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Statistical reporting errors in economics

Author

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  • Bruns, Stephan
  • Herwartz, Helmut
  • Ioannidis, John P.A.
  • Islam, Chris-Gabriel
  • Raters, Fabian H. C.

Abstract

We developed a tool that scrapes and interprets statistical values (DORIS) to analyze reporting errors, which occur if the eye-catcher depicting the level of statistical significance is inconsistent with the reported statistical values. Using 578,132 tests from the top 50 economics journals, we find that 14.88 % of the articles have at least one strong error in the main tests. Our pre-registered analysis suggests that mandatory data and code availability policies reduce the prevalence of strong errors, while suggestive indication of a reversed effect is found for top 5 journals. Integrating DORIS into the review process can help improving article quality.

Suggested Citation

  • Bruns, Stephan & Herwartz, Helmut & Ioannidis, John P.A. & Islam, Chris-Gabriel & Raters, Fabian H. C., 2023. "Statistical reporting errors in economics," MetaArXiv mbx62, Center for Open Science.
    • Handle: RePEc:osf:metaar:mbx62
    DOI: 10.31219/osf.io/mbx62
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    References listed on IDEAS

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    1. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
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