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.
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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|Item Type:||Journal Article|
|Keywords:||Censoring, Overdispersion, Poisson regressions, Series approximation, Unobserved heterogeneity, Zero inflation|
|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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