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

All Employees: Mining, Logging and Construction — Reading, PA (NSA) was up 3.5% year on year in September 2026, compared with 1.1% in August 2026.
The level stood at 8.90 thousands.
That is the highest reading since September 2025.
Over the past ten years it has ranged from −40.7% (Apr 2020) to 60.4% (Apr 2021), averaging 1.0%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-39740.PAYEMS.M.NSA.IND-15000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-mining-logging-and-construction-reading-pa-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 8.90 thousands | 3.5 |
| August 2026 | 8.90 thousands | 1.1 |
| July 2026 | 8.90 thousands | 1.1 |
| June 2026 | 8.80 thousands | 2.3 |
| May 2026 | 8.50 thousands | 1.2 |
| April 2026 | 8.40 thousands | 1.2 |
| March 2026 | 8.10 thousands | 2.5 |
| February 2026 | 7.80 thousands | 2.6 |
| January 2026 | 8.00 thousands | 2.6 |
| December 2025 | 8.20 thousands | 1.2 |
| November 2025 | 8.40 thousands | 2.4 |
| October 2025 | 8.40 thousands | 2.4 |
| September 2025 | 8.60 thousands | 3.6 |
| August 2025 | 8.80 thousands | 4.8 |
| July 2025 | 8.80 thousands | 4.8 |
| June 2025 | 8.60 thousands | 4.9 |
| May 2025 | 8.40 thousands | 5.0 |
| April 2025 | 8.30 thousands | 5.1 |
| March 2025 | 7.90 thousands | 2.6 |
| February 2025 | 7.60 thousands | 2.7 |
| January 2025 | 7.80 thousands | 5.4 |
| December 2024 | 8.10 thousands | 2.5 |
| November 2024 | 8.20 thousands | 2.5 |
| October 2024 | 8.20 thousands | 0.0 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-39740.PAYEMS.M.NSA.IND-15000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-39740.PAYEMS.M.NSA.IND-15000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```