Forrest D. Nelson

The Promise of Prediction Markets

The ability of groups of people to make predictions is a potent research tool that should be freed of unnecessary government restrictions.

Use of Prediction Markets to Forecast Infectious Disease Activity

Prediction markets have accurately forecasted the outcomes of a wide range of future events, including sales of computer printers, elections, and the Federal Reserves decisions about interest rates. We propose that prediction markets may be useful for tracking and forecasting emerging infectious diseases, such as severe acute respiratory syndrome and avian influenza, by aggregating expert opinion quickly, accurately, and inexpensively. Data from a pilot study in the state of Iowa suggest that these markets can accurately predict statewide seasonal influenza activity 2-4 weeks in advance by using clinical data volunteered from participating health care workers. Information revealed by prediction markets may help to inform treatment, prevention, and policy decisions. Also, these markets could help to refine existing surveillance systems.

Chapter 80 Results from a Dozen Years of Election Futures Markets Research

Introduction and description of election futures markets The Iowa Electronic Markets are small-scale, real-money futures markets conducted by the University of Iowa College of Business. In this review we focus on the best known of these markets, The Iowa Political Markets. Contracts in these markets are designed so that prices should predict election outcomes. The data set contains the results of 49 markets covering 41 elections in 13 countries. The Iowa Markets operate 24-hours a day, using a continuous, double-auction trading mechanism. Traders invest their own funds, make their own trades, and conduct their own information search. The markets occupy a niche between the stylized, tightly controlled markets conducted in the laboratory and the information-rich environments of naturally occurring markets. By virtue of this design, the Iowa Markets provide data to researchers that is not otherwise available.