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Measuring Income in Household Panel Surveys for Germany: A Comparison of EU-SILC and SOEP

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  • Joachim R. Frick
  • Kristina Krell

Abstract

Empirical analyses of economic inequality, poverty, and mobility in Germany are, to an increas-ing extent, using microdata from the German Federal Statistical Office's contribution to the European Union Statistics on Income and Living Conditions (EU-SILC) as well as data from the German Socio-Economic Panel (SOEP). In addition to their significance for national reporting, the EU-SILC data are of great international significance for comparative EU-wide measurement, description, and analysis in support of the European Commission's stated objective of fighting poverty and reducing social inequality through the European social cohesion process. It is therefore crucial to assess the quality of the German contribution to EU-SILC, particularly in view of evidence in the literature of methodological problems in this still relatively young survey with respect to the representation of specific social groups and the distri-bution of key educational characteristics that can have a considerable impact on the degree and structure of inequality and poverty (see Hauser 2008, Causa et al. 2009, Nolan et al. 2009). While previous papers have critically examined the German EU-SILC contribution in comparison to the cross-sectional data from the German Survey of Income and Expenditure (EVS), the present paper compares EU-SILC-based results about income trends, inequality, and mobility with results based on SOEP, a widely used alternate panel survey of private households in Germany. The - in some cases severe - differences identified are discussed in the context of the surveying and interviewing methods, post-data-collection treatment of the micro-data as well as sample characteristics of the two studies, all of which exert a major influence on the substantive results and thus on the core findings regarding the social situation of Germany in EU-wide comparison.

Suggested Citation

  • 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).
  • Handle: RePEc:diw:diwsop:diw_sp265
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    References listed on IDEAS

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    Cited by:

    1. Leonardo Gasparini & Leopoldo Tornarolli, 2015. "A review of the OECD Income Distribution Database," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(4), pages 579-602, December.
    2. Xavier Timbeau & Ofce Observatoire Français Des Conjonctures Économiques, 2014. "From austerity to stagnation how to avoid the deflation trap," Post-Print hal-03603164, HAL.
    3. Naticchioni, Paolo & Ragusa, Giuseppe & Massari, Riccardo, 2014. "Unconditional and Conditional Wage Polarization in Europe," IZA Discussion Papers 8465, Institute of Labor Economics (IZA).
    4. Van Kerm, Philippe & Pi Alperin, Maria Noel, 2013. "Inequality, growth and mobility: The intertemporal distribution of income in European countries 2003–2007," Economic Modelling, Elsevier, vol. 35(C), pages 931-939.
    5. Xavier Timbeau & OFCE Observatoire français des conjonctures économiques, 2014. "From austerity to stagnation how to avoid the deflation trap: The independant annual growth survey 2014," Sciences Po publications info:hdl:2441/c5gs2rgi93a, Sciences Po.
    6. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and Inequality Measurement: A Comparative Analysis of Correction Methods Using the EU SILC Data," Econometrics, MDPI, vol. 6(2), pages 1-21, June.
    7. 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.
    8. Kvedaras, Virmantas & Cseres-Gergely, Zsombor, 2021. "China’s WTO accession and income inequality in European regions: External pressure and internal adjustments," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 34-53.
    9. Stefan Bach & Peter Haan & Richard Ochmann, 2013. "Taxation of Married Couples in Germany and the UK: One-Earner Couples Make the Difference," International Journal of Microsimulation, International Microsimulation Association, vol. 6(3), pages 3-24.
    10. David Johann & Markus Steinbrecher & Kathrin Thomas, 2020. "Channels of participation: Political participant types and personality," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-13, October.
    11. Bea Cantillon & Natascha Van Mechelen & Olivier Pintelon & Aaron Van den Heede, 2012. "Household Work Intensity and the Adequacy of Social Protection in the EU," Working Papers 1204, Herman Deleeck Centre for Social Policy, University of Antwerp.
    12. repec:hal:spmain:info:hdl:2441/c5gs2rgi93abt1s4jkeabou1 is not listed on IDEAS
    13. Benedetti, Ilaria & Crescenzi, Federico, 2023. "The role of income poverty and inequality indicators at regional level: An evaluation for Italy and Germany," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    14. Irena Antošová & Naďa Hazuchová & Jana Stávková, 2021. "Income situation of agricultural households of EU countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(4), pages 121-128.
    15. Vincent Corluy & Frank Vandenbroucke, 2012. "Individual Employment, Household Employment and Risk of Poverty in the EU. A Decomposition Analysis," Working Papers 1206, Herman Deleeck Centre for Social Policy, University of Antwerp.

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    More about this item

    Keywords

    Inequality; poverty; mobility; household panel; EU-SILC; SOEP;
    All these keywords.

    JEL classification:

    • D3 - Microeconomics - - Distribution
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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