This course is organized into two parts. Part I covers univariate and multivariate time domain models of stationary and nonstationary time series. Topics covered include univariate time series models, unit root tests, time series regression modeling, systems of regression equations, vector autoregressive models for multivariate time series and cointegration. In Part II the course introduces the issues and opportunities that arise with panel data and the main statistical techniques used for its analysis. Topics covered include fixed-effects models, random-effects models, dynamic models and limited dependent variable models. Throughout the course, the emphasis will be on how to use S-plus and Stata to estimate panel data and time series models. There is relatively less emphasis on statistical theory. Evaluation in the course is based on home work assignments and a term project. Prerequisite: MGTSC 705 or equivalent.