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Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective


  • Joachim R. Frick
  • Markus M. Grabka


Using data on annual individual labor income from three representative panel datasets (German SOEP, British BHPS, Australian HILDA) we investigate a) the selectivity of item non-response (INR) and b) the impact of imputation as a prominent post-survey means to cope with this type of measurement error on prototypical analyses (earnings inequality, mobility and wage regressions) in a cross-national setting. Given the considerable variation of INR across surveys as well as the varying degree of selectivity build into the missing process, there is substantive and methodological interest in an improved harmonization of (income) data production as well as of imputation strategies across surveys. All three panels make use of longitudinal information in their respective imputation procedures, however, there are marked differences in the implementation. Firstly, although the probability of INR is quantitatively similar across countries, our empirical investigation identifies cross-country differences with respect to the factors driving INR: survey-related aspects as well as indicators accounting for variability and complexity of labor income composition appear to be relevant. Secondly, longitudinal analyses yield a positive correlation of INR on labor income data over time and provide evidence of INR being a predictor of subsequent unit-non-response, thus supporting the “cooperation continuum” hypothesis in all three panels. Thirdly, applying various mobility indicators there is a robust picture about earnings mobility being significantly understated using information from completely observed cases only. Finally, regression results for wage equations based on observed (“complete case analysis”) vs. all cases and controlling for imputation status, indicate that individuals with imputed incomes, ceteris paribus, earn significantly above average in SOEP and HILDA, while this relationship is negative using BHPS data. However, once applying the very same imputation procedure used for HILDA and SOEP, namely the “row-and-columnimputation” approach suggested by Little & Su (1989), also to BHPS-data, this result is reversed, i.e., individuals in the BHPS whose income has been imputed earn above average as well. In our view, the reduction in crossnational variation resulting from sensitivity to the choice of imputation approaches underscores the importance of investing more in the improved cross-national harmonization of imputation techniques.

Suggested Citation

  • 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).
  • Handle: RePEc:diw:diwsop:diw_sp49

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    References listed on IDEAS

    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. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Denise Hawkes & Ian Plewis, 2006. "Modelling non-response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491.
    8. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
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    Cited by:

    1. Michael Ziegelmeyer, 2013. "Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 49-76, January.
    2. Katja Landau & Stephan Klasen & Walter Zucchini, 2012. "Measuring Vulnerability to Poverty Using Long-Term Panel Data," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 118, Courant Research Centre PEG.
    3. Ute Hanefeld & Jürgen Schupp, 2008. "Die ersten sechs Wellen des SOEP: das Panelprojekt in den ersten Jahren 1983-1989," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 77(3), pages 27-42.
    4. Michael Ziegelmeyer, 2009. "Documentation of the logical imputation using the panel structure of the 2003-2008 German SAVE Survey," MEA discussion paper series 09173, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    5. Frick, Joachim R. & Grabka, Markus M. & Groh-Samberg, Olaf, 2012. "Dealing With Incomplete Household Panel Data in Inequality Research," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 89-123.
    6. Ute Hanefeld & Jürgen Schupp, 2008. "The First Six Waves of SOEP: The Panel Project in the Years 1983 to 1989," SOEPpapers on Multidisciplinary Panel Data Research 146, DIW Berlin, The German Socio-Economic Panel (SOEP).
    7. Ernst Fehr, 2009. "On The Economics and Biology of Trust," Journal of the European Economic Association, MIT Press, pages 235-266.
    8. Carsten Kuchler & Martin Spiess, 2009. "The data quality concept of accuracy in the context of publicly shared data sets," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 3(1), pages 67-80, June.
    9. S. Anger & J. R. Frick & J. Goebel & M. M. Grabka & O. Groh-Samberg & H. Haas & E. Holst & P. Krause & M. Kroh & H. Lohmann & R. Pischner & J. Schupp & I. Sieber & T. Siedler & C. Schmitt & C. K. Spie, 2008. "Zur Weiterentwicklung von SOEPsurvey und SOEPservice," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 77(3), pages 157-177.
    10. Joachim R. Frick & Kristina Krell, 2010. "Measuring Income in Household Panel Surveys for Germany: A Comparison of EU-SILC and SOEP," SOEPpapers on Multidisciplinary Panel Data Research 265, DIW Berlin, The German Socio-Economic Panel (SOEP).
    11. Frick, Joachim R. & Jenkings, Stephen P. & Lillard, Dean R. & Lipps, Oliver & Wooden, Mark, 2007. "The Cross-National Equivalent File (CNEF) and Its Member Country Household Panel Studies," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 627-654.

    More about this item


    Item non-response; imputation; income inequality; income mobility; panel data; SOEP; BHPS; HILDA;

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution

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