Endogeneity in Semiparametric Binary Response Models

Richard Blundell () and James Powell

The Review of Economic Studies, 2004, vol. 71, issue 3, 655-679

Abstract: This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single-index binary response models to the case of endogenous regressors. It develops a control function approach to account for endogeneity in triangular and fully simultaneous binary response models. The proposed estimation method is applied to estimate the income effect in a labour market participation problem using a large micro data-set from the British Family Expenditure Survey. The semiparametric estimator is found to perform well, detecting a significant attenuation bias. The proposed estimator is contrasted to the corresponding probit and linear probability specifications. Copyright 2004, Wiley-Blackwell.

Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (307)

Downloads: (external link)
http://hdl.handle.net/10.1111/j.1467-937X.2004.00299.x (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Endogeneity in semiparametric binary response models (2001)
Working Paper: Endogeneity in semiparametric binary response models (2001)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:71:y:2004:i:3:p:655-679

Access Statistics for this article

The Review of Economic Studies is currently edited by Thomas Chaney, Xavier d’Haultfoeuille, Andrea Galeotti, Bård Harstad, Nir Jaimovich, Katrine Loken, Elias Papaioannou, Vincent Sterk and Noam Yuchtman

More articles in The Review of Economic Studies from Review of Economic Studies Ltd
Bibliographic data for series maintained by Oxford University Press ().