Statistical Causal Inference
AECO 480 #7443 for undergraduate students
AECO 580 #7444 for master students
Instructor: Professor Byoung Park - [email protected]
Time: T/Th 9:00AM - 10:20AM
Classroom: Humanities 109
This course is designed to introduce master and advanced undergraduate level students to basic concepts of causal inference.
In economics and many related fields, it is an important task to determine the causal effect of an event, for example, receiving a treatment, participating in a program, implementing an intervention, or adopting a policy. We will learn how to define causal effects in the potential outcome framework and why it is difficult to estimate causal effects from data. Then we will study statistical causal inference methods that are widely-used in empirical economics and social sciences including regression with the conditional independence assumption, matching estimator, instrumental variables estimator, and difference-in-differences. In assignments, students will learn how to implement causal methods to real data analysis in a statistical software.