# Connecticut Employment (household survey)

Connecticut Employment (household survey) was down 1.3% year on year in September 2025, compared with −0.8% in August 2025.
The level stood at 1,810,603 thousands.
That is the lowest reading since March 2023.
Over the past ten years it has ranged from −10.8% (May 2020) to 11.4% (Mar 2022), averaging 0.5%.

- Source agency: U.S. Bureau of Labor Statistics
- Makrognosis code: `US-CT.EMP.M.NSA`
- Frequency: monthly
- Units: thousands
- Coverage: 1996-01-01 to 2026-09-01 (368 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/connecticut-employment-household-survey-not-seasonally-adjusted-monthly

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,810,603 thousands | — |
| August 2026 | 1,790,788 thousands | — |
| July 2026 | 1,799,103 thousands | — |
| June 2026 | 1,784,931 thousands | — |
| May 2026 | 1,775,653 thousands | — |
| April 2026 | 1,773,502 thousands | — |
| March 2026 | 1,790,079 thousands | — |
| February 2026 | 1,794,882 thousands | — |
| January 2026 | 1,806,367 thousands | — |
| December 2025 | 1,841,419 thousands | — |
| November 2025 | 1,854,687 thousands | — |
| September 2025 | 1,857,914 thousands | −1.3 |
| August 2025 | 1,856,221 thousands | −0.8 |
| July 2025 | 1,877,636 thousands | −0.6 |
| June 2025 | 1,876,486 thousands | −0.5 |
| May 2025 | 1,864,324 thousands | −0.4 |
| April 2025 | 1,866,717 thousands | 0.5 |
| March 2025 | 1,859,764 thousands | 0.07 |
| February 2025 | 1,840,468 thousands | 0.4 |
| January 2025 | 1,857,788 thousands | 0.9 |
| December 2024 | 1,877,628 thousands | 1.7 |
| November 2024 | 1,878,868 thousands | 0.4 |
| October 2024 | 1,879,406 thousands | 1.2 |
| September 2024 | 1,881,511 thousands | 1.2 |

## API

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

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