Data and Code for: Methods Matter: P-Hacking and Publication Bias in Causal Analysis in Economics
Principal Investigator(s): View help for Principal Investigator(s) Abel Brodeur, University of Ottawa; Nikolai Cook, University of Ottawa; Anthony Heyes, University of Ottawa
Version: View help for Version V2
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Project Citation:
Brodeur, Abel, Cook, Nikolai, and Heyes, Anthony. Data and Code for: Methods Matter: P-Hacking and Publication Bias in Causal Analysis in Economics. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-02-16. https://doi.org/10.3886/E120246V2
Project Description
Summary:
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The credibility revolution in economics has promoted causal identification using randomized control trials (RCT), difference-in-differences (DID), instrumental variables (IV) and regression discontinuity design (RDD). Applying multiple approaches to over 21,000 hypothesis tests published in 25 leading economics journals we find that the extent of p-hacking and publication bias varies greatly by method. IV (and to a lesser extent DID) are particularly problematic. We find no evidence that: (1) Papers published in the `Top 5' journals are different to other; (2) The journal revise and resubmit process mitigates the problem; (3) Things are improving through time.
Scope of Project
Subject Terms:
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p-hacking;
publication bias;
research methods;
causal inference;
p-curves
JEL Classification:
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A11 Role of Economics; Role of Economists; Market for Economists
B41 Economic Methodology
C13 Estimation: General
C40 Econometric and Statistical Methods: Special Topics: General
I23 Higher Education; Research Institutions
A11 Role of Economics; Role of Economists; Market for Economists
B41 Economic Methodology
C13 Estimation: General
C40 Econometric and Statistical Methods: Special Topics: General
I23 Higher Education; Research Institutions
Time Period(s):
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1/1/2015 – 12/31/2018 (2015 and 2018)
Data Type(s):
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other
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