We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey (MEPS) data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favoured, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required. © 2011 Taylor & Francis.
|Publication status||Published - 1 Jul 2011|