Nonseparable sample selection models with censored selection rules

Ivan Fernandez-Val (), Aico van Vuuren and Francis Vella

No CWP10/18, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: We consider identi?cation and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss di?erent objects of interest based on (1) local e?ects conditional on the control function, and (2) global e?ects obtained from integration over ranges of values of the control function. We provide conditions under which these objects are appropriate for the total population. We also present results regarding the estimation of counterfactual distributions. We derive conditions for identi?cation for these di?erent objects and suggest strategies for estima-tion. We also provide the associated asymptotic theory. These strategies are illustrated in an empirical investigation of the determinants of female wages and wage growth in the United Kingdom.

Keywords: Sample selection; nonseparable models; control function; quantile and distribution regression (search for similar items in EconPapers)
Date: 2018-02-02
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Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Nonseparable sample selection models with censored selection rules (2024)
Working Paper: Nonseparable Sample Selection Models with Censored Selection Rules (2020)
Working Paper: Nonseparable Sample Selection Models with Censored Selection Rules (2018)
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