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Working paper 756

Shengjie Hong, Yu-Chin Hsu, Yuanyuan Wan, "Subvector inference for Varying Coefficient Models with Partial Identification", 2023-08-31
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Abstract: This paper develops inference methods for a general class of varying coefficient models defined by a set of moment inequalities and/or equalities, where unknown functional parameters are not necessarily point-identified. We propose an inferential procedure for a subvector of the parameters and establish the asymptotic validity of the resulting confidence sets uniformly over a broad family of data-generating processes. We also propose a specification test for the varying coefficient models considered in this paper. Monte Carlo studies show that the proposed methods work well in finite samples.

Keywords: Varying coefficient; Moment inequalities; Partial-identification; Multiplierbootstrap

JEL Classification: C12, C14, C15