Identification of and Correction for Publication Bias
- (pp. 2766-94)
(Complimentary)
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.Citation
Andrews, Isaiah, and Maximilian Kasy. 2019. "Identification of and Correction for Publication Bias." American Economic Review, 109 (8): 2766-94. DOI: 10.1257/aer.20180310Additional Materials
JEL Classification
- C13 Estimation: General
- C90 Design of Experiments: General
- I23 Higher Education; Research Institutions
- J23 Labor Demand
- J38 Wages, Compensation, and Labor Costs: Public Policy
- L82 Entertainment; Media