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Data and Code for "Statistical Non-Significance in Empirical Economics"

Version
V0
Resource Type
Dataset : experimental data
Creator
  • Abadie, Alberto (MIT)
Publication Date
2020-05-28
Description
  • Abstract

    Statistical significance is often interpreted as providing greater information than non-significance. In this article we show, however, that rejection of a point null often carries very little information, while failure to reject may be highly informative. This is particularly true in empirical contexts that are common in economics, where data sets are large and there are rarely reasons to put substantial prior probability on a point null. Our results challenge the usual practice of conferring point null rejections a higher level of scientific significance than non-rejections. Therefore, we advocate visible reporting and discussion of non-significant results.
Availability
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Relations
  • Is cited by
    DOI: 10.1257/aer.20180310 (Text)
  • Is cited by
    DOI: 10.3886/E116208V1 (Dataset)
Publications
  • Abadie, Alberto. “Statistical Non-Significance in Empirical Economics.” AER: Insights, n.d.
  • Andrews, Isaiah, and Maximilian Kasy. “Identification of and Correction for Publication Bias.” American Economic Review 109, no. 8 (August 2019): 2766–94. https://doi.org/10.1257/aer.20180310.
    • ID: 10.1257/aer.20180310 (DOI)
  • Andrews, Isaiah, and Maximilian Kasy. “Replication Data for: Identification of and Correction for Publication Bias.” ICPSR - Interuniversity Consortium for Political and Social Research. American Economic Association, 2019. https://doi.org/10.3886/E116208V1.
    • ID: 10.3886/E116208V1 (DOI)

Update Metadata: 2020-05-28 | Issue Number: 1 | Registration Date: 2020-05-28

Abadie, Alberto (2020): Data and Code for "Statistical Non-Significance in Empirical Economics". Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E115087