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dc.contributor.authorBrodeur, A
dc.contributor.authorCook, N
dc.contributor.authorHeyes, A
dc.date.accessioned2022-06-15T09:45:31Z
dc.date.issued2022-09-01
dc.date.updated2022-06-14T20:55:20Z
dc.description.abstractIn Brodeur et al. (2020) we present evidence that IV (and to a lesser extent DID) articles are more p-hacked than RCT and RDD articles. We also find no evidence that: (i) articles published in the Top 5 journals are different; (ii) the “revise and resubmit” process mitigates the problem; (iii) things are improving through time. Kranz and Pütz (2022) apply a novel adjustment to address rounding errors. They successfully replicate our results with the exception of our shakiest finding: after adjusting for rounding errors, bunching of test statistics for DID articles is now smaller around the 5% level (and coincidentally larger at the 10% level).en_GB
dc.format.extent3137 - 3139
dc.identifier.citationVol. 112 (9), pp. 3137 - 3139en_GB
dc.identifier.doi10.1257/aer.20220277
dc.identifier.urihttp://hdl.handle.net/10871/129954
dc.identifierORCID: 0000-0003-1847-9374 (Heyes, Anthony)
dc.language.isoenen_GB
dc.publisherAmerican Economic Associationen_GB
dc.rights© 2022 American Economic Association
dc.titleMethods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Replyen_GB
dc.typeArticleen_GB
dc.date.available2022-06-15T09:45:31Z
dc.identifier.issn0002-8282
dc.descriptionThis is the final version. Available from the American Economic Association via the DOI in this recorden_GB
dc.identifier.journalAmerican Economic Reviewen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2022-06-13
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-06-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-06-14T20:55:22Z
refterms.versionFCDAM
refterms.dateFOA2022-09-12T15:11:12Z
refterms.panelCen_GB


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