- The paper, written by researchers at the Universities of Lancaster and Exeter, explains how expert ‘prediction markets’ might enhance climate-risk estimates that influence crucial economic and governmental choices.
- Organizations realize that they must incorporate climate risks into their strategic planning, whether physical hazards to buildings and locations or risks linked with the transition to net zero emissions.
- However, the researchers claim that the forward-looking knowledge required to support these strategic decisions is restricted.
- The authors explain how expert ‘prediction markets’ can help overcome structural problems and shortfalls in providing forward-looking climate-risk information in their paper, ‘Prediction-market Innovations Can Improve Climate-Risk Forecasts,’ which will become more important as demand for long-term climate information grows.
- These long-term markets have yet to emerge, partly due to legislative impediments.
An article by scientists at the Universities of Lancaster and Exeter, published in the journal Nature Climate Change, reveals how expert ‘prediction markets’ could improve the climate-risk estimates that influence crucial commercial and regulatory choices. Organizations today recognize the need to include climate risks in their strategic planning, whether physical hazards to buildings and sites or risks linked with the transition to net zero emissions.
Prediction markets can provide the knowledge required for strategic decisions
However, the researchers claim that the forward-looking knowledge required to support these strategic decisions is restricted. “The institutional arrangements under which climate-risk information is currently provided mirrors the incentive problems and conflicts of interest that prevailed in the credit-rating industry before the 2007/8 financial crisis,” said Dr. Kim Kaivanto, a co-author from Lancaster University’s Department of Economics.
“In order to make sense of emissions scenarios and to support planning and decision-making, organisations have a pressing need for this type of forward-looking expert risk information. Understanding climate risks requires diverse and complementary expertise from political science, economics and policy, as well as country-specific knowledge on the major emitters. Prediction markets incentivise and reward participants with distinct expertise and information to come forward — and they offer a level playing field for experts from these complementary fields of expertise.”
“If providers of climate forecasts are paid upfront irrespective of accuracy, you don’t need to be an economist to spot the problem with that arrangement,” said Mark Roulston, one of the Exeter University co-authors.
The authors explain how expert ‘prediction markets’ can help overcome structural problems and shortfalls in the provision of forward-looking climate-risk information in their paper, ‘Prediction-market innovations can improve climate-risk forecasts’, which will become more important as demand for long-term climate information grows.
What are prediction markets?
Prediction markets are intended to incentivize persons with vital knowledge to come forward and to allow information aggregation through the buying and selling contracts that result in a predetermined reward if the stated event happens.
An result of interest, such as average CO2 concentration in the year 2040, is divided into intervals. Expert participants compare their modeling findings to the pricing of these intervals and buy or sell claims if their model indicates that the price is too low or too high.
The price of a contract may be read as the market-based likelihood of the event occurring in a well-designed market, such as Lancaster University’s AGORA prediction-market platform. These types of long-term markets have yet to emerge, partly due to legislative impediments.
The researchers, however, think that the markets may be built to overcome these difficulties by eliminating the ‘pay-to-play’ feature of present prediction markets, in which the losses of less-well-informed individuals support the gains of better-informed ones.
Instead, markets can be arranged as vehicles for dividing up research funding to experts and modelers in accordance with the principles of effective altruism: an initial stake provided by a sponsor is distributed to participants in proportion to the quality and quantity of information they bring into the market through trading activity.
They note that access to market participation would require selection criteria to guarantee variety of viewpoints and a breadth of skills to combine various sources of information. Kim Kaivanto of Lancaster University and Mark Roulston, Todd Kaplan, and Brett Day of the University of Exeter wrote the study.