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 Description

Summary: 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: p-hacking; publication bias; research methods; causal inference; p-curves

JEL Classification:
      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

Data Type(s): other

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Published Versions

V2 [2022-02-16]

V1 [2020-09-15]

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