We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretation of a policy question—affect the variation in estimated treatment effects. A total of 146 research teams each completed the same causal inference task three times each: first with few constraints, then using a shared research design, and finally with pre-cleaned data in addition to a specified design. We find that even when analyzing the same data, teams reach different conclusions. In the first stage, the interquartile range (IQR) of the reported policy effect was 3.1 percentage points, with substantial outliers. Surprisingly, the second stage, which restricted research design choices, exhibited slightly higher IQR (4.0 percentage points), largely attributable to imperfect adherence to the prescribed protocol. By contrast, the final stage, featuring standardized data cleaning, narrowed variation in estimated effects, achieving an IQR of 2.4 percentage points. Reported sample sizes also displayed significant convergence under more restrictive conditions, with the IQR dropping from 295,187 in the first stage to 29,144 in the second, and effectively zero by the third. Our findings underscore the critical importance of data cleaning in shaping applied microeconomic results and highlight avenues for future replication efforts.

This paper investigates the causal effect of the term length of political executives on economic policy outcomes. To establish causality, we exploit the staggered adoption of four-year terms for governors across US states, using data for the period 1937–2008. We find that increasing governors’ tenure in office from two years to four years reduced state expenditures and revenues by approximately 0.3–0.5 percentage points of GDP. The effect on state finances is primarily driven by a reduction of current spending and grants from the federal government, and it is concentrated in states where the incumbent governor expects fierce competition in the next election. Lastly, we discuss the implications of longer terms for macroeconomic stabilization, political budget cycles, and intergovernmental resource allocation

We conduct an online survey across four countries of the European Union (Germany, Ireland, Poland, and Spain) to study how the socio-economic determinants of their citizens condition their ability to detect fake headlines and their likelihood of sharing them using social media. Additionally, we analyze the impact of attitudinal and ideological variables on the probability of detecting (and sharing) fake news. Results point to a significant role of some socio-economic and political variables in determining both the probability of detecting and sharing fake news on social media; results also show interesting country heterogeneity. Political headlines are more likely to be misclassified, which underscores the challenge of overcoming ideological biases in media consumption. We highlight the importance of fostering digital literacy, especially among young and more vulnerable individuals, to promote responsible democratic citizenship.

October 7, 2025 – Room 1038 – 14.30h