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Statistical Nonsignificance in Empirical Economics†

Statistical Nonsignificance in Empirical Economics† AbstractStatistical significance is often interpreted as providing greater information than nonsignificance. 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 nonsignificant results. (JEL C12, C90) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Economic Review: Insights American Economic Association

Statistical Nonsignificance in Empirical Economics†

American Economic Review: Insights , Volume 2 (2) – Jun 1, 2020

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Publisher
American Economic Association
Copyright
Copyright © 2020 © American Economic Association
ISSN
2640-205X
eISSN
2640-2068
DOI
10.1257/aeri.20190252
Publisher site
See Article on Publisher Site

Abstract

AbstractStatistical significance is often interpreted as providing greater information than nonsignificance. 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 nonsignificant results. (JEL C12, C90)

Journal

American Economic Review: InsightsAmerican Economic Association

Published: Jun 1, 2020

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