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American Economic Review Vol. 112 No. 9 2022

Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Reply

Abel Brodeur1; Nikolai Cook2; Anthony Heyes3

1 Department of Economics, University of Ottawa (email: ) · 2 Department of Economics, Wilfrid Laurier University (email: ) · 3 Department of Economics, University of Ottawa and University of Exeter Business School (email: )

open access

Abstract

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 Pütz (2022) apply a novel adjustment to address rounding errors. They successfully 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).

DOI
10.1257/aer.20220277
Volume
112
Issue
9
Pages
3137-3139
Language
en
Sources
openalex bibtex:phds-export.bib crossref

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