Research

Can Being Competitive but Unsuccessful Harm You, Even More So If You Are a Woman? — with Simone Haeckl and Anita Zednik, Journal of Economic Behavior & Organisation (2025)

We investigate the fairness views of impartial spectators toward workers who behave competitively but are unsuccessful in a winner-take-all, real-effort task. In an online experiment with more than 5800 participants, spectators show significantly less concern for unsuccessful workers who voluntarily entered a competition for pay or behaved selfishly by trying to sabotage, compared to those who had to compete. We do not find evidence that women are punished more for competitive behavior than men, unless spectators have very strong gender norms. 

Read the paper 

Borrowed Plumes: The Gender Gap in Claiming Credit for Teamwork — with Klara Kinnl and Anna Walter-Dockx

Teamwork is prevalent in many forms of production, but individual contributions to team output are often ambiguous. We use a large-scale online experiment to investigate gender differences in claiming credit for contributions to teamwork with misaligned incentives: Team members have an incentive to exaggerate their contribution, but this harms the other team member. In this setting, we find that men claim to have contributed more than equally contributing women. Using two further between-subject treatments, we experimentally test and rule out gender differences in social preferences and in overconfidence as mechanisms for the gender claim-gap. Instead, we provide exploratory evidence that men and women place different cognitive weights on factors when deciding on their claim. Further, we show that the gender claim-gap is particularly pronounced for large claims and among high-contributors, which has potentially important consequences for gender equity in labour market outcomes.

Read the working paper 

Nudges for COVID-19 Vaccine Hesitant Population are Effective — with Martin Halla and Tobias Thomas

Vaccine hesitancy is a major public health challenge. In this paper, we provide evidence on the effectiveness of pre-booked COVID-19 vaccination appointments for vaccine-hesitant populations from a nationwide programme in Austria. We exploit two sources of exogenous variation: First, we make comparisons between residents in participating and non-participating states. Second, we use variation in timing of the appointments within states to identify the causal impact of the appointment. We find that the pre-booked appointment significantly increases the individual probability of vaccination. Our large and rich data allows us to explore heterogeneous treatment effects. We find that the intervention is particularly effective for individuals who are older, less educated, have lower income, or are foreigners. 

See the pre-registration 

The Dynamics and Spillovers of Management Interventions: A Comment on Bianchi and Giorcelli (2022) — with Gonçalo Lima, Marco Schmandt and Christian Westheide

Bianchi and Giorcelli (2022) study the long-term and spillover effects of a management intervention program on firm performance in the US, between 1940 and 1945. The authors find that the Training Within Industry (TWI) program led to positive effects which lasted for at least 10 years. Firm sales of treated firms increasedd by 5.3% in the first year after implementation, peaking at 21.7% after 8 years, before reducing to 16% gains after a decade. The authors claim that the program generated long-lasting changes in managerial practices. Finally, the program also led to positive spillover effects on the supply chain of treated firms. 

First, we reproduce the paper’s main findings. Second, we test the robustness of the results to (1) changing the main specification sample and (2) testing other difference-in-differences estimators, using the same data, provided by the authors. We find that the results are robust to these changes. All point estimates in the study remain statistically significant and of similar magnitude. 

While the paper’s finding reproduce and replicate, challenges in reproducing results we encountered lead us to recommend improvements to journals’ code policies.

Read the paper 

Mass Reproducibility and Replicability: A New Hope — see list of co-authors

This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.

Read the working paper