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Methods Matter: P-Hacking and Causal Inference in Economics

dc.contributor.authorBrodeur, Abel
dc.contributor.authorCook, Nikolai
dc.contributor.authorHeyes, Anthony
dc.date.accessioned2020-04-06T15:59:05Z
dc.date.available2020-04-06T15:59:05Z
dc.date.issued2018
dc.description.abstractThe 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.en_US
dc.identifier.urihttp://hdl.handle.net/10393/40324
dc.identifier.urihttps://doi.org/10.20381/ruor-24557
dc.language.isoenen_US
dc.subjectresearch methodsen_US
dc.subjectcausal inferenceen_US
dc.subjectp-curvesen_US
dc.subjectp-hackingen_US
dc.subjectpublication biasen_US
dc.titleMethods Matter: P-Hacking and Causal Inference in Economicsen_US
dc.typeWorking Paperen_US

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