# United States PCE: Nondurable Goods (SAAR)

United States PCE: Nondurable Goods (SAAR) was up 6.7% year on year in September 2026, compared with 5.9% in August 2026.
The level stood at 4,556,177 US$ million.
Over the past ten years it has ranged from −9.0% (Apr 2020) to 26.8% (Apr 2021), averaging 5.2%.

- Source agency: U.S. Bureau of Economic Analysis
- Makrognosis code: `US.PCE.M.SA.GRP-NONDURABLES`
- Frequency: monthly
- Units: US$ million
- Coverage: 1966-01-01 to 2026-09-01 (729 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/pce-nondurable-goods-saar

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 4,556,177 US$ million | 6.7 |
| August 2026 | 4,507,492 US$ million | 5.9 |
| July 2026 | 4,449,368 US$ million | 5.3 |
| June 2026 | 4,461,649 US$ million | 5.8 |
| May 2026 | 4,486,260 US$ million | 7.4 |
| April 2026 | 4,463,901 US$ million | 6.9 |
| March 2026 | 4,413,313 US$ million | 5.4 |
| February 2026 | 4,307,494 US$ million | 2.6 |
| January 2026 | 4,275,837 US$ million | 2.7 |
| December 2025 | 4,285,682 US$ million | 2.6 |
| November 2025 | 4,282,761 US$ million | 4.0 |
| October 2025 | 4,268,478 US$ million | 3.6 |
| September 2025 | 4,269,137 US$ million | 3.4 |
| August 2025 | 4,255,758 US$ million | 4.3 |
| July 2025 | 4,225,036 US$ million | 2.9 |
| June 2025 | 4,216,681 US$ million | 3.2 |
| May 2025 | 4,176,980 US$ million | 2.4 |
| April 2025 | 4,174,605 US$ million | 2.8 |
| March 2025 | 4,187,787 US$ million | 3.3 |
| February 2025 | 4,198,370 US$ million | 5.0 |
| January 2025 | 4,164,208 US$ million | 4.4 |
| December 2024 | 4,177,502 US$ million | 3.6 |
| November 2024 | 4,119,440 US$ million | 2.3 |
| October 2024 | 4,119,110 US$ million | 2.0 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.PCE.M.SA.GRP-NONDURABLES"

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