A Monte Carlo Study of Ec-Estimation in Panel Data Models with Limited Dependent Variables and Heterogeneity.

The EC (Estimation-Classification) estimator, and its companion EC-algorithm, were introduced in El- Gamal and Grether (1995), and their properties further analyzed in El-Gamal and Grether (1996). The purpose of EC estimation is to uncover heterogeneity in panel data models in a manner which is more parsimonious and computationally less costly than some of the standard methods (e.g. fixed effects). The latter concern is particularly evident in limited dependent variable models where no simple method of estimating fixed effects is available (e.g. probits).