Nonfarm Payrolls — Impact on Fed Rate Prediction Markets
The Fed has a dual mandate: price stability AND maximum employment. A blowout jobs number means the economy can handle higher rates, reducing the case for cuts.
+/-
per 1σ surprise
↑ Hawkish
when high vs consensus
Pre-calibration
data points
Release Schedule
Frequency
Monthly
Release time
8:30 AM ET
Delay
First Friday of the following month
FRED series
PAYEMS
Historical Releases
| Period | Actual | Consensus | Surprise |
|---|---|---|---|
| Apr 2026 | 158736.0 | — | — |
How Nonfarm Payrolls Moves Fed Rate Prediction Markets
Monthly change in employed workers across all non-farm sectors — the headline jobs report number.
The Fed has a dual mandate: price stability AND maximum employment. A blowout jobs number means the economy can handle higher rates, reducing the case for cuts.
The Bayesian Sensitivity Model
The model calibrates a sensitivity coefficient for each indicator: how many percentage points the cut probability at the next FOMC meeting moves per standard deviation of surprise. For NFP, the preliminary coefficient is ±+/- 4–8pp on cut probability. This means ifNFP comes in 1 standard deviation above consensus (hawkish surprise), the model reduces cut probability by approximately +/- 4–8pp on cut probability.
These coefficients are preliminary until calibrated from at least 20 historical observations of Kalshi price reactions to each release. The calibration uses a regression of (surprise_zscore × sensitivity_coefficient) against observed Kalshi probability changes, cross-validated against CME FedWatch data going back to 2015.
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