Twenty Steps Towards an Adequate Inferential Interpretation of p-Values in Econometrics

Abstract

We suggest twenty immediately actionable steps to reduce widespread inferential errors related to "statistical significance testing." Our propositions refer to the theoretical preconditions for using p-values. They furthermore include wording guidelines as well as structural and operative advice on how to present results, especially in research based on multiple regression analysis, the working horse of empirical economists. Our propositions aim at fostering the logical consistency of inferential arguments by avoiding false categorical reasoning. They are not aimed at dispensing with p-values or completely replacing frequentist approaches by Bayesian statistics.