Advanced Econometrics: An Introduction t

Claims of causality are nearly ubiquitous in scholarly work spanning the social sciences, journalistic products from media outlets, policy circles, and other social spaces.  However, many of these claims are often subject to some of the well-documented econometric concerns of bias—including omitted variable bias, simultaneity, and other confounding influences.  This course will introduce students to the fundamental concepts of causal inference and expose them to several contemporary econometric tools employed in an effort to make some of the aforementioned claims more credible.  With randomized controlled trials (RCTs) serving as the gold standard for empirical work, students will learn how many econometric techniques and “natural” experiments attempt to emulate the best characteristics of well-executed RCTs.

In addition to problem sets and an in-class midterm exam, students will carry out a group research project on a topic of their choosing (in consultation with the professor) in order to demonstrate their proficiency in several key course concepts.  This project remains critical to learning the scholastic (and practical) challenges in making rigorous causal claims, navigating the logistics of group collaboration, and learning how to critically evaluate empirical work.