Frequentist properties of Bayesian inequality tests

David Kaplan and Longhao Zhuo

No 1910, Working Papers from Department of Economics, University of Missouri

Abstract: Bayesian and frequentist criteria fundamentally differ, but often posterior and sampling distributions agree asymptotically (e.g., Gaussian with same covariance). For the corresponding single-draw experiment, we characterize the frequentist size of a certain Bayesian hypothesis test of (possibly nonlinear) inequalities. If the null hypothesis is that the (possibly infinite-dimensional) parameter lies in a certain half-space, then the Bayesian test's size is alpha; if the null hypothesis is a subset of a half-space, then size is above alpha; and in other cases, size may be above, below, or equal to alpha. Rejection probabilities at certain points in the parameter space are also characterized. Two examples illustrate our results: translog cost function curvature and ordinal distribution relationships.

Keywords: generalized Bayes rule; limit experiment; minimax; nonstandard inference; posterior (search for similar items in EconPapers)
JEL-codes: C11 C12 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://drive.google.com/file/d/18K67TvcSfX6h3LfEj ... ZYa/view?usp=sharing (application/pdf)

Related works:
Working Paper: Frequentist properties of Bayesian inequality tests (2024)
Journal Article: Frequentist properties of Bayesian inequality tests (2021)
Working Paper: Frequentist size of Bayesian inequality tests (2019)
Working Paper: Bayesian and frequentist inequality tests (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:umc:wpaper:1910

Access Statistics for this paper

More papers in Working Papers from Department of Economics, University of Missouri Contact information at EDIRC.
Bibliographic data for series maintained by Chao Gu ().