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China's Income Distribution over Time: Reasons for Rising Inequality

  • Wu, Ximing
  • Perloff, Jeffrey M.

We use a new method to estimate China’s income distributions using publicly available interval summary statistics from China’s largest national household survey. We examine rural, urban, and overall income distributions for each year from 1985-2001. By estimating the entire distributions, we can show how the distributions change directly as well as examine trends in traditional welfare indices such as the Gini. We find that inequality has increased substantially in both rural and urban areas. Using an inter-temporal decomposition of aggregate inequality, we determine that increases in inequality within the rural and urban sectors and the growing gap in rural and urban incomes have been equally responsible for the growth in overall inequality over the last two decades. However, the rural-urban income gap has played an increasingly important role in recent years. In contrast, only the growth of inequality within rural and urban areas is responsible for the increase in inequality in the United States, where the overall inequality is close to that of China. We also show that urban consumption inequality (which may be a better indicator of economic well-being than income inequality) rose considerably.

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Paper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt166747gz.

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Date of creation: 01 Feb 2004
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Handle: RePEc:cdl:agrebk:qt166747gz
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  1. Dirk Kreuger & Fabrizio Perri, 2002. "Does Income Inequality Lead to Consumption Inequality? Evidence and Theory," Working Papers 02-15, New York University, Leonard N. Stern School of Business, Department of Economics.
  2. Keane, Michael & Prasad, Eswar, 2001. "Social Transfers and Inequality During the Polish Transition," MPRA Paper 54326, University Library of Munich, Germany.
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  4. Milanovic, Branko, 1995. "Poverty, inequality, and social policy in transition economies," Policy Research Working Paper Series 1530, The World Bank.
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  6. 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.
  7. D. Ormoneit & H. White, 1999. "An efficient algorithm to compute maximum entropy densities," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 127-140.
  8. Xin Meng, 2004. "Economic Restructuring and Income Inequality in Urban China," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 50(3), pages 357-379, 09.
  9. Simon Kuznets, 1950. "Shares of Upper Income Groups in Income and Savings," NBER Books, National Bureau of Economic Research, Inc, number kuzn50-1.
  10. Burkhauser, Richard V. & Butler, J. S. & Feng, Shuaizhang & Houtenville, Andrew J., 2004. "Long term trends in earnings inequality: what the CPS can tell us," Economics Letters, Elsevier, vol. 82(2), pages 295-299, February.
  11. Wu, Ximing, 2003. "Calculation of maximum entropy densities with application to income distribution," Journal of Econometrics, Elsevier, vol. 115(2), pages 347-354, August.
  12. Dale W. Jorgenson, 1998. "Did We Lose the War on Poverty?," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 79-96, Winter.
  13. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
  14. Dennis Tao Yang, 1999. "Urban-Biased Policies and Rising Income Inequality in China," American Economic Review, American Economic Association, vol. 89(2), pages 306-310, May.
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