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Dealing With Incomplete Household Panel Data in Inequality Research

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

Abstract

In trying to capture complete within-household heterogeneity, household panel surveys typically try to interview all adult household members. Following from this, such surveys tend to suffer from partial unit nonresponse (PUNR), that is, the nonresponse of at least one member of an otherwise participating household, most likely yielding an underestimation of aggregate household income. Using data from the German Socio-Economic Panel (SOEP), the authors evaluate four different strategies to deal with this phenomenon: (a) ignorance, that is, 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 reweighting of households observed to be at risk of but not affected by PUNR; and (d) longitudinal imputation of the missing income components. The aim of this article is to show how the choice of technique affects substantive results in inequality research. The authors find indications of substantial bias on income inequality and poverty as well as on income mobility.

Suggested Citation

  • Frick, Joachim R. & Grabka, Markus M. & Groh-Samberg, Olaf, 2012. "Dealing With Incomplete Household Panel Data in Inequality Research," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 41(1), pages 89-123.
    • Handle: RePEc:zbw:espost:68600
    DOI: 10.1177/0049124112440796
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    Cited by:

    1. 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.
    2. Anthony Barnes Atkinson, 2010. "Macerata Lectures on European Economic Policy. Poverty and the EU: the New Decade," Working Papers 24-2010, Macerata University, Department of Studies on Economic Development (DiSSE), revised May 2010.
    3. Hornykewycz, Anna & Kapeller, Jakob & Weber, Jan David & Schütz, Bernhard & Cserjan, Lukas, 2024. "Carbon neutrality in the residential sector: A general toolbox and the case of Germany," ifso working paper series 41, University of Duisburg-Essen, Institute for Socioeconomics (ifso).
    4. Coban, Mustafa & Sauerhammer, Sarah, 2017. "Transmission channels of intergenerational income mobility: Empirical evidence from Germany and the Unites States," Discussion Paper Series 138, Julius Maximilian University of Würzburg, Chair of Economic Order and Social Policy.
    5. Theresa Köhler, 2016. "Income and Wealth Poverty in Germany," SOEPpapers on Multidisciplinary Panel Data Research 857, DIW Berlin, The German Socio-Economic Panel (SOEP).
    6. repec:iab:iabfme:201202(en is not listed on IDEAS
    7. 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.
    8. Markus M. Grabka, 2014. "Codebook for the $PEQUIV File 1984-2013: CNEF Variables with Extended Income Information for the SOEP," Data Documentation 74, DIW Berlin, German Institute for Economic Research.
    9. Jonas Beste & Markus M. Grabka & Jan Goebel, 2018. "Armut in Deutschland [Poverty in Germany]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(1), pages 27-62, April.
    10. Jaenichen, Ursula & Sakshaug, Joseph, 2012. "Multiple imputation of household income in the first wave of PASS," FDZ Methodenreport 201202_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    11. Beatriz Larraz, 2015. "Decomposing the Gini Inequality Index," Sociological Methods & Research, , vol. 44(3), pages 508-533, August.
    12. 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).
    13. J. F. Muñoz & E. à lvarez-Verdejo & R. M. García-Fernández, 2018. "On Estimating the Poverty Gap and the Poverty Severity Indices With Auxiliary Information," Sociological Methods & Research, , vol. 47(3), pages 598-625, August.
    14. 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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    More about this item

    Keywords

    household panel surveys; partial unit nonresponse; inequality; mobility; imputation; SOEP;
    All these keywords.

    JEL classification:

    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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