Applied Econometrics I: Regression Analysis for Causal Inference

Catalog description

Provides a rigorous foundation in applied econometrics with a focus on regression analysis for causal inference. Regression analysis helps address real-world problems beyond prediction, offering tools to examine causal relationships. Emphasizes both theoretical foundations—model assumptions, derivations, and identification strategies—and hands-on empirical data analysis. By the end of the course, students will be able to frame testable hypotheses, analyze complex real-world data, and apply econometric methods to inform research, policy, and data-driven business strategies.