Colorful Character Again

I just learned of a new Scientific American article on prediction markets, which is pretty positive: 

A paper … compares the performance of the IEM as a predictor of presidential elections from 1988 to 2004 with 964 polls over that same period and shows that the market was closer to the outcome of an election 74 percent of the time. … Attracted by the markets’ apparent soothsaying powers, companies such as Hewlett-Packard (HP), Google and Microsoft have established internal markets that allow employees to trade on the prospect of meeting a quarterly sales goal or a deadline for release of a new software product. As in other types of prediction markets, traders frequently seem to do better than the internal forecasts do. … Prediction markets may truly hark back to the future. "My long-run prediction is that newspapers in 2020 will look like newspapers in 1920," Wharton School’s Wolfers says. If that happens, the wisdom of crowds will have arrived at a juncture that truly rivals the musings of the most seasoned pundits.

But I am personally singled out as the colorful character who is way too positive: 

The ardor for market-based answers can at times border on the hyperbolic. Robin Hanson, a professor of economics at George Mason University, has advocated that if trading patterns on prediction markets suggest that implementation of a particular policy will cause the economy to grow and unemployment to shrink, then policy officials should, by fiat, adopt that policy – an interest rate cut or a public works project, perhaps. Hanson reasons that the collective information held by traders is superior to the analyses that can be marshaled by a panel of economists or other experts. Hanson has even proposed a form of government called futarchy, based on policy-making markets.

So even if markets are consistently more accurate it is "hyperbolic ardor" to suggest we actually follow their advice?  The article then repeats old errors about DARPA’s Policy Analysis Market (PAM): 

Such utopian leanings have sometimes led advocates to push too far too fast. Several years ago the Defense Advanced Research Projects Agency (DARPA) began planning for a project called the Policy Analysis Market, which would have allowed investors to trade on geopolitical events, not unlike the Intrade Iran contract, including assassinations, wars and the next al-Qaeda attack. If the market – for which Hanson was an adviser – bid up a contract that would pay off if a terrorist attack occurred, the Department of Homeland Security might then decide to raise the threat condition status from yellow to red. Or so went the rationale.

No, PAM was not intended to warn us about individual terrorist attacks!  PAM was intended to forecast geopolitical trends – two Senators claimed otherwise based on a small miscellaneous section of a sample web page, but out of hundreds of articles on PAM it has been years since a journalist repeated this error.  As someone who grew up reading Scientific American, it is sad to see their standards sink so low. 

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  • “The only thing worse than being talked about is not being talked about.” Oscar Wilde

    Scientific American getting their facts wrong is annoying. However if you consider Popsci’s article and prediction market it runs it does now mean that a large number of people interested in science have been exposed to the use of prediction markets.

    So while their introduction may be biased they at least know about the topic.

  • Dr. Science

    I think the implication is that once laws are passed based on a prediction market, it stops being a prediction market and starts being a law-passing market, where people would play the market to get the most pork-barrel money flowing their way and ignore the prediction aspect. The SciAm author probably thought this was obvious enough to go without saying.

  • Dr, prediction markets seem encouragingly resistant to such manipulation.

  • Scientific American has definitely dumbed down its publication over the course of the past few decades. If you looked at an issue 20 years ago, there is no comparison to what it looks like today.

    I think when making predictions a lot of people suffer from “missing-piece-of-the-puzzleism, meaning they lack critical pieces information when making a prediction that give them an incomplete picture. I think its really hard to find a person who is knowledgable enough about a subject to make an accurate prediction. Having a high general intelligence and an extensive knowledge base helps, though. So I suspect that prediction markets reward people for having a high IQ and a more complete knowledge about a particular subject.

  • it stops being a prediction market and starts being a law-passing market, where people would play the market to get the most pork-barrel money flowing their way and ignore the prediction aspect.

    Not in a straightforward way, though. A market is resistant to simple manipulation. Betting insincerely is just throwing your money away. What it’s not resistant to is collusion between issue proposers and issue investors. I call it the Opacity Problem.

    On the futarchy discuss forum, we’ve talked about solutions to this and a few other apparent problems. You’re welcome to drop by and contribute.

  • It’s not a huge surprise that prediction markets would predict elections better than polls, seeing as your typical poll includes 1000 people. All that really means is predictive markets are better at sampling.

    Predictive markets based on a measure which cannot be influenced by a group of which the predictors are a sample would be a different story. Example: How good would a predictive market be at figuring out if there is water on Europa? Or if the Riemann hypothesis is true? Or how much electricity will be solar-generated by 2020?

    Policy decisions would be particularly sensitive, because presumably if you follow the markets you’re just following the will of the people. But with some things, particularly economics, what people think would be best may not actually be.