Teaching

I am teaching ECMA 31360 at Chicago in the fall of 2023. Please sign up for courses on the University website. If you have any specific questions about course topics, feel free to message my office, and a teaching staff member will respond as soon as possible.

33160: Causal Inference

Semester: Fall

Offered: 2023

This course reviews modern causal inference techniques and their applications to business and economics. The course covers the treatment-control comparison estimator, regression adjustment, matching (on covariates and propensity score), difference in differences (canonical and with staggered treatment), panel data methods, regression discontinuity design (sharp and fuzzy), and instrumental variables and local average treatment effect (LATE) estimator. At different points during the course, we mention how machine learning (ML) techniques have recently been used to enrich the classical methods. The course involves programming (R language) and working with data. Students are expected to have a solid background in statistics and econometrics.

Prerequisites: ECON 21020/21030, and working knowledge of R and familiarity with RStudio.

Course Requirements: There will be weekly long-format home assignments containing both theoretical and coding problems. Students are encouraged to work in small groups (2-4 people). The final grade is based 40% on homework and 60% on exams (a midterm and a final exam).

321: Course Name

Semester: Spring

Offered: 2023

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421: Course Name

Semester: Spring

Offered: 2023

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521: Course Name

Semester: Spring

Offered: 2023

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621: Course Name

Semester: Spring

Offered: 2023

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