Finite Mixture for Panels with Fixed Effects

This paper develops nite mixture models with xed effects for two families of distributions for which the incidental parameter problem has a solution. Analytical results are provided for mixtures of Normals and mixtures of Poisson. We provide algorithms based on the expectations-maximization (EM) approach as well as computationally simpler equivalent estimators that can be used in the case of the mixtures of normals. We design and implement a Monte Carlo study that examines the nite sample performance of the proposed estimator and also compares it with other estimators such the Mundlak-Chamberlain conditionally correlated random e¤ects estimator. The results of Monte Carlo experiments suggest that our proposed estimators of such models have excellent nite sample properties, even in the case of relatively small T and moderately sized N dimensions. The methods are applied to models of healthcare expenditures and counts of utilization using data from the Health and Retirement Study.