Comparisons of Estimators and Tests Based on Modified Likelihood And Message Length Functions

The presence of nuisance parameters causes unexpected complications in econometric inference problems. A number of modified likelihood and message length functions have been developed for better handling of nuisance parameters but all of them are not equally efficient. In this paper, we empirically compare different modified likelihood and message length functions in the context of estimation and testing of parameters from linear regression disturbances that follow either a first-order moving average of firts-order autoregressive error processes.