Nonseparable Sample Selection Models with Censored Selection Rules

TL;DR

This paper develops identification and estimation methods for nonseparable sample selection models with censored rules, using control functions to analyze local and global effects, and applies these methods to study female wages in the UK.

Contribution

It introduces new identification strategies and estimation techniques for complex nonseparable models with censored selection, expanding the toolkit for empirical analysis.

Findings

Effective control function strategies for nonseparable models

Identification conditions for local and global effects

Empirical insights into female wage determinants in the UK

Abstract

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from integration over ranges of values of the control function. We derive the conditions for the identification of these different objects and suggest strategies for estimation. Moreover, we provide the associated asymptotic theory. These strategies are illustrated in an empirical investigation of the determinants of female wages in the United Kingdom.