Estimating Nonseparable Selection Models: A Functional Contraction Approach

Fan Wu and Yi Xin

Papers from arXiv.org

Abstract: We propose a novel method for estimating nonseparable selection models. We show that, given the selection rule and the observed selected outcome distribution, the potential outcome distribution can be characterized as the fixed point of an operator, which we prove to be a functional contraction. We propose a two-step semiparametric maximum likelihood estimator to estimate the selection model and the potential outcome distribution. The consistency and asymptotic normality of the estimator are established. Our approach performs well in Monte Carlo simulations and is applicable in a variety of empirical settings where only a selected sample of outcomes is observed. Examples include consumer demand models with only transaction prices, auctions with incomplete bid data, and Roy models with data on accepted wages.

Date: 2024-11, Revised 2025-02
New Economics Papers: this item is included in nep-dcm and nep-ecm
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