Three researchers affiliated with the US Federal Reserve argued in a Feb. 12 paper that prediction market platform Kalshi could better measure macroeconomic expectations in real time than traditional tools.
In “Kalshi and the Rise of Macro Markets,” the authors compared Kalshi data with surveys and market-implied forecasts, concluding that managing expectations is central to modern macroeconomic policy and that existing tools have drawbacks.
“Kalshi markets provide a high-frequency, continuously updated, distributionally rich benchmark that is valuable to both researchers and policymakers,”
The researchers wrote, adding that the platform captures market beliefs directly and in real time.
Kalshi allows traders to bet on outcomes tied to Federal Reserve decisions, including inflation, payroll data, GDP growth and gas prices, generating live probability estimates around policy moves.
The researchers proposed using Kalshi data to construct risk-neutral probability density functions for Federal Open Market Committee meetings, arguing that current benchmarks are too removed from actual rate decisions.
They highlighted Kalshi’s “rich intraday dynamics,” noting that implied odds of a July rate cut rose to 25% after remarks from Governors Christopher Waller and Michelle Bowman before falling following a stronger-than-expected employment report.
However, the paper is described as preliminary research meant to stimulate discussion and does not represent official Federal Reserve policy, even as prediction markets have surpassed $10 billion in monthly trading volume and face ongoing regulatory scrutiny.