Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations
On prediction markets
Does this idea seem ludicrous? Since 1988, the University of Iowa has run the Iowa Electronic Markets, which allow people to bet on the outcome of presidential elections. As a predictor, the Iowa Electronic Markets have produced extraordinarily accurate judgments, often doing better than professional polling organizations. In the week before each of the last four elections, the predictions in the Iowa market have shown an average absolute error of just 1.5 percentage points, a significant improvement over the 2.1 percentage point error in the final Gallup Polls. Or consider the Hollywood Stock Exchange, in which people predict Oscar nominees and winners, as well as opening weekend box-office successes. Here, too, the level of accuracy has been exceptionally impressive, with (for example) correct predictions of thirty-five out of forty Oscar nominees in 2002.
Surowiecki might object that some crowds can be wise even when ignorance is widespread. Consider the astonishing accuracy of the Iowa Electronic Markets (and other prediction markets), in which good judgments come from groups of investors that include many people who know little and are perhaps more likely to be wrong than to be right. But we cannot easily generalize from prediction markets, because they have several distinctive features. Most important, they do not simply rely on the median or average judgment of a randomly selected group of people. They are genuine markets, in which people voluntarily choose to participate, presumably because they think they know something. In addition, people are permitted to buy and to sell shares on a continuing basis. In these circumstances, accurate answers can emerge even if only a small percentage of participants have good information.
In the Iowa Electronic Markets, it turns out that 85 percent of the traders aren't so smart. They hold onto their shares for a long period and then just accept someone else's prices. The market's predictions appear to be driven by the other 15 percent--frequent traders who post their offers rather than accepting those made by other people. The broader point is that to work well, prediction markets do not require accurate judgments by anything like the majority of participants. In this sense, prediction markets are very different from judgments by ordinary crowds. Surowiecki's claims about group wisdom don't adequately emphasize the unique characteristics of these markets.