# All Employees: Government — Boston, MA Metropolitan Division (NSA)

All Employees: Government — Boston, MA Metropolitan Division (NSA) was up 0.8% year on year in September 2026, compared with 0.8% in August 2026.
The level stood at 155.2 thousands.
That is the highest reading since August 2025.
Over the past ten years it has ranged from −5.3% (Jun 2020) to 3.7% (Mar 2024), averaging 0.4%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-14454.PAYEMS.M.NSA.IND-90000000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-government-boston-ma-metropolitan-division-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 155.2 thousands | 0.8 |
| August 2026 | 146.8 thousands | 0.8 |
| July 2026 | 149.1 thousands | 0.4 |
| June 2026 | 155.7 thousands | 0.6 |
| May 2026 | 156.9 thousands | 0.5 |
| April 2026 | 156.1 thousands | 0.5 |
| March 2026 | 155.3 thousands | 0.5 |
| February 2026 | 154.8 thousands | 0.5 |
| January 2026 | 152.0 thousands | 0.3 |
| December 2025 | 155.4 thousands | 0.6 |
| November 2025 | 155.5 thousands | 0.3 |
| October 2025 | 154.2 thousands | 0.4 |
| September 2025 | 153.9 thousands | 0.7 |
| August 2025 | 145.6 thousands | 1.0 |
| July 2025 | 148.5 thousands | 1.6 |
| June 2025 | 154.8 thousands | 1.2 |
| May 2025 | 156.1 thousands | 1.6 |
| April 2025 | 155.4 thousands | 2.0 |
| March 2025 | 154.5 thousands | 1.0 |
| February 2025 | 154.1 thousands | 1.7 |
| January 2025 | 151.6 thousands | 1.8 |
| December 2024 | 154.4 thousands | 2.3 |
| November 2024 | 155.1 thousands | 3.0 |
| October 2024 | 153.6 thousands | 2.8 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-14454.PAYEMS.M.NSA.IND-90000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-14454.PAYEMS.M.NSA.IND-90000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```