Alternative Asymptotically Optimal Tests in Econometrics

A method of generating asymptotically optimal test statistics using consistent estimators is presented and is useful when full maximum likelihood estimation is difficult under null and alternative hypotheses. Generalizing Neyman's (1959) work, statistics are derived for hypotheses of the constraint equation and parameter type and my be computed from simple GLS or OLS regressions. Testing strategies are given for an ordered sequence of hypotheses and for evaluating a null model against several alternatives. These methods are applied to dynamic equation systems and common factor restrictions in a single dynamic equation model.