Certain types of health expenditures, such as inpatient expenditures, have a predominance of observations at zero and a continuous, often skewed, distribution among the remaining responses. In cross-sectional analyses of such expenditures, two-part models can be estimated in a straightforward way because the two parts are separable. For longitudinal analyses of such expenditures, analysts may extend the two-part model to fit a generalized linear mixed model for the probability of a nonzero response over time and a conditional linear mixed model for the mean response given that it is nonzero. However, the zero and non-zero data generating processes may be serially correlated in longitudinal data and a more appropriate two-part model would include jointly distributed random effects for the zero and non-zero processes. We apply both types of longitudinal modeling to annual specialty expe