MA Econometrics I

This is an introductory graduate level course in econometrics. This course is designed to introduce students to the fundamental tools of econometrics. The primary goal of the course is to provide students an in-depth understanding of the classical linear regression model (CLRM) and the key identification assumptions. Upon completing the course, successful students will be able to formulate econometric models, manage data and estimate regressions, and interpret results (sign, significance, and magnitude). Successful students will understand finite and asymptotic properties of commonly used estimators, hypotheses testing, identification, estimation, accurate inference, linear, instrumental variables, logit/probit, and maximum likelihood regressions. [Also taught in Fall 2019, Fall 2018]