1 / 12

IDEA FUTURES Designing Markets for Information Aggregation

IDEA FUTURES Designing Markets for Information Aggregation. Robin Hanson RWJF Health Policy Scholar UC Berkeley. Talk Outline. Information aggregation (IA) is good. Many design IA institutions by intuition. Economists have good theories of IA failures & fixes, and

abigail-ewing
Télécharger la présentation

IDEA FUTURES Designing Markets for Information Aggregation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. IDEA FUTURESDesigning Markets for Information Aggregation Robin Hanson RWJF Health Policy Scholar UC Berkeley

  2. Talk Outline • Information aggregation (IA) is good. • Many design IA institutions by intuition. • Economists • have good theories of IA failures & fixes, and • see speculative markets work IA wonders, but • not pursued; markets too complex for theory; don’t do “prototypes” (designs w/o theory) • Let’s explore space of IA market designs

  3. Why We Want Info Aggregation Gun-toting deter crime? Sea level rise with CO2? Some alcohol healthy? Divorce hurt children? Deliver product on time? Dump CEO help stock? • Most inefficiency due to secrets. • war, crime, poverty, conformity, rat races, … • Secrets can help sometimes though.

  4. Attempts to Design IA systems History: trials, news media, polls, peer review Intuitive: Delphi method, science courts, DesignShop(TM) , hypertext publishing, collaborative filtering Economic-Theory-Based: scoring rules, pivot mechanisms, contracts, auctions, voting rules, public good mechanisms

  5. Theory suggests IA easier when • each info known to several people • more possible (visible) actions, e.g., repeat • action payoffs correlated well with info • e.g., cheap talk, burning $, costly signals, bets • claims verifiable (even possibly, eventually) • see others’ beliefs (no agreeing to disagree)

  6. Markets Work IA Wonders • It’s hard to find info not reflected in prices [40+ years of “market efficiency” research] • O.J. futures beat govt. forecasts [‘84 R. Roll AER] • Election markets beat polls [‘92 Foresythe et.al. AER] • most traders biased, but not active traders • Experimental markets tend to reveal info • if traders experienced & know net payoffs [‘90 Forsythe & Lundholm, Econometrica]

  7. Market IA Theory Is Complex • Simple (RE) theories say all info revealed. • Full game has many actors, actions, periods. • Too complex for theory to give general results? • Mostly, economists don’t do prototypes. • So “economic design” neglects market IA. • Hedging markets easier to model; is field.

  8. Regulation of Speculation Gambling IA Capitalize Entertainment Hedging

  9. Recent IA Market Prototypes • Play-$ web games show small markets work • HSX: 100K players, ~500 movies, stars • FX: 2K players, 200+ claims, 80+ sci/tech • Internal company markets on sales, delivery • at HP, Siemens, Xanadu, Sun. • Limit participation & stakes. • DARPA interested in for tech forecasts

  10. Design Dimensions • Who sees offers, identities, stakes, prices? • Who plays? What win? Limit on stakes? • Who judges & how? Who pays for? • Property rights in claims? • Asset pays f(x), e.g. distribution moments • Supporting mutual funds & conjuncts • Distribution of computation & security

  11. Neglected Design Dimensions • Conditional estimates, esp. on decisions • e.g., conditional on clear resolution • Subsidies: hedgers, addicts, braggarts, decisions, $ (allows single trader markets) • Random judging/focus • e.g., GIS markets w/ random pixels checked • Factoring out risk premium biases

  12. Summary • Information aggregation (IA) is important. • Economic theory suggests we can do better, and speculative markets seem to do well. • Economists neglect potential because don’t test prototypes (designs w/o direct theory). • Let’s have econ-savvy folks explore design space via lab tests, field trials. • Then pioneer new market regulatory realm?

More Related