# All Employees: Private Service Providing — Waterbury-Shelton, CT (NSA)

All Employees: Private Service Providing — Waterbury-Shelton, CT (NSA) was down 0.3% year on year in September 2026, compared with 0.7% in August 2026.
The level stood at 114.4 thousands.
Over the past ten years it has ranged from −20.7% (Apr 2020) to 17.4% (Apr 2021), averaging 0.08%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-47930.PAYEMS.M.NSA.IND-08000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-private-service-providing-waterbury-shelton-ct-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 114.4 thousands | −0.3 |
| August 2026 | 115.6 thousands | 0.7 |
| July 2026 | 116.5 thousands | 1.0 |
| June 2026 | 116.5 thousands | −0.2 |
| May 2026 | 115.0 thousands | −0.8 |
| April 2026 | 113.5 thousands | −0.8 |
| March 2026 | 112.4 thousands | −0.8 |
| February 2026 | 112.3 thousands | −0.2 |
| January 2026 | 112.9 thousands | −0.5 |
| December 2025 | 115.2 thousands | −0.2 |
| November 2025 | 114.9 thousands | −0.09 |
| October 2025 | 115.3 thousands | −0.3 |
| September 2025 | 114.7 thousands | −0.6 |
| August 2025 | 114.8 thousands | −0.09 |
| July 2025 | 115.4 thousands | 0.0 |
| June 2025 | 116.7 thousands | 0.9 |
| May 2025 | 115.9 thousands | 1.2 |
| April 2025 | 114.4 thousands | 1.1 |
| March 2025 | 113.3 thousands | 0.6 |
| February 2025 | 112.5 thousands | 0.9 |
| January 2025 | 113.5 thousands | 1.0 |
| December 2024 | 115.4 thousands | 0.3 |
| November 2024 | 115.0 thousands | 0.2 |
| October 2024 | 115.6 thousands | 0.6 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-47930.PAYEMS.M.NSA.IND-08000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-47930.PAYEMS.M.NSA.IND-08000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```