# All Employees: Leisure and Hospitality — TX (statewide) (NSA)

All Employees: Leisure and Hospitality — TX (statewide) (NSA) was up 1.7% year on year in September 2026, compared with 1.8% in August 2026.
The level stood at 1,551.1 thousands.
Over the past ten years it has ranged from −38.4% (Apr 2020) to 47.6% (Apr 2021), averaging 2.4%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-TX.PAYEMS.M.NSA.IND-70000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-leisure-and-hospitality-tx-statewide-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,551.1 thousands | 1.7 |
| August 2026 | 1,571.8 thousands | 1.8 |
| July 2026 | 1,586.1 thousands | 2.3 |
| June 2026 | 1,592.3 thousands | 1.8 |
| May 2026 | 1,569.6 thousands | 0.6 |
| April 2026 | 1,542.6 thousands | −0.05 |
| March 2026 | 1,530.5 thousands | 0.5 |
| February 2026 | 1,512.2 thousands | 1.1 |
| January 2026 | 1,505.5 thousands | 1.7 |
| December 2025 | 1,515.4 thousands | −0.2 |
| November 2025 | 1,520.8 thousands | 0.2 |
| October 2025 | 1,531.2 thousands | 0.8 |
| September 2025 | 1,525.7 thousands | 0.7 |
| August 2025 | 1,543.3 thousands | 0.7 |
| July 2025 | 1,550.7 thousands | 1.2 |
| June 2025 | 1,564.8 thousands | 0.6 |
| May 2025 | 1,560.8 thousands | 1.4 |
| April 2025 | 1,543.3 thousands | 1.6 |
| March 2025 | 1,522.3 thousands | 1.4 |
| February 2025 | 1,496.1 thousands | 1.4 |
| January 2025 | 1,480.4 thousands | 1.6 |
| December 2024 | 1,517.8 thousands | 2.1 |
| November 2024 | 1,517.2 thousands | 2.0 |
| October 2024 | 1,519.6 thousands | 2.0 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-TX.PAYEMS.M.NSA.IND-70000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-TX.PAYEMS.M.NSA.IND-70000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```