# Unemployment: Corning, NY Micropolitan Statistical Area (U)

Unemployment: Corning, NY Micropolitan Statistical Area (U) was up 16.7% year on year in September 2025, compared with 1.4% in August 2025.
The level stood at 1,575.0 thousands.
That is the highest reading since October 2023.
Over the past ten years it has ranged from −70.0% (Apr 2021) to 321.3% (Apr 2020), averaging −0.4%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-18500.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-corning-ny-micropolitan-statistical-area-u

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,575.0 thousands | — |
| August 2026 | 1,596.0 thousands | — |
| July 2026 | 1,572.0 thousands | — |
| June 2026 | 1,532.0 thousands | — |
| May 2026 | 1,567.0 thousands | — |
| April 2026 | 1,583.0 thousands | — |
| March 2026 | 1,901.0 thousands | — |
| February 2026 | 2,234.0 thousands | — |
| January 2026 | 1,984.0 thousands | — |
| December 2025 | 1,662.0 thousands | — |
| November 2025 | 1,548.0 thousands | — |
| September 2025 | 1,491.0 thousands | 16.7 |
| August 2025 | 1,517.0 thousands | 1.4 |
| July 2025 | 1,511.0 thousands | −4.3 |
| June 2025 | 1,353.0 thousands | −4.7 |
| May 2025 | 1,235.0 thousands | −10.4 |
| April 2025 | 1,315.0 thousands | −6.7 |
| March 2025 | 1,708.0 thousands | −2.7 |
| February 2025 | 1,955.0 thousands | −3.3 |
| January 2025 | 1,880.0 thousands | −3.3 |
| December 2024 | 1,527.0 thousands | −6.1 |
| November 2024 | 1,444.0 thousands | 0.6 |
| October 2024 | 1,397.0 thousands | −1.8 |
| September 2024 | 1,278.0 thousands | −7.2 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-18500.UNEMPLVL.M.NSA"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-18500.UNEMPLVL.M.NSA",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```