Applied Econometrics I
Description: Econometrics is the statistical analysis of causal relationships in human affairs. Econometrics is essential for advancing understanding in the social sciences, conducting public policy evaluation, and assessing the impact of business practices. Applied Econometrics I and II is an integrated two-course sequence designed to teach the essentials of the econometric methodology. Econometrics I covers random assignment, multiple regression, and instrumental variables methods. Econometrics II covers regression discontinuity, difference-in-differences techniques, event study analysis, and synthetic control methods. Both Applied Econometrics I and Applied Econometrics II are “hands on” courses. Students learn to read and interpret existing studies, but also to conduct econometric analyses of their own. Pre-requisites: Applied Econometrics I: Students are presumed to have a solid grounding in basic statistics, at the level of 90-711 (Empirical Methods for Public Policy and Management), 90-786 (Intermediate Empirical Methods) or 95-796 (Statistics for IT Managers). We will make good use of the material covered in those courses.
Learning Outcomes: Upon completion of the course, students should: 1. Fully understand the linear regression estimator – its properties, assumptions, and sampling distribution. 2. Have mastery of common hypothesis tests and confidence intervals based on regression models. 3. Be competent and confident in the use of Stata to perform regression analysis with large datasets. 4. Understand and apply modern practices in the use of regressions, specifically – recognizing the difference between causal and statistical associations, using large-sample theory for inference, and accounting for common forms of non-independence of the error term.
Prerequisites: 90-711 or 95-796 or 90-707 or 90-777