Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Reply
成果类型：
Article
署名作者：
Brodeur, Abel; Cook, Nikolai; Heyes, Anthony
署名单位：
University of Ottawa; Wilfrid Laurier University; University of Ottawa
刊物名称：
AMERICAN ECONOMIC REVIEW
ISSN/ISSBN：
0002-8282
DOI：
10.1257/aer.20220277
发表日期：
2022
页码：
3137-3139
关键词：
摘要：
In Brodeur, Cook, and Heyes (2020) we present evidence that instrumental variable (and to a lesser extent difference-in -difference) articles are more p-hacked than randomized controlled trial and regression discontinuity design articles. We also find no evidence that (i) articles published in the top five journals are different; (ii) the revise and resubmit process mitigates the problem; (iii) things are improving through time. Kranz and Putz (2022) apply a novel adjustment to address rounding errors. They success-fully replicate our results with the exception of our shakiest finding: after adjusting for rounding errors, bunching of test statistics for difference-in-difference articles is now smaller around the 5 percent level (and coincidentally larger at the 10 percent level).
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