Komarova, Tatiana 
ORCID: 0000-0002-6581-5097
(2008)
Binary choice models with discrete regressors: identification and misspecification.
In: Nuffield Econometric/INET Seminar Series, 2008-10-17, Oxford, United Kingdom.
(Submitted)
Abstract
In semiparametric binary response models, support conditions on the regressors are required to guarantee point identification of the parameter of interest. For example, one regressor is usually assumed to have continuous support conditional on the other regressors. In some instances, such conditions have precluded the use of these models; in others, practitioners have failed to consider whether the conditions are satisfied in their data. This paper explores the inferential question in these semiparametric models when the continuous support condition is not satisfied and all regressors have discrete support. I suggest a recursive procedure that finds sharp bounds on the parameter of interest and outline several applications. After deriving closed-form bounds on the parameter, I show how these formulas can help analyze cases where one regressor's support becomes increasingly dense. Furthermore, I investigate asymptotic properties of estimators of the identification set. I also propose three approaches to address the problem of empty identification sets when a model is misspecified. Finally, I present a Monte Carlo experiment and an empirical illustration to compare several estimation techniques.
| Item Type: | Conference or Workshop Item (Other) |
|---|---|
| Official URL: | http://www.nuffield.ox.ac.uk/General/Seminars/ |
| Additional Information: | © 2008 The Author |
| Divisions: | Economics |
| Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
| JEL classification: | C - Mathematical and Quantitative Methods > C0 - General |
| Date Deposited: | 20 Feb 2012 12:40 |
| Last Modified: | 15 Sep 2023 08:25 |
| URI: | http://eprints.lse.ac.uk/id/eprint/41948 |
Actions (login required)
 |
View Item |
