Bayesian Statistics and Econometrics

This course examines econometrics from a Bayesian perspective including linear and nonlinear regression, covariance structures, panel data, qualitative variable models, nonparametric and semiparametric methods, time series, Bayesian model averaging and variable selection. It explores Bayesian methodology including Markov Chain Monte Carlo methods, hierarchical models, model checking, mixture models, empirical Bayes approaches, approximations, and computational issues and gives some attention to foundations. Elements used in grading: Attendance, Class Participation, Exam.