Likelihood-Based Approaches to Modeling Demand for Medical Care

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1912

Title:	Likelihood-Based Approaches to Modeling Demand for Medical Care
Keywords:	Health care demand Count data Maximum likelihood
Description:	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://dspace.mediu.edu.my:8181/xmlui/handle/10261/1912
Other Identifiers:	http://hdl.handle.net/10261/1912
Appears in Collections:	Digital Csic

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