# Unemployment: Putnam, CT Micropolitan Statistical Area (U)

Unemployment: Putnam, CT Micropolitan Statistical Area (U) was up 43.4% year on year in September 2025, compared with 29.3% in August 2025.
The level stood at 2,485.0 thousands.
That is the highest reading since February 2021.
Over the past ten years it has ranged from −49.6% (May 2021) to 219.7% (May 2020), averaging 1.0%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-39480.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-putnam-ct-micropolitan-statistical-area-u

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 2,485.0 thousands | — |
| August 2026 | 2,244.0 thousands | — |
| July 2026 | 2,867.0 thousands | — |
| June 2026 | 2,470.0 thousands | — |
| May 2026 | 2,486.0 thousands | — |
| April 2026 | 2,678.0 thousands | — |
| March 2026 | 2,853.0 thousands | — |
| February 2026 | 3,176.0 thousands | — |
| January 2026 | 2,971.0 thousands | — |
| December 2025 | 2,223.0 thousands | — |
| November 2025 | 2,371.0 thousands | — |
| September 2025 | 2,180.0 thousands | 43.4 |
| August 2025 | 2,168.0 thousands | 29.3 |
| July 2025 | 2,199.0 thousands | 19.0 |
| June 2025 | 1,833.0 thousands | 26.7 |
| May 2025 | 1,932.0 thousands | 25.9 |
| April 2025 | 1,751.0 thousands | 37.0 |
| March 2025 | 2,122.0 thousands | 25.0 |
| February 2025 | 2,315.0 thousands | 16.3 |
| January 2025 | 2,206.0 thousands | 16.5 |
| December 2024 | 1,527.0 thousands | 9.3 |
| November 2024 | 1,641.0 thousands | 15.3 |
| October 2024 | 1,580.0 thousands | 2.3 |
| September 2024 | 1,520.0 thousands | −1.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-39480.UNEMPLVL.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-39480.UNEMPLVL.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```