Yuichi Kitamura University of Minnesota - Twin Cities SBR-9632101 This research will investigate parametric likelihood methods. Parametric likelihood methods are central to econometric and statistical research. In general, parametric methods involve the use of rather arbitrary assumptions on the data generating process. This research will build on recent literature on nonparametric likelihood methods which extends the concept of likelihood to models without distributional assumptions. One of the contributions of this research is to extend various empirical likelihood methods to time series observations by treating the dependence structure nonparametrically. Extensive simulation studies will be undertaken to examine the nature of these new methods. In addition, the project will investigate a new criterion for model comparison, looking at various specifications of dynamic asset pricing models.
