Analysis: Kalshi Did Not Significantly Outperform Traditional Economists in U.S. Nonfarm Payrolls Forecasting

According to Bloomberg, academic research and Bloomberg data analysis show that prediction market platform Kalshi has not yet demonstrated a statistically significant advantage over traditional economists in forecasting U.S. nonfarm payrolls. Over the past 33 months, the average forecast error of Kalshi traders and Bloomberg survey economists both exceeded 60,000 jobs—showing no statistically meaningful edge. For example, in April 2026, when the official U.S. nonfarm payroll report revealed an increase of 178,000 jobs, Kalshi’s final forecast error exceeded 90,000 jobs. Some Wall Street economists argue that prediction markets resemble “a new form of gambling,” offering limited analytical value for deeper labor-market structural data.