I am a Ph.D. candidate in Economics at the University of Mannheim. Before joining the University of Munich as an assistant professor next year, I will spend one year as a Postdoc at the University of Zurich starting this fall.
My research studies the causes and consequences of socioeconomic inequalities using both structural models, reduced-form techniques and micro data from a variety of sources.
In my job market paper, I construct and estimate a rich search-matching model in order to investigate how employment, output and welfare respond to raising the minimum wage beyond observed levels, as is being discussed in many developed countries.
Also take a look at my other papers where I use novel personnel data to study the role of (male) managers for gender gaps (with Felix Holub), and investigate the link between rising income inequality and the household debt boom in the US (with Fabian Greimel).
You can download my CV here.
Macroeconomics Labor Economics Inequality Urban Economics Computational Economics
Tom Krebs Michèle Tertilt Sebastian Siegloch Andreas Peichl
Job Market Paper
Many countries are discussing substantial increases in the minimum wage. However, policy makers lack a comprehensive analysis of the macroeconomic implications of raising the minimum wage. This paper investigates how employment, output and welfare respond to increases in the minimum wage beyond observable levels, both in the short- and long run. To that end, I incorporate endogenous job search effort, differences in employment levels, and a progressive tax-transfer system into a search-matching model with worker and firm heterogeneity. I estimate my model using German administrative and survey data. The model can capture the muted employment response, as well as the reallocation effects in terms of productivity and employment levels found by reduced form research on the German introduction of a federal minimum wage in 2015. Simulating the model, I find that long-run employment increases slightly until the minimum wage is equal to 60% of the full-time median wage (Kaitz index) as higher search effort offsets lower vacancy posting. In addition, raising the minimum wage reallocates workers towards full-time jobs and high-productivity firms. Total hours worked and output peak at Kaitz indices of 73% and 79%. However, policy makers face an important inter-temporal trade-off as large minimum wage hikes lead to substantial job destruction, unemployment and recessions in the short-run. Finally, not all workers benefit equally from higher minimum wages. For women, who often rely on low-hours jobs, the disutility from working longer hours outweighs the utility of higher incomes. Moreover, high minimum wages force low-skill workers into long-term unemployment.
with Felix Holub
Abstract: This paper investigates the contribution of managers to gender gaps and analyzes whether the over-representation of men in management positions puts women at a disadvantage. Relying on personnel data from one of the largest European manufacturing firms, we separate out the factors explaining gender gaps. Adjusted pay gaps are positive, which means that men earn more than observationally equivalent women. A significant share of pay gaps can be explained by the sorting of men and women to different managers. More importantly, gender gaps in bonus payments causally depend on the manager's gender. Accounting for worker and manager heterogeneity, bonus gaps are larger when the manager is male. This is driven by the fact that performance ratings are more favorable to men if handed out by a male manager. We present suggestive evidence that the relevance of manager gender for pay gaps is driven by discrimination rather than same-gender complementarities in productivity. However, independent of the root cause of these differences in evaluations by manager gender, the findings imply that a lower number of female managers increases gender gaps and thus constitutes a structural disadvantage for women.
with Fabian Greimel
Abstract: We evaluate the hypothesis that rising inequality was a causal source of the US household debt boom since 1980. The mechanism builds on the observation that households care about their social status. To keep up with the ever richer Joneses, the middle class substitutes status-enhancing houses for status-neutral consumption. These houses are mortgage-financed, creating a debt boom across the income distribution. Using a stylized model we show analytically that aggregate debt increases as top incomes rise. In a quantitative general equilibrium model we show that Keeping up with the Joneses and rising income inequality generate 60% of the observed boom in mortgage debt and 50% of the house price boom. We compare this channel to two competing mechanisms. The Global Saving Glut hypothesis gives rise to a similar debt boom, but does not generate a house prices boom. Loosening collateral constraints does not generate booms in either debt or house prices. Finally, we provide novel empirical evidence on the relationship between top incomes and household debt. Mortgage debt rose substantially more in US states that experienced stronger growth in top incomes. There is no such relationship between top incomes and non-mortgage debt. These findings support to the importance of the comparisons channel.
Work in Progress
Do Housing Booms Drive Up Socioeconomic Segregation?
Income Risk - How Do Labor and Business Income Differ?
with Andreas Peichl and Kai D. Schmid