Using Futures Markets in Public Policy Formation

1. Using Futures Markets in Public Policy Formation Robin Hanson Associate Professor of Economics, GMU

2. “Pays $1 if Bush wins” Will price rise or fall? sell E[ price change | ?? ] buy price sell Lots of ?? get tried, price includes all! buy Buy Low, Sell High (All are “gambling” “prediction” “info”)

3. Today’s Current Event Prices 93-94% Blue-Ray > HD-DVD sales in ‘07 5-12% Dick Cheney Resigns by 4/’08. 7-25% Bird Flu confirmed in US. By 4/’08. 11-12% Bin Laden caught by 4/’08. 20-28% US or Israel air strike on Iran by 4/’08. 65-66% Hillary Democrat Pres. Nominee in ‘08. 57-58% Democrat President in ‘08. 85-90% China war act on Taiwan by Apr. ‘11 63-72% Women talk >1.1x men in next study TradeSports.com

4. In direct compare, beats alternatives • Vs. Public Opinion • I.E.M. beat presidential election polls 451/596 (Berg et al ‘01) • Re NFL, beat ave., rank 7 vs. 39 of 1947 (Pennock et al ’04) • Vs. Public Experts • Racetrack odds beat weighed track experts (Figlewski ‘79) • If anything, track odds weigh experts too much! • OJ futures improve weather forecast (Roll ‘84) • Stocks beat Challenger panel (Maloney & Mulherin ‘03) • Gas demand markets beat experts (Spencer ‘04) • Econ stat markets beat experts 2/3 (Wolfers & Zitzewitz ‘04) • Vs. Private Experts • HP market beat official forecast 6/8 (Plott ‘00) • Eli Lily markets beat official 6/9 (Servan-Schreiber ’05) • Microsoft project markets beat managers (Proebsting ’05)

5. Hollywood Stock Exchange Science 291:987-988, February 9 2001

6. Track Odds Beat Handicappers Figlewski (1979) Journal of Political Economy 14 Estimated on 146 races, tested on 46

7. Economic Derivatives Market Wolfers & Zitzewitz “Prediction Markets” (2004) Journal of Economic Perspectives

8. NFL Markets vs Individuals Average of Forecasts Servan-Schreiber, Wolfers, Pennock & Galebach (2004) Prediction Markets: Does Money Matter? Electronic Markets, 14(3). 1,947 Forecasters

9. “Accuracy and Forecast Standard Error of Prediction Markets” Joyce Berg, Forrest Nelson and Thomas Rietz, July 2003.

10. Iowa Electronic Markets vs. Polls “Accuracy and Forecast Standard Error of Prediction Markets” Joyce Berg, Forrest Nelson and Thomas Rietz, July 2003.

11. Policy Analysis Market • Every nation*quarter: • Political stability • Military activity • Economic growth • US $ aid • US military activity • & global, special • & all combinations

12. Return to Focus ? Trade IQcs4 IQcs4 < 85 85 03 03 SAum3 105-125 03 Update Payoffs: If & Ave. pay Select New Price 65% Max Up 95.13% +$34.74 -$85.18 -$19.72 Buy 10% Up 68.72% +$2.74 -$3.28 -$1.07 You Pick 65 % +1.43 -2.04 +0.34 Saudi Arabian Economic Health No Trade 62.47% $0.00 $0.00 $0.00 125 30 15 10% Dn 56.79% -$2.61 +$2.74 -$1.12 65 70 Sell Exit Issue 48.54% -$15.34 +$26.02 -$6.31 35 40 100 94 100 Max Dn 22.98% -$120.74 +$96.61 -$22.22 < 85 25 35 35 30 10 10 75 1 2 3 4 1 2 > 03 03 03 03 04 04 ? Return to Form Execute a Trade If US military involvement in Saudi Arabia in 3rd Quarter 2003 is not between 105 and 125, this trade is null and void. Otherwise, if Iraq civil stability in 4th Quarter 2003 is below 85, then I will receive $1.43, but if it is not below 85, I will pay $2.04. Abort trade if price has changed? Execute Trade Scenario

13. The Fuss: Analysts often use prices from various markets as indicators of potential events. The use of petroleum futures contract prices by analysts of the Middle East is a classic example. The Policy Analysis Market (PAM) refines this approach by trading futures contracts that deal with underlying fundamentals of relevance to the Middle East. Initially, PAM will focus on the economic, civil, and military futures of Egypt, Jordan, Iran, Iraq, Israel, Saudi Arabia, Syria, and Turkey and the impact of U.S. involvement with each. [Click here for a summary of PAM futures contracts] The contracts traded on PAM will be based on objective data and observable events. These contracts will be valuable because traders who are registered with PAM will use their money to acquire contracts. A PAM trader who believes that the price of a specific futures contract under-predicts the future status of the issue on which it is based can attempt to profit from his belief by buying the contract. The converse holds for a trader who believes the price is an over-prediction – she can be a seller of the contract. This price discovery process, with the prospect of profit and at pain of loss, is at the core of a market’s predictive power. The issues represented by PAM contracts may be interrelated; for example, the economic health of a country may affect civil stability in the country and the disposition of one country’s military may affect the disposition of another country’s military. The trading process at the heart of PAM allows traders to structure combinations of futures contracts. Such combinations represent predictions about interrelated issues that the trader has knowledge of and thus may be able to make money on through PAM. Trading these trader-structured derivatives results in a substantial refinement in predictive power. [Click here for an example of PAM futures and derivatives contracts] The PAM trading interface presents A Market in the Future of the Middle East. Trading on PAM is placed in the context of the region using a trading language designed for the fields of policy, security, and risk analysis. PAM will be active and accessible 24/7 and should prove as engaging as it is informative. Became:

14. PAM Press Of 500+ articles, these gave more favorable PAM impression: Article: later in time, more words, mentioned insider, news (not Editorial) style, not anonymous Publication: finance or science specialty, many awards, many readers

15. PAM Concerns Terrorists themselves could drive up the market for an event they are planning and profit from an attack, or even make false bets to mislead intelligence authorities. U.S. Senators Wyden and Dorgan, Press Release, July 28, 2003. Would-be assassins and terrorists could easily use disinformation and clever trading strategies to profit from their planned misdeeds while distracting attention from their real target. Steven Pearlstein, Washington Post, July 30, 2003. Trading . . . could be subject to manipulation, particularly if the market has few participants – providing a false sense of security or . . . alarm. . . . the lack of intellectual foundation or a firm grasp of economic principles - or the pursuit of other agendas - has led to a proposal that almost seems a mockery of itself. Joseph Stiglitz, Los Angeles Times, July 31, 2003.

16. Terror Betting Is “Unthinkable” • We deny our “Taboo Tradeoffs” (P. Tetlock) • E.g., money vs. risk of death • Outraged at those we see do (really, we all do) • More outraged if they think a long time first • If catch ourselves, seek moral cleansing • PAM painted as crossing a moral boundary • “None of us should intend to benefit when some of them hurt some of us.” • So politicians must not think long before rejecting

17. Source:

18. Inputs Outputs Prediction Markets Theory For Same Compare! Status Quo Institution

19. Not Experts vs. Self-chosen Amateurs • Forecasting Institution Goal: • Given same participants, resources, topic • Want most accurate institution forecasts • Separate question: who let participate? • Can limit who can trade in market • Markets have low penalty for add fools • Hope: get more info from amateurs?

20. Advantages • Numerically precise • Consistent across many issues • Frequently updated • Hard to manipulate • Need not say who how expert when • At least as accurate as alternatives

21. $1 if A p(A) $1 $1 if A&B p(A&B) $1 $ x if A E[x|A]*p(A) $1 $ x E[x] $1 $1 if A&B p(B|A) $1 if A $ x if A E[x|A] $1 if A Estimates from Prices

22. Single Payer Decision Markets $1 if Lifespan Up & Single Payer P(S) $1 if Single Payer P(L | S) $1 Compare! P(L | not S) $1 if Not Single Payer $1 if Lifespan Up & Not Single Payer P(not S)

23. Decision Market Applications E[ Lifespan | Single Payer Health? ] E[ f(inflation,unemploy) | Fed raise rates? ] E[ Student test scores | School voucher? ] E[ red team in | new building security? ] E[ US terror deaths | halve DHS budget? ] E[ Unemployment | Demo. Pres. ’08? ] E[ firm stock price | dump CEO? ] Market costs start high, not depend on topic, so do big value questions first.

24. Legal permission Outcome Measured Aggregate-enough Linear-enough Conditional-enough Decision Distinct options Important enough Enough influence Public credibility Traders Enough informed Decision-insiders Enough incentives Anonymity Prices Intermediate-enough Can show enough Decision Market Requirements

25. Concerns • Self-defeating prophecies • Decision selection bias • Price manipulation • Inform enemies • Share less info • Combinatorics • Moral hazard • Alarm public • Embezzle • Bozos • Lies • Rich more “votes” • Risk distortion • Bubbles

26. Three Premises and a Conclusion • It is not too hard to tell rich happy nations from poor miserable ones long after fact. • Governments largely fail by not aggregating available information. • Betting markets are the best known institution for aggregating information. • Try to vote on values, but bet on beliefs.

27. E[ GDP+ | Alternative ] >? E[ GDP+ | Status Quo ] Vote On Values But Bet On Beliefs

28. Futarchy’s One Rule When a market estimates currently-defined GDP+ to be higher given some proposed alternative policy, that policy becomes law. • Unless market on future-defined GDP+ vetoes it • Start with existing policies, fee to propose change • Like contract, proposal says how handle conflicts • High standards at base, recurse to relax standards http://hanson.gmu.edu/futarchy.html

29. Concerns • Self-defeating prophecies • Decision selection bias • Price manipulation • Inform enemies • Share less info • Combinatorics • Moral hazard • Alarm public • Embezzle • Bozos • Lies • Rich more “votes” • Risk distortion • Bubbles

30. Typical Problems In Field Now • Legal Barriers • “Moral” Concerns • Not really want to know • Hard to find precise related events • Can not get participation for cheap • Not enough events to validate, learn • Awkward interfaces