Identification of and Correction for Publication Bias

Published on Aug 1, 2019in The American Economic Review9.17
路 DOI :10.1257/AER.20180310
Isaiah Andrews12
Estimated H-index: 12
(Harvard University),
Maximilian Kasy11
Estimated H-index: 11
(University of California, Berkeley)
Sources
Abstract
Some empirical results are more likely to be published than others. Such selective publication leads to biased estimates and distorted inference. This paper proposes two approaches for identifying the conditional probability of publication as a function of a study鈥檚 results, the first based on systematic replication studies and the second based on meta-studies. For known conditional publication probabilities, we propose median-unbiased estimators and associated confidence sets that correct for selective publication. We apply our methods to recent large-scale replication studies in experimental economics and psychology, and to meta-studies of the effects of minimum wages and de-worming programs.
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