Course Detail
Course Components:
The second course in a two-course sequence in econometrics. Designed to give doctoral students the tools to conduct empirical research. Topics include: research design; causality; potential outcomes framework; clustering and multiway clustering; difference in difference estimators; panel data; fixed effects and random effects; non-linear estimation;, maximum likelihood; censored data; truncated data; tobit; Heckman selection; applications of instrumental variables; stationary ARMA; VARMA; forecasting; cointegration; Bayesian approaches to research; more quantile regressions; and nonlinear hypothesis testing.