Latent class models for utilisation of health care
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This paper explores different approaches to econometric modelling of count measures of health care utilisation, with an emphasis on latent class models. A new model is proposed that combines the features of the two most common approaches: the hurdle model and the finite mixture negative binomial. Additionally, the panel structure of the data is taken into account. The proposed finite mixture hurdle model is shown to fit the data substantially better than the existing models for a particular application to data from the RAND Health Insurance Experiment. The estimation results indicate a higher price effect for low users of health care. It is furthermore found that this results mainly from the difference of the price effects on the probability to visit a doctor, while the price effect on the conditional number of visits does not differ significantly between high and low users.