Publications Based on SOEP Data: SOEPlit

Industrial Restructuring, Unemployment and Migration

Labour Responses to Taxes and Benefits in Germany

German Job Mobility and Wages

Migrant Ethnic Identity: Concept and Policy Implications

Gender Identity and Womens' Supply of Labor and Non-market Work: Panel Data Evidence for Germany

This paper aims to verify results of the innovative study on gender identity for the USA by Bertrand et al. (2015) for Germany. They found that women who would earn more than their husbands distort their labor market outcome in order not to violate traditional gender identity norms. Using data from the German Socio-economic Panel Study we also find that the distribution of the share of income earned ...

Forecasting Behavioural and Distributional Effects of the Bofinger-Walwei Model using Microsimulation

Since Germany's social assistance reform ("Hartz-IV-Reform") in 2005 there has been a strong increase in the number of working poor and long-term unemployed. This development is often attributed to the remaining disincentives of the reformed social assistance to take up a low-paid full time job. Therefore, several proposals have been worked out to reduce these disincentives. In this ...

Restricted likelihood ratio testing in linear mixed models with general error covariance structure

We consider the problem of testing for zero variance components in linear mixed models with correlated or heteroscedastic errors. In the case of independent and identically distributed errors, a valid test exists, which is based on the exact finite sample distribution of the restricted likelihood ratio test statistic under the null hypothesis. We propose to make use of a transformation to derive the ...

Gender Differences in Poverty: A Cross-National Study

Essays on Framing Effects in Experimental Economics

Voluntary Turnover: What We Measure and What It (Really) Means

In this paper, we run regression analyses to explain voluntary turnover intentions with data from more than 5,000 employees and with about 250 explanatory variables. The findings of our multi-factor approach highlight the fact that previous empirical research might have over-estimated the impact and significance of many factors. We show the relevance of the so-called omitted variable bias to our findings ...