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Estimating Income Poverty in the Presence of Missing Data and Measurement Error

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  • Cheti Nicoletti
  • Franco Peracchi
  • Francesca Foliano

Abstract

Reliable measures of poverty are an essential statistical tool for public policies aimed at reducing poverty. In this paper we consider the reliability of income poverty measures based on survey data which are typically plagued by missing data and measurement error. Neglecting these problems can bias the estimated poverty rates. We show how to derive upper and lower bounds for the population poverty rate using the sample evidence, an upper bound on the probability of misclassifying people into poor and non-poor, and instrumental or monotone instrumental variable assumptions. By using the European Community Household Panel, we compute bounds for the poverty rate in ten European countries and study the sensitivity of poverty comparisons across countries to missing data and measurement error problems. Supplemental materials for this article may be downloaded from the JBES website.

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Bibliographic Info

Paper provided by DIW Berlin, The German Socio-Economic Panel (SOEP) in its series SOEPpapers on Multidisciplinary Panel Data Research with number 252.

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Length: 30 p.
Date of creation: 2009
Date of revision:
Handle: RePEc:diw:diwsop:diw_sp252

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Keywords: Misclassification error; survey non-response; partial identification;

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References

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  1. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, Elsevier, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
  2. Charles F. Manski & John V. Pepper, 2009. "More on monotone instrumental variables," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 12(s1), pages S200-S216, 01.
  3. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, Econometric Society, vol. 68(4), pages 997-1012, July.
  4. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, Econometric Society, vol. 63(2), pages 281-302, March.
  5. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 9(1), pages 1-24, January.
  6. Horowitz, J.L. & Manski, C.F., 1995. "Censoring of Outcomes and Regressors Due to Survey Nonresponse: Identification and estimation Using Weights and Imputations," Working Papers, University of Iowa, Department of Economics 95-12, University of Iowa, Department of Economics.
  7. 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, Econometric Society, vol. 51(4), pages 1093-108, July.
  8. Juan Carlos Chavez-Martin del Campo, 2004. "Partial Identification of Poverty Measures with Contaminated Data," Econometric Society 2004 Latin American Meetings, Econometric Society 221, Econometric Society.
  9. Cheti Nicoletti & Franco Peracchi, 2006. "The effects of income imputation on microanalyses: evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, Royal Statistical Society, vol. 169(3), pages 625-646.
  10. Nicoletti, Cheti, 2003. "Poverty analysis with unit and item nonresponses: alternative estimators compared," ISER Working Paper Series 2003-20, Institute for Social and Economic Research.
  11. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, Elsevier, vol. 144(1), pages 81-117, May.
  12. Cowell, Frank A & Victoria-Feser, Maria-Pia, 1996. "Robustness Properties of Inequality Measures," Econometrica, Econometric Society, Econometric Society, vol. 64(1), pages 77-101, January.
  13. Kreider, Brent & Pepper, John V., 2007. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 102, pages 432-441, June.
  14. Nicoletti, Cheti & Peracchi, Franco, 2002. "A cross-country comparison of survey nonparticipation in the ECHP -ISER working paper-," ISER Working Paper Series 2002-32, Institute for Social and Economic Research.
  15. Vazquez-Alvarez, R. & Melenberg, B. & Soest, A.H.O. van, 1999. "Bounds on Quantiles in the Presence of Full and Partial Item Nonresponse," Discussion Paper, Tilburg University, Center for Economic Research 1999-38, Tilburg University, Center for Economic Research.
  16. Andrew Chesher & Christian Schluter, 2002. "Welfare Measurement and Measurement Error," Review of Economic Studies, Oxford University Press, vol. 69(2), pages 357-378.
  17. Ravallion, Martin, 1994. "Poverty rankings using noisy data on living standards," Economics Letters, Elsevier, Elsevier, vol. 45(4), pages 481-485, August.
  18. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
  19. Vazquez-Alvarez, R. & Melenberg, B. & Soest, A.H.O. van, 2001. "Nonparametric Bounds in the Presence of Item Nonresponse, Unfolding Brackets and Anchoring," Discussion Paper, Tilburg University, Center for Economic Research 2001-67, Tilburg University, Center for Economic Research.
  20. Biewen, Martin, 2002. "Bootstrap inference for inequality, mobility and poverty measurement," Journal of Econometrics, Elsevier, Elsevier, vol. 108(2), pages 317-342, June.
  21. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 12(3), pages 345-68, July.
  22. Pudney, Stephen & Francavilla, Francesca, 2006. "Income mis-measurement and the estimation of poverty rates: an analysis of income poverty in Albania," ISER Working Paper Series 2006-35, Institute for Social and Economic Research.
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Cited by:
  1. Donal O'Neill & Olive Sweetman, 2013. "Estimating Obesity Rates in Europe in the Presence of Self-Reporting Errors," Economics, Finance and Accounting Department Working Paper Series, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth n236-13.pdf, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
  2. Bruno Arpino & Elisabetta De Cao & Franco Peracchi, 2011. "Using panel data to partially identify HIV prevalence When HIV status is not missing at random," Working Papers, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi 048, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
  3. Diaz, Yadira & Pudney, Stephen, 2013. "Measuring poverty persistence with missing data with an application to Peruvian panel data," ISER Working Paper Series 2013-22, Institute for Social and Economic Research.
  4. Adrian Chadi, 2014. "Dissatisfied with Life or with Being Interviewed? Happiness and Motivation to Participate in a Survey," IAAEU Discussion Papers, Institute of Labour Law and Industrial Relations in the European Union (IAAEU) 201403, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
  5. O'Neill, Donal & Sweetman, Olive, 2013. "Estimating Obesity Rates in the Presence of Measurement Error," IZA Discussion Papers 7288, Institute for the Study of Labor (IZA).

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