The Bayesian Score Statistic
Year: 2000
Type: preprint
Abstract: We propose a novel Bayesian test under a (noninformative) Jeffreys'priorspecification. We check whether the fixed scalar value of the so-calledBayesian Score Statistic (BSS) under the null hypothesis is aplausiblerealization from its known and standardized distribution under thealternative. Unlike highest posterior density regions the BSS isinvariantto reparameterizations. The BSS equals the posterior expectation oftheclassical score statistic and it provides an exact test procedure,whereasclassical tests often rely on asymptotic results. Since the statisticisevaluated under the null hypothesis it provides the Bayesiancounterpart ofdiagnostic checking. This result extends the similarity of classicalsampling densities of maximum likelihood estimators and Bayesianposteriordistributions based on Jeffreys' priors, towards score statistics. Weillustrate the BSS as a diagnostic to test for misspecification inlinearand cointegration models.
Authors: Frank Kleibergen, Richard Kleijn, Richard Paap
Institutions: University of Amsterdam, Erasmus University Rotterdam
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2142683605