ساختارشکنی برزیل، روسیه، هند، و چین : تحول ساختاری و رشد بهره وری کل

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.

A central insight in development economics is that development entails structural change. Structural change, narrowly defined as the reallocation of labor across sectors, featured prominently in the early literature on economic development by Kuznets (1966). As labor and other resources move from traditional into modern economic activities, overall productivity rises and incomes expand. The nature and speed with which structural transformation takes place is considered one of the key factors that differentiate successful countries from unsuccessful ones (McMillan and Rodrik, 2011). Therefore, new structural economists argue that production structures should be the starting point for comparative economic analysis and the design of appropriate policies (Lin, 2011).1 Technological change typically takes place at the level of industries and induces differential patterns of sectoral productivity growth. At the same time, changes in domestic demand and international trade patterns drive a process of structural transformation in which labor, capital and intermediate inputs are continuously relocated between firms, sectors and countries (Kuznets, 1966, Chenery et al., 1986, Harberger, 1998 and Hsieh and Klenow, 2009). One of the best documented patterns of structural change is the shift of labor and capital from production of primary goods to manufacturing and later to services. This featured prominently in explanations of divergent growth patterns across Europe, Japan and the U.S. in the post-WW-II period (Denison, 1967, Maddison, 1987 and Jorgenson and Timmer, 2011). Another finding is that in low-income countries the level and growth rate of labor productivity in agriculture is considerably lower than in the rest of the economy, reflecting differences in the nature of the production function, in investment opportunities, and in the rate of technical change (Syrquin, 1984, Crafts, 1984 and Gollin et al., 2011). Together these findings suggest a potentially important role for resource allocation from lower to higher productive activities to boost aggregate productivity growth. Based on the sector database of Timmer and de Vries (2009), the IADB (2010) and McMillan and Rodrik (2011) found that structural change was contributing to productivity growth in Asia; whereas it was absent or even reducing growth in Africa and Latin America. Also Bosworth and Collins (2008) found strong growth-enhancing structural change in China and India. So far, however, analyses of structural change in developing countries are constrained by the availability of detailed sector data, obscuring a proper assessment of the role of structural transformation in driving aggregate productivity growth. Typically, data is only available for broad sectors such as agriculture, industry and services, hiding important reallocations that can take place, for example from low-productive garment making to high-productive transport equipment manufacturing. Also a distinction between formal and informal activities within a sector, say informal and formal textile manufacturing may have important consequences for our understanding of the effects of structural change on aggregate growth. Productivity growth in the formal sector could go hand-in-hand with a substitution of capital for labor and thereby a push of employment into low-productive informality, but such reallocation effects would not be picked up in an aggregate analysis. This paper addresses these issues by studying the role of structural change for growth in four large developing countries, the BRIC countries: Brazil, China, India and Russia. The acronym BRIC was invented by Jim O’Neill in 2001 to group these four developing countries because of their recent growth spurts and potential for future domination of the world economy due to their population and economic size. Economic growth in China and India in particular has been well above world average, and provides a foundation for the growth of world GDP. Fig. 1 shows that the share of the BRICs in world GDP increased from about 15% in 1980 to 27% in 2008.To analyze the role of structural change in BRICs’ growth, we present a harmonized time-series database of value added and persons engaged with a common detailed 35 sector classification (ISIC revision 3). The dataset builds upon the time-series of broad sectors for China and India by Bosworth and Collins (2008) and for Asian and Latin American countries by Timmer and de Vries (2009). It adds further detail and harmonizes the measurement of output and employment across countries, which is important for a comparative and more fine-grained analysis of economic growth and production. Data on number of workers is based on the broadest employment concept, including self-employment, family-workers and other informal workers. The dataset is based on a critical assessment of the coverage and consistency of concepts and definitions used in various primary data sources. The sector database is publicly available.2 Using the canonical shift-share method we find strong growth-enhancing effects of structural change in China, India, and Russia, but not in Brazil. This confirms the findings of McMillan and Rodrik (2011) and Bosworth and Collins (2008). However, we show that these results are sensitive to the level of aggregation by performing the same decomposition at various levels of aggregation such as 3, 10 and 35 industries. This is true in particular, when a distinction is made between formal and informal activities within sectors. To this end, we use detailed national accounts data for India, and nationally representative surveys of the informal sector in Brazil. For example, in India the informal sector accounts for up to 30% of manufacturing’s value added, compared with an 80% share in employment, indicating large differences in productivity between formal and informal activities. Our analysis suggests that in India the expansion of informal activities after the reforms is associated with a reduction in aggregate growth. In contrast, employment reallocation towards formal activities in Brazil is increasing aggregate growth after 2000. This shows the importance of using detailed industry data to analyze structural change as the standard decomposition method is quite sensitive to the level of aggregation. We extend the decomposition method to show formally that by relying on aggregate sector data only, reallocation effects can be substantially over- or underestimated. The remainder of the paper is organized as follows. Section 2 discusses the main issues in constructing the harmonized BRIC dataset, relegating a detailed description of sources and methods by country to a Supplementary data. The decomposition method to measure the contribution of sectors to growth is presented in Section 3. Section 4 discusses trends in production structures and presents decomposition results by country. In Section 5, we account for employment reallocation across formal and informal activities in decomposing growth for Brazil and India. Section 6 provides concluding remarks.

New structural economists reinvigorate the argument that the nature and speed of structural transformation is a key factor in explaining economic growth (Lin, 2011). McMillan and Rodrik (2011) argue that structural change is growth-enhancing in Asia, whereas it is growth-reducing in Africa and Latin America. However, empirical analysis of structural change in developing countries has been based on aggregated sector data (e.g. Bosworth and Collins, 2008, IADB, 2010 and McMillan and Rodrik, 2011), which may hide diverging trends at a more detailed level and thereby obscure a proper assessment of the role of structural transformation for aggregate productivity growth. This paper studied patterns of structural change and productivity growth in four major developing countries since the 1980s, the BRIC countries, using a newly constructed detailed sector database. Based on a structural decomposition, we find that for China, India and Russia reallocation of labor across sectors is contributing to aggregate productivity growth, whereas in Brazil it is not. This strengthens the findings of McMillan and Rodrik (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. The case of Brazil shows that growth-enhancing structural change is necessary but not sufficient for aggregate productivity growth. The shift of employment from informal to formal activities coincided with slow or even negative productivity improvements in formal industry and services. On the other hand, in India, informal activities expanded after the reforms, creating more dualism. The expansion of the low-productive informal activities was accompanied by dynamic formal activities, especially in the manufacturing and business services sector (Eichengreen and Gupta, 2011). India shows that growth-reducing structural change can go hand-in-hand with productivity improvements within particular industries generating high aggregate productivity growth. These divergent growth paths between India and Brazil indicate that within- and reallocation-effects have to be considered in combination in any analyses of structural change. Clearly, these analyses also depend critically on the level of sector detail used and should be interpreted with care. The new sector database provides a more fine-grained analysis of economic growth and production in the BRIC countries. As such, the level of detail in this paper is in between micro (firm-level) analysis and macro analysis of growth. A drawback of this approach is that we may still miss out on important dynamics within sectors. For example, Hsieh and Klenow (2009) explore the productivity distribution of firms within detailed manufacturing sectors within India and China and find that resource reallocation towards the most productive firms within narrowly defined industries may double productivity. In the end though, one is interested in the economy-wide effects of structural change and future empirical analysis should aim to analyze the role of resource reallocation for aggregate growth building up from the micro-level. The increasing availability of micro data that allow tracking employees across firms (e.g. McCaig and Pavcnik (2011) for Vietnam, and Menezes-Filho and Muendler (2011) for Brazil), opens up a promising research agenda.