On Baseline Conditions For Zero-Inflated Longitudinal Count Data
We describe a mixed-effects hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations. We show how model parameters can be estimated in a fnite mixture context, allowing for overdispersion, multivariate association and endogeneity of the baseline variable. The model behavior is investigated through a large scale simulation experiment. An empirical example on health care utilization data is provided.
|Date of creation:||2012|
|Date of revision:||2012|
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- Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
- Murat K. Munkin & Partha Deb & Pravin K. Trivedi, 2006. "Bayesian analysis of the two-part model with endogeneity: application to health care expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1081-1099.
- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, April.
- William Greene, 2009. "Models for count data with endogenous participation," Empirical Economics, Springer, vol. 36(1), pages 133-173, February.
- Monica Auteri & Antonello Maruotti, 2012. "Modelling waiting times in the Italian National Health Service," Applied Economics Letters, Taylor & Francis Journals, vol. 19(5), pages 459-465, March.
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