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
Data populates automatically once the FRED ingest pipeline is running.
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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