# All Employees: Employment Services — Dallas-Fort Worth-Arlington, TX (NSA)

All Employees: Employment Services — Dallas-Fort Worth-Arlington, TX (NSA) was up 5.9% year on year in September 2026, compared with 9.3% in August 2026.
The level stood at 140.0 thousands.
Over the past ten years it has ranged from −20.5% (Apr 2020) to 34.2% (Apr 2021), averaging 1.8%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-19100.PAYEMS.M.NSA.IND-60561300`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-employment-services-dallas-fort-worth-arlington-tx-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 140.0 thousands | 5.9 |
| August 2026 | 139.2 thousands | 9.3 |
| July 2026 | 133.3 thousands | 7.2 |
| June 2026 | 133.8 thousands | 6.4 |
| May 2026 | 132.7 thousands | 5.1 |
| April 2026 | 132.9 thousands | 7.4 |
| March 2026 | 133.5 thousands | 10.4 |
| February 2026 | 130.9 thousands | 7.6 |
| January 2026 | 130.2 thousands | 6.5 |
| December 2025 | 131.3 thousands | −0.3 |
| November 2025 | 131.8 thousands | −1.0 |
| October 2025 | 131.2 thousands | −0.3 |
| September 2025 | 132.2 thousands | 3.0 |
| August 2025 | 127.3 thousands | 1.5 |
| July 2025 | 124.4 thousands | 2.0 |
| June 2025 | 125.8 thousands | 2.3 |
| May 2025 | 126.3 thousands | 1.6 |
| April 2025 | 123.8 thousands | 0.08 |
| March 2025 | 120.9 thousands | −2.1 |
| February 2025 | 121.7 thousands | −3.2 |
| January 2025 | 122.2 thousands | −3.3 |
| December 2024 | 131.7 thousands | −0.9 |
| November 2024 | 133.1 thousands | −1.9 |
| October 2024 | 131.6 thousands | −2.7 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-19100.PAYEMS.M.NSA.IND-60561300"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-19100.PAYEMS.M.NSA.IND-60561300",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```