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Survey nonresponse and the distribution of income

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  • Anton Korinek
  • Johan Mistiaen
  • Martin Ravallion

    ()

Abstract

The authors examine the distributional implications of selective compliance in sample surveys, whereby households with different incomes are not equally likely to participate. They discuss poverty and inequality measurement implications for monotonically decreasing and inverted-U compliance-income relationships. The authors demonstrate that the latent income effect on the probability of compliance can be estimated from information on response rates across geographic areas. On implementing the method on the Current Population Survey for the United States, they find that the compliance probability falls monotonically as income rises. Correcting for non-response appreciably increases mean income and inequality, but has only a small impact on poverty incidence up to poverty lines common in the United States.

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File URL: http://hdl.handle.net/10.1007/s10888-005-1089-4
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Bibliographic Info

Article provided by Springer in its journal The Journal of Economic Inequality.

Volume (Year): 4 (2006)
Issue (Month): 1 (April)
Pages: 33-55

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Handle: RePEc:kap:jecinq:v:4:y:2006:i:1:p:33-55

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Web page: http://springerlink.metapress.com/link.asp?id=111137

Related research

Keywords: income distribution; poverty and inequality measurement; survey nonresponse;

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References

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  1. Xavier Sala-i-Martin, 2002. "The world distribution of income (estimated from individual country distributions)," Economics Working Papers 615, Department of Economics and Business, Universitat Pompeu Fabra, revised May 2002.
  2. van Praag, Bernard M S & Hagenaars, Aldi J M & van Eck, Wim, 1983. "The Influence of Classification and Observation Errors on the Measurement of Income Inequality," Econometrica, Econometric Society, vol. 51(4), pages 1093-108, July.
  3. Ravallion, Martin, 1994. "Poverty rankings using noisy data on living standards," Economics Letters, Elsevier, vol. 45(4), pages 481-485, August.
  4. Atkinson, A B, 1987. "On the Measurement of Poverty," Econometrica, Econometric Society, vol. 55(4), pages 749-64, July.
  5. 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.
  6. Andrew Chesher & Christian Schluter, 2001. "Welfare measurement and measurement error," CeMMAP working papers CWP03/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2007. "An econometric method of correcting for unit nonresponse bias in surveys," Journal of Econometrics, Elsevier, vol. 136(1), pages 213-235, January.
  8. Surjit Bhalla, 2002. "Imagine There's No Country: Poverty, Inequality, and Growth in the Era of Globalization," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 348.
  9. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
  10. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  11. Nijman, Theo & Verbeek, Marno, 1992. "Nonresponse in Panel Data: The Impact on Estimates of a Life Cycle Consumption Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 243-57, July-Sept.
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