Econometric applications of empirical likelihood

We provide some evidence of Empirical Likelihood's (EL) practical value in econometrics.
We present EL as an alternative to GMM estimation and assess the
finite-sample properties of their overidentification tests (size and power) through
Monte Carlo simulations. We address the issue of the importance of the results
to applied workers and use as laboratories to our experiments two settings with
potential empirical applications: the Mean-Variance and Three-Moment CAPM
and a dynamic panel model with individual effects. In cases in which we found
important size distortions we introduced efficient bootstrap critical values. Prior
research applied this bootstrapping technique to the GMM (GMM-bootstrap)
and we present results for the EL (EL-bootstrap). We also include an empirical
example on a United States panel cash-flow model. Even if our findings do not
uniformly support the conclusion that one estimator dominates the other, we
found evidence that EL and EL-bootstrap are good alternatives to GMM and
GMM-bootstrap in some econometric applications