Research
Can Being Competitive but Unsuccessful Harm You, Even More So If You Are a Woman? — with Simone Haeckl and Anita Zednik
We investigate the fairness views of impartial spectators towards workers who act or communicate competitively but are unsuccessful in a winner-take-all real-effort task. In an online experiment with over 5,800 participants, spectators show significantly less concern toward unsuccessful workers who voluntarily entered a competition for pay, behaved selfishly, or communicated in a dominant tone. There are two main drivers behind the spectators’ changes in financial redistributions towards low earners: firstly, spectators hold workers more accountable when they behave competitively, and secondly, spectators dislike if a worker communicates in a dominant style. We further find that unsuccessful male workers are treated harsher than female workers when workers’ displayed competitiveness is low. However, this gender gap is diminished when workers acted competitively, and both genders are shown equally low concern.
Borrowed Plumes: The Gender Gap in Claiming Credit for Teamwork — with Klara Kinnl and Anna Walter-Dockx
We investigate gender differences in individual credit claiming for teamwork. In a large-scale online experiment, participants work on an interactive task in teams of two and subsequently report their subjective contribution to the teamwork. In three between-subject treatments, we incentivize participants to either i) state their beliefs about their contribution honestly, ii) to exaggerate their contribution, or iii) to exaggerate and thereby harm the other team member. Our setup allows us to distinguish between overconfidence and exaggeration with and without negative externalities, and to test whether there is a gender gap in credit claiming. We find that men and women both equally overestimate their contributions, but men exaggerate more than women: As soon as there is an incentive to exaggerate, men claim to have contributed more than women, even when exaggeration harms the team member. This gender gap in credit claiming is particularly pronounced among large claims and for high-contributors.
Assessing the Impact of an Invitation-Based COVID-19 Vaccination Campaign in Austria — with Martin Halla and Tobias Thomas
Towards the end of 2021, the Austrian government sent letters with a suggested appointment for COVID-vaccination to all unvaccinated Austrian residents. Austria is a federal state. The vaccine programs are organized on a federal state level. Not all states decided to participate in this program. This provides us with control units who did not receive a suggested appointment (treatment). Among the federal states who participated in the program, there is regional variation in the timing of the appointments. In this study, we aim to evaluate the effects of this campaign on vaccination take-up. We exploit two sources of exogenous variation. First, we can make comparisons between residents in participating and non-participating states. Second, we can exploit the variation in timing of the appointment depending on the ZIP-code to estimate the causal impact of the campaign. The main hypothesis we test is that the invitation to a vaccination appointment per letter increases the propensity of an individual to get vaccinated. Further, we test for heterogeneous effects within the Austrian population. Our aim is to identify those demographic groups for whom the invitation is particularly effective.
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.
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.