# Unemployment: Northwest Hills Planning Region, CT (U)

Unemployment: Northwest Hills Planning Region, CT (U) was up 39.2% year on year in September 2025, compared with 21.8% in August 2025.
The level stood at 2,572.0 thousands.
That is the highest reading since March 2021.
Over the past ten years it has ranged from −40.7% (Jul 2021) to 200.9% (May 2020), averaging 1.7%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-CT-09160.UNEMPLVL.M.NSA`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (440 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/unemployment-northwest-hills-planning-region-ct-u

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 2,572.0 thousands | — |
| August 2026 | 2,289.0 thousands | — |
| July 2026 | 2,990.0 thousands | — |
| June 2026 | 2,517.0 thousands | — |
| May 2026 | 2,552.0 thousands | — |
| April 2026 | 2,737.0 thousands | — |
| March 2026 | 3,112.0 thousands | — |
| February 2026 | 3,461.0 thousands | — |
| January 2026 | 3,278.0 thousands | — |
| December 2025 | 2,400.0 thousands | — |
| November 2025 | 2,508.0 thousands | — |
| September 2025 | 2,201.0 thousands | 39.2 |
| August 2025 | 2,220.0 thousands | 21.8 |
| July 2025 | 2,401.0 thousands | 20.0 |
| June 2025 | 2,015.0 thousands | 30.7 |
| May 2025 | 2,164.0 thousands | 29.1 |
| April 2025 | 1,898.0 thousands | 30.1 |
| March 2025 | 2,445.0 thousands | 22.4 |
| February 2025 | 2,645.0 thousands | 12.6 |
| January 2025 | 2,537.0 thousands | 13.2 |
| December 2024 | 1,697.0 thousands | 6.6 |
| November 2024 | 1,759.0 thousands | 12.3 |
| October 2024 | 1,650.0 thousands | 4.7 |
| September 2024 | 1,581.0 thousands | 2.7 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-CT-09160.UNEMPLVL.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-CT-09160.UNEMPLVL.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```