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Likelihood-Based Approaches to Modeling Demand for Medical Care

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dc.creator Creel, Michael
dc.creator Farell, Montserrat
dc.date 2007-11-06T10:51:51Z
dc.date 2007-11-06T10:51:51Z
dc.date 2001-10-05
dc.date.accessioned 2017-01-31T00:58:10Z
dc.date.available 2017-01-31T00:58:10Z
dc.identifier http://hdl.handle.net/10261/1912
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1912
dc.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.
dc.language eng
dc.relation UFAE and IAE Working Papers
dc.relation 498.01
dc.rights openAccess
dc.subject Health care demand
dc.subject Count data
dc.subject Maximum likelihood
dc.title Likelihood-Based Approaches to Modeling Demand for Medical Care
dc.type Documento de trabajo


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