How Do Prediction Markets Help Economic Forecasting?

In March 2026, Federal Reserve economists published research showing that prediction market data — specifically from Kalshi — performs as well as or better than traditional economic forecasting tools for predicting key macroeconomic variables including interest rate decisions, CPI inflation, nonfarm payrolls, unemployment, and GDP growth.

What the Fed Studied

The Federal Reserve research team analyzed Kalshi's event contracts on macroeconomic indicators, comparing their implied probabilities and probability distributions against established benchmarks:

• Bloomberg consensus estimates — surveys of professional economists
• Blue Chip economic forecasts — monthly surveys of ~50 top forecasters
• Federal funds futures — CME derivatives that imply market expectations for interest rates
• Survey of Market Expectations — the Fed's own survey of primary dealers and market participants

The researchers chose Kalshi because it "represents the most mature and comprehensive prediction market for economic forecasting," with contracts covering a broad range of macroeconomic events dating back to 2022.

Key Findings

Prediction markets match or beat professional surveys

For Federal Reserve rate decisions, Kalshi's implied probabilities tracked closely with federal funds futures — the gold standard for interest rate expectations. In several instances, Kalshi contracts captured probability shifts faster than survey-based measures because they update in real-time rather than on monthly or quarterly survey cycles.

Full probability distributions, not just point estimates

Traditional economic surveys produce a median forecast and sometimes a range. Prediction markets naturally generate complete probability distributions — you can see the market-implied probability of every possible outcome, not just the most likely one. This is particularly valuable for tail-risk analysis.

Real-time updating

Bloomberg surveys update monthly. Blue Chip forecasts update monthly. Prediction market prices update continuously. When a surprise economic release hits (an unexpected CPI print, a jobs number miss), prediction market prices adjust within minutes. Survey-based forecasts cannot do this.

Why This Matters Beyond Economics

The Fed study validates prediction markets as a serious analytical tool, which has ripple effects across the industry:

Legitimacy signal

When the Federal Reserve publishes research treating prediction markets as a valid data source, it undermines the argument that these platforms are "just gambling." This legitimacy extends to regulators, institutional investors, and potential enterprise customers.

Data monetization opportunity

Kalshi's prediction market data is now cited in Federal Reserve research. This creates a data licensing opportunity — financial institutions, hedge funds, and research firms will pay for access to prediction market pricing data if it demonstrably improves their forecasting.

Expansion to new categories

If prediction markets can forecast macroeconomic variables as well as professional surveys, the same mechanism can be applied to industry-specific predictions — iGaming market size, player behavior trends, regulatory outcomes, technology adoption rates.

What This Means for iGaming Operators

The Fed study has several implications for operators building prediction market products:

1. Institutional credibility drives volume. As prediction markets gain recognition as legitimate forecasting tools, institutional participants (trading firms, hedge funds) will bring significant volume. Operators who can attract institutional flow will benefit from deeper liquidity and tighter spreads.

2. Economic event contracts are a growth category. Sports is the most visible prediction market category, but economic events — rate decisions, inflation data, employment reports — generate consistent, high-frequency trading opportunities. Operators should consider economic contracts as part of their market catalog.

3. Data products are a revenue stream. The pricing data generated by prediction markets has standalone value. Operators can license their market data to financial institutions, media companies, and research organizations as an additional revenue line.

4. Cross-sell between financial and sports markets. Users who trade economic prediction markets may also trade sports markets, and vice versa. A multi-category platform captures more wallet share than a single-category one.

Limitations

The Fed study acknowledged several limitations:

• Liquidity constraints: Kalshi's macroeconomic markets are less liquid than federal funds futures, which means prices can be more volatile and less informationally efficient in thin-market conditions
• Limited history: Kalshi data begins in 2022, providing only ~4 years of comparison. More data is needed to assess performance across full economic cycles
• Selection bias: The study only examined Kalshi, the most established economic prediction market. Results may not generalize to less mature platforms

FAQ

Did the Federal Reserve endorse prediction markets?

Not officially. The research was published by Fed economists as a working paper, not as a policy statement. However, the paper's tone is notably positive, describing prediction markets as a "valuable research tool" — a significant endorsement from the world's most influential central bank.

Are prediction markets better than polls for economic forecasting?

For short-term economic events (next month's CPI, next Fed meeting), prediction markets appear comparable to or slightly better than professional surveys, primarily because they update in real-time. For longer-term forecasts (annual GDP, multi-year trends), the evidence is less clear.

Can regular users benefit from prediction market economic data?

Yes. Even if you do not trade economic prediction markets, the probability data they generate is useful for decision-making — understanding the market-implied probability of a rate cut, for example, can inform investment and business decisions.