# All Employees: Direct Property and Casualty Insurance Carriers — CT (statewide) (NSA)

All Employees: Direct Property and Casualty Insurance Carriers — CT (statewide) (NSA) was down 1.6% year on year in September 2026, compared with −3.2% in August 2026.
The level stood at 12.00 thousands.
Over the past ten years it has ranged from −6.1% (Dec 2017) to 3.4% (Aug 2023), averaging −0.8%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-CT.PAYEMS.M.NSA.IND-55524126`
- Frequency: monthly
- Units: thousands
- Coverage: 2001-01-01 to 2026-09-01 (309 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-direct-property-and-casualty-insurance-carriers-ct

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 12.00 thousands | −1.6 |
| August 2026 | 12.00 thousands | −3.2 |
| July 2026 | 12.20 thousands | −2.4 |
| June 2026 | 12.10 thousands | −2.4 |
| May 2026 | 12.00 thousands | 0.0 |
| April 2026 | 12.00 thousands | 0.0 |
| March 2026 | 12.10 thousands | 0.0 |
| February 2026 | 12.10 thousands | −0.8 |
| January 2026 | 12.10 thousands | 0.8 |
| December 2025 | 12.20 thousands | 1.7 |
| November 2025 | 12.20 thousands | 1.7 |
| October 2025 | 12.20 thousands | 1.7 |
| September 2025 | 12.20 thousands | 1.7 |
| August 2025 | 12.40 thousands | 0.8 |
| July 2025 | 12.50 thousands | 1.6 |
| June 2025 | 12.40 thousands | 0.0 |
| May 2025 | 12.00 thousands | 0.8 |
| April 2025 | 12.00 thousands | 0.8 |
| March 2025 | 12.10 thousands | 1.7 |
| February 2025 | 12.20 thousands | 2.5 |
| January 2025 | 12.00 thousands | 0.8 |
| December 2024 | 12.00 thousands | −1.6 |
| November 2024 | 12.00 thousands | 0.0 |
| October 2024 | 12.00 thousands | 0.0 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-CT.PAYEMS.M.NSA.IND-55524126"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-CT.PAYEMS.M.NSA.IND-55524126",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```