Researchers at the U.S. Federal Reserve have released a paper highlighting the growing usefulness of prediction markets as a real time tool for economic analysis. The study examined performance data from Kalshi, a regulated U.S. prediction market platform, and concluded that such markets can offer statistically significant improvements over traditional forecasting methods in certain areas.
According to the research, Kalshi’s forecasts for the federal funds rate and the U.S. Consumer Price Index demonstrated measurable advantages when compared with fed funds futures and professional survey based forecasts. One notable distinction was the ability of prediction markets to provide continuously updated probability distributions rather than infrequent point estimates. This feature allows policymakers and analysts to observe not only the most likely outcome but also the full range of market implied expectations.
The paper found that since 2022, Kalshi’s contracts tracking the federal funds rate matched the realized rate by the day of each Federal Open Market Committee meeting. The researchers noted that this level of alignment was not achieved by either survey forecasts or futures markets during the same period. The implication is that aggregated crowd expectations, when properly structured, may capture evolving economic signals faster than traditional institutional channels.
Beyond interest rates, the study emphasized the value of prediction markets for economic variables where no other market based probability distributions exist. Gross domestic product growth, core inflation, unemployment, and payroll data were cited as examples where prediction contracts can provide unique forward looking insights. These markets allow participants to buy and sell contracts tied to specific economic outcomes, creating price signals that reflect collective expectations.
One factor identified as contributing to the effectiveness of prediction markets is the participation of retail investors alongside professional traders. Unlike institutionally dominated futures markets, prediction platforms often include a broader cross section of participants. Researchers suggested that this diversity may enhance information aggregation by incorporating a wider range of perspectives and decentralized data inputs.
The Federal Reserve paper does not position prediction markets as a replacement for established tools such as futures pricing or economist surveys. Instead, it frames them as a complementary data source that can enrich policy analysis. By offering continuously updated probabilities, prediction markets may help policymakers gauge shifts in sentiment between official data releases and scheduled meetings.
Kalshi operates under U.S. regulatory oversight, which distinguishes it from offshore or unregulated prediction platforms. Its structure allows participants to trade contracts on binary outcomes across economics, politics, and other sectors, while maintaining compliance with commodity market rules.
The research arrives amid increasing interest in alternative data sources for macroeconomic forecasting. As policymakers seek more responsive tools to interpret evolving economic conditions, prediction markets are gaining recognition as a measurable and transparent input into the broader analytical framework.
