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Measuring pro-poor growth

  • Ravallion, Martin
  • Shaohua Chen

It is important to know how aggregate economic growth or contraction was distributed according to initial levels of living. In particular, to what extent can it be said that growth was"pro-poor?"There are problems with past methods of addressing this question, notably that the measures used are inconsistent with the properties that are considered desirable for a measure of the level of poverty. The authors provide some new tools for assessing to what extent the aggregate growth process in an economy is pro-poor. The key measurement tools is the"growth incidence curve,"which gives growth rates by quantiles (such as percentiles) ranked by income. Taking the area under this curve up to the headcount index of poverty gives a measure of the rate of pro-poor growth consistent with the Watts index for the level of poverty. The authors give examples using survey data for China during the 1990s. Over 1990-99, the ordinary growth rate of household income per capita in China was 7 percent a year. The growth rate by quantile varied from 3 percent for the poorest percentile to 11 percent for the richest, while the rate of pro-poor growth was around 4 percent. The pattern was reversed for a few years in the mid-1990s, when the rate of pro-poor growth rose to 10 percent a year--above the ordinary growth rate of 8 percent.

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Paper provided by The World Bank in its series Policy Research Working Paper Series with number 2666.

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Date of creation: 31 Aug 2001
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Handle: RePEc:wbk:wbrwps:2666
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  1. Dollar, David & Kraay, Aart, 2001. "Growth is good for the poor," Policy Research Working Paper Series 2587, The World Bank.
  2. Shorrocks, Anthony F, 1983. "Ranking Income Distributions," Economica, London School of Economics and Political Science, vol. 50(197), pages 3-17, February.
  3. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-31, March.
  4. Ravallion, Martin & Chen, Shaohua, 1999. " When Economic Reform Is Faster Than Statistical Reform: Measuring and Explaining Income Inequality in Rural China," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(1), pages 33-56, February.
  5. Atkinson, A B, 1987. "On the Measurement of Poverty," Econometrica, Econometric Society, vol. 55(4), pages 749-64, July.
  6. Foster, James E & Shorrocks, Anthony F, 1991. "Subgroup Consistent Poverty Indices," Econometrica, Econometric Society, vol. 59(3), pages 687-709, May.
  7. Nanak Kakwani, 1997. "Growth Rates Of Per-Capita Income And Aggregate Welfare: An International Comparison," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 201-211, May.
  8. Datt, Gaurav & Ravallion, Martin, 1992. "Growth and redistribution components of changes in poverty measures : A decomposition with applications to Brazil and India in the 1980s," Journal of Development Economics, Elsevier, vol. 38(2), pages 275-295, April.
  9. Ravallion, Martin & Shaohua Chen, 1998. "When economic reform is faster than statistical reform - measuring and explaining inequality in rural China," Policy Research Working Paper Series 1902, The World Bank.
  10. Foster, James E. & Shorrocks, Anthony F., 1988. "Inequality and poverty orderings," European Economic Review, Elsevier, vol. 32(2-3), pages 654-661, March.
  11. Foster, James E & Shorrocks, Anthony F, 1988. "Poverty Orderings," Econometrica, Econometric Society, vol. 56(1), pages 173-77, January.
  12. Gastwirth, Joseph L, 1971. "A General Definition of the Lorenz Curve," Econometrica, Econometric Society, vol. 39(6), pages 1037-39, November.
  13. Eichhorn, Wolfgang & Funke, Helmut & Richter, Wolfram F., 1984. "Tax progression and inequality of income distribution," Journal of Mathematical Economics, Elsevier, vol. 13(2), pages 127-131, October.
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