Identification of and Correction for Publication Bias

被引：199

作者：

Andrews, Isaiah ^{[1
]}

Kasy, Maximilian ^{[2
]}

机构：

[1] Harvard Univ, Littauer Ctr, Cambridge, MA 02138 USA

[2] Harvard Univ, Littauer Ctr, Dept Econ, Cambridge, MA 02138 USA

来源：

AMERICAN ECONOMIC REVIEW | 2019年 / 109卷 / 08期

基金：

美国国家科学基金会;

关键词：

MEDIAN-UNBIASED ESTIMATION; POWER;

D O I：

10.1257/aer.20180310

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：2766 / 2794

页数：29

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