Rice Price History: Monthly Global Price Since 2010

Rice is the staple food for over half the world’s population, and its international price is dominated by Asia — India alone supplies around 40% of world exports. This dataset tracks the IMF Primary Commodity Prices benchmark, Thai white rice (5% broken, FOB Bangkok), published monthly in US dollars per metric ton and distributed via FRED under the code PRICENPQUSDM, with coverage beginning in 2010.

Dataset: Rice Price (2010–2026) · Updated 2026-03-01

Source: IMF Primary Commodity Prices · International Monetary Fund (via FRED)

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns. Each row represents one calendar month.

Column names match the CSV headers exactly.

Download the Complete Dataset

The full dataset is available in CSV and Excel formats — monthly observations covering more than three decades.

FRED Direct CSV Access

The underlying data is published in the Federal Reserve Economic Data (FRED) database under the series code PRICENPQUSDM, sourced from the IMF Primary Commodity Prices dataset:

https://fred.stlouisfed.org/graph/fredgraph.csv?id=PRICENPQUSDM

The Eco3min dataset mirrors the same monthly series, packaged in a stable, versionable CSV with consistent column names — designed for direct ingestion in Python, R, or any data pipeline. The URL never changes, making it suitable for automated scripts.

Direct CSV Access — Eco3min Structured Dataset

https://eco3min.fr/dataset/rice-price.csv

This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/rice-price.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(df.head())
print(df["rice_price"].describe())

df.plot(x="date", y="rice_price", title="Rice Price", legend=False)

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/rice-price.csv"
df <- read_csv(url)

head(df)
summary(df$rice_price)

Both examples load the dataset directly from the URL — no download or API key required.

Methodology

The IMF reports the rice price in US dollars per metric ton, based on Thai white rice, 5% broken, FOB Bangkok.

Values are monthly averages, which smooth the intra-month swings visible in daily futures and physical quotes. The series begins in 2010.

This dataset is updated monthly via an automated pull from the FRED API (series PRICENPQUSDM) by an Eco3min pipeline running on GitHub Actions, which regenerates the cleaned CSV and Excel files and refreshes the page metadata.

Data Quality & Provider Notes

The IMF/benchmark price is a widely cited physical-market reference. A few provider-specific points matter when using this series.

• Release latency. The IMF publishes Primary Commodity Prices monthly, typically in the first week of the following month. FRED ingests the update shortly after, and Eco3min mirrors it with a monthly pull. The series is not a real-time price.
• Monthly average vs futures spot. This series is a monthly average. It will differ from any single exchange settlement, and a monthly average necessarily understates intra-month peaks.
• Revisions. Prices are market-derived and not subject to the vintage revisions of survey-based macro series, though the IMF can restate recent observations.
• Alternative sources. ICE futures and the originating auction or indicator bodies provide higher-frequency or contract-specific quotes.

Common Pitfalls When Using This Series

1. Confusing nominal and real prices. This series is nominal. Comparing an early-1990s reading to a recent one without adjusting for cumulative inflation overstates the real change. Deflating by CPI gives the true purchasing-power move.
2. Reading the monthly average as a market price. Headlines quote exchange futures; this dataset reports the monthly benchmark average. The two diverge most during fast-moving rallies.
3. Unit confusion. This series is an export FOB quote for Thai 5% broken white rice, not a futures price; it differs from US CBOT rough-rice futures and from Indian or Vietnamese export quotes.

Historical Regimes

2010–2012 — Post-crisis, elevated then easing. After the 2008 export-restriction crisis (which preceded this series and roughly doubled prices), the market stayed elevated, then eased as Asian supply recovered.

2013–2019 — Low and stable. Ample Asian stocks, especially in India and Thailand, held the Thai benchmark in a relatively low band.

2020–2021 — Pandemic firmness. Covid logistics and stockpiling lifted prices modestly.

2022–2023 — India restricts. India phased in export curbs from 2022 and banned non-basmati white rice in July 2023; with El Niño threatening output, the Thai benchmark jumped over 20% to its highest since 2008.

2024–2026 — Ban lifted, correction. India lifted the non-basmati ban in September 2024 with a $490-per-ton floor, and prices fell back as Indian stocks proved ample.

Related Macroeconomic Datasets

Commodity Price Hub

This dataset is part of the Eco3min commodity price repository — energy, metals, agricultural softs, and grains, all sourced from IMF Primary Commodity Prices via FRED.

Explore the Commodity Price Hub

Sources

• International Monetary Fund — Primary Commodity Prices, Global Price of Rice
• Federal Reserve Bank of St. Louis — FRED database, series PRICENPQUSDM
• Thai white rice (5% broken) FOB Bangkok export quotations — basis underlying the IMF series

Dataset Reference

Eco3min Research. (2026). Rice Price — Global Monthly Price (2010-2026). Source: IMF Primary Commodity Prices via FRED.<br> https://eco3min.fr/en/rice-price-history-dataset/