# All Employees: Services to Buildings and Dwellings — CO (statewide) (NSA)

All Employees: Services to Buildings and Dwellings — CO (statewide) (NSA) was down 2.0% year on year in September 2026, compared with −3.8% in August 2026.
The level stood at 50.00 thousands.
Over the past ten years it has ranged from −8.8% (Mar 2025) to 11.4% (Apr 2021), averaging 1.0%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-CO.PAYEMS.M.NSA.IND-60561700`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-services-to-buildings-and-dwellings-co-statewide-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 50.00 thousands | −2.0 |
| August 2026 | 50.30 thousands | −3.8 |
| July 2026 | 51.40 thousands | −2.3 |
| June 2026 | 51.10 thousands | −1.5 |
| May 2026 | 49.80 thousands | −2.2 |
| April 2026 | 48.30 thousands | 1.5 |
| March 2026 | 46.10 thousands | 6.0 |
| February 2026 | 44.70 thousands | 3.7 |
| January 2026 | 43.60 thousands | 0.7 |
| December 2025 | 45.30 thousands | 1.8 |
| November 2025 | 47.70 thousands | 0.2 |
| October 2025 | 50.10 thousands | 0.8 |
| September 2025 | 51.00 thousands | 1.0 |
| August 2025 | 52.30 thousands | 0.8 |
| July 2025 | 52.60 thousands | 0.8 |
| June 2025 | 51.90 thousands | 0.4 |
| May 2025 | 50.90 thousands | 2.6 |
| April 2025 | 47.60 thousands | −2.9 |
| March 2025 | 43.50 thousands | −8.8 |
| February 2025 | 43.10 thousands | −6.7 |
| January 2025 | 43.30 thousands | −5.0 |
| December 2024 | 44.50 thousands | −4.5 |
| November 2024 | 47.60 thousands | −0.8 |
| October 2024 | 49.70 thousands | 0.4 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-CO.PAYEMS.M.NSA.IND-60561700"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-CO.PAYEMS.M.NSA.IND-60561700",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```