Course # 41430 Section Number 2 Day(s) Tu- Th Time(s) 5:00pm-6:20pm Term Fall 2024 Syllabus Syllabus 9/18/24 This course explores how modern developments in machine learning, AI and statistical learning may be leveraged in order to improve regression analysis and reduced-form econometrics more generally. For instance, we provide a modern, optimization-conscious treatment of linear regression, quantile regression, instrumental variables, and Fréchet-Hoeffding bounds. Throughout, we make an effort to produce methods that remain valid even when models are --as they always are-- misspecified. To produce such regression methods, we fetch tools and results from fields such as linear programming, optimal transport, numerical linear algebra, deep learning and reinforcement learning. Quarter Title Instructor Day(s) Time(s) Syllabus Fall 2024 Modern Methods for Applied Regression Tuesday, Thursday 3:30pm-4:50pm Syllabus Fall 2024 Modern Methods for Applied Regression Tuesday, Thursday 5:00pm-6:20pm Syllabus Recent News More news Student Profile: Maria Villamizar Londono Wed., July 16, 2025 Q&A: Assistant Professor Erin Kelley on Her Work in Program Evaluation, International Development, and With the World Bank Wed., July 09, 2025 University of Chicago’s Harris School of Public Policy and Institute for Climate and Sustainable Growth Launch New Pathbreaking Master’s Program in Climate and Energy Policy Tue., July 08, 2025 Upcoming Events More events Harris Summer Mixer in Beijing Fri., July 18, 2025 | 6:00 PM Maison Flo 18 Xiaoyun Rd Chaoyang Qu Beijing Shi, 100027 China Harris Summer Mixer in Jakarta Sat., July 19, 2025 | 4:30 PM Rusty Rabbit | Plaza Festival, Jl. H. R. Rasuna Said No.22 Kav. C, Karet Kuningan, Setiabudi Jakarta Selatan, DKI Jakarta 12940 Indonesia Harris Summer Open House Mon., July 21, 2025 | 9:30 AM Harris School of Public Policy Keller Center 1307 E. 60th St. Chicago, IL 60637 United States