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 C13, C90, I23, J23, J38, L82)
Identification of and Correction for Publication Bias
Maximilian Kasy,Isaiah Andrews
Published 2017 in The American Economic Review
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- Publication year
2017
- Venue
The American Economic Review
- Publication date
2017-03-01
- Fields of study
Computer Science, Economics, Psychology
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