Kalshi Prediction Markets Match or Beat Traditional Forecasting Tools For Macro Indicators, NBER Study Finds

A groundbreaking new working paper from the National Bureau of Economic Research (NBER) is sending shockwaves through the worlds of economics, finance, and technology. The research, authored by experts from the Federal Reserve, Northwestern University’s Kellogg School of Management, and Johns Hopkins University, delivers a stunning verdict: Kalshi, the largest federally regulated prediction market in the United States, is now producing macroeconomic forecasts that are on par with—or even superior to—those generated by professional economists and traditional financial instruments.

For years, Wall Street’s elite, central bankers, and academic economists have relied on surveys like the New York Fed’s Survey of Market Expectations and instruments such as fed funds futures to gauge the future direction of interest rates, inflation, and unemployment. But according to this new research, a relatively young player in the financial technology space is now outperforming these established tools.

Kalshi, which operates under the watchful eye of the Commodity Futures Trading Commission (CFTC), has quietly become a powerhouse for real-time, crowd-sourced economic intelligence. The NBER paper compared Kalshi’s implied forecasts for the federal funds rate, Consumer Price Index (CPI) inflation, and unemployment against those from both the New York Fed’s survey and Bloomberg’s consensus estimates. The results were nothing short of remarkable.

For the federal funds rate—arguably the most closely watched economic indicator—Kalshi’s modal forecast correctly predicted the rate on the very day before every Federal Open Market Committee (FOMC) meeting since 2022. Neither the New York Fed’s survey nor fed funds futures managed to achieve this level of accuracy. When it came to forecasting headline CPI inflation, Kalshi’s median and modal predictions produced statistically significant improvements over the Bloomberg consensus.

But what truly sets Kalshi apart is its ability to fill a void that no other financial market has addressed: the provision of real-time probability distributions for a range of key economic indicators, including GDP growth, core CPI, unemployment, and nonfarm payrolls. This means that, for the first time, investors, policymakers, and the public can see not just a single point estimate for where the economy might be headed, but a full distribution of possible outcomes—updated in real time as new data and news emerge.

The paper goes further, documenting how these probability distributions shift in response to macroeconomic news. For example, positive surprises in CPI data moved the mean of the federal funds rate distribution four times more than negative surprises—a finding that underscores the market’s sensitivity and responsiveness to real-world events.

Trading volumes on Kalshi have exploded, reaching nearly 100 million contracts for a single FOMC meeting. This surge in activity has been supported by liquidity from some of the biggest names in quantitative trading, including Susquehanna, Citadel, and Two Sigma. The involvement of these firms not only lends credibility to Kalshi’s platform but also ensures that its markets remain deep and efficient, even during periods of high volatility.

The implications of this research are profound. If prediction markets like Kalshi can consistently outperform traditional forecasting methods, they could become indispensable tools for central banks, hedge funds, and policymakers. The ability to tap into the collective wisdom of thousands of traders, each incentivized to make accurate predictions, offers a powerful alternative to the subjective judgments of a small group of experts.

Moreover, the transparency and real-time nature of Kalshi’s forecasts could democratize access to high-quality economic intelligence. No longer would such insights be the exclusive domain of Wall Street insiders or government officials; anyone with an internet connection could track the market’s evolving view of the economy.

Of course, the rise of prediction markets is not without controversy. Critics have raised concerns about the potential for manipulation, the ethical implications of betting on economic outcomes, and the risk that such markets could exacerbate financial instability. Regulators will need to remain vigilant to ensure that these platforms operate fairly and transparently.

Nevertheless, the evidence presented in this NBER paper is hard to ignore. Kalshi has not only proven its mettle as a forecasting tool but has also demonstrated the transformative potential of financial technology. As the boundaries between traditional finance, technology, and collective intelligence continue to blur, prediction markets may well become a central feature of the economic landscape.

In an era where the pace of change is accelerating and uncertainty is the only constant, the ability to harness the wisdom of the crowd—backed by rigorous regulation and cutting-edge technology—could prove to be one of the most valuable innovations of our time. Kalshi’s rise is a testament to the power of markets to aggregate information and anticipate the future, and its story is only just beginning.

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