Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics
分析了25本顶级经济学期刊中超过21,000个假设检验，发现不同因果识别方法（如工具变量法、双重差分法）的p值操纵和发表偏倚程度差异很大，工具变量法问题尤为严重，且顶级期刊、审稿流程和时间推移均未改善这一现象。
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 (i) papers published in the Top 5 journals are different to others; (ii) the journal “revise and resubmit” process mitigates the problem; (iii) things are improving through time.