# United States All employees, thousands, nonresidential property managers, seasonally adjusted

United States All employees, thousands, nonresidential property managers, seasonally adjusted was up 1.1% year on year in September 2026, compared with 1.9% in August 2026.
The level stood at 176.7 thousands.
Over the past ten years it has ranged from −7.1% (Dec 2020) to 7.8% (Sep 2022), averaging 1.8%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US.EMP.M.SA.IND-55531312`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-thousands-nonresidential-property-managers-seasonally

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 176.7 thousands | 1.1 |
| August 2026 | 177.6 thousands | 1.9 |
| July 2026 | 177.3 thousands | 1.8 |
| June 2026 | 177.4 thousands | 1.1 |
| May 2026 | 178.3 thousands | 1.8 |
| April 2026 | 178.1 thousands | 2.1 |
| March 2026 | 178.4 thousands | 2.6 |
| February 2026 | 178.3 thousands | 2.4 |
| January 2026 | 177.8 thousands | 1.8 |
| December 2025 | 177.0 thousands | 1.8 |
| November 2025 | 175.3 thousands | 0.9 |
| October 2025 | 176.1 thousands | 1.7 |
| September 2025 | 174.8 thousands | 1.5 |
| August 2025 | 174.3 thousands | 0.8 |
| July 2025 | 174.1 thousands | 0.9 |
| June 2025 | 175.4 thousands | 3.1 |
| May 2025 | 175.1 thousands | 2.1 |
| April 2025 | 174.4 thousands | 2.0 |
| March 2025 | 173.8 thousands | 0.6 |
| February 2025 | 174.1 thousands | 1.2 |
| January 2025 | 174.6 thousands | 0.8 |
| December 2024 | 173.8 thousands | 0.2 |
| November 2024 | 173.8 thousands | 0.8 |
| October 2024 | 173.1 thousands | 0.3 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-55531312"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-55531312",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```