CARBON DIVIDENDS | SECTORAL BARGAINING
CLIMATE PREDICTION MARKET
How to link a carbon tax to climate forecasting
A 2011 paper by SHI-LING HSU suggests a way of using a carbon tax to generate more accurate predictions of future climate conditions:
“The market for tradable permits to emit in the future is essentially a prediction market for climate outcomes. And yet, unlike prediction markets that have been operated or proposed thus far, this prediction market for climate outcomes operates against the backdrop of an actual and substantial tax liability. Whereas prediction markets have heretofore largely involved only recreational trading, this prediction market will operate against a regulatory backdrop and thus will provide much stronger incentives for traders to acquire and trade on information.”
Link to the full paper.
A 2018 paper by GARY LUCAS and FELIX MORMANN suggests using similar predictions for climate policies beyond carbon taxes:
“We explain how both the federal and state governments could use prediction markets to help resolve high-profile controversies, such as how best to allocate subsidies to promote clean technology innovation and which policy strategy promises the greatest reduction in carbon emissions.”
Link to their paper.
- In 2016, a group of researchers modeled the way that information would converge in a climate prediction market, and found “market participation causes most traders to converge quickly toward believing the ‘true’ climate model, suggesting that a climate market could be useful for building public consensus.” Link.
- Tyler Cowen wrote about Hsu’s paper in 2011: “I think of such fine-tuning as a misguided approach. Is there such a good ‘basket’ measure of climate outcomes with sufficiently low short-term volatility?” Link.
- A 2017 paper by Michael Thicke makes a similar point about prediction models for science generally: “Prediction markets for science could be uninformative or deceptive because scientific predictions are often long-term, while prediction markets perform best for short-term questions.” Link.