization that structural change as labor relocation across sectors as well as capital accumulation play a supportive role in economic progress of the countries under study. However, the estimated coefficients of the structural change variable are relatively smaller than that of capital stock. Interestingly, the role of trade openness is statistically insignificant. In much of the 1990s many developing economies included in the sample were undergoing market reforms under the Structural Adjustment Programs. This may imply that labor relocation across sectors, and capital stock matter more for economic growth than just opening up the economies for increasing the size of tradables. The role of human capital is also statistically insignificant. Institutions are found to be playing a supportive role towards economic progress in case of the developing countries of Asia included in the sample over the study period.
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Economic growth, although being a major quest of all the economies, is not an automatic phenomenon. Among its determinants, structural change in the form of reallocation of labour from low to high productivity sectors is of crucial importance. In view of the remarkable growth performance and unprecedented structural change of Asia in the last couple of decades, this paper empirically investigated the case of 20 selected Asian countries. By employing the data spanning from 1991 to 2018, the study shows three main results. First, by employing Shift Share Analysis framework, it reaffirms the findings of previous literature that structural change contributes to the aggregate productivity growth. Second, by utilizing Generalized Methods of Moments technique, the results find it to be an important booster of growth. Third, the results are reliable and consistent with alternative measures of structural change like Norm of Absolute Values and Modified Lilien Index. Taken together, these fin...
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Industrial change processes are underlying forces that determine the change of regional productivity. In developed market economies, less productive firms are more likely to exit while productive firms have more chance to enter and to survive. As a result, spatial inequality of firm dynamics will directly influence the inequality of regional productivity. This study investigates how firm dynamics would affect regional productivity using firm level data during 1998-2007 in China. We first estimate total factor productivity (TFP) for each firm based on the semi-parametric method proposed by Olley and Pakes (1996). Regional productivity is derived by weighing the firm TFP using gross industrial output. There is considerable spatial inequality of TFP paired with a trend of convergence over the time period of 1999-2007. Decomposition of TFP growth shows that firm entry, exit and survival do contribute to TFP change and their contributions vary across prefectures substantially. The betwee...
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In their period of rapid economic growth China and India have experienced profound structural transformations. The aim of the paper is to analyze the relation between structural change, the process of globalization and economic growth in the two great Asian countries, using a highly disaggregated dataset for the 1987-2009 period. While China had a longer and more intensive productivity growth than India, the latter had a somewhat more balanced growth. Both countries registered higher withinsectors gains in productivity than between-sectors ones. Our analysis also shows that there exist important feedbacks between structural change, globalization and economic growth over time. When the reallocation of labor is large, it may positively impact on the future rates of economic growth. At the same time, however, it seems that a too rapid economic growth may hinder a smooth reallocation of labor. In both countries, new policies should be designed to favor labor movement across sectors and areas, to reduce the wage-productivity differentials and to integrate the informal sector in formal markets in India, in order to foster structural changes and enhance economic growth. If a too unbalanced economic growth has somewhat limited the extent of structural change, globalization has on the contrary promoted it. High level of export, import and FDI not only has been related to higher rates of economic growth, but also to a deeper reallocation of resources across sectors, modifying the comparative advantage and reorganizing the production.
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The literature on regional disparities in China is both broad and deep. Nonetheless, much of its focus has been on the effects of trade liberalization and national policies toward investment in interior provinces. Few pieces have examined whether the disparities might simply be due to differences in industry mix, final demand, or even interregional trade. Using two newly published multiregional input-output tables and disaggregated employment data, we decompose change in labor productivity growth for seven regions of China between 1987 and 1997 into five partial effects-changes in value added coefficients, direct labor requirements, aggregate production mix, interregional trade, and final demand. Subsequently we summarize the contributions to labor productivity of the different factors at the regional level. In this way, we present a new perspective on recent causes of China's interregional disparity in GDP per capita.