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Binary choice models with discrete regressors: identification and misspecification

Komarova, Tatiana (2013) Binary choice models with discrete regressors: identification and misspecification. Journal of Econometrics, 177 (1). pp. 14-33. ISSN 0304-4076

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Identification Number: 10.1016/j.jeconom.2013.05.005

Abstract

This paper explores the inferential question in semiparametric binary response models when the continuous support condition is not satisfied and all regressors have discrete support. I focus mainly on the models under the conditional median restriction, as in Manski (1985). I find sharp bounds on the components of the parameter of interest and outline several applications. The formulas for bounds obtained using a recursive procedure help analyze cases where one regressor’s support becomes increasingly dense. Furthermore, I investigate asymptotic properties of estimators of the identification set. I describe a relation between the maximum score estimation and support vector machines and propose several approaches to address the problem of empty identification sets when the model is misspecified.

Item Type: Article
Official URL: http://www.journals.elsevier.com/journal-of-econom...
Additional Information: © 2013 Elsevier B.V.
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C10 - General
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables
C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C25 - Discrete Regression and Qualitative Choice Models
Sets: Departments > Economics
Collections > Economists Online
Date Deposited: 14 Jun 2013 13:12
Last Modified: 20 Nov 2019 10:48
URI: http://eprints.lse.ac.uk/id/eprint/46821

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