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Identification of and Correction for Publication Bias

Isaiah Andrews and Maximilian Kasy ()

American Economic Review, 2019, vol. 109, issue 8, 2766-94

Abstract: 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)
Date: 2019
Note: DOI: 10.1257/aer.20180310
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Related works:
Working Paper: Identification of and correction for publication bias (2018) Downloads
Working Paper: Identification of and correction for publication bias (2017) Downloads
Working Paper: Identification of and Correction for Publication Bias (2017) Downloads
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