# Average Weekly Earnings: Total Private — Waterbury-Shelton, CT (NSA)

Average Weekly Earnings: Total Private — Waterbury-Shelton, CT (NSA) was down 3.1% year on year in September 2026, compared with −3.3% in August 2026.
The level stood at 1,152.8 USD/week.
Over the past ten years it has ranged from −5.7% (May 2023) to 13.6% (Jan 2025), averaging 2.5%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-47930.AWE.M.NSA.IND-05000000`
- Frequency: monthly
- Units: USD/week
- Coverage: 2011-01-01 to 2026-09-01 (189 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/average-weekly-earnings-total-private-waterbury-shelton-ct-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,152.8 USD/week | −3.1 |
| August 2026 | 1,138.7 USD/week | −3.3 |
| July 2026 | 1,142.8 USD/week | −3.1 |
| June 2026 | 1,143.7 USD/week | −3.4 |
| May 2026 | 1,109.6 USD/week | −5.2 |
| April 2026 | 1,121.4 USD/week | −3.8 |
| March 2026 | 1,138.9 USD/week | −2.1 |
| February 2026 | 1,135.3 USD/week | −0.3 |
| January 2026 | 1,142.3 USD/week | −1.8 |
| December 2025 | 1,182.7 USD/week | 3.5 |
| November 2025 | 1,185.0 USD/week | 2.9 |
| October 2025 | 1,171.9 USD/week | 3.0 |
| September 2025 | 1,189.2 USD/week | 6.5 |
| August 2025 | 1,177.5 USD/week | 8.6 |
| July 2025 | 1,179.2 USD/week | 8.2 |
| June 2025 | 1,184.3 USD/week | 6.1 |
| May 2025 | 1,170.0 USD/week | 7.9 |
| April 2025 | 1,165.9 USD/week | 6.9 |
| March 2025 | 1,163.1 USD/week | 9.6 |
| February 2025 | 1,138.4 USD/week | 11.6 |
| January 2025 | 1,163.3 USD/week | 13.6 |
| December 2024 | 1,142.6 USD/week | 8.3 |
| November 2024 | 1,151.2 USD/week | 10.3 |
| October 2024 | 1,137.7 USD/week | 8.7 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-47930.AWE.M.NSA.IND-05000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-47930.AWE.M.NSA.IND-05000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```