# United States All employees, thousands, telecommunications, seasonally adjusted

United States All employees, thousands, telecommunications, seasonally adjusted was down 5.9% year on year in October 2026, compared with −5.9% in September 2026.
The level stood at 559.1 thousands.
Over the past ten years it has ranged from −5.9% (Sep 2026) to 1.2% (Jul 2022), averaging −3.3%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US.EMP.M.SA.IND-50517000`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-10-01 (442 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-thousands-telecommunications-seasonally-adjusted

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| October 2026 | 559.1 thousands | −5.9 |
| September 2026 | 559.8 thousands | −5.9 |
| August 2026 | 564.7 thousands | −5.0 |
| July 2026 | 569.1 thousands | −4.1 |
| June 2026 | 570.3 thousands | −4.3 |
| May 2026 | 575.6 thousands | −3.8 |
| April 2026 | 575.1 thousands | −3.8 |
| March 2026 | 577.2 thousands | −3.5 |
| February 2026 | 576.9 thousands | −4.0 |
| January 2026 | 580.0 thousands | −3.6 |
| December 2025 | 598.3 thousands | −3.1 |
| November 2025 | 591.2 thousands | −2.8 |
| October 2025 | 594.1 thousands | −1.9 |
| September 2025 | 595.1 thousands | −2.8 |
| August 2025 | 594.5 thousands | −3.0 |
| July 2025 | 593.2 thousands | −4.2 |
| June 2025 | 596.0 thousands | −4.3 |
| May 2025 | 598.4 thousands | −3.7 |
| April 2025 | 598.0 thousands | −4.3 |
| March 2025 | 598.2 thousands | −4.9 |
| February 2025 | 601.0 thousands | −4.4 |
| January 2025 | 601.7 thousands | −4.8 |
| December 2024 | 617.4 thousands | −2.4 |
| November 2024 | 608.2 thousands | −3.9 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-50517000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-50517000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```