Can Prediction Markets Test Public Policy?

Prediction markets are hot again.  With the Presidential election next week and the relative accuracy of prediction markets about the election in 2008, I decided to finish this article that I first started in March 2009, but put aside for various reasons.

What is a prediction market?  James Surowiecki, the author of the book, “The Wisdom of Crowds” explains:

The premise is that under the right circumstances, the collective judgment of a large group of people will generally provide a better picture of what the future might look like than anything one expert or even a small group of experts will come up with. [Prediction markets] work much like a futures market, in which the price of a contract reflects the collective day-to-day judgment either on a straight numberfor instance, what level sales will reach over a certain periodor a probabilityfor example, the likelihood, measured as a percentage, that a product will hit a certain milestone by a certain date.

[F]or a crowd to be smart, it needs to satisfy certain criteria. It needs to be diverse, so that people are bringing different pieces of information to the table. It needs to be decentralized, so that no one at the top is dictating the crowds answer. It needs to summarize peoples opinions into one collective verdict. And the people in the crowd need to be independent, so that they pay attention mostly to their own information and dont worry about what everyone around them thinks.

These markets have been around for a few years and have a good, if not perfect, track record.  Various studies have found prediction markets to be better than experts or public opinion polling.

But my focus is not on predicting who wins the White House or the SuperBowl or the number of coins in a large bottle.  Rather there is a use of prediction markets for government leaders testing the likelihood that a particular public policy will achieve success, especially if the policy is intended to change the behavior of people.

Often it is difficult to assess how the public will react to a proposed policy will people actually sign up for program X; will people recycle; etc.  I’m suggesting that prediction markets be used to estimate the reaction ahead of time.

Implicit in the diversity of views that Surowiecki notes is that enough people need to care about the policy.  The reason they care may be to win money, in some cases, but thats not the only reason.  They might care because the market deals with something that affects their lives.

And, the nice thing about this is that if only a few people care about a policy that also tells you something about the policy or, at least, whether youll get into deep trouble proposing it.

You can learn from prediction markets and they may be more effective predictors of policy success than traditional tools.

So far I can tell this has not really been tried yet in the way I’m describing.  The closest was in 2003, when DARPA created a Policy Analysis Market to be “a market in the future of the Middle East”.  That market looked, to critics, like a betting parlor on political assassinations by terrorists and was withdrawn.

In a more futuristic vision, Robin D. Hanson, an economist at George Mason University and a fan of alternative institutions, writes about futarchy, “a form of government enhanced by prediction markets. Voters would decide broad goals of national welfare, but betting in speculative markets would determine the policy steps to achieve those goals.”

I’m not proposing anything so revolutionary as he is.  Instead, let’s try to use prediction markets on a more experimental basis.

More background on prediction markets can be found in:

  • Wikipedia and

  • When the Crowd Isnt Wise

  • Interpreting the Predictions of Prediction Markets

© 2012 Norman Jacknis


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