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Computational Reproducibility and Robustness of Empirical Economics and Political Science Research Between 2022 and 2023
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Computational Reproducibility and Robustness of Empirical Economics and Political Science Research Between 2022 and 2023

Abel Brodeur, Derek Mikola, Nikolai Cook, Lenka Fiala, Thomas Brailey, Ryan Briggs, Alexandra de Gendre, Yannick Dupraz, Jacopo Gabani, Romain Gauriot, …
287
I4R Discussion Paper Series, 287, Leibniz Institute for Economic Research
2026-03

Abstract

Robustness Research Transparency Open Science Economics Political Science Reproduction
This systematic and large-scale reproduction effort tests the reproducibility and robustness of economics and political science. We reproduced original analyses and conducted robustness checks of 110 articles recently published in leading economics and political science journals (all of which have mandatory data and code sharing policies). We found that over 85% of published claims were computationally reproducible. In robustness checks, our re-analyses led to 72% of statistically significant estimates to remain significant and in the same direction, and the median reproduced effect size is (nearly) the same as the originally published effect size (that is, 99% of the published effect size). Additionally, six independent research teams examined 12 pre-specified hypotheses about determinants of robustness. Research teams with more experience found lower levels of robustness, and robustness correlated with neither author characteristics nor data availability.
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