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Survey nonresponse and the distribution of income

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  • Korinek, Anton
  • Mistiaen, Johan A.
  • Ravallion, Martin

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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Bibliographic Info

Paper provided by The World Bank in its series Policy Research Working Paper Series with number 3543.

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Date of creation: 01 Mar 2005
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Handle: RePEc:wbk:wbrwps:3543

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Keywords: Governance Indicators; Poverty Impact Evaluation; Health Economics&Finance; Inequality; Economic Theory&Research;

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References

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  1. 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.
  2. Ravallion, Martin, 1994. "Poverty rankings using noisy data on living standards," Economics Letters, Elsevier, vol. 45(4), pages 481-485, August.
  3. Nijman, T.E. & Verbeek, M.J.C.M., 1992. "Non-response in panel data: The impact on estimates of a life cycle consumption function," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153282, Tilburg University.
  4. 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.
  5. Lee Lillard & James P. Smith & Finis Welch, 2004. "What Do We Really Know About Wages: The Importance of Nonreporting and Census Imputation," Labor and Demography 0404005, EconWPA.
  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, 2005. "An econometric method of correcting for unit nonresponse bias in surveys," Policy Research Working Paper Series 3711, The World Bank.
  8. Xavier Sala-i-Martin, 2002. "The World Distribution of Income (estimated from Individual Country Distributions)," NBER Working Papers 8933, National Bureau of Economic Research, Inc.
  9. 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.
  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. Atkinson, A B, 1987. "On the Measurement of Poverty," Econometrica, Econometric Society, vol. 55(4), pages 749-64, July.
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