# All Employees: Mining, Logging and Construction — Bloomington, IN (NSA)

All Employees: Mining, Logging and Construction — Bloomington, IN (NSA) was up 2.6% year on year in September 2026, compared with 5.3% in August 2026.
The level stood at 3.90 thousands.
That is the lowest reading since June 2024.
Over the past ten years it has ranged from −6.1% (Dec 2021) to 20.0% (Jan 2026), averaging 3.9%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-14020.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-bloomington-in-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 3.90 thousands | 2.6 |
| August 2026 | 4.00 thousands | 5.3 |
| July 2026 | 4.00 thousands | 8.1 |
| June 2026 | 3.90 thousands | 8.3 |
| May 2026 | 3.80 thousands | 8.6 |
| April 2026 | 3.70 thousands | 12.1 |
| March 2026 | 3.70 thousands | 12.1 |
| February 2026 | 3.60 thousands | 16.1 |
| January 2026 | 3.60 thousands | 20.0 |
| December 2025 | 3.70 thousands | 12.1 |
| November 2025 | 3.70 thousands | 12.1 |
| October 2025 | 3.70 thousands | 8.8 |
| September 2025 | 3.80 thousands | 11.8 |
| August 2025 | 3.80 thousands | 11.8 |
| July 2025 | 3.70 thousands | 8.8 |
| June 2025 | 3.60 thousands | 9.1 |
| May 2025 | 3.50 thousands | 9.4 |
| April 2025 | 3.30 thousands | 6.5 |
| March 2025 | 3.30 thousands | 10.0 |
| February 2025 | 3.10 thousands | 3.3 |
| January 2025 | 3.00 thousands | 3.4 |
| December 2024 | 3.30 thousands | 6.5 |
| November 2024 | 3.30 thousands | 3.1 |
| October 2024 | 3.40 thousands | 6.2 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-14020.PAYEMS.M.NSA.IND-15000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-14020.PAYEMS.M.NSA.IND-15000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```