# Average Weekly Earnings: Total Private — Santa Fe, NM (NSA)

Average Weekly Earnings: Total Private — Santa Fe, NM (NSA) was down 4.6% year on year in September 2026, compared with 0.4% in August 2026.
The level stood at 1,002.0 USD/week.
That is the lowest reading since July 2024.
Over the past ten years it has ranged from −15.2% (Sep 2016) to 21.1% (Nov 2020), averaging 3.5%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US-42140.AWE.M.NSA.IND-05000000`
- Frequency: monthly
- Units: USD/week
- Coverage: 2007-01-01 to 2026-09-01 (237 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/average-weekly-earnings-total-private-santa-fe-nm-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 1,002.0 USD/week | −4.6 |
| August 2026 | 1,015.9 USD/week | 0.4 |
| July 2026 | 997.0 USD/week | −0.9 |
| June 2026 | 1,033.8 USD/week | 3.2 |
| May 2026 | 992.7 USD/week | 0.02 |
| April 2026 | 987.1 USD/week | −2.1 |
| March 2026 | 1,030.2 USD/week | 3.2 |
| February 2026 | 1,037.4 USD/week | 4.8 |
| January 2026 | 1,034.2 USD/week | 11.6 |
| December 2025 | 1,046.5 USD/week | 10.3 |
| November 2025 | 1,038.2 USD/week | 11.5 |
| October 2025 | 1,022.3 USD/week | 8.6 |
| September 2025 | 1,050.3 USD/week | 15.4 |
| August 2025 | 1,012.4 USD/week | 14.6 |
| July 2025 | 1,005.7 USD/week | 15.2 |
| June 2025 | 1,001.3 USD/week | 14.1 |
| May 2025 | 992.5 USD/week | 13.4 |
| April 2025 | 1,008.7 USD/week | 12.7 |
| March 2025 | 997.9 USD/week | 15.6 |
| February 2025 | 989.9 USD/week | 12.3 |
| January 2025 | 926.4 USD/week | 3.1 |
| December 2024 | 948.7 USD/week | 7.0 |
| November 2024 | 931.1 USD/week | 3.6 |
| October 2024 | 941.6 USD/week | 2.3 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US-42140.AWE.M.NSA.IND-05000000"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US-42140.AWE.M.NSA.IND-05000000",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```