Economists have pushed for prediction markets. They're not what they'd hoped for
Economists who long advocated for prediction markets as a way to improve forecasting are finding the reality disappointing, as these betting platforms have not lived up to their theoretical promise and instead face issues with accuracy, manipulation, and legality.
Background
Prediction markets (like PredictIt or Kalshi) let people bet on future events — election outcomes, interest rate moves, etc. — and the prices are supposed to act like crowd-sourced probabilities. Many economists championed them as more accurate than polls or expert surveys. But by mid-2026, real-world prediction markets have been plagued by low liquidity (too few traders), manipulation risks (a single whale can move a price), and regulatory whiplash in the U.S. as the CFTC has allowed some and blocked others. The result: prices that often diverge wildly from survey-based forecasts, disappointing the economists who saw them as a forecasting panacea. This article examines why the theoretical ideal hasn't matched reality.