InTrade was not able to predict anything regarding the Fukushima nuclear energy plant. — [PREDICTION POST-MORTEM] –> See Jason Ruspini’s comment, by the way.

Jason: I can see how you might think that of Chris, but I think it is more true that as Chris acquired more knowledge about prediction markets, he became more skeptical. I have to admit that the same thing happened to me. It is inevitable, if you delve deeply into the literature. That doesn’t mean that prediction markets will never work, it just means that they don’t work now, at least not as robustly as they must.

In a limited set of circumstances, prediction markets can work, but to tout them as being “better” at predicting the future for virtually any type of outcome is ridiculous, naive, and downright misleading. While I thought Robin [Hanson] explained the concept well, he’s still a huge fan of prediction markets for just about everything. This is the problem.

The only thing I find odd about Chris’s viewpoint is that he seems to believe in the usefulness of public, real-money PMs. Oddly, I think Robin Hanson is too! While these markets *may* be “accurate”, I believe their usefulness is confined to being gambling venues.

Wikipedia on Ray Kurzweil’s predictions.

Ray Kurzweil’s prediction track record is investigated by IEEE Spectrum.

Background

This paper presents the outcome of a study conducted at the Royal Devon and Exeter Hospital in which a prediction market was established in order to forecast demand for services. To the researcher’s knowledge, it does not appear that prediction markets have been previously utilized in a healthcare environment.

Purposes

The purpose of this study is to provide evidence for the effective use of prediction markets in a healthcare environment.

Methodology and Approach

The study was conducted over a period of one week, and involved sixty-five participants. Each was asked to provide an estimate for demand for services at the Royal Devon and Exeter Hospital. Characteristics gathered for each participant included level of education, occupation, directorate, number of years worked for the hospital, and number of years worked for the National Health Service.

Findings

The study confirms the effectiveness of prediction markets to forecast future events as overall hospital demand was forecasted with an error of only 0.3%. The prediction market was less successful in predicting demand for services for each department, which the researcher attributes to the small sample size and lack of diversity of participants. Additionally, only a very small percentage of the characteristics captured registered a statistically significant correlation with the accuracy of the estimate. Further studies should focus on different characteristics and/or use a larger sample size to either confirm or refute the existence of such characteristics.

Practical Implications

The findings of this work could potentially be used as an innovative way to augment the forecasting function for a wide range of healthcare facilities. With the preliminary success of this study to forecast demand, further research in the field is warranted.

Followed from:

- Crowdsourcing and Prediction Markets: Right-Timing Revisited

Via the Spigit guy

No, I don’t mean the post-election gatherings by the candidates and their supporters, I mean the post-election gathering of academics and other researchers to assess what has been learned about the performance of prediction markets over the 2008 presidential campaign cycle.

I’ve checked the usual suspects and found nothing.

(The Southern Economic Association meeting this year is in Washington, D.C., a few weeks after the election. It would be an excellent time and place for an early post-mortem on the performance of prediction markets addressing the 2008 U.S. presidential election. But a look at the program doesn’t reveal any related panels. (The deadline for submission of abstracts was April 1, 2008.) In January 2008, the American Economic Association meetings featured a panel put together by Eric Zitzewitz. The next American Economic Association meeting is in San Francisco in January, but from my scan of the preliminary program no prediction market sessions are planned. (You really have to plan ahead for the AEA meetings, the deadline was February 28.))

This ongoing election cycle has featured an explosion of interest in political prediction markets, periodic allegations of manipulation and related analysis (and here, and here, and here, and here, etc.), innovations in market design (and disputations thereof) and various claims of market failure. A lot has happened. What have we learned?

Where is the post-election academic conference on prediction market performance?

(And, in a related question, where is the post-conference party going to be?)

What’s next?

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Do the economists like Robin Hanson agree with Tom W. Bell’s classification?

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