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Project Citation: 

Kranz, Sebastian, and Pütz, Peter. Data and Code for: Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Comment. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-08-23. https://doi.org/10.3886/E159221V1

Project Description

Summary:  View help for Summary Brodeur, Cook, and Heyes (2020) study hypothesis tests from economic articles and fi nd evidence for p-hacking and publication bias, in particular for IV and DID studies. When adjusting for rounding errors (introducing a novel method), statistical evidence for p-hacking from randomization tests and caliper tests at the 5% signi ficance threshold vanishes for DID studies but remains for IV studies. Results at the 1% and 10% significance thresholds remain largely similar. In addition, Brodeur, Cook, and Heyes derive latent distributions of z-statistics absent publication bias using two di fferent approaches. We establish for each approach a result that challenges its applicability.


Scope of Project

Subject Terms:  View help for Subject Terms p-hacking; publication bias ; research methods ; causal inference; rounding; replication
JEL Classification:  View help for JEL Classification
      A14 Sociology of Economics
      B41 Economic Methodology
      C12 Hypothesis Testing: General
      C40 Econometric and Statistical Methods: Special Topics: General
      C52 Model Evaluation, Validation, and Selection
Time Period(s):  View help for Time Period(s) 1/1/2015 – 12/31/2018 (2015 and 2018)


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