ECON 826
Partial Identification: Theory and Applications in Industrial Organization
Adam M. Rosen, Allan Collard-Wexler
Description from DukeHub
Focus on the use of partially identifying models for applications in industrial organization, investigating a mix of methodological, theoretical, econometric, and applied issues. Particular areas of application in the IO literature will comprise a selection of research employing various models of auctions, entry, matching, and demand estimation. For each area of application, we will cover both the econometric theory underlying the partial identification analysis employed, as well as the motivation for the use of the partially identifying model in empirical practice. Economics 703D and Economics 707D. Economics Ph.D. Students only; all others require consent from the instructor.
Skills
- data and statisticsdescription: "econometric" and 1 more
AI-resilient: 0 of 5
- No: Physical, lab or field work
- No: Live work with people
- No: Judgment someone is accountable for
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
More in ECON
- Economic Principles ECON 101CCD
- Statistical Foundations of Econometrics and Data Science ECON 104D
- Uncertainty, Risk, and Society ECON 140CN
- Financial Accounting ECON 174
- Intermediate Microeconomics I ECON 201D
- Econometrics and Data Science ECON 204D