This paper contributes to the empirical literature on the employment effects of minimum wages. We analysed the introduction of a statutory minimum wage in Germany in 2015 exploiting cross-sectional variation of the minimum wage affectedness. We construct two variables that measure the affectedness for approximately 300 state-industry combinations based on aggregate monthly income data. The estimation strategy consists of two steps. We test for (unidentified) structural breaks in a model with cross-section specific trends to control for state-industry specific developments prior to 2015. In a second step, we test whether the trend deviations are correlated with the minimum wage affectedness. To identify the minimum wage effect on employment, we assume that the minimum wage introduction is exogenous. Our results point towards a negative effect on marginal employment and a positive effect on socially insured employment. Furthermore, we analyse if the increase in socially insured employment is systematically related to the reduction of marginal employment but do not detect evidence.

This paper estimates the effect of a foreign funding shock to banks in Brazil after the collapse of Lehman Brothers in September 2008. Our robust results show that bank-specific shocks to Brazilian parent banks negatively affected lending by their individual branches and trigger real economic consequences in Brazilian municipalities: More affected regions face restrictions in aggregated credit and show weaker labor market performance in the aftermath which documents the transmission mechanism of the global financial crisis to local labor markets in emerging countries. The results represent relevant information for regulators concerned with the real effects of cross-border liquidity shocks.

We investigate firm outcomes after a major flood in Germany in 2013. We robustly find that firms located in the disaster regions have significantly higher turnover, lower leverage, and higher cash in the period after 2013. We provide evidence that the effects stem from firms that already experienced a similar major disaster in 2002. Overall, our results document a positive net effect on firm performance in the direct aftermath of a natural disaster.

Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers’ automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages.

This field experiment investigates the causal impact of mothers’ perceptions of gender norms on their employment attitudes and labor-supply expectations. We provide mothers of young children in Germany with information about the prevailing gender norm regarding maternal employment in their city. At baseline, over 70% of mothers incorrectly perceive this gender norm as too conservative. Our randomized treatment improves the accuracy of these perceptions, significantly reducing the share of mothers who misperceive gender norms as overly conservative. The treatment also shifts mothers’ own labor-market attitudes towards being more liberal – and we show that specifically the shifted attitude is a strong predictor of mothers’ future labor-market participation. Consistently, treated mothers are significantly more likely to plan an increase in their working hours one year ahead.

Im Koalitionsvertrag von CDU, CSU und SPD vom 7. Februar 2018 formuliert die neue Bundesregierung ihre rentenpolitischen Ziele. Diese sind vor dem Hintergrund der Bevölkerungsdynamik in Deutschland zu sehen. Ab dem Jahr 2020 wird sich die Altersstruktur der deutschen Bevölkerung deutlich verändern. In diesem Beitrag werden Simulationsrechnungen zu den Konsequenzen der rentenpolitischen Maßnahmen aus dem Koalitionsvertrag für die Finanzierung der gesetzlichen Rentenversicherung mit Hilfe eines Simulationsmodells dargestellt. Die im Koalitionsvertrag vorgesehenen Leistungsausweitungen verursachen langfristig Kosten in Höhe von etwa 2½ Prozentpunkten beim Beitragssatz zur gesetzlichen Rentenversicherung. Es werden ferner Maßnahmen – auch im Vergleich zu den Rentensystemen anderer Länder – diskutiert, mit denen der Anstieg des Beitragssatzes begrenzt werden könnte.

Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers’ automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages.