Structural transformation, growth, and inequality: Evidence from Viet Nam

Sarma, Vengadeshvaran; Paul, Saumik; Wan, Guanghua Working Paper Structural transformation, growth, and inequality: Evidence from Viet Nam ADBI Working Paper, No. 681 Provided in Cooperation with: Asian Development Bank Institute (ADBI), Tokyo Suggested Citation: Sarma, Vengadeshvaran; Paul, Saumik; Wan, Guanghua (2017) : Structural transformation, growth, and inequality: Evidence from Viet Nam, ADBI Working Paper, No. 681, Asian Development Bank Institute (ADBI), Tokyo This Version is available at: https://hdl.handle.net/10419/163188 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/3.0/igo/ ADBI Working Paper Series STRUCTURAL TRANSFORMATION, GROWTH, AND INEQUALITY: EVIDENCE FROM VIET NAM Vengadeshvaran Sarma, Saumik Paul, and Guanghua Wan No. 681 March 2017 Asian Development Bank Institute The Working Paper series is a continuation of the formerly named Discussion Paper series; the numbering of the papers continued without interruption or change. ADBI’s working papers reflect initial ideas on a topic and are posted online for discussion. ADBI encourages readers to post their comments on the main page for each working paper (given in the citation below). Some working papers may develop into other forms of publication. In this publication, “$” refers to US dollars. Suggested citation: Sarma, V., S. Paul, and G. Wan. 2017. Structural Transformation, Growth, and Inequality: Evidence from Viet Nam. ADBI Working Paper 681. Tokyo: Asian Development Bank Institute. Available: https://www.adb.org/publications/structural-transformation-growth-andinequality-evidence-viet-nam Please contact the authors for information about this paper. Email: [email protected] Vengadeshvaran Sarma is an assistant professor at the University of Nottingham, Malaysia. Saumik Paul is an associate professor at Hitotsubashi University, Tokyo. Guanghua Wan is the director of research at the Asian Development Bank Institute. The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms. Working papers are subject to formal revision and correction before they are finalized and considered published. Asian Development Bank Institute Kasumigaseki Building, 8th Floor 3-2-5 Kasumigaseki, Chiyoda-ku Tokyo 100-6008, Japan Tel: +81-3-3593-5500 Fax: +81-3-3593-5571 URL: www.adbi.org E-mail: [email protected] © 2017 Asian Development Bank Institute ADBI Working Paper 681 Sarma, Paul, and Wan Abstract We examine whether structural transformation leads to growth and income inequality in Viet Nam. Using three rounds of the Vietnam Household Living Standards Survey (2002, 2006, and 2010), we estimate re–centered influence functions to construct a decomposition analysis. Our results indicate that Viet Nam continues to experience sustained structural transformation and growth, but this growth is heterogeneous across regions. The growth exhibits pro–rich gains, with returns to agriculture and manufacturing increasing only for the top 10 to 20th percentiles. We also find that such growth increases income inequality in Viet Nam, and change in income inequality is heterogeneous across regions. Differences in growth and income inequality are driven by differences in the rate of industrialisation across regions and by structural effects such as access to seaports. For a more inclusive growth, access to non-farm activities may need to be increased for households that are not in areas with high levels of structural transformation. JEL Classification: O15, P46, O12, O53 ADBI Working Paper 681 Sarma, Paul, and Wan Contents 1. INTRODUCTION ......................................................................................................... 1 2. STRUCTURAL TRANSFORMATION AND INCOME INEQUALITY: THE CASE OF VIET NAM .......................................................................................... 2 3. DATA ........................................................................................................................... 6 4. EMPIRICAL STRATEGY AND RESULTS ................................................................... 9 4.1 Mapping Changes in Income Inequality .......................................................... 9 4.2 Returns to Sectoral Participation across Income Quantiles .......................... 11 4.3 Structural Change and Income Inequality: Decomposition ............................ 12 5. CONCLUSION .......................................................................................................... 13 REFERENCES ..................................................................................................................... 15 APPENDIXES ....................................................................................................................... 17 ADBI Working Paper 681 Sarma, Paul, and Wan 1. INTRODUCTION Economic development and growth entail large-scale structural transformation of economies (Hnatkovska and Lahiri 2014). Many Asian and African economies are now undergoing such large scale structural transformation—typically from agriculture to manufacturing and service sectors. Such structural transformation inevitably entails reallocation of workers from the primary sector to the manufacturing and service sectors. One of the important questions arising from such structural transformation led growth is, whether such growth helps the poor. On the one hand, growth may lift people out of poverty and therefore improve living standards for everyone. On the other hand, growth may increase income inequality by benefitting the rich more than the poor. There is no consensus in the literature on whether structural transformation led growth achieves the twin goals of improving welfare for the poor and decreasing income inequality. Viet Nam, one such developing economy, introduced a series of economic reforms in 1986—termed Doi Moi. These reforms enabled private lease of agricultural land (which enabled lease holders to trade land and seek rent on land), deregulated the domestic market significantly and also introduced trade liberalization measures. In particular, agricultural products were allowed to be exported, and foreign ownership of manufacturing firms was allowed. Price of agricultural goods increased as a result of trade liberalization, but it was the manufacturing sector that experienced rapid expansion over the last 3 decades. Workers have also therefore increasingly moved from agriculture to manufacturing (and to a smaller extent to services). Structural transformation has led to sustained economic growth in Viet Nam but at the expense of increasing income inequality. Economic growth in Viet Nam averaged 5%–6% over the last 3 decades. In particular, the 2000s saw average growth rates of about 6.4%. Gross domestic product (GDP) per capita at purchasing power parity (PPP) increased from $970 in 1990 to $6,023 in 2015. The proportion of the population living on under $3.10 a day (at 2011 PPP) decreased from 34.7% to 3.5%. However, in the same period the World Bank GINI index increased from 35.7 in 1992 to 38.7 in 2012.1 There is also evidence that the reduction in poverty and dividends from growth were spread unevenly across Viet Nam, increasing income inequality between regions and to some extent within regions (World Bank 2013). In this chapter, we examine how structural transformation through growth contributes to income inequality. In particular, we address the following research questions: • Does economic growth affect income inequality? • Is change in income inequality explained by sectoral participation within the income distribution? We use three rounds of repeated cross-sectional Vietnamese data to analyze structural change and income inequality over an 8-year period. We use the 2002, 2006, and 2010 rounds of the Vietnam Household Living Standards Survey (VHLSS) conducted by the General Statistics Office (GSO) in Viet Nam. The VHLSS data show significant structural transformation in Viet Nam over the 8-year period. Descriptive evidence also indicates a significant increase in household income over the period emulating the increase in national GDP. Further, similar to the World Bank GINI index, our data indicate a widening income disparity in Viet Nam over the years. There is also evidence 1 These statistics are downloaded from the World Bank’s World Development Indicators (WDI) database. 1 ADBI Working Paper 681 Sarma, Paul, and Wan to suggest the existence of significant regional disparity in structural transformation, income growth, and income inequality. Using growth incidence curves (GICs) and re-centered influence functions (RIFs) we identify how structural transformation maps onto the income distribution over the time periods. The data suggests that the labor mobility between the agriculture and manufacturing sectors was more prominent for the 30th to 65th percentile population. Regression outcomes also indicate that participation in agriculture and manufacturing yielded lower income compared to participation in the service sector, indicating negative returns to both working in agriculture and the manufacturing sectors. However, unconditional quantile RIF regression coefficients indicate that returns to agriculture and manufacturing are only negative for the poor—the returns are in fact positive for the top 20 percentile in agriculture and the top 10 percentile in manufacturing. While the returns to both agriculture and manufacturing are improving across the income distribution, there is evidence that, currently, the disparity in sectoral returns across the income distribution contribute to widening the income inequality. We then apply an Oxaca–Blinder style decomposition to our RIF estimates to identify the composition and structural effects of change. About 90% of the variation in growth across the income distribution is explained by structural effects across both periods: 2002–2006 and 2006–2010. We do not find that structural transformation explains these structural effects. For those in the bottom half of the income distribution, we find that household characteristics contribute significantly in explaining structural effects. Overall, our results indicate the need for the state to work towards improving the distribution of growth dividends across the income distribution. There is also some evidence that the poor may be concentrated in interior Viet Nam, away from the coastal regions and industrial zones—engaging in smallholder farming. Government policies may be required to ensure access to non-farm activities for such workers. Without adequate measures to address the widening income inequality, sustained growth may accelerate income inequality along geographical, and perhaps ethnic lines. We make two key contributions to the literature. First, we add to the work of McCaig, Benjamin, and Brandt (2015) by applying RIF estimates to decompose growth effects and map those onto the income distribution. Second, we also identify how sectoral returns on participation affect individuals and households along the income distribution, thus analyzing how growth dividends are shared along the income distribution and how this contributes to income (in)equality. This chapter proceeds as follows. In section 2, we briefly discuss the literature on structural transformation and inequality with a special focus on Viet Nam. In section 3, we discuss the data. Section 4, outlines the estimation strategy and the results. Section 5 concludes. 2. STRUCTURAL TRANSFORMATION AND INCOME INEQUALITY: THE CASE OF VIET NAM As Hnatkovska and Lahiri (2014) discuss, structural transformation has led to sustained economic growth in developing countries in Africa, Latin America, and especially, Asia. Such structural transformation typically entails a shift in economic activity from agriculture to manufacturing and services. This is characterised in dual economy models as that of Lewis (1954), where agriculture—the traditional sector has lower productivity while the modern sectors—manufacturing and services have higher 2 ADBI Working Paper 681 Sarma, Paul, and Wan productivity. 2 Globalization and transfer of technology have helped developing countries to accelerate structural transformation (Aizenman, Lee, and Park 2012). As resources, especially labor, move from the less productive agricultural sector to the more productive manufacturing and service sectors, the economy grows and people’s income grows (McMillian and Rodrik 2011; Rodrik 2013). Whether such growth benefits everyone in an economy is contentious. Kuznets (1955) hypothesized an inverted U-shaped relationship between economic growth and income inequality. Kuznets argued that as economies grow, income inequality will initially worsen. This is because much of the growth is likely to reward skills and those with access to capital—exhibiting pro-rich growth. Gradually over time, as low-skilled workers move to higher productivity and income sectors, the growth is likely to be more pro-poor. The empirical literature on this topic has boomed since the publication of the Deininger and Squire (1996) inequality dataset. Many of the cross-country studies (such as Datt and Ravallion 1998; Dollar and Kraay 2002; Ravallion 2012) and country case studies (such as Ravaliio and Datt 1996; Ravallion and Chen 2007) show that economic growth in fact reduces poverty. However, as Gunatilaka and Chotikapanich (2009) and Rubin and Segal (2015) show, growth is likely to increase income inequality and be pro-rich through two channels: (1) the rich receive larger shares of their income through wealth, which is more sensitive to growth than wage income; and (2) access to better education, infrastructure, and mobility yield better returns for the rich. There is also some evidence that the causal relationship flows both ways, and in fact high levels of inequality can hamper growth, and vice versa (UNRISD 2010)3. Viet Nam has experienced significant sustained economic growth since the economic reforms of 1986, termed Doi Moi (meaning: renovation). Since 1986, the Vietnamese economy has grown at average growth rates of between 5% and 6% (with exceptions during the Asian financial crisis in 1999 and the global economic crisis in 2009) [see Figure 1]. The economic reforms introduced private lease of agricultural land (previously all agricultural land was state owned), enabling trade and rental of such land. The reforms also introduced trade liberalization policies encouraging agricultural and manufacturing exports. The government also allowed for foreign ownership of manufacturing firms, at one point up to 100%. Prior to the reforms, almost the entire manufacturing sector was led by state owned enterprises (SOEs). Between 1989 and 2010, however, the number of SOEs declined by as much as 75% and the labor force in SOEs shrunk by about 40% (World Bank 2011). Since the economic reforms, productivity and wages in manufacturing have increased, causing a pull factor for workers to move from agriculture to manufacturing (see Appendix A for change in labor force participation across sectors and Appendix B for change in sectoral productivity). It should however be noted that, opening up of the agricultural sector for exports, increased prices of agricultural products and also improved rice yield from 3.33 tons per hectare in 1992 to 4.90 in 2006 (Benjamin et al. 2009). McCaig and Pavcnik (2013) however point out that 2 McMillan and Rodrik (2011) posit that the productivity gap between the traditional and modern sectors exhibit a U-shaped relationship. Initially, the productivity gap widens as productivity in the modern sectors grow with technology and reforms. As economies experience a shift in resources, especially labor, from agriculture to the modern sectors, productivity gap between agriculture and the modern sectors is likely to decrease. 3 Similar evidence is presented in 12 studies summarized in Benabou (2000). However, Banerjee and Duflo (2003) show that the causal relationship between income inequality and economic growth is likely to be non-linear, and any changes to income inequality (in any direction) are likely to reduce future growth. 3 ADBI Working Paper 681 Sarma, Paul, and Wan this increase was still not sufficient to incentivize agricultural workers to remain in the sector. Labour productivity in Viet Nam increased by 5.1% between 1990 and 2005, and 38% of this can be attributed to structural change (McCaig and Pavcnik 2013). McCaig and Pavcnik also argue that the flexible labor force ensured that structural unemployment remained very low and only for brief periods. Rapid and sustained economic growth in Viet Nam however was accompanied by an increase in income inequality [Figure 2]. Figure 1: Annual GDP Growth Source: World Development Indicators. Figure 2: GINI Index Source: World Development Indicators. 4 ADBI Working Paper 681 Sarma, Paul, and Wan Growth dividends are also ethnically polarised. As evident from Figure 6, the proportion of Kinh (ethnic majority) in the lowest income quantiles dropped dramatically from 2002 to 2010 and marginally increased in the highest income quantiles. More than half of those in the bottom 20th quantiles are ethnic minorities despite making up only about 15% of the population. Further, the proportion of ethnic minorities in the bottom 20th quantiles in fact increased over the 8-year period. Slower paced structural transformation among the ethnic minorities partially explains the widening income disparity across majority Kinhs and the ethnic minorities (see Appendix G). 4.2 Returns to Sectoral Participation across Income Quantiles We use Recentered Influence Function (RIFs) regressions to connect unconditional marginal quantiles to observable covariates (including household, structural factors, and geographical factors) based on Paul (2016) and Fortin, Lemieux, and Firpo (2010). Collecting the leading terms of a Von Mises (1947) linear approximation of the associated functional, the rescaled influence function of the pth quantile of the distribution of y can be written as: 𝑅𝐼𝐹�𝑦; 𝑞𝑝�=𝑞𝑝+𝐼𝐹�𝑦; 𝑞𝑝�=𝑞𝑝+�𝑝 − 𝐼(𝑦 ≤ 𝑞𝑝)� 𝑓 𝑦(𝑞𝑝) We consider movements from agriculture to manufacturing to be the main channel of structural transformation. The RIF regression for the pth quantile of the distribution of income (y) can therefore be written as: 𝑅𝐼𝐹�𝑦; 𝑞𝑝�= 𝛽0+𝛽1𝐴𝑔𝑟𝑖 +𝛽2𝑀𝐴𝑁 +𝑋′𝛾 +𝜀 where the unconditional or marginal quantile is 𝑞𝑝=∫𝐸�𝑅𝐼𝐹�𝑦; 𝑞𝑝, 𝐹 𝑦��𝑋�𝑑𝐹(𝑋). Agri is a dummy for participation in agriculture, MAN is a dummy for participation in manufacturing, 𝛾 is a set of covariates, and 𝜀 is the error term. We produce ordinary least square estimations of the RIF (presented in Appendix H) and also plot the RIF coefficients in Figure 7 above. The RIF regressions indicate negative income gains associated with participation in both agriculture and manufacturing as opposed to participation in the service sector. However, skilled workers across all three sectors experienced positive income returns. There is also some evidence in the regression results to suggest that agricultural land holding size adversely affects income, but this result is likely to be driven by non-agricultural high-wage employment. There is also strong evidence to suggest households in the South East had higher per capita income than the rest of the regions, the magnitude is also statistically large. This highlights the concentration of modern sector economic activity in the Ho Chi Minh province and its neighbouring provinces. The RIF coefficients when plotted against the income distribution, however, illustrate an interesting narrative—returns to agriculture and manufacturing (and even services) is only positive for the rich. In 2002, returns to participation in agriculture and manufacturing are negative across the income distribution. But in 2010, returns to both agriculture and manufacturing improve for those in the top 20th percentile and top 10th percentile, respectively. These results again re-iterate a widening income disparity in Viet Nam alongside economic growth and rising incomes. 11 ADBI Working Paper 681 Sarma, Paul, and Wan Figure 7: Unconditional Quantile Regression Coefficients Source: Authors’ calculations based on VHLSS 2002, 2006, and 2010. 4.3 Structural Change and Income Inequality: Decomposition While the evidence thus far has demonstrated a link between economic growth and widening income inequality, it is important to analyze how much of this widening income inequality is explained by structural change. We use a generalised Oaxaca– Blinder decomposition analysis (discussed in Fortin, Lemieux, and Firpo (2010) and Paul (2016)) to estimate the relative contribution of sectoral transformation on income inequality. We can denote the decomposition function as: ∆𝑂𝑣𝑒𝑟𝑎𝑙𝑙 𝜃= 𝐸(𝑋|𝑡= 1)(𝛽1 𝜃− 𝛽𝐶 𝜃) + 𝐸(𝑋|𝑡= 1)𝛽𝐶 𝜃− 𝐸(𝑋|𝑡= 0)𝛽0 𝜃 Where, the linear RIF-regressions of the pth quantile of the distribution of y is estimated by replacing y with the estimated value of 𝑅𝐼𝐹 ��𝑦; 𝑞𝑝�. The structure and composition effects can be decomposed as: Structure Effect = 𝐸(𝑋|𝑡= 1)𝑇. (𝛾�1 𝑞𝑝− 𝛾�𝐶 𝑞𝑝) Composition Effect =𝐸(𝑋|𝑡= 1)𝑇.𝛾�𝐶 𝑞𝑝− 𝐸(𝑋|𝑡= 0)𝑇.𝛾�0 𝑞𝑝. The decomposed GICs in Figure 8 indicate that much of the variation in income growth is explained by structural effects. About 90% of the variation in growth across the income distribution is explained by structural effects across both periods: 2002–2006 and 2006–2010. The contribution of structural effects in explaining growth, however, declines for the rich, across both time periods. Composition effects have a marginally higher capacity to explain the income growth of the top 10th percentile, but yet, the contribution in explaining is very small. We then decompose the structural and composition effects by covariates, to identify which factors affect structural and composition effects. In particular, we are interested to know whether structural transformation—differences in participation rates in agriculture and manufacturing, explain the differences in growth across the income distribution. We present the decomposition of covariates’ contribution to structural effects in Appendix I. We do not find that structural transformation explains the structural effects. Structural transformation contributes less than 1% in explaining structural effects, but contributes more significantly in explaining composition effects (not presented here for brevity). 12 ADBI Working Paper 681 Sarma, Paul, and Wan Much of the structural effects are unexplained and can be attributed to unobservable factors. For those in the lowest half of the income distribution, we find that household characteristics (including ethnicity) contribute significantly in explaining structural effects. But the lack of significant contributions by sectoral covariates in the Oaxaca– Blinder decomposition indicate that while structural transformation led growth has increased income inequality, structural transformation by itself may not sufficiently explain changes in the income inequality. Figure 8: Decomposition Analysis Source: Authors’ calculations based on VHLSS 2002, 2006, and 2010. 5. CONCLUSION Viet Nam has experienced sustained and rapid economic growth since the Doi Moi economic reforms of 1986. Viet Nam’s growth levels have surpassed the average growth for the East Asia and Pacific regions and the economy continues to grow at an annual average 6%. With economic growth, Viet Nam has also experienced a marginal albeit significant increase in income inequality. Growth in Viet Nam, however, has not been entirely inclusive. The data indicate that structural transformation occurred across all income quantiles, but the shift from agriculture to manufacturing was more prominent for those at the center of the income distribution. The data also indicate that returns to agriculture and manufacturing were only positive for the top 10th to 20th percentile, exacerbating the income divide. Growth incidence curves indicate that Viet Nam’s growth, especially from 2002 to 2010, has been pro-rich. Further, growth has been heterogeneous across ethnic groups and regions. In Viet Nam, ethnic concentration of regions also varies. The regions experiencing high levels of growth and modern sector activity are predominantly occupied by the Kinh ethnic group—the major ethnic group in Viet Nam. Such geographical and hence ethnic concentration of structural transformation have widened income inequality between regions and between ethnic groups. In decomposition analyses, however, we find that structural transformation does not sufficiently explain variations in income growth across the income distribution. The decomposition analysis indicates that household characteristics (including ethnicity) and unobservables explain much of the variations in growth across the income distribution. 13 ADBI Working Paper 681 Sarma, Paul, and Wan Given the widening income inequality, government policies need to address more inclusive growth strategies. We propose three strategies to improve income equality in Viet Nam. First, improve skills acquisition for those at the lowest percentiles of the income distribution. There is strong evidence that skilled workers across the income distribution earn positive returns on their skills. Distinctions between those with and without skills—especially in the agricultural sector—widen overall income inequality. Second, as Phan and Coxhead (2010) point out, it is important to improve access to non-farm activities for the poor. Given that sectoral productivity and incomes are higher in the modern sectors, the poor, who are unable to move to regions with higher modern sector concentration may be left out from reaping growth dividends. Government policies aimed at increasing access to non-farm activities in regions with very high agricultural activity and poverty may help improve income equality. Third, reduce ethnic disparities in income growth. Geographical concentration of modern sector activity in the Red River Delta, the South East, and the Mekong River Delta have contributed to widening income disparities among Kinh and the ethnic minorities, as ethnic composition in Viet Nam is highly localized across different regions. While ethnic minorities have also experienced rising income over the years, their rate of increase in income has been significantly lower than that for Kinhs. 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Vietnam Poverty Assessment: Well Begun, Not Yet Done – Vietnam’s Remarkable Progress on Poverty Reduction and the Emerging Challenges. Report. Washington, DC: The World Bank. 16 ADBI Working Paper 681 Sarma, Paul, and Wan APPENDIX A Sectoral Contribution to GDP and Share of Labor Force (%) GDP = gross domestic product. Source: World Development Indicators and McCaig and Pavcnick (2013). 17 ADBI Working Paper 681 Sarma, Paul, and Wan APPENDIX B Sectoral Productivity (Share of GDP/Share of Employment, by Sector, US$, PPP) GDP = gross domestic product; PPP = purchasing power parity. Source: World Development Indicators and McCaig and Pavcnick (2013). 18 ADBI Working Paper 681 Sarma, Paul, and Wan APPENDIX C Net Migration Source: General Statistics Office (GSO), Viet Nam. 19 ADBI Working Paper 681 Sarma, Paul, and Wan APPENDIX D Change in Sectoral Participation by Region Source: Authors’ calculations based on VHLSS 2002, 2006 and 2010. 20