Predictocracy — A Preliminary Response

Thanks to Robin for posting a mini-review of Predictocracy. We’ve promised to debate the relative merits of a “futarchy” and a “predictocracy” later.

I’ll use this opportunity to respond briefly to his criticism (while gratefully accepting his praise). I agree that it’s best when technical designs for prediction markets can be supported by mathematical models or empirical evidence. At the same time, I didn’t want to scare away readers by including math. Meanwhile, I agree that field experiments can be helpful, and I am developing a web site that will test some of the ideas of the book (subject, of course and unfortunately, to legal restrictions). While recognizing the contributions of experimental economics, I doubt that laboratory experiments will be of much use in persuading skeptics that prediction markets can be useful in real-world institutions.

Nonetheless, almost all of the market designs that I describe in the book already have some support of the kind that Robin recommends (in some cases by Robin himself). For example, I previously offered a mathematical elaboration of “deliberative markets,” which seek to encourage participants to seek to persuade others that their predictions are correct.

Admittedly, there are a few exceptions. The incentives provided by two of my technical proposals (the decentralized subsidy approach and the nobody-loses prediction market) are sufficiently straightforward to me that math seems superfluous to me, though I agree that field tests comparing these with alternatives would be useful. Two of the proposals (the text-authoring market and the market web) could certainly benefit from experimentation, but the software needed to implement them would be considerably more complicated than what is needed for existing prediction markets.

A concluding thought: Robin’s articles are generally ridiculously underplaced in comparison to both their quality and their influence. But certainly I’m glad that Robin didn’t wait to publish his articles on science claims and futarchy until he had developed mathematical models or laboratory experiments. I don’t think that they would have added much. Academia may well be biased against articles whose primary thrust is to propose new institutions; I’ve also generally had better luck in placing more conventional articles. But I still think that such articles perform a useful function, and while they should include support, there may be an efficient division of labor between those who sketch out broad ideas and those who elaborate them (with or without mathematical models) or test them (in laboratory and field experiments). This is particularly so when the practical reality is that many different forms of elaboration and confirmation will be necessary before new institutions can be adopted.

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  • Looks like your web site is still under construction? Most of the links at the left don’t work. The link to “blog” does work, but the blog seems to be composed of excerpts from the book – is that right? Anyway that part seems to be the most interesting right now. I started reading that and ran into a small error right away: paragraph 2:

    “Someone who thinks that an event has more than a 75 percent chance of occurring offers to place three quarters against the single quarter of any challenger. Someone else who thinks that an event has less than a 25 percent chance of occurring would have a financial incentive to take that bet.”

    This is a typo, the 25 should be 75, assuming that by “an event” you mean “the event” in the 2nd sentence.

    I am curious about the methodology you suggest for improving the quality of information supplied by mass media:

    “With regard to some issues, ‘just the facts’ may be all the public needs, but in many cases an important fact may be what the consensus opinion about the issue is or whether such a consensus exists. This chapter suggests that prediction markets can provide objective gauges of expert consensus for the media to pass along to the public.”

    Would this be done by creating a prediction market which was only open to experts? Or by the process you described earlier (if I understood it) where the general public bets on what he would say if you surveyed a random academic on the issue?

    One final comment, it might be helpful to discuss the well known failures of markets such as bubbles. As we witness a global economic system shaken to its foundations by what was apparently an enormous market failure regarding pricing of real estate loans, any proposal for greater emphasis on market mechanisms must be prepared to overcome considerable skepticism.

  • Neel Krishnaswami

    Do you discuss how to generate liquidity in these markets? This is the point where I find it hardest to imagine reliable, scalable ways of getting off the ground, so that’s what I’d be most interested in reading about.