Stanford Root

Schedule

Stanford Root

Schedule

ECON 287

Topics in Market Design (MS&E 365)

UNITS:3
GRADING:Letter or Credit/No Credit
LEVEL:Graduate
GER:—

The rapid deployment of LLMs and autonomous agents may reshape how markets are structured and how participants will interact and what frictions will arise. These technologies raise questions about incentives, information, and institutional design. Examples include entry-level labor markets, transportation, healthcare, etc. This PhD-level course surveys recent theoretical and applied research at the intersection of economics, OR, and CS that may be affected by AI. The course further examines how AI-based capabilities challenge and enrich traditional approaches to market design. In what ways does the presence of autonomous agents alter strategic behavior? How should markets be designed when AI systems act as complements or substitutes for human participants? How to achieve alignment in marketplaces with AI agents? How can AI algorithms be incorporated into the design of marketplaces? The course encourages students to begin research projects in this emerging field. The course assumes basic knowledge in game theory and market design.

Syllabus for selected term:
View Winter 2027 Syllabus

Sections

1 Term
Lecture 1Open
ID: 12440
0 / 12 enrolled
DAYS:Wednesday
TIME:12:30 PM – 3:20 PM
LOCATION:Departmental Room
INSTRUCTOR:
Ashlagi, Itai, Jagadeesan, Ravi
3units

ECON 287: Topics in Market Design (MS&E 365)

3 units · Letter or Credit/No Credit

The rapid deployment of LLMs and autonomous agents may reshape how markets are structured and how participants will interact and what frictions will arise. These technologies raise questions about incentives, information, and institutional design. Examples include entry-level labor markets, transportation, healthcare, etc. This PhD-level course surveys recent theoretical and applied research at the intersection of economics, OR, and CS that may be affected by AI. The course further examines how AI-based capabilities challenge and enrich traditional approaches to market design. In what ways does the presence of autonomous agents alter strategic behavior? How should markets be designed when AI systems act as complements or substitutes for human participants? How to achieve alignment in marketplaces with AI agents? How can AI algorithms be incorporated into the design of marketplaces? The course encourages students to begin research projects in this emerging field. The course assumes basic knowledge in game theory and market design.

Offered in Winter 2027 at Stanford University.

Winter 2027 sections

  • Lecture — Wednesday 12:30 PM – 3:20 PM — Departmental Room — Ashlagi, Itai, Jagadeesan, Ravi (Graduate)

More ECON courses

  • ECON 280: Behavioral and Experimental Economics III
  • ECON 281: Designing Experiments for Impact
  • ECON 282: Contracts, Information, and Incentives
  • ECON 284: Simplicity and Complexity in Economic Theory (CS 360)
  • ECON 285: Matching and Market Design
  • ECON 286: Game Theory and Economic Applications
  • ECON 288: Computational Economics and Machine Learning
  • ECON 290: Multiperson Decision Theory
  • ECON 291: Social and Economic Networks
  • ECON 293: Machine Learning and Causal Inference
  • ECON 294: Continuous-time Methods in Economics and Finance
  • ECON 295: The AI Awakening: Implications for the Economy and Society

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