# All Employees: Goods Producing — Grand Island, NE (NSA)

All Employees: Goods Producing — Grand Island, NE (NSA) was up 3.9% year on year in September 2026, compared with 2.9% in August 2026.
The level stood at 10.70 thousands.
That is the highest reading since January 2024.
Over the past ten years it has ranged from −14.3% (Apr 2020) to 13.1% (Apr 2021), averaging 1.2%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-24260.PAYEMS.M.NSA.IND-06000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-goods-producing-grand-island-ne-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 10.70 thousands | 3.9 |
| August 2026 | 10.70 thousands | 2.9 |
| July 2026 | 10.70 thousands | 1.9 |
| June 2026 | 10.70 thousands | 0.9 |
| May 2026 | 10.50 thousands | 0.0 |
| April 2026 | 10.40 thousands | 0.0 |
| March 2026 | 10.30 thousands | 0.0 |
| February 2026 | 10.20 thousands | 0.0 |
| January 2026 | 10.20 thousands | −1.9 |
| December 2025 | 10.30 thousands | −3.7 |
| November 2025 | 10.40 thousands | −3.7 |
| October 2025 | 10.40 thousands | −3.7 |
| September 2025 | 10.30 thousands | −5.5 |
| August 2025 | 10.40 thousands | −5.5 |
| July 2025 | 10.50 thousands | −4.5 |
| June 2025 | 10.60 thousands | −3.6 |
| May 2025 | 10.50 thousands | −5.4 |
| April 2025 | 10.40 thousands | −4.6 |
| March 2025 | 10.30 thousands | −4.6 |
| February 2025 | 10.20 thousands | −4.7 |
| January 2025 | 10.40 thousands | −2.8 |
| December 2024 | 10.70 thousands | −0.9 |
| November 2024 | 10.80 thousands | −0.9 |
| October 2024 | 10.80 thousands | −1.8 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-24260.PAYEMS.M.NSA.IND-06000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-24260.PAYEMS.M.NSA.IND-06000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```