# All Employees: Heavy and Civil Engineering Construction — Lake Charles, LA (NSA)

All Employees: Heavy and Civil Engineering Construction — Lake Charles, LA (NSA) was up 6.4% year on year in September 2026, compared with 2.0% in August 2026.
The level stood at 5.00 thousands.
Over the past ten years it has ranged from −40.2% (Aug 2020) to 25.0% (Jul 2025), averaging −5.6%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-29340.PAYEMS.M.NSA.IND-20237000`
- Frequency: monthly
- Units: thousands
- Coverage: 2005-01-01 to 2026-09-01 (261 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-heavy-and-civil-engineering-construction-lake-charles-la

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 5.00 thousands | 6.4 |
| August 2026 | 5.00 thousands | 2.0 |
| July 2026 | 5.00 thousands | 0.0 |
| June 2026 | 5.00 thousands | −2.0 |
| May 2026 | 4.90 thousands | 2.1 |
| April 2026 | 4.80 thousands | 6.7 |
| March 2026 | 4.90 thousands | 11.4 |
| February 2026 | 4.80 thousands | 9.1 |
| January 2026 | 4.60 thousands | 15.0 |
| December 2025 | 4.50 thousands | 18.4 |
| November 2025 | 4.70 thousands | 20.5 |
| October 2025 | 4.70 thousands | 17.5 |
| September 2025 | 4.70 thousands | 17.5 |
| August 2025 | 4.90 thousands | 22.5 |
| July 2025 | 5.00 thousands | 25.0 |
| June 2025 | 5.10 thousands | 24.4 |
| May 2025 | 4.80 thousands | 14.3 |
| April 2025 | 4.50 thousands | 12.5 |
| March 2025 | 4.40 thousands | 4.8 |
| February 2025 | 4.40 thousands | 7.3 |
| January 2025 | 4.00 thousands | 21.2 |
| December 2024 | 3.80 thousands | 11.8 |
| November 2024 | 3.90 thousands | 8.3 |
| October 2024 | 4.00 thousands | 11.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-29340.PAYEMS.M.NSA.IND-20237000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-29340.PAYEMS.M.NSA.IND-20237000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```