What's the Difference?! Gender, Personality, and the Propensity to Start a Business

Women start fewer businesses than men. The start-up rate among women in Germany falls short of males' start-up rate by one third. We scrutinize this gender gap using individual-level data from the KfW Start-up Monitor, a large-scale population survey on start-up activity in Germany. As a unique feature, the data combine socio-demographic characteristics, entrepreneurship-related attitudes, and general personality traits of both business starters and non-starters. Estimating binary choice models and employing decomposition techniques, we find that gender differences in socio-demographics alone would even be in favor of higher start-up rates among women, while the distribution of personality traits is less favorable for business start-ups among women and explains about one third of the entire gender difference. Most substantially, men opt for a start-up more often even given identical human capital and related endowments. Qualificational policies targeted towards higher educational attainments of potential entrepreneurs do thus not suffice to increase the number of female business starters.entrepreneurship, gender difference, start-up propensity, decomposition analysis, KfW Start-up Monitor, Germany

Benchmarking regions: estimating the counterfactual distribution of labor market outcomes

This paper develops and implements a new benchmarking approach for labor market regions. Based on panel data for regions, we use nonparametric matching techniques to account for observed labor market characteristics and for spatial proximity. As the benchmark, we estimate the counterfactual distribution of labor market outcomes for a region based on outcomes of similar regions. This allows to measure both the rank (relative performance) and the absolute performance based on the actual outcome for a region. Our outcome variable of interest is the hiring rate among the unemployed. We implement different similarity measures to account for differences in labor market conditions and spatial proximity, and we choose the tuning parameters in our matching approach based on a cross-validation procedure. The results show that both observed labor market characteristics and spatial proximity are important features to successfully match regions. Specifically, the modified Zhao (2004) distance measure and geographic distance in logs work best in our applications. Our estimated performance measures remain quite stable over time

End-of-year spending and the long-run employment effects of training programs for the unemployed

This study re-estimates the employment effects of training programs for the unemployed using exogenous variation in participation caused by budget rules in Germany in the 1980s and early 1990s, resulting in the infamous "end-of-year spending". In addition to estimating complier effects with 2SLS, we implement a exible control-function approach to obtain the average treatment effect on the treated (ATT). Our findings are: Participants who are only selected for budgetary reasons do not benefit from training programs. However, the ATT estimates suggest modest positive effects in the long run. Longer programs are more effective than shorter and more practice-oriented programs