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Dealing with Incomplete Household Panel Data in Inequality Research

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  • Joachim R. Frick
  • Markus M. Grabka
  • Olaf Groh-Samberg

Abstract

Population surveys around the world face the problem of declining cooperation and participation rates of respondents. Not only can item nonresponse and unit nonresponse impair important outcome measures for inequality research such as total household disposable income; there is also a further case of missingness confronting household panel surveys that potentially biases results. The approach commonly used in such surveys of interviewing all adult household members and aggregating their individual incomes to yield a final outcome measure for welfare analyses often suffers from partial unit non-response (PUNR), i.e., the non-response of at least one unit, or member, of an otherwise participating household. In these cases, the aggregate income of all household members lacks at least one individual's income. These processes are typically not random and require appropriate correction. Using data from more than twenty waves of the German Socio-Economic Panel (SOEP) we evaluate four different strategies to deal with this phenomenon: (a) Ignorance, i.e., assuming the missing individual's income to be zero. (b) Adjustment of the equivalence scale to account for differences in household size and composition. (c) Elimination of all households observed to suffer PUNR, and re-weighting of households observed to be at risk of but not affected by PUNR. (d) Longitudinal imputation of the missing income components. The aim of this paper is to show how the choice of technique affects substantive results in the inequality research. We find indications of substantial bias on income inequality and poverty as well as on income mobility. These findings are obviously even more important in cross-national comparative analyses if the data providers in the individual countries deal differently with PUNR in the underlying data.

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Bibliographic Info

Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 991.

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Length: 32 p.
Date of creation: 2010
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Handle: RePEc:diw:diwwpp:dp991

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Keywords: Household Panel Surveys; Partial Unit Non-Response; Inequality; Mobility; Imputation; SOEP;

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References

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  1. Joachim R. Frick & Markus M. Grabka, 2007. "Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," SOEPpapers on Multidisciplinary Panel Data Research 49, DIW Berlin, The German Socio-Economic Panel (SOEP).
  2. Markus M. Grabka & Joachim R. Frick, 2008. "The Shrinking German Middle Class: Signs of Long-Term Polarization in Disposable Income?," Weekly Report, DIW Berlin, German Institute for Economic Research, vol. 4(4), pages 21-27.
  3. Shorrocks, Anthony, 1978. "Income inequality and income mobility," Journal of Economic Theory, Elsevier, Elsevier, vol. 19(2), pages 376-393, December.
  4. repec:ese:iserwp:2008-42 is not listed on IDEAS
  5. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP): Scope, Evolution and Enhancements," SOEPpapers on Multidisciplinary Panel Data Research 1, DIW Berlin, The German Socio-Economic Panel (SOEP).
  6. 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.
  7. Arie Kapteyn & Pierre-Carl Michaud & James P. Smith & Arthur van Soest, 2006. "Effects of Attrition and Non-Response in the Health and Retirement Study," Working Papers, RAND Corporation Publications Department 407, RAND Corporation Publications Department.
  8. Jens Bonke & Hans Uldall-Poulsen, 2007. "Why do families actually pool their income? Evidence from Denmark," Review of Economics of the Household, Springer, Springer, vol. 5(2), pages 113-128, June.
  9. Frick, Joachim R. & Grabka, Markus M., 2003. "Imputed Rent and Income Inequality: A Decomposition Analysis for Great Britain, West Germany and the U.S," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 513-537.
  10. Daniel H. Hill & Robert J. Willis, 2001. "Reducing Panel Attrition: A Search for Effective Policy Instruments," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 416-438.
  11. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, Econometric Society, vol. 52(3), pages 761-66, May.
  12. Fields, Gary S & Ok, Efe A, 1999. "Measuring Movement of Incomes," Economica, London School of Economics and Political Science, London School of Economics and Political Science, vol. 66(264), pages 455-71, November.
  13. Smeeding, Timothy M & Weinberg, Daniel H, 2001. "Toward a Uniform Definition of Household Income," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(1), pages 1-24, March.
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Citations

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Cited by:
  1. Markus M. Grabka, 2013. "Codebook for the $PEQUIV File 1984-2012: CNEF Variables with Extended Income Information for the SOEP," Data Documentation 69, DIW Berlin, German Institute for Economic Research.
  2. Anthony Barnes Atkinson, 2010. "Macerata Lectures on European Economic Policy. Poverty and the EU: the New Decade," Working Papers, Macerata University, Department of Studies on Economic Development (DiSSE) 24-2010, Macerata University, Department of Studies on Economic Development (DiSSE), revised May 2010.
  3. Jaenichen, Ursula & Sakshaug, Joseph, 2012. "Multiple imputation of household income in the first wave of PASS," FDZ Methodenreport, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] 201202_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  4. Markus M. Grabka, 2011. "Codebook for the $PEQUIV File 1984-2010: CNEF Variables with Extended Income Information for the SOEP," Data Documentation 57, DIW Berlin, German Institute for Economic Research.
  5. Jan Goebel & Peter Krause & Joachim R. Frick & Markus M. Grabka & Gert G. Wagner, 2010. "Eine exemplarische Anwendung der regionalisierten Preisniveau-Daten des BBSR auf die Einkommensverteilung für die Jahre 2005 bis 2008," SOEPpapers on Multidisciplinary Panel Data Research 284, DIW Berlin, The German Socio-Economic Panel (SOEP).
  6. Markus M. Grabka, 2012. "Codebook for the $PEQUIV File 1984-2011: CNEF Variables with Extended Income Information for the SOEP," Data Documentation 65, DIW Berlin, German Institute for Economic Research.

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