This course aims to provide students with an understanding of and experience with the key methods economists use to quantify the relationships among variables. A major goal is to prepare students to carry out statistical analysis themselves. We will focus on multivariate regression and causal inference. Topics will include functional form, heteroskedasticity, serial correlation, omitted variables and simultaneity bias, and instrumental variables. We will consider several types of data, including cross-sectional data, time series data, and panel data. Practical as well as theoretical issues will be discussed in how to distinguish correlations from causal effects.
A large part of this syllabus follows the course structure of the Introductory Econo- metrics lectured by Jeffrey Weaver and Vittorio Bassi at the University of Southern California. I appreciate their generosity in sharing this material with me.