Identification of and Correction for Publication Bias
Isaiah Andrews and
Maximilian Kasy ()
American Economic Review, 2019, vol. 109, issue 8, 2766-94
Some empirical results are more likely to be published than others. Selective publication leads to biased estimates and distorted inference. We propose two approaches for identifying the conditional probability of publication as a function of a study's results, the first based on systematic replication studies and the second on meta-studies. For known conditional publication probabilities, we propose bias-corrected estimators and confidence sets. We apply our methods to recent replication studies in experimental economics and psychology, and to a meta-study on the effect of the minimum wage. When replication and meta-study data are available, we find similar results from both.
JEL-codes: C13 C90 I23 J23 J38 L82 (search for similar items in EconPapers)
Note: DOI: 10.1257/aer.20180310
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to AEA members and institutional subscribers.
Working Paper: Identification of and correction for publication bias (2018)
Working Paper: Identification of and correction for publication bias (2017)
Working Paper: Identification of and Correction for Publication Bias (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aea:aecrev:v:109:y:2019:i:8:p:2766-94
Ordering information: This journal article can be ordered from
Access Statistics for this article
American Economic Review is currently edited by Esther Duflo
More articles in American Economic Review from American Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by Michael P. Albert ().