Empirical Likelihood Estimation in Dynamic Panel Models

This paper proposes and analyses an hybrid of Owen.s (1988, 1990, 1991) Empirical Likelihood (EL) and bootstrap, EL-bootstrap, as an alternative to the General Method of Moments (GMM) within dynamic panel data models. We concentrate on the .nite-sample size properties of their over-identification tests. Our results show that EL-bootstrap may be a good alternative to GMM estimation within this setting. The practical usefulness of our findings is illustrated via application on an AR(1) univariate panel data model with individual e¤ects using the cash-flow series of 174 firms in the United States.