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

The presence of nuisance parameters causes unwanted complications in statistical and econometric inference procedures. A number of modified likelihood and message length functions have been developed for better handling of nuisance parameters but they 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 first order moving average or first order autoregressive error processes.