Name File Type Size Last Modified
  code 02/16/2022 08:06:AM
  data 02/04/2022 09:24:AM
  environment 03/25/2021 11:08:AM
  metadata 03/25/2021 11:08:AM
.gitignore text/plain 7 bytes 03/25/2021 07:07:AM
Changelog.txt text/plain 2.7 KB 02/16/2022 03:07:AM
REPRODUCING.md text/x-web-markdown 2.1 KB 03/25/2021 07:07:AM

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:  View help for 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:  View help for Subject Terms p-hacking; publication bias; research methods; causal inference; p-curves
JEL Classification:  View help for 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
Time Period(s):  View help for Time Period(s) 1/1/2015 – 12/31/2018 (2015 and 2018)
Data Type(s):  View help for Data Type(s) other


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