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Frequentist size of Bayesian inequality tests

David Kaplan () and Longhao Zhuo
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Longhao Zhuo: Bank of America

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Abstract: Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (e.g., Gaussian). For the corresponding limit 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 $\alpha$ (sometimes strictly); and in other cases, size may be above, below, or equal to $\alpha$. Two examples illustrate our results: testing stochastic dominance and testing curvature of a translog cost function.

New Economics Papers: this item is included in nep-ecm
Date: 2016-07, Revised 2018-02
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http://arxiv.org/pdf/1607.00393 Latest version (application/pdf)

Related works:
Working Paper: Frequentist size of Bayesian inequality tests (2018) Downloads
Working Paper: Frequentist size of Bayesian inequality tests (2018) Downloads
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