Publication Type

Working Paper

Version

publishedVersion

Publication Date

3-2023

Abstract

Hypothesis testing via p-value has been criticized in recent years. Bayes factors (BFs) have been tipped as a possible replacement of p-value for hypothesis testing. However, the standard BFs suffer from some theoretical and practical difficulties. For example, they are not well defined under improper priors and are subject to Jeffreys-Lindley-Bartlett’s paradox under vague priors. Moreover, they are difficult to compute for many models. In this paper, we propose to compare sampling distributions of the posterior-test-based statistics for hypothesis testing. Two posterior-test-based BFs are constructed from the posterior version of the likelihood ratio test and the Wald test, respectively. Under regularity conditions, we show that the new methods can avoid the p-hacking problem and the problems in the standard BFs. The advantages of the proposed methods are investigated using several simulation and empirical studies.

Keywords

Bayes factor, Consistency, p-value, p-hacking, Posterior likelihood ratio test, Posterior Wald test

Discipline

Econometrics

Research Areas

Econometrics

First Page

1

Last Page

48

Publisher

Paper No. 06-2023

Included in

Econometrics Commons

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