Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/1912
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Título : Likelihood-Based Approaches to Modeling Demand for Medical Care
Autor : Creel, Michael, Farell, Montserrat
Palabras clave : Health care demand
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Maximum likelihood
Fecha de publicación : 5-Oct-2001
Citación : UFAE and IAE Working Papers
498.01
Resumen: We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.
URI : http://hdl.handle.net/10261/1912
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