Econometrics for Data Science

Catalog description

Catalogue DescriptionEconometrics represents the branch of economics devoted to the quantitative analysis of economic data and relationships. This course is devoted to introducing students to the most important econometric tools by developing a theoretical understanding of the concepts and familiarity with their application. The course starts by introducing the Linear Regression Model (LRM) and related estimation and inferential techniques. This basic linear cross-sectional framework will then be extended to nonlinear relationships, limited dependent variables, panel data and issues related to time series data. Particular emphasis will be devoted to discussing the causal interpretation of the LRM and related estimation techniques. Throughout the course, students will engage weekly with data using programming languages such as R or Python. Credits cannot be received for both ECO 4000 and ECO 4001.