China’s (Uneven) Progress Against Poverty

1. China’s (Uneven) Progress Against Poverty Martin Ravallion and Shaohua ChenDevelopment Research Group, World Bank

2. Questions • How much progress has China made against absolute poverty? • When and where was the greatest progress made? • What happened to inequality? A poverty-inequality trade off? • What were the proximate causes of uneven progress over time and across provinces? What role was played by public policies? • What lessons does China’s past success against poverty hold for China in the future and for the rest of the developing world?

3. Data Five findings Five lessons

4. Data

5. Distributional data for China • Newly constructed poverty lines • Old lines seen as out of date: “too low” + no allowance for geographic COL differences • New lines: 850 Yuan per year for rural areas and 1200 Yuan for urban areas, both in 2002 prices; also province-specific lines • Newly assembled distributional data • much of which has not previously been analyzed • Rural Household Surveys (from 1980) and Urban Household Surveys (1981) of National Bureau of Statistics • Early surveys small for 30% of provinces, but no sign of bias • Time series of tabulated distributions (micro data not available) • Incomplete data at provincial level • though we can still provide estimates of the trends.

6. New poverty lines • Region-specific food bundles for urban and rural areas, valued at median unit values by province. • Food bundles based on the actual consumption of those between the 15th and 25th percentile nationally. • These bundles are then scaled to reach 2100 calories per person per day, with 75% of the calories from foodgrains. • Allowances for non-food consumption are based on the nonfood spending of households in a neighborhood of the point at which total spending equaled the food poverty line in each province (and separately for urban and rural areas).

7. Deflators over time • Urban and rural CPI • Urban inflation rate higher than rural, esp., in the 1990s (higher costs of previously subsidized goods)

8. Rising urban-rural COL differential

9. Corrections for 1990 change in valuation method in RHS • 1990 change in valuation methods for imputing income from consumption of own-farm output • Distributions by both methods for 1990 are used to correct the data for the late 1980s

10. Corrections for 1990 change in valuation method in RHS • 1990 change in valuation methods for imputing income from consumption of own-farm output • Distributions by both methods for 1990 are used to correct the data for the late 1980s

11. Poverty measures • Headcount index (H): % living in households with income per person below the poverty line. • Poverty gap index (PG): mean distance below the poverty line as a proportion of the poverty line • Squared poverty gap index (SPG): poverty gaps are weighted by the gaps themselves, so as to reflect inequality amongst the poor (Foster et al., 1984). • Parameterized Lorenz Curves • alternative functional forms (Beta+general elliptical) • checks for theoretical consistency and accuracy

12. Inequality measures • Relative Gini index based on sum of income differences normalized by the mean for that distribution • Absolute Gini index based on sum of income differences normalized by a fixed mean

13. Persistent data problems • Sample frame based on registration system => underestimation of urban poverty • Survey compliance problems, esp., urban areas • Single price indices, independent of level of income

14. Five findings

15. Huge overall progress against poverty, but uneven progress • Rising inequality, though more so in some periods and places • The pattern of growth matters to both poverty and inequality in China • No sign of an aggregate growth-equity trade off • Poverty would have fallen much faster without rising inequality

16. Finding 1: Huge overall progress against poverty, but uneven progress • In the 20 year period after 1981, the proportion living below our new poverty lines fell from 53% to 8%. ( 62%+ in 1980.) • Half of the decline in poverty came in 1981-84. • However, there were many setbacks for the poor. • Poverty rose in the late 1980s and stalled in early 1990s, • recovered pace in the mid-1990s, • but stalled again in the late 1990s.

17. Headcount index, 1981-2001

18. Headcount index for “$1/day”, 1981-2001 China Developing world less China East Asia less China

19. Effect on headcount index of our correction for the change in valuation methods

20. Trend rates of change in rural headcount index (upper line; by province; %/year; 1983-2001)

21. Trend rates of change in rural headcount index (upper line; by province; %/year; 1983-2001) Fujian, Jiangsu Beijing Guangdong

22. Finding 2: Rising inequalityBut not continuously and more so in some periods and some provinces • Relative inequality is higher in rural than urban areas • in marked contrast to most developing countries. • Though steeper increase in urban inequality. • Relative inequality between urban and rural areas has not shown a rising trend once one allows for the higher rate of increase in the urban cost-of-living. • Absolute inequality has increased appreciably • between and within both urban and rural areas, • and absolute inequality is higher in urban areas.

23. Relative inequality between urban and rural areas

24. Absolute inequality between urban and rural areas

25. Relative inequality in rural and urban areas and nationally

26. Absolute inequality in rural and urban areas and nationally

27. Effect on Gini index and mean of our correction for the change in valuation methods

28. Finding 3: The pattern of growth matters • Economic growth was clearly a key proximate cause of poverty reduction • Growth elasticity of poverty reduction = – 3.2 (t= – 8.7) (using survey means) – 2.6 (t= – 2.2) (using GDP per capita)

29. The sectoral pattern of growth matters • The gains to the poor from aggregate economic growth depended on its sectoral composition. • Decomposition of change in poverty: • Within-sector effect is the change in poverty measures over time weighted by final year population shares • Population shift effect measures the partial contribution of urbanization over time, weighted by the initial urban-rural difference in poverty measures. (Kuznets process of migration.)

30. Decomposition of the change in poverty Migration to urban areas helped, but the bulk of the reduction in poverty came from within rural areas • Note: Quite rapid urbanization despite restrictions on migration • Urban share of 19% in 1980; rose to 39% in 2002

31. Regression decomposition for mean income growth • Mean income: • Growth rate: • Test equation: • Null hypothesis:

34. Decomposing GDP growth • Standard classification of its origins, namely • “primary” (mainly agriculture), • “secondary” (manufacturing and construction) and • “tertiary” (services and trade). • The primary sector’s share fell from 30% in 1980 to 15% in 2001, though not montonically. • Almost all of this decline was made up for by an increase in the tertiary-sector share.

35. Shares of GDP by sector

36. Regression decomposition for sectoral decomposition • Test equation: • Null hypothesis:

39. Primary sector was the main engine of poverty reduction • Growth in the primary sector (primarily agriculture) did more to reduce poverty than either the secondary or tertiary sectors. • Starting in 1981, if the same aggregate growth rate had been balanced across sectors then it would have taken 10 years to bring the national poverty rate down to 8%, rather than 20 years. • But could a more equitable growth process have allowed the same rate of growth?

40. Province level • Complete series of mean income from 1980 • But less complete distributional data; 11-12 years • Marked differences in initial conditions; Gini index around mid-1980s varied from 18% to 33%. • OLS estimates of province specific trends:

41. Provinces with higher growth rates in rural mean income saw faster poverty reduction

42. Provinces with higher growth rates in rural mean income saw faster poverty reduction Reliability? H<2%

43. Provinces with higher growth rates in rural mean income saw faster poverty reduction Elasticity = -2.4 (t = -4.3) (dropping Beijing, Shanghai, Tianjin)

44. Wide variation in growth elasticities of poverty reduction • 95% CI for the impact of a 3% growth rate on H is (0%, 9%) • Dropping Beijing, Shanghai and Tianjin the 95% CI for 3% growth rate is (4%, 10%) • Growth elasticity calculated as ratio of trend in H to trend in mean varies from –6.6 ro 1.0 (mean=-2.3) • Geographic composition of growth mattered to aggregate rate of poverty reduction….

45. Growth did not occur where it would have most impact on poverty

46. Inequality and the pattern of growth • The composition of growth also mattered to the evolution of aggregate inequality. • Agricultural growth was inequality decreasing.

47. Inequality and GDP growth by origin

48. Inequality and GDP growth by origin

49. Inequality and growth in mean urban and rural incomes Rural economic growth reduced inequality within both urban and rural areas, as well as between them

50. Inequality and growth in mean urban and rural incomes Rural economic growth reduced inequality within both urban and rural areas, as well as between them