Can Expert Prediction Markets Forecast Climate-Related Risks?

Abstract Prediction markets use a betting-like mechanism to aggregate information from disparate sources to produce probability forecasts that represent the collective view of participants. They have similarities with financial markets but are designed specifically to discover information rather than transfer assets or risks. Contracts that pay out a fixed amount if a well-defined event occurs are traded in these markets and, under certain conditions, the price at which these event-contracts trade can be interpreted as a probability estimate that the event will occur. This article examines the performance of 24 prediction markets for climate-related variables that have been run over the past 5 years. The predicted variables included the monthly temperature and rainfall for the United Kingdom, an index of El Niño–Southern Oscillation, Atlantic hurricane activity, and U.K. wheat yield. The markets had horizons of 2–12 months. Invitations to participate in the markets were extended to individuals and teams with relevant expertise. Participants did not have to pay to take part but did receive cash rewards based on their performance. Trades were made through an automated market maker overcoming the problems of low activity that have affected previous prediction markets for specialized topics. The predictions of the markets were consistent with good reliability, given the resolving power afforded by the sample size. Whether this level of reliability would persist for longer, multiyear, horizons relevant to climate change cannot be known without running markets on such time scales, something that we strongly advocate. Significance Statement Climate forecasting requires combining information from many disparate sources. Also, because forecasters cannot provide track records demonstrating skillful predictions decades ahead, it is difficult for forecast users to choose a provider. “Prediction markets” use the mechanics of betting to aggregate information and expertise into unified forecasts while rewarding forecasters for accuracy, removing the need to pick a single forecaster. Over the past 5 years, pilot prediction markets have been run for climate-related risks with horizons of up to 1 year. They produced forecast probabilities, which were consistent with the frequency with which outcomes occurred. Such markets could provide an innovative way to produce unified probabilistic climate forecasts on decadal horizons and allocate funds for forecasting research.