Longtime readers are familiar with my views on prediction markets. I believe they have some value, when applied correctly. Where prediction markets excel is in acting as a collective real time polling mechanism for their participants. The closer the collective group is to the broader population, the more accurate these markets tend to be. Where they do poorly is when the collective attempt to “pool their ignorance” and forecast the random or the unknowable.

There is strength in any mechanism that can factor a large pool of participants collective experience and knowledge, discount several possibilities into the most likely outcome. These market mechanisms are hardly the Oracles of Delphi their supporters make them out to be. It is only by din of Humans’ even worse forecasting abilities (with experts leading the way down) that these markets garner so much respectability in the first place. Blame fuzzy thinking for placing too much credibility on a mechanism with so mixed a track record. There is also a subtle but important distinction between forecasting the future versus discounting various outcomes.

Which leads me to [the] New York Times column. In a bizarre twist of logic, the massive failure of the prediction markets in the US 2006 mid-term elections somehow gets credit for being right. They were not a day late and a dollar short, they were completely, totally and incontrovertibly wrong.

Except in the NY Times:

Consider the following: As of 11:50 p.m. on the evening of Election day, with the voting completed (except for Hawaii) and the majority of the ballots counted, Intrade gave the Republicans an 85 percent chance of retaining the Senate. Of course, we know that’s not at all what happened. If that’s not a forecasting failure, then what is?

If forecasting the results of an election held yesterday is considered prescience, then sign me up — and find me a bookie who will take my Superbowl bets on the Monday after the game. I suspect I will at least cover the spread.

To reiterate my views, these markets — thinly traded, easily manipulated, poorly administered — do have some real value. However, they have hardly been “remarkably clairvoyant,” as the Times describes them. Consider these recent acts of “clairvoyance:”

- GOP Retention of Senate
- Michael Jackson Trial Results
- Morgan Stanley CEO Purcell resignation
- Howard Dean’s Iowa Primary
- Pre-Election 2004
- Election day trading frenzy

There are some interesting explanations for some of these errors: Pooling the collective ignorance of millions does not produce Wisdom. The Michael Jackson Trial and Morgan Stanley’s CEO are perfect examples of that.

As to the prediction market’s failure of the Howard Dean primary and the 2006 mid-term elections, I’ve been toying with a theory. Since the political affiliation of Wall Street tends toward Republican, and since there is a big overlap between Wall Street and the participants of the prediction markets, the collective had an inherent bias built into it. Remember, where these markets excel is when they act as a realtime polling mechanism of their particpants. If the pool has a bias, the outcome may very well too. Hence, these widescale failures.

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Bottom line: While having value, prediction markets are subject to error and bad outcomes. Some of this is due to their relative thinness of the markets; some is due to the inherent biases of the participants, and their failure to parallel the population at large.

They should be considered with the recognition of their fallibility.

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Source:
Odds Are, They’ll Know ’08 Winner
DAVID LEONHARDT
New York Times, February 14, 2007
Economix

http://www.nytimes.com/2007/02/14/business/14leonhardt.html

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Cross-Posted from The Big Picture

The costs of building coalitions are also a neglected element in the theory of organizations. Even in the private sector, once we consider cohesion and morale, businesses have many fewer degrees of freedom than we might think. That is why merit pay and prediction markets are not as common as an economist might expect. Too often those institutions put people at odds with each other.

My Answer:

#1. Economists are poor innovators and lame marketers. Their “expectations” are necessarily always out of the ball park. (Note: I view Robin Hanson as an inventor, but maybe not as an innovator. And, anyway, Robin Hanson is “unusual”. He is an institution designer; the others economists are data analysts.)

#2. The field of prediction markets lacks a bunch of good Guy Kawasaki-type professionals (i.e., clever marketers).

#3. You shouldn’t expect the Planet Earth’s whole population to spend nights and days frantically and frenetically trading contracts on prediction markets. Only a small portion of the world’s people will play this game, and only a few topics will be of interest to this small group of prediction market traders. In the global forecasting industry (polls, predictive models, Delphi method, etc.), the market-generated prediction providers will always be tiny (if not microscopic). Think of the Hawaii islands in the Pacific Ocean.

2006 US Senate races

2006 US Governor races

My Rant: In the Senate map, Missouri and Virginia appear as WHITE, whereas they should be pale blue, since the Dems are over 55% there. And the Hawaii people should have deserved some kind of magnifying glass over their islands. And pale gray for the no-race states is not adequate either. (Sorry for being such an orifice, Professor Fortnow.)
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Addendum:

Suggestion To Professor Lance Fortnow: Inside each state, put an image that tells the reader whether the state was previously Republican or Democrat, so he/she can spot the “swing states”.