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

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  • Nicoletti, Cheti
  • Peracchi, Franco
  • Foliano, Francesca

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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  • Nicoletti, Cheti & Peracchi, Franco & Foliano, Francesca, 2011. "Estimating Income Poverty in the Presence of Missing Data and Measurement Error," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 61-72.
    • Handle: RePEc:bes:jnlbes:v:29:i:1:y:2011:p:61-72
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    1. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    2. Andrew Chesher & Christian Schluter, 2002. "Welfare Measurement and Measurement Error," Review of Economic Studies, Oxford University Press, vol. 69(2), pages 357-378.
    3. Juan Carlos Chavez-Martin del Campo, 2004. "Partial Identification of Poverty Measures with Contaminated Data," Econometric Society 2004 Latin American Meetings 221, Econometric Society.
    4. 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.
    5. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    6. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    7. 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, vol. 102, pages 432-441, June.
    8. Cowell, Frank A & Victoria-Feser, Maria-Pia, 1996. "Robustness Properties of Inequality Measures," Econometrica, Econometric Society, vol. 64(1), pages 77-101, January.
    9. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    10. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    11. 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, vol. 9(1), pages 1-24, January.
    12. 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, vol. 169(3), pages 625-646, July.
    13. Ravallion, Martin, 1994. "Poverty rankings using noisy data on living standards," Economics Letters, Elsevier, vol. 45(4), pages 481-485, August.
    14. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
    15. 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.
    16. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    17. 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.
    18. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 2001. "Nonparametric Bounds in the Presence of Item Nonresponse, Unfolding Brackets and Anchoring," Other publications TiSEM cb4befff-4232-459b-ab68-2, Tilburg University, School of Economics and Management.
    19. Biewen, Martin, 2002. "Bootstrap inference for inequality, mobility and poverty measurement," Journal of Econometrics, Elsevier, vol. 108(2), pages 317-342, June.
    20. 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 1093-1108, July.
    21. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
    22. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    23. 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.
    24. Charles F. Manski & John V. Pepper, 2009. "More on monotone instrumental variables," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 200-216, January.
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    Cited by:

    1. Margaret M. C. Thomas, 2022. "Longitudinal Patterns of Material Hardship Among US Families," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 341-370, August.
    2. Nic Baigrie & Katherine Eyal, 2014. "An Evaluation of the Determinants and Implications of Panel Attrition in the National Income Dynamics Survey (2008-2010)," South African Journal of Economics, Economic Society of South Africa, vol. 82(1), pages 39-65, March.
    3. Ayllón, Sara & Fusco, Alessio, 2017. "Are income poverty and perceptions of financial difficulties dynamically interrelated?," Journal of Economic Psychology, Elsevier, vol. 61(C), pages 103-114.
    4. Battistin, Erich & De Nadai, Michele & Vuri, Daniela, 2017. "Counting rotten apples: Student achievement and score manipulation in Italian elementary Schools," Journal of Econometrics, Elsevier, vol. 200(2), pages 344-362.
    5. Pudney, Stephen & Diaz, Yadira, 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.
    6. Zachary Parolin, 2019. "The Effect of Benefit Underreporting on Estimates of Poverty in the United States," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 869-898, July.
    7. 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 048, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    8. Adrian Chadi, 2019. "Dissatisfied with life or with being interviewed? Happiness and the motivation to participate in a survey," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 519-553, October.
    9. Donal O'Neill & Olive Sweetman, 2013. "Estimating Obesity Rates in Europe in the Presence of Self-Reporting Errors," Economics Department Working Paper Series n236-13.pdf, Department of Economics, National University of Ireland - Maynooth.
    10. Zhang, Lixuan & Yencha, Christopher, 2022. "Examining perceptions towards hiring algorithms," Technology in Society, Elsevier, vol. 68(C).
    11. Srini Vasan & Adelamar Alcantara, 2016. "GIS-based Methods for Estimating Missing Poverty Rates & Projecting Future Rates in Census Tracts," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 1-13, August.
    12. Maria Michela Dickson & Giuseppe Espa & Lorenzo Fattorini & Flavio Santi, 2022. "Double-calibration estimators accounting for under-coverage and nonresponse in socio-economic surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1273-1288, December.
    13. Firouzeh Noghrehchi & Jakub Stoklosa & Spiridon Penev, 2020. "Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables," Computational Statistics, Springer, vol. 35(3), pages 1291-1317, September.
    14. Mark Brooks & Rattiya S. Lippe & Hermann Waibel, 2020. "Comprehensive data quality studies as a component of poverty assessments," TVSEP Working Papers wp-019, Leibniz Universitaet Hannover, Institute of Development and Agricultural Economics, Project TVSEP.
    15. Fikri Lahafi & Agus Muchsin & Syahriyah Semaun & Zalina Abdul Rahim, 2019. "Development of Creative Industries Training Towards Sharia Economic Empowerment In Bilalangnge Community, Parepare City, South Sulawesi," Malaysian E Commerce Journal (MECJ), Zibeline International Publishing, vol. 3(2), pages 33-35, August.
    16. Yang Ou & Jiang Bin & Sung Kim Jun & Li Chuhui, 2018. "Social Network Structure and Risk Sharing in Villages," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 18(3), pages 1-7, July.
    17. Donal O’Neill & Olive Sweetman, 2016. "Bounding obesity rates in the presence of self-reporting errors," Empirical Economics, Springer, vol. 50(3), pages 857-871, May.

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