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