Lilambd/world-prices

World Prices Long Record: what things cost, month by month, since 1960

One flat, long-form table of the prices that move the world, ready to join by country and month:

• 70 commodity prices and 16 indices from 1960-01 to 2026-08, monthly: crude oil (Brent, WTI, Dubai), natural gas (US, Europe, Japan LNG), coal, cocoa, coffee, tea, rice, wheat, maize, soybeans, palm oil, sugar, beef, chicken, shrimp, fertilisers (urea, DAP, potash), metals (copper, aluminium, nickel, zinc, tin, iron ore) and gold, silver, platinum.
• Consumer prices for 187 countries from 1970-01 to 2025-03, monthly: headline, food and energy CPI.
• Yearly panel adding Eurostat household gas and electricity prices and US state energy prices (EIA SEDS).
• Computed per-country features: how much food prices rose 2021-2023, how many months energy and food CPI lag world commodity prices, and how unstable headline inflation was 2015-2024.

Nothing is generated by a model. Values are as published by each source; the computed features are documented in feature_doc.

Data as of 2026-11-02 (commodity prices up to 2026-08; World Bank inflation database monthly up to 2025-03).

Quick start

from datasets import load_dataset
m = load_dataset("Lilambd/world-prices", "monthly", split="train")
oil = m.filter(lambda r: r["feature"] == "px_crude_oil_brent")
jp_food = m.filter(lambda r: r["unit"] == "JPN" and r["feature"] == "cpi_food")

Tables

config	rows	columns
monthly	220,053	unit_kind (world / country), unit (WLD or ISO3), grp, period (YYYY-MM), year, month, feature, value, source
yearly	26,898	unit_kind, unit, grp, year, feature, value, source
features_country	668	iso3, feature, value, year, unit, source
feature_doc	94	feature, unit_kind, ledger, kind, definition, source, caveat

Feature names: px_* are commodity prices in US dollars (units as in the World Bank Pink Sheet, e.g. $/bbl, $/mt, $/kg, $/troy oz); pxi_* are World Bank price indices (2010 = 100); cpi_* are national CPI index levels.

What the numbers say

• August 2026: crude oil average $84.4/bbl, gold $4,411/troy oz, Thai 5% rice $471/mt, arabica coffee $7.97/kg, cocoa $5.95/kg.
• Food prices from the 2021 average to the 2023 average rose most in Venezuela (×12.5), Lebanon (×12.1), Argentina (×4.3) and Turkey (×3.1).
• In 2016-2025 the most volatile monthly series were US natural gas, European natural gas and Kolkata tea; the most stable were EU sugar, timber and tobacco, which behave like administered prices.

Gaps and known limits

• CPI values are index levels and base years differ by country: compare changes, not levels, across countries.
• The World Bank inflation database is monthly only up to 2025-03; later months are not filled or estimated.
• Commodity prices are world benchmark prices, not local retail prices. For local market prices see Lilambd/world-markets.
• Japan's detailed BOJ and Statistics Bureau series and EIA US fuel series exist in the source model but are not in this first release.

Use it in production

For AI agents: 14 more Lilambd open-data APIs (airports, regions, markets, security, travel and more), pay per call with x402 (from $0.005 USDC on Base, no signup), free sample with sample=1, also as an MCP server: https://xsrtcehyqluhvywmaihd.supabase.co/functions/v1/agent-api/llms.txt

Need a monthly feed, a price or country that is not here, or a finished answer ("how exposed is this country's food basket to world prices?")? Write to submissions@lilambd.com.

Related: Lilambd/world-hazard, Lilambd/world-earth, Lilambd/world-signals.

Sources and licence

• World Bank Commodity Price Data (Pink Sheet), monthly and annual. CC BY 4.0.
• World Bank Global Database of Inflation (Ha, Kose and Ohnsorge 2023). CC BY 4.0.
• Eurostat HICP and energy prices (nrg_pc_202 to 205). CC BY 4.0 under the Eurostat reuse policy.
• US Energy Information Administration, State Energy Data System. Public domain.

The derived tables are released under CC BY 4.0. Please cite "Lilambd World Prices Long Record" and the World Bank, Eurostat and EIA.

Maintained by Lilambd. Questions: submissions@lilambd.com

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