Job Openings vs Nonfarm Payrolls: Correlation Analysis
Pearson correlation of daily returns for JOLTS Job Openings and Nonfarm Payrolls. Rolling windows, yearly breakdown, regression beta, and divergence analysis. Data window spans to (57 aligned observations).
What the Number Means
With a correlation of 0.14, JOLTS Job Openings and Nonfarm Payrolls are essentially uncorrelated at daily frequency. Either the relationship operates at a different time horizon or the shared driver has been dominated by idiosyncratic noise during the observation window.
Recent vs Long-Run Behavior
Recent correlation tracks the long-run relationship closely. No meaningful divergence. The historical pattern between JOLTS Job Openings and Nonfarm Payrolls is intact and should continue to serve as a reasonable baseline for positioning.
Statistical Details (1-Year Window)
| Pearson Correlation (r) | +0.142 |
| R-Squared (r²) | 0.020 |
| Beta (JOLTS Job Openings vs Nonfarm Payrolls) | 4.432 |
| Daily Volatility σ(JOLTS Job Openings) | 4.51% |
| Daily Volatility σ(Nonfarm Payrolls) | 0.14% |
| Observations | 57 |
Correlation measures directional co-movement; R² quantifies the fraction of variance explained by the linear relationship. Beta is the slope coefficient from regressing JOLTS Job Openings returns on Nonfarm Payrolls returns. A beta above 1 means the first asset amplifies moves of the second.
Year-by-Year Correlation
| Year | Correlation | Strength | Observations |
|---|---|---|---|
| 2026 | — | Insufficient data | 4 |
| 2025 | +0.068 | Essentially uncorrelated | 12 |
| 2024 | -0.308 | Weak negative | 12 |
| 2023 | -0.206 | Weak negative | 12 |
| 2022 | +0.281 | Weak positive | 12 |
| 2021 | +0.653 | Strong positive | 5 |
Year-by-year correlation reveals how the relationship has held up across different macro regimes. Sharp year-over-year swings in correlation often mark the transition between stress and calm periods.
Methodology
Correlations are computed on daily log-adjacent returns for JOLTS Job Openings and Nonfarm Payrolls, aligned on shared trading dates. We use the Pearson product-moment coefficient, which measures the linear relationship between two return series.
Windows are the most recent N observations for 30D, 90D, and 1Y (252 trading days); the 5Y figure uses all aligned data up to 1,260 observations. Beta is the OLS slope from regressing the first series on the second. Data updates daily with a 24-hour revalidation cadence.
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Get daily macro analysis on shifting correlations, regime transitions, and cross-asset signals.
Correlation is not causation and backward-looking statistics can fail when regimes shift. Positions sized on historical correlation assumptions should be stress-tested against scenarios where the relationship breaks. For informational purposes only.