Empirical Likelihood as an alternative to GMM estimation in the area of asset pricing
This paper proposes and analyses Owens (1998, 1990, 1991) Empirical Likelihood (EL) as an alternative to the General Method of Moments (GMM) within the Capital Asset Pricing Model (CAPM). We concentrate on the finite-sample properties, size and power, of their over identifi cation tests. Our simulation evidence shows that there are no clear advantages in terms of size when the GMMs over identfi cation tests based on two-step and continuously updated estimators are compared to that based on the Empirical Likelihood Ratio (ELR) within a Mean-Variance and Three-Moment setting. The three tests have moderate size distortions. However, our findings illustrate that the ELR over identifi cation statistic is more powerful in detecting deviations from the null under the alternatives that we analyse.