ECO372: Data Analysis and Applied Econometrics in Practice is an intermediate-level econometrics course that focuses on using data to answer causal questions. The course introduces students to various empirical techniques, including random assignment, linear regression, instrumental variables, difference-in-differences, and regression discontinuity design. Students will engage with these methods by reading, critically evaluating, and replicating existing research, as well as conducting their own original analyses. Emphasis is placed on both understanding the technical foundations and applying these tools to real-world economic questions.

Main topics include the fundamentals of regression analysis, causal inference frameworks (such as the Rubin Causal Model and experimental designs), and advanced methods like instrumental variables, matching, regression discontinuity, and synthetic control. Students will also explore panel data techniques, difference-in-differences models, and the challenges of ensuring valid inference, such as addressing issues with standard errors. By the end of the course, students will develop the ability to select appropriate identification strategies, interpret quantitative results, and understand the assumptions and limitations of various econometric models.

The course builds on foundational knowledge from prerequisites in economics and statistics (ECO200Y1, ECO220Y1, or equivalent courses) and is designed to equip students with practical skills for conducting empirical research.