方法:经济学中的P-Hacking和因果推理

A. Brodeur, Nikolai Cook, A. Heyes
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引用次数: 34

摘要

经济学的“可信度革命”促进了使用差异中的差异(DID)、工具变量(IV)、随机对照试验(RCT)和回归不连续设计(RDD)方法来识别因果关系。读者应该在多大程度上相信关于结果的统计显著性的声明,对方法非常敏感。通过对2015年25家顶级经济学期刊报道的13440个假设检验的多种方法分析,我们发现选择性发表和p-hacking是使用DID和(特别是)IV的研究中的一个实质性问题。RCT和RDD的问题要小得多。在IV论文中,几乎有25%的边缘性显著结果是误导性的。
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Methods Matter: P-Hacking and Causal Inference in Economics
The economics 'credibility revolution' has promoted the identification of causal relationships using difference-in-differences (DID), instrumental variables (IV), randomized control trials (RCT) and regression discontinuity design (RDD) methods. The extent to which a reader should trust claims about the statistical significance of results proves very sensitive to method. Applying multiple methods to 13,440 hypothesis tests reported in 25 top economics journals in 2015, we show that selective publication and p-hacking is a substantial problem in research employing DID and (in particular) IV. RCT and RDD are much less problematic. Almost 25% of claims of marginally significant results in IV papers are misleading.
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