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Longitudinal Wealth Data and Multiple Imputation: An Evaluation Study

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  • Westermeier, Christian
  • Grabka, Markus M.
Abstract
Statistical analysis in surveys is generally facing missing data. In longitudinal studies for some missing values there might be past or future data points available. The question arises how to successfully transform this advantage into improvedimputation strategies. In a simulation study the authors compare six combinations of cross-sectional and longitudinal imputation strategies for German wealth panel data. The authors create simulation data sets by blanking out observed data points: they induce item non response by a missing at random (MAR) and two differential non-response (DNR) mechanisms. We test the performance of multiple imputation using chained equations (MICE), an imputation procedure for panel data known as the row-and-column method and a regression prediction with correction for sample selection. The regression and MICE approaches serve as fallback methods, when only cross-sectional data is available. The row-and-column method performs surprisingly well considering the cross-sectional evaluation criteria. For trend estimates and the measurement of inequality, combining MICE with the row-and-column technique regularly improves the results based on a catalogue of six evaluation criteria including three separate inequality indices. As for wealth mobility, two additional criteria show that a model based approach such as MICE might be the preferable choice. Overall the resultsshow that if the variables, which ought to be imputed, are highly skewed, the row-and-column technique should not be dismissed beforehand.

Suggested Citation

  • Westermeier, Christian & Grabka, Markus M., 2016. "Longitudinal Wealth Data and Multiple Imputation: An Evaluation Study," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(3), pages 237-252.
    • Handle: RePEc:zbw:espost:180907
    DOI: 10.18148/srm/2016.v10i3.6387
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    References listed on IDEAS

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    1. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, September.
    2. Joachim R. Frick & Markus M. Grabka & Jan Marcus, 2007. "Editing and Multiple Imputation of Item-Non-Response in the 2002 Wealth Module of the German Socio-Economic Panel (SOEP)," Data Documentation 18, DIW Berlin, German Institute for Economic Research.
    3. Philip Vermeulen, 2018. "How Fat is the Top Tail of the Wealth Distribution?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 357-387, June.
    4. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 300-301, July.
    5. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
    6. Joachim R. Frick & Markus M. Grabka & Jan Marcus, 2010. "Editing und Multiple Imputation der Vermögensinformation 2002 und 2007 im SOEP," Data Documentation 51, DIW Berlin, German Institute for Economic Research.
    7. Rubin, Donald B, 1986. "Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 87-94, January.
    8. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
    9. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    10. Uhrig, S.C. Noah & Bryan, Mark L. & Budd, Sarah, 2012. "UKHLS Innovation Panel household wealth questions: preliminary analysis," Understanding Society Working Paper Series 2012-01, Understanding Society at the Institute for Social and Economic Research.
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