USDA ERS Food Price Outlook
USDA ERS Food Price Outlook
USDA ERS publishes CSV and XLSX files for food Consumer Price Index and Producer Price Index changes, forecasts, intervals, and prior forecast vintages. Files identify food category, forecast month and year, target year, interval attribute and percent change, and no key is required.
Coverage
The series concern U.S. retail, farm-level and wholesale food-price indexes. Forecasts update monthly and extend up to 18 months; archived CPI forecasts reach 2003 and archived PPI forecasts reach 2014, while the historical CPI file checked here starts with 2002 forecast vintages. The October 23, 2026 files scheduled their next update for November 24, 2026.
Verdict
This is a monthly food-inflation expectation and forecast-revision signal across retail, farm and wholesale categories. Forecast rows are vintages, so preserve both forecast date and target year rather than overwriting prior releases. ERS changed methodology in 2023 and warns that its reconstructed historical series is not comparable with forecasts archived under the earlier method. Forecast intervals express uncertainty, not observed price changes.
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Use in your agent
Load USDA food-price forecast vintages into pandas and Parquet. Checked against the provider's documentation on Nov 1, 2026.
Access
- No account or key. Historical CPI forecast CSV files are public downloads.
Request
curl -O 'https://www.ers.usda.gov/media/6464/historical-consumer-price-index-cpi-forecast-series.csv?v=65444'Format
CSV rows with CPI item, forecast month, forecast year, target year, interval attribute and forecast percent change.
Load into pandas and Parquet
Needs Python 3 with requests, pandas and pyarrow.
"""USDA ERS historical CPI forecast vintages -> pandas -> Parquet. No key."""
import io
import requests
import pandas as pd
URL = "https://www.ers.usda.gov/media/6464/historical-consumer-price-index-cpi-forecast-series.csv?v=65444"
r = requests.get(URL, timeout=60)
r.raise_for_status()
df = pd.read_csv(io.BytesIO(r.content), encoding="utf-8-sig")
df.to_parquet("usda_food_price_outlook_cpi_history.parquet", index=False)
print(len(df), "forecast rows", df["Year of forecast"].min(), "to",
df["Year of forecast"].max(), df["Consumer Price Index item"].nunique(), "CPI items")Run by us on 2026-11-01 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 28622 forecast rows 2002 to 2026 22 CPI items
Limits
- Rate limit: Not stated.
- Forecasts extend up to 18 months.
- Current forecast files normally update monthly.
Quirks
- Treat forecast month and year as the vintage and Year being forecast as the target period.
- Each point forecast is accompanied by lower and upper interval rows.
- Historical series reconstructed with the current method are not comparable with originally published archived forecasts.
Terms and attribution
- No separate data licence is stated on the checked product pages.
- The product page states no separate licence for the downloadable files.
Sources
- https://www.ers.usda.gov/data-products/food-price-outlook: “The ERS Food Price Outlook (FPO) provides data on food prices and forecasts annual food price changes up to 18 months in the future.”
- https://www.ers.usda.gov/data-products/food-price-outlook: “On a monthly basis, ERS forecasts the annual percentage change in food prices for the current year and, beginning in July each year, for the following year.”
- https://www.ers.usda.gov/data-products/food-price-outlook: “Users are reminded that the Historical Data series and the archived forecasts are not comparable due to changes in forecasting methods.”
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