WIDER Dev Conf 2019 Bangkok Industrial growth with poverty and equity? Predictions from night lights in Vietnam Takahiro Yamada * and Christian S. Otchia + *Ministry of Finance, Japan + Nagoya U. September 2019
Stylized facts 1
Abstract While agriculture did not work, industrial outputs performed as a strong driver for poverty reduction in Vietnam in 2000s (the poverty elasticity ranges from -0.678 to -0.381). The result suggests that there is no stable relationship between poverty-initial inequality, and poverty-initial inequality through industrial outputs. Vietnam’s development after the Doi Moi policy has been characterized by triple successes: A high economic growth, significant poverty reduction, and low inequality. By employing provincial panel data of Vietnam from 2002 to 2010, this study verifies the relationship between industrial growth and poverty reduction with the consideration of initial conditions using data in 2002 and 1997/98. The main estimation results show that (i) industrial sector outputs are a strong driver of poverty reduction, while agriculture sector outputs do not have statistical significance (ii) there is no stable relationship between poverty-initial inequality, and poverty-initial inequality through industrial outputs. 2
Contribution Our paper extends the findings of Ravallion and Datt (JDE, 2002) and Ferreira et al. (JDE, 2010) by employing unique evidence from Vietnam to verify how the sectoral composition of growth and initial inequality interacted to affect poverty. India: a country with vast numbers of poor people even now the latest available poverty headcount ratio was 21.2% in 2011, according to PovcalNet very high before that (54.8% as of 1983). Brazil: unequal distribution of income with the Gini index approximately 0.6 record of poverty reduction was disappointing due both to low growth rates and a low growth elasticity of poverty reduction Vietnam: Large absolute poverty reduction along with higher and more inclusive economic growth through structural change over the past 30 years since the Doi Moi ; from the agricultural sector dominance to the manufacturing export–oriented economy, which has been backed by the introduction of foreign investments . 3
Contribution (cont.) Our paper provides more robust estimations by employing the nighttime lights data as a proxy for industrial outputs, and the robustness check tool proposed by Oster (JBES, forthcoming) , the unobservable selection and coefficient stability test. The potentially insufficient quality of growth indicators due to measurement errors in less developed countries (Henderson et al., AER, 2012; Johnson et al., NBERWP, 2013; Keola et al., WD, 2015; Nordhaus, 2006; Ravallion and Chen, 1999), which is the case in Vietnam, as well (International Monetary Fund [IMF], 2010) use of night lights data given the strong correlation between night lights and industrial growth (Henderson et al., AER, 2012) Oster (JBES, forthcoming) check the effect of omitted variable bias by changing the degree of observable and unobservable with the consideration of R-squared value 4
World has committed to poverty eradication, but… Distribution of the extreme poor, non-poor bottom 40 percent and non- poor top 60 percent in 2011 and 2030 Source: Lakner et al (2014) Note: Based on the idea by Beegle et al. (2014), Lakner et al. (2014) updated data for 2011 and 2030 (distribution- 5 neutral growth, meaning not necessarily leading to either a worsening or an improvement in distribution).
Higher growth by integrating to the World economy via Doi Moi Real sector development and major historical events in Vietnam 6
Large poverty reduction and low and stable inequality Poverty and inequality index in Vietnam Poverty headcount ratio Poverty gap ratio Gini index Year GSO's overall $1.90 a day GSO's overall $1.90 a day GSO's overall $1.90 a day poverty line (2011 PPP) poverty line (2011 PPP) poverty line (2011 PPP) 2002 33.5% 40.1% 5.6% 11.2% 0.299 0.376 2004 23.5% 31.4% 4.6% 8.5% 0.316 0.368 2006 17.8% 21.4% 4.3% 5.3% 0.316 0.358 2008 20.1% 16.8% 3.8% 3.7% 0.316 0.358 2010 18.3% 3.9% 3.0% 0.8% 0.333 0.393 Source: GSO, VHLSS2002, 2004, 2006, 2008, 2010 and PovcalNet, the World Bank. Note: We use "overall poverty line" (GSO 2008, 2010) expressed as the monthly average expenditure per capita of household adjusted for the cost of living by region and overtime as follows: 160 thousand dongs in 2002; 173 thousand dongs in 2004; 213 thousand dongs in 2006; 290 thousand dongs in 2008; 430 thousand dongs in 2010, respectively. Poverty indicators using $1.90 a day (2011 PPP) are in parenthesis. 7
Agri to manufacturing Value added by sector (constant 2010 US$) Source: WDI, the World Bank. 8
Agri to manufacturing Employment share by sector (%) Source: WDI, the World Bank. 9
Reduction of tariff rate, FDI inflows and export-oriented Weighted mean applied tariff rate, FDI, and trade indicators of Vietnam Sources: WDI, the World Bank using the World Integrated Trade Solution system, based on data from the United Nations Conference on Trade and Development’s Trade Analysis and Information System (TRAINS) database and the WTO Integrated Data Base (IDB) and Consolidated Tariff Schedules (CTS) database. FDI data are from the Statistical Yearbooks of Vietnam; they include supplementary capital to licensed projects in previous years. 10 Note: The weighted mean applied tariff rate is the average of the effectively applied rate that is weighted by the product import shares corresponding to each partner country.
Concentration of FDI on manufacturing Foreign direct investment (FDI) projects licensed by economic activity (total registered capital, USD million) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Agriculture, forestry, and fishing 58.9 30.4 49.5 47.3 107.6 51.1 169.4 58.6 223.5 134.5 36.2 Mining and quarrying 37.9 153.4 56.0 144.3 262.3 6,840.8 397.0 5.6 620.1 1,176.7 Manufacturing 1,401.1 3,110.2 4,818.4 8,270.9 10,882.5 28,902.4 3,942.8 5,979.3 Electricity, gas, steam, and air conditioning 2,139.1 2,952.6 supply 1,184.0 0.0 0.0 17.2 20.4 0.0 9.6 3.7 183.9 Water supply, sewage, waste management, 10.1 and remediation activities Construction 24.1 9.5 80.2 25.3 212.8 171.1 641.4 993.3 492.1 652.0 1,816.0 Wholesale and retail trade; repair of motor vehicles, motorcycles, and personal and 0.0 0.0 0.0 7.6 38.2 99.3 141.1 129.9 54.8 261.1 462.1 household goods Transportation and storage/transport, storage, 8.0 231.5 20.4 15.3 56.3 684.2 52.3 356.5 1,882.1 299.8 881.0 and communications Hotels and restaurants 22.8 10.1 168.6 140.2 141.0 61.8 498.4 1,968.1 1,350.2 9,156.8 315.5 Financial, banking, and insurance activities 10.0 0.0 5.0 0.8 30.6 145.9 32.0 32.3 62.6 100.0 59.1 Real estate activities 0.0 0.0 0.0 183.7 200.9 460.8 1,818.8 6,114.8 23,702.8 7,808.4 6,827.9 Education and training 6.7 14.6 25.8 22.1 11.6 86.7 30.4 74.7 Health and social work 67.2 53.2 26.5 2.3 16.5 203.4 7.9 112.5 402.9 15.0 205.6 Recreational, cultural, and sporting activities 24.5 121.2 21.1 189.1 410.3 5.8 107.4 62.3 Community, social, and personal service 17.0 29.2 30.8 7.0 1.7 20.5 16.1 5.5 0.6 18.2 15.5 activities Total 2,012.1 2,503.0 1,557.7 1,899.7 4,222.2 6,839.8 12,003.8 21,347.8 64,011.0 23,107.3 19,703.5 Source: Author’s compilation is based on the Statistical Yearbooks of Vietnam. Note: FDI includes supplementary capital to licensed projects in previous years. 11
Contribution (cont.) Our paper complements another group of reports in the literature that seek the answer to a recurring issue: whether the focus of development plans should be on growth, poverty, and/or inequality The recurring issue e.g. Jain and Tendulkar, 1990; Kakwani and Subbarao, 1990; Kakwani et al., 2000; Ravallion, 2001; Kalwiji and Verschoor, 2007; Bourguignon, 2004; Lopez, 2006; Ravallion, 2007 Growth-poverty relationship Dollar and Kraay (JEG, 2002) and Dollar et al. (EER, 2016) • Growth is (still) good for the poor—the average incomes of nations rise proportionately with average incomes of the poor segments. Growth-inequality and poverty-inequality relationships are open questions. Sectoral Output Growth and Poverty Relationship …Unique development on Ravallion and Datt (JDE, 2002) and Ferreira, Leite and Ravallion (henceforth FLR) (JDE, 2010): • (i) from cross-country to one-country case study using panel data, and (ii) from aggregate output to disaggregated output data. 12
Ravallion and Datt (JDE, 2002) Confirmed the importance of farm yields and non-farm outputs, among others. Also, stressed the importance of initial conditions for poverty reduction through non-farm growth Regressed disaggregated sectoral outputs to poverty indices by controlling initial conditions for India’s 15 states during 1960-1994. Higher farm yields , higher non-farm outputs, higher state development spending, and lower inflation were all poverty reducing. Non-farm growth process was more pro-poor in states with initially higher literacy, higher farm productivity, higher rural living standards relative to urban areas, lower landlessness and lower infant mortality. 13
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