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Data from U.S. Bureau of Labor Statistics. Forecasts by Sigmanomics Forecast Engine.
United StatesUS Nonfarm Productivity QoQ fell to 0.3% in Q1 2026
U.S. Bureau of Labor StatisticsMonthlyReleased June 2026
US Nonfarm Productivity QoQ fell to 0.3% in Q1 2026, released June 2026, down 1.3% from December's 1.6% reading. The reading missed the 0.5% consensus by 0.2%. Nonfarm Productivity QoQ has now declined for 5 consecutive months. Over the past 3 months, Nonfarm Productivity QoQ averaged 1.3%, vs 4.2% in the prior 3-month window. Nonfarm Productivity QoQ is now the lowest in 10 months.
Latest Release
0.3
Actual
0.5
Consensus
1.6
Previous
Median Absolute Error
±0.37 percentage points
across last 12 releases
Last Call
Jun 2026
Predicted: 0.4
Actual: 0.3
Error: +0.1
Sigmacast Σ-direction model: consensus + ½ × mean(surprise, trailing 90d).
CORRELATED SYMBOLS— markets that historically move with this indicator
| Symbol | Direction | Correlation | Asset Class | Signal Bias | Action |
|---|---|---|---|---|---|
| GOOGL | ▲ Direct | +0.66 | STOCKS | Bullish GOOGL | → View |
| AAPL | ▲ Direct | +0.56 | STOCKS | Bullish AAPL | → View |
| GBP/USD | ▲ Direct | +0.34 | FOREX | Bullish GBP | → View |
| USD/CAD | ▲ Direct | +0.30 | FOREX | Bullish USD | → View |
Correlation based on 12-month rolling window. Click any symbol to view its Sigmanomics forecast page.
THE RELEASE
Nonfarm Productivity QoQ (United States) was reported at 0.3% in June 2026. This missed the market consensus of 0.5% by 0.2%. The reading fell from the previous value of 1.6%. Trailing 12-month context per ETL data through June 2026. Over the past 12 months, the indicator has averaged 2.91%, ranging from 0.3% to 4.9% across 7 releases.
WHY IT MATTERS
The indicator has been trending downward over the last three releases. The trailing three releases averaged 1.63%, down from the prior three at 4.37%. Volatility over the past year (σ 1.53%) is comparable than the prior year (σ 1.43%). In June readings over the past 3 years, Nonfarm Productivity QoQ has averaged -0.33%.
THE MODEL'S TAKE
Historically, this indicator is positively correlated with GOOGL (Bullish GOOGL). A secondary relationship exists with AAPL, positively correlated (Bullish AAPL). Over the last 12 releases, the Sigmacast model's median absolute error is 0.38%.
WHAT TO WATCH NEXT
Same-country events in the next 14 days include MBA 30-Year Mortgage Rate (Jun 17) and Retail Sales MoM (Jun 17).
Auto-generated from current model state · Refreshes on each release · Last update June 2026.
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Nonfarm Productivity QoQ - US
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About Nonfarm Productivity QoQ — United States
DEFINITION
Nonfarm Productivity QoQ (Quarter over Quarter) is a key financial indicator that measures the efficiency and output of businesses and industries in the nonfarm sector. It calculates the change in productivity from one quarter to the next, providing valuable insights into the overall health and growth of the economy. This indicator is closely monitored by investors, policymakers, and analysts as it can impact economic growth, inflation, and labor market trends. A positive Nonfarm Productivity QoQ indicates increased efficiency and output, while a negative reading may suggest a decline in productivity.
WHY THIS INDICATOR MATTERS
This release contributes to the broader macro picture used by cross-asset investors for positioning and risk management. Surprises against consensus can drive short-term moves, particularly when the print breaks an established trend. Released monthly.
WHAT CHANGED THIS MONTH
Latest reading (Jan 2026): actual 0.3 %, consensus 0.5 %. Prior reading (Jan 2026): 0.8 %. Before that (Oct 2025): 2.8 %.
WHAT'S NEXT
Sigmacast's 1-month forecast points to a materially lower reading versus the latest print, with the 3-month outlook reinforcing that direction. Both horizons are aligned bearish for this indicator, suggesting a consistent trend signal. Trend-driven dynamics are the primary headwind in the current projection. This indicator correlates most strongly with GOOGL (Bullish GOOGL, r=0.66) — a useful reference for stocks-focused traders.