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A quantile regression decomposition of urban-rural inequality in Vietnam

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  • Nguyen, Binh T.
  • Albrecht, James W.
  • Vroman, Susan B.
  • Westbrook, M. Daniel

Abstract

We use the Vietnam Living Standards Surveys from 1992-93 and 1997-98 to examine inequality between urban and rural areas in Vietnam. Real per capita household consumption expenditure (RPCE) is our measure of well being. We apply a quantile regression decomposition technique to analyze the difference between the urban and rural distributions of log RPCE. Most of the difference between the upper tails of the distributions is due to differences in the marginal effects of covariates such as age or education rather than differences in the covariates themselves, but the opposite is true in the lower tails. Interesting regional and time effects are also identified.
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  • Nguyen, Binh T. & Albrecht, James W. & Vroman, Susan B. & Westbrook, M. Daniel, 2007. "A quantile regression decomposition of urban-rural inequality in Vietnam," Journal of Development Economics, Elsevier, vol. 83(2), pages 466-490, July.
    • Handle: RePEc:eee:deveco:v:83:y:2007:i:2:p:466-490
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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Dwayne Benjamin & Loren Brandt, 2002. "Agriculture and Income Distribution in Rural Vietnam under Economic Reforms: A Tale of Two Regions," Working Papers benjamin-02-01, University of Toronto, Department of Economics.
    3. Quy-Toan Do & Lakshmi Iyer, 2003. "Land rights and economic development : evidence from Vietnam," Policy Research Working Paper Series 3120, The World Bank.
    4. Jolliffe, Dean, 2002. "Whose Education Matters in the Determination of Household Income? Evidence from a Developing Country," Economic Development and Cultural Change, University of Chicago Press, vol. 50(2), pages 287-312, January.
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    7. José A. F. Machado & José Mata, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465, May.
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