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Frick, Joachim R.
Krell, Kristina
Year of Publication: 
Series/Report no.: 
SOEPpapers on Multidisciplinary Panel Data Research 265
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.
household panel
Document Type: 
Working Paper

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