An excellent post from Marginal Revolution on prediction markets, worth quoting in full:

Last week in The New York Times (TimesSelect), Joseph Nocera quoted Robin Hanson as saying private businesses had not made a breakthrough with the use of idea futures. It seems natural to let your employees bet on future business conditions, the success of product lines, or broader questions of corporate strategy. Microsoft and Google and a few other companies have played with the idea, but it does not (yet?) seem to be taking off. Why not?

1. Prediction markets threaten the hierarchical control of top managers. It would become too obvious that most managers are idiots, unable to predict the future.

2. Prediction markets make a big chunk of the bettors into “losers.” Yet within a company morale is all-important. Businesses proceed by soliciting feedback, and by reshaping their plans to pretend that everyone is on board and has an ego stake in the final outcome. Prediction markets make this coordination more difficult. Once people make bets, they start rooting for their bet to win and for the other bet to lose. They move away from maximizing the value of the firm and develop an oppositional mentality vis-a-vis other employees. Furthermore it is disruptive to have a running tally on who are the winners and losers each day.

3. No matter what they pretend, businesses are not much interested in forecasting many future variables. Successful businesses find product markets they can control for long periods of time. They do a few things really well, and let a surprisingly large number of tasks slide.

4. We already have implicit betting markets in the form of resource prices. When the information contained in those prices is sufficiently important, institutions will be organized in terms of “markets,” rather than “firms.” Or firms can look at resource prices in outside markets for the information they need.

5. Most employees have no rational basis on which to bet. If someone knows the truth, but is otherwise locked out from credibly signaling that knowledge to management, something is wrong with the organization of the company. The small prizes from corporate prediction markets won’t be enough to elicit that knowledge from him in any case.

6. The corporate beast is far more constrained than most outsiders imagine. Interest groups must be courted, coordinated, and sometimes fought every step of the way. When it comes to choice, there are fewer degrees of freedom than one might think. The real question is not what to do, but rather having the will and effectiveness to do it. A bit like international free trade, no? Prediction markets don’t help much in this regard.

7. When reward systems are created, employees view them as a means to distribute further privileges to insiders and favorites. Prediction markets would be viewed the same way and in fact this might be true. Who else is going to win all those bets? Do corporations really need more insider favoritism?

Your thoughts? Here are five open questions about prediction markets.

On a related note, David Perry points us towards this helpful list of factors which can influence the success of an internal corporate prediction market once adopted:

• how congruent is the organizational structure and decision-making process with the forces and yearnings that prediction markets inevitably unleash? (flat, fast and democratic? or hierarchical, slow and autocratic?)
• how secure do executives feel in their role(s) as facilitators and empowerers? (as opposed to being the smartest and best informed in every situation)
• how (and how well) does information flow through the organization today? (are cross-boundary exchanges encouraged? or are silos and secret-keeping behaviors implicitly rewarded?)
• how are heretics, truth-tellers, gadflies and other critics of conventional wisdom utilized (or ‘dealt with’) inside the confines of a particular corporate culture?

Hot off the presses today is a brand new prediction market for trading shares of various predictions of the future — Inkling. There aren’t many active markets yet, but the site appears to be getting alot of traffic. The latest markets include the most popular programming language, the next Big 10 men’s basketball coach to leave, Project Runway season two results, and Apple rumors. From what I’ve seen so far, the site seems fairly well implemented. Of particular note is the trading wizard they use to facilitate trading for users who are less market-savvy. The wizard very explicitly interprets current share price as a probability, and uses a simple set of choices to suggest an optimal trade. When I looked at shares of Daniel Vosovic winning Project Runway Season 2, they were selling at $31.70. The wizard first asked me if I thought Daniel had exactly a 32% chance of winning (his current share price rounded up), or a higher chance, or a lower chance. After I specified that I thought he had a higher chance of winning than that, it asked me how low I thought 32% was “just below”, “low”, or “way too low”, with corresponding recommended trade sizes of 5, 20, or 50 shares. This is a well thought out way to elicit well-calibrated trades from inexperienced users.
In the spirit of full disclosure, here are my current holdings

• Nick Lachey vs. Jessica Simpson
• Nick will get money in the divorce settlement, bought @ $86.80
• Project Runway Season 2
• Daniel Vosovic, bought @ $31.70
• Del.icio.us vs. Digg vs. Reddit vs. Slashdot
• Reddit, sold @ $74.50

It looks like the markets are active and volatile right now - I’m up $580 in just the last few minutes. Join in!

Today in TCSDaily, Michael Strong wonders whether academia might be made better of by encouraging professors to place monetary bets on the future states of the world which their theories imply.

The credibility of academia is based on the notion that professors are “experts in their field” who have achieved their position by means of a track record of exemplary scholarship. In the hard sciences, where “exemplary scholarship” is based on scientific work that is consistent with empirical research, this credibility is based on a solid foundation. Outside the hard sciences, the foundation for the credibility is more tenuous.

In the hard sciences non-obvious facts, such as the existence of unimagined planets and elements, were predicted in advance of discovery. It is striking that one of the few non-obvious predictions in the social sciences, the prediction by Mises and Hayek that communism would fail due to the lack of price information, was ridiculed or neglected in the social science literature from the 1930s until the 1990s, when it suddenly became accepted wisdom. Paul Samuelson’s Principles of Economics 13^th edition, published in 1989, claimed “the Soviet economy is proof that, contrary to what many skeptics had earlier believed, a socialist command economy can function and even thrive.” The “skeptics” being sneered at here are Mises and Hayek. Samuelson’s economics textbooks, selling more than 4 million copies, represented “expert judgment” in economics throughout the 50s, 60s, 70s, and 80s.

…

The issue would be harmless enough if nothing were at stake but thousands of delusional professors taking a few billion dollars out of our economy. But lives are at stake. In 1989, when some academic economists were still praising the Soviet economy, I had dinner with an Egyptian reporter who noted that the Soviet Union had to change because a generation of Soviet military advisors, sent to advise “third world” nations such as Egypt, had discovered, to their humiliation, that ordinary Egyptians had cars, refrigerators, and a host of modern conveniences that were only available to the nomenklatura of the Soviet Union. Throughout the world more than four million leaders and professionals were taught to believe that Samuelson’s work was authoritative. His judgment was a major force for defining economic reality for the entire world throughout the second half of the 20^th century. And he was completely clueless regarding the state of the Soviet economy.

The article is based on Robin Hanson’s essay Could Gambling Save Science?: Encouraging an Honest Consensus

Read more: Put Your Money Where Your Theory Is

Previously: Consensus View