Semiparametric estimation of count regression models

Gurmu, S., Rilstone, P., & Stern, Steven (1999) Semiparametric estimation of count regression models. Journal of Econometrics, 88(1), pp. 123-150.

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Abstract

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

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ID Code: 73224
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Censoring, Overdispersion, Poisson regressions, Series approximation, Unobserved heterogeneity, Zero inflation
DOI: 10.1016/S0304-4076(98)00026-8
ISSN: 0304-4076
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 1999 Elsevier BV * North-Holland
Deposited On: 02 Jul 2014 01:37
Last Modified: 02 Jul 2014 01:37

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