Bayesian Statistics and Econometrics

2–6 credits · Law

Linear and nonlinear regression, covariance structures, panel data, qualitative variable models, nonparametric and semiparametric methods, time series, Bayesian model averaging and variable selection. Bayesian methodology including Markov chain Monte Carlo methods, hierarchical models, model checking, mixture models, empirical Bayes approaches, approximations, and computational issues and foundations. Prerequisite: graduate-level econometrics or equivalent.