On Gaussian Process Priors in Conditional Moment Restriction Models

Sid Kankanala

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arXiv · 2311.00662

On Gaussian Process Priors in Conditional Moment Restriction Models

Sid Kankanala

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Abstract

This paper studies quasi Bayesian estimation and uncertainty quantification for an unknown function that is identified by a nonparametric conditional moment restriction. We derive contraction rates for a class of Gaussian process priors. Furthermore, we provide conditions under which a Bernstein von Mises theorem holds for the quasi-posterior distribution. As a consequence, we show that optimally weighted quasi-Bayes credible sets have exact asymptotic frequentist coverage.

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Sid Kankanala. 2023-11-01. On Gaussian Process Priors in Conditional Moment Restriction Models. https://arxiv.org/abs/2311.00662

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