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Identification of and correction for publication bias

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  • Isaiah Andrews
  • Maximilian Kasy

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's 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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  • Isaiah Andrews & Maximilian Kasy, 2017. "Identification of and correction for publication bias," Papers 1711.10527, arXiv.org.
  • Handle: RePEc:arx:papers:1711.10527
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    References listed on IDEAS

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    6. Garret S. Christensen & Edward Miguel, 2016. "Transparency, Reproducibility, and the Credibility of Economics Research," NBER Working Papers 22989, National Bureau of Economic Research, Inc.
    7. Michael A. Clemens, 2017. "The Meaning Of Failed Replications: A Review And Proposal," Journal of Economic Surveys, Wiley Blackwell, vol. 31(1), pages 326-342, February.
    8. Hristos Doucouliagos & T. D. Stanley, 2009. "Publication Selection Bias in Minimum-Wage Research? A Meta-Regression Analysis," British Journal of Industrial Relations, London School of Economics, vol. 47(2), pages 406-428, June.
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    16. Andrews, Donald W K, 1993. "Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models," Econometrica, Econometric Society, vol. 61(1), pages 139-165, January.
    17. Hou, Kewei & Xue, Chen & Zhang, Lu, 2017. "Replicating Anomalies," Working Paper Series 2017-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
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    Cited by:

    1. Alberto Abadie, 2018. "Statistical Non-Significance in Empirical Economics," NBER Working Papers 24403, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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