“Why Prediction Markets Beat Political Polls” is a headline on the cover of the March 2008 issue of Scientific American. The headline is a bit misleading because why or how prediction markets work is not all that clear. However, the fact that they outperform polls, based on the evidence of the Iowa Electronic Markets (IEM), is indisputable: The IEM example covering U.S. Federal elections between 1988 and 2004 demonstrates that markets beat polls 3 times out of 4. This is as true on the day of the election as it is 100 days in advance.
The basic distinction between polling and a prediction market, using the example of an election poll, is that the poll takes a representative sample to find out how the group is going to vote. Prediction markets allow a diverse group of people to predict (or bet) who’s going to win.
With risk-based regulation, there are times when the consequences of a wrong decision are high enough that a best guess isn’t good enough. Prediction markets, or information markets, as they are sometimes called, present a technique of tapping into the “wisdom of the crowds” to get a better reading. New types of markets can be developed to assist in regulatory decision making. Already, prediction markets have proven themselves in diverse areas such as disease forecasting, Hollywood box office success, and economic and financial forecasts.
Information Markets: A New Way of Making Decisions. This document captures the proceedings of a 2004 regulatory conference about information markets. The conference was hosted by the “Reg-Markets Center,” officially the AEI Center for Regulatory and Market Studies (formerly known as the AEI-Brookings Joint Center).
Our review of Wisdom of the Crowds by James Suroweicki.