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I started to comment on this and it turned into a longish post on my own site. Here it is:
http://torontopm.wordpress.com/2009/11/25/use-and-abuse-of-public-policy-prediction-markets/
Essentially, Matt does not believe that public policy markets will be free of manipulation. Robin thinks that manipulative effects will be eliminated by the informed traders. I examine some of the assumptions built into Robin’s public prediction market framework, and come to the following conclusion:
In theory, it is a nice idea to try and accurately aggregate as much information as possible in order to determine the best course of action in public policy decisions. Most public policy decisions are remarkably complex with numerous tradeoffs among competing interests. All decision-making benefits from more information that is more accurate and more timely. Unfortunately, simply inserting a prediction market framework into the decision-making process does not eliminate the political biases that have been, and will always be, there.
While it may be possible to operate public policy prediction markets for some issues, their use in the climate change or global warming debate is questionable. Not only can there be no guarantee of manipulation-free markets, we wouldn’t even know if market predictions had been manipulated. If actual public policy were to depend on false readings from such markets, the potential for significant misallocation of resources is immense. It is simply too great a risk to consider at this time, in my opinion.
I made a correction to my post. If the traders are *informed*, it should make no difference whether the noise trade comes from a manipulator or an uninformed trader. I had previously said that it did matter.
Robin suggested that I read his papers before popping off with a few thoughts. So, I’ve completed reviewing the technical paper, “A Manipulator Can Aid Prediction Market Accuracy”, and have added my comments here:
http://torontopm.wordpress.com/2009/11/26/is-it-enough-to-provide-incentives/