Publication Type

Journal Article

Publication Date

3-2018

Abstract

We consider the estimation of a semiparametric sample selection model without instrument or large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. We propose a simple estimator based on extremal quantile regression and establish its asymptotic normality by extending previous results on extremal quantile regressions to allow for selection. Finally, we apply our method to estimate the black-white wage gap among males from the NLSY79 and NLSY97. We find that premarket factors such as AFQT and family background play a key role in explaining the black-white wage gap.

Keywords

Black-white gap, Extreme quantile regression, Intermediate quantile, sample selection models

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

203

Issue

1

First Page

129

Last Page

142

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2017.11.004

Publisher

Elsevier

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1016/j.jeconom.2017.11.004

Included in

Econometrics Commons

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