Regression spline bivariate probit models: a practical approach to testing for exogeneity
Marra, G. and Radice, Rosalba and Filippou, P. (2015) Regression spline bivariate probit models: a practical approach to testing for exogeneity. Communications in Statistics - Simulation and Computation 46 (3), pp. 2283-2298. ISSN 0361-0918.
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Abstract
Bivariate probit models can deal with a problem usually known as endogeneity. This issue is likely to arise in observational studies when confounders are unobserved. We are concerned with testing the hypothesis of exogeneity (or absence of endogeneity) when using regression spline recursive and sample selection bivariate probit models. Likelihood ratio and gradient tests are discussed in this context and their empirical properties investigated and compared with those of the Lagrange multiplier and Wald tests through a Monte Carlo study. The tests are illustrated using two datasets in which the hypothesis of exogeneity needs to be tested.
Metadata
| Item Type: | Article |
|---|---|
| Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis, available online: http://wwww.tandfonline.com/10.1080/03610918.2015.1041974 |
| Keyword(s) / Subject(s): | Bivariate probit model, Endogeneity, Gradient test, Lagrange multiplier test, Likelihood ratio test, Non-random sample selection, Penalized regression spline, Wald test |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Rosalba Radice |
| Date Deposited: | 10 Jul 2015 13:14 |
| Last Modified: | 02 Aug 2023 17:17 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/12508 |
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