Working Papers
Restrictions to Civil Liberties in a Pandemic and Satisfaction with Democracy
With Daniel Graeber and Panu Poutvaara. [CESifo Working Paper No. 10875],R&R at European Journal of Political Economy
In times of crises, democracies face the challenge of balancing effective interventions with civil liberties. This study examines Germany’s response during the early stages of the COVID-19 pandemic, focusing on the interplay between civil liberties and public health goals. Using state-level variation in mobility restrictions, we employ a difference-in-differences design to show that stay-at-home orders notably increased satisfaction with democracy and shifted political support towards centrist parties. Individuals who were exposed to the authoritarian regime of the German Democratic Republic show the largest reactions, underscoring the endogeneity of preferences for state intervention.
Work in Progress
The Effect of Terror on Risk Attitudes
With Daniel Graeber and Neil Murray.Terrorism imposes high economic costs on the affected population, while the observable economic damage is usually small. Addressing this puzzle, we highlight a crucially overlooked aspect: costly behavioural responses. Based on a representative sample of the German population, we employ a staggered difference-in-differences (DiD) design that compares individuals living within the 25-kilometer radius of an attack with those who do not. Our results reveal that terror attacks are followed by an immediate and significant decline in exposed individuals’ risk propensity and risky behavior, such as stock market participation or self-employment. This effect is amplified by attack-related news reach and more negatively-toned news reporting. Additionally, we identify happiness as a potential mediator in the relationship between exposure to terror attacks and risk attitudes.
Work From Home, Stock Market Participation, and Inequality
With Lukas Menkhoff and Carsten Schröder. Stock market participation among working household heads jumped upwards in the year 2020, in Germany by about 25%. A major cause is the required use of work from home (WfH). We show this by repeating a benchmark study with demanding data requests and adding WfH to the explanatory variables. Moreover, we implement an instrumental variables estimation based on industry-specific levels of WfH-capacity. The transmission channels seem to work via increased available time and time flexibility. Moreover, we show that WfH makes the stock market accessible to a broader population, including lower income groups, which may contribute to lower income inequality.
Random Forests for Labor Market Analysis: Balancing Precision and Interpretability
With Daniel Graeber, Carsten Schröder and Sabine Zinn.Machine learning methods are becoming increasingly popular due to their predictive power. However, the results are sometimes not as straight-forward to interpret compared to classic regression models, for example. In this paper, we address this trade-off by comparing the predictive performance of random forests and logistic regressions to analyze labor market vulnerabilities during the COVID-19 pandemic, and a global surrogate model to enhance our understanding of the complex dynamics. Our study shows that especially in the presence of non-linearities and feature interactions, random forests outperform regressions both in predictive accuracy and interpretability, yielding policy-relevant insights on vulnerable groups affected by labor market disruptions.