Statistical Nonsignificance in Empirical Economics

Abstract

Statistical 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)