IDEAL Special Quarter on Data Economics
Synopsis
As data science transforms science and society, it is important to develop the economics of data. Collecting data is costly, possessing data gives market power, sharing data has risks and benefits, conclusions from data depend on data quantity and quality. Topics include: valuing data, eliciting data, incentivizing data collection and sharing, adaptive data analysis, game theory with data.
Organizers
- Jason Hartline (Northwestern University)
- Ian Kash (University of Illinois, Chicago)
- Nicolas Lambert (Mass. Institute of Tech.)
- Grant Schoenebeck (University of Michigan)
- Bo Waggoner (University of Colorado, Boulder)
- Zhaoran Wang (Northwestern University)
- Haifeng Xu (University of Chicago)
Virtual Institute
- Time: meetings Friday 11-2pm, virtual. More info to come.
- Participants:
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- Yang Cai (Yale University)
- Modibo Camara (UChicago)
- Raul Fernandez Castro (UChicago)
- Yiding Feng (Microsoft Research)
- Rafael Frongillo (Colorado Univ.- Boulder)
- Nicole Immorlica (Microsoft Research)
- Vijay Kamble (Univ. of Illinois, Chicago)
- Yuqing Kong (Peking University)
- Yingkai Li (Yale University)
- Brendan Lucier (Microsoft Research)
- Rad Niazadeh (UChicago-Booth)
- Mallesh Pai (Rice University)
- David Pennock (Rutgers Univ.)
- Kangning Wang (UC Berkeley-Simons)
- Jens Witkowski (Frankfurt School of Finance & Management)
- James Wright (Univ. of Alberta)
- Zhuoran Yang (Princeton University)
- Fang-Yi Yu (George Mason Univ.)
- Hanrui Zhang (Carnegie Mellon University)
Graduate Courses
The following graduate courses will be offered during this special quarter:
- Time: Friday 2:00-4:50pm (Central Time), virtual, Northwestern Univ., Prof. Jason Hartline
- Enrollment details: Northwestern: COMP_SCI 497-0-8 (Hartline), UChicago CMSC 31801-1 (Xu)
- Synopsis: This is an advanced topics seminar that will consider theoretical topics in the space of data economics. As data science transforms science and society, it is important to develop the economics of data. Collecting data is costly, possessing data gives market power, sharing data has risks and benefits, conclusions from data depend on data quantity and quality. The readings of the course will be drawn from the recent and classic literature pertaining to data economics. Topics include: valuing data, eliciting data, incentivizing data collection and sharing, adaptive data analysis, game theory with data.
Econ 414-1: Economics of Information
- Time: TuTh 3:30-5:20pm (Central Time), in person, Northwestern Univ., Room KGH 3301, Prof. Annie Liang
- Synopsis: Information imperfections and asymmetries in markets and organizations. The theory and application of mechanism design to markets and contracts. Topics include: modeling information, search, the value of information, games with incomplete information, adverse selection and moral hazard.
Workshops
- Friday, October 14, 2022: Elicitation Mechanisms in Practice Workshop
- Friday, October 28, 2022: Elicitation and Evaluation Workshop
- Friday, November 11, 2022: Challenges in Data Economics Workshop
Visit the events page to see a full list of workshops coming up.
Calendar
April 2025 |
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