# All Employees: Heavy and Civil Engineering Construction — TX (statewide) (NSA)

All Employees: Heavy and Civil Engineering Construction — TX (statewide) (NSA) was up 3.3% year on year in September 2026, compared with 3.4% in August 2026.
The level stood at 207.6 thousands.
Over the past ten years it has ranged from −14.8% (Feb 2021) to 12.2% (May 2019), averaging 3.6%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-TX.PAYEMS.M.NSA.IND-20237000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-heavy-and-civil-engineering-construction-tx-statewide-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 207.6 thousands | 3.3 |
| August 2026 | 207.3 thousands | 3.4 |
| July 2026 | 204.8 thousands | 3.2 |
| June 2026 | 204.4 thousands | 2.7 |
| May 2026 | 204.6 thousands | 2.4 |
| April 2026 | 204.3 thousands | 3.0 |
| March 2026 | 203.6 thousands | 2.9 |
| February 2026 | 205.3 thousands | 4.7 |
| January 2026 | 202.7 thousands | 6.3 |
| December 2025 | 202.1 thousands | 4.2 |
| November 2025 | 203.1 thousands | 3.6 |
| October 2025 | 206.1 thousands | 5.1 |
| September 2025 | 201.0 thousands | 4.2 |
| August 2025 | 200.5 thousands | 5.1 |
| July 2025 | 198.5 thousands | 6.3 |
| June 2025 | 199.1 thousands | 6.0 |
| May 2025 | 199.8 thousands | 7.5 |
| April 2025 | 198.3 thousands | 8.5 |
| March 2025 | 197.8 thousands | 8.1 |
| February 2025 | 196.1 thousands | 7.9 |
| January 2025 | 190.7 thousands | 8.9 |
| December 2024 | 194.0 thousands | 9.9 |
| November 2024 | 196.0 thousands | 10.9 |
| October 2024 | 196.1 thousands | 10.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-TX.PAYEMS.M.NSA.IND-20237000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-TX.PAYEMS.M.NSA.IND-20237000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```