# All Employees: Mining, Logging and Construction — Pittsburgh, PA (NSA)

All Employees: Mining, Logging and Construction — Pittsburgh, PA (NSA) was down 4.2% year on year in September 2026, compared with −4.4% in August 2026.
The level stood at 66.80 thousands.
Over the past ten years it has ranged from −40.5% (Apr 2020) to 54.4% (Apr 2021), averaging 0.1%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-38300.PAYEMS.M.NSA.IND-15000000`
- Frequency: monthly
- Units: thousands
- Coverage: 2005-01-01 to 2026-09-01 (261 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-mining-logging-and-construction-pittsburgh-pa-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 66.80 thousands | −4.2 |
| August 2026 | 67.10 thousands | −4.4 |
| July 2026 | 66.80 thousands | −5.0 |
| June 2026 | 66.50 thousands | −4.6 |
| May 2026 | 64.30 thousands | −6.4 |
| April 2026 | 63.90 thousands | −3.6 |
| March 2026 | 61.90 thousands | −2.5 |
| February 2026 | 60.00 thousands | −1.0 |
| January 2026 | 61.10 thousands | 2.2 |
| December 2025 | 64.40 thousands | 1.1 |
| November 2025 | 66.40 thousands | −0.3 |
| October 2025 | 68.50 thousands | 0.4 |
| September 2025 | 69.70 thousands | 2.5 |
| August 2025 | 70.20 thousands | 1.9 |
| July 2025 | 70.30 thousands | 1.4 |
| June 2025 | 69.70 thousands | 1.0 |
| May 2025 | 68.70 thousands | 1.2 |
| April 2025 | 66.30 thousands | 0.8 |
| March 2025 | 63.50 thousands | 0.3 |
| February 2025 | 60.60 thousands | −1.8 |
| January 2025 | 59.80 thousands | −2.4 |
| December 2024 | 63.70 thousands | −2.3 |
| November 2024 | 66.60 thousands | −1.0 |
| October 2024 | 68.20 thousands | −1.3 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-38300.PAYEMS.M.NSA.IND-15000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-38300.PAYEMS.M.NSA.IND-15000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```