Working Papers
“Dynamically Optimal Treatment Allocation” (with Karun Adusumilli and Friedrich Geiecke)
How should we assign candidates to job training - or, more generally, any treatment? In practice, individuals often arrive sequentially and the planner faces various constraints such as limited budget/capacity, borrowing constraints, or the need to place people in a queue. In such settings involving inter-temporal trade-offs, previous work on devising optimal policy rules in a static context is either not applicable, or is sub-optimal. We show how one can use offline observational data to estimate an optimal policy rule that maximizes expected welfare in this dynamic context. We allow the class of policy rules to be restricted for legal, ethical or incentive compatibility reasons. The problem is equivalent to one of optimal control under a constrained policy class and we exploit recent developments in Reinforcement Learning to propose an algorithm to solve this. We also characterize the statistical regret and find that it decays at a n-1/2 rate in most examples; this is the same rate as in the static case.
Reject and Resubmit, American Economic Review
“How Selectivity Shapes Selection”
This field experiment investigates how stressing selectivity at career information events affects the diversity, size, and quality of the applicant pool. While the total number of applications is not affected by stressing selectivity, it discourages female participants and children of migrants from applying, implying a "diversity cost". Treated participants perceive their (also treated) peers to behave more competitively at the event. In groups where selectivity is stressed, male participants are noticed more often by the company-staff as desirable applicants by showing interest and participating actively. In contrast, I find the opposite treatment-effect for female participants. I find no significant effect on the applicants’ perception of the work environment or the quality of the applicant pool. If anything, suggestive evidence points to female applicants being less qualified if they have been subject to treatment.
Draft available on request
“Hate Crime after the Brexit Vote: Heterogeneity Analysis based on a Universal Treatment”
I investigate the change in hate crimes targeting the victim's race or religion after the Brexit vote. My results reveal a substantial and transitory increase in such crimes following the vote. The central focus of my analysis is the considerable spatial heterogeneity of this increase. Areas with a greater increase in hate crime are characterized by both a greater immigrant share, and higher income proxies. Differences in unemployment rates do not significantly contribute to the observed variance. More specifically, parsimonious linear prediction models show the shares of recent immigrants and people with formal qualifications as key predictors of the hate crime increase. My findings are consistent with treating the Brexit vote as an update of expected social sanctions to hate offenders. Issues of multiple hypothesis testing and model selection limit the use of classic methods; therefore I apply and adapt recent machine learning methods as well.
Reject and Resubmit, European Economic Review
Work in Progress
“Trying out Counter-Stereotypical Jobs: Evidence from Apprenticeships” (with Anne Brenøe, Alexia Delfino, and Stefan Wolter)
In Switzerland, more than half of the people do a three- to four-year apprenticeship after secondary school. Virtually all students inform themselves via trial apprenticeships during which they can try a job for 1 to 3 days. Even though boys and girls perform similarly in secondary school, their choice of apprenticeships - and subsequent occupations - differ massively. Girls are often found in health care occupations like nursing, while boys predominantly opt for technical jobs like computer science. When choices follow stereotypes, society misses out on a potentially great number of female engineers and male nurses. We will conduct a randomized controlled trial (RCT) to explore whether encouraging teenagers to try out jobs, which are uncommon for their own gender (“counter-stereotypical”), can help them make more informed choices. Further, we aim to analyze if this leads to a better match between adolescents’ talents and the apprenticeships they choose.
Data collection in progress