World Bank Commodity Markets (Pink Sheet) Data

The reference price book of global commodities. World Bank Commodity Markets (Pink Sheet) - filed under Diversified Metals & Mining - is the Development Prospects Group's monthly-and-annual price series for roughly 70 commodities spanning energy, fertilizers, agriculture and, critically for this industry slice, nine quoted metals and minerals. Each metal column is specified down to exchange grade: aluminum quotes LME high-grade primary ingots at minimum 99.7% purity, copper LME grade A cathodes at minimum 99.9935% purity, iron ore any-origin 62% Fe fines CFR China since December 2008.

The structure is deliberately boring and therefore immortal: one row per period, one column per commodity, a units line beneath every header, '...' marking unavailable observations. The monthly file carries 805 rows from January 1960; the annual file adds nominal and constant-2010 dollar versions of the same series, deflated via the MUV index so 1962 and 2026 can share a chart without a lie. Ten composite indices on a 2010=100 basis - incl. Metals & Minerals, Base Metals excluding iron ore and Precious Metals - give baskets with documented weights. Get a sample of this dataset and we return the rows cut to your metals, months and units.

Latest months and recent annual averages, exactly as the workbook states them:

period      : 2026M07
aluminum    : 3161   ($/mt, LME 99.7% ingot)
iron_ore    : 98.2   ($/dmtu, 62% Fe cfr China)
copper      : 13543  ($/mt, LME grade A)
lead        : 1842   ($/mt)
tin         : 52971  ($/mt)
nickel      : 16651  ($/mt)
zinc        : 3599   ($/mt)
gold        : 4073   ($/troy oz)

period      : 2026M06
aluminum    : 3439   iron_ore: 100.8   copper: 13552   gold: 4228

period      : 2025M12
aluminum    : 2876   copper: 11785   gold: 4309

year        : 2025_annual_nominal_avg
aluminum    : 2632   copper: 9947    gold: 3442

year        : 2024_annual_nominal_avg
aluminum    : 2419   copper: 9142    gold: 2388

Read the shape, not just the values: wide matrix, one header row, units declared once, no joins required to get a time series. That flatness is why the Pink Sheet survives as the citation layer under most commodity analysis - and why it loads cleanly into anything from a spreadsheet to a warehouse table without transformation gymnastics.

The record resolves the workbook's layout into named fields. Three families anchor every delivery - the period key, the quoted metal prices, and the composite index family - and all three arrive verified against the August 4, 2026 edition rather than inferred from documentation:

Geography - global benchmark prices quoted at exchange and regional reference points (LME settlements, China CFR iron ore spot, London fixings). This is a price dataset: there is no country production split and no company cut.

Temporal - January 1960 to the latest complete month for monthly data; 1960 to the last full year for annual data; real-dollar twins of every series deflated to constant 2010 prices through the MUV index.

Granularity - monthly and annual per commodity, plus forecast vintages aligned to the quarterly outlook cycle. No weekly, no daily: if your model needs intraday prints, pair this record with an exchange-tick feed rather than asking the Pink Sheet to be something it isn't.

API, files, or your warehouse. Daily, weekly, or hourly.

You pick the channel and the cadence; we absorb the workbook quirks - the AFOSHEET automation sheet, the units row sitting under headers, '...' standing in for missing observations - so your schema never has to think about them. When the September edition lands or an outlook revision moves the forecast columns, your feed updates in place: same columns, same units, same join keys. Tell us which commodities and date ranges you need and get a sample of this dataset shaped that way.

• Long-run factor research - six decades of deflated copper, aluminum, iron ore and gold prices make supercycle analysis possible at all; nothing else in the catalog reaches 1960 monthly.
• Input-cost escalation clauses - contract escalators need a neutral, citable benchmark; the constant-2010 series plus index family supplies one number both parties can verify.
• Forecast anchoring - quarterly outlook projections set the consensus baseline that company guidance and sell-side models get measured against.
• Market-sizing and cost curves - consultants convert physical volumes into dollar terms using the same benchmarks their clients' boards read.
• Demand modeling - commodity price paths as exogenous features in volume forecasts; see demand forecasting use cases.

Data scientists and ML engineers rank highest (relevance 3 of 3): merging seventy-plus monthly-and-annual series from January 1960 in nominal and constant-2010 dollars is exactly the feature-table job this record was built for. See data scientists use cases.

Investors and quants (3/3) backtest metals factors on six decades of deflated benchmarks plus forecasts - the longest clean panel available anywhere in the slice. See investors quants use cases.

Market researchers and consultants (3/3) put a citable World Bank benchmark behind every input-cost and market-sizing claim. See market researchers use cases.

Developers and data-product builders (3/3) wire the flat matrix straight into product backends: one period key, one column per commodity, no dimension maze to model. See developers builders use cases.

Notes worth reading next:

• Diversified metals mining data hub - the pooled industry view, sixteen datasets deep, from exchange statistics to mine-safety filings.
• International Copper Study Group (ICSG) - the supply-demand twin for copper; pair its balance rows with these price columns.
• International Lead and Zinc Study Group (ILZSG) - lead and zinc balances under the same intergovernmental methodology.
• International Nickel Study Group (INSG) - nickel market balance with 2026 forecasts, priced here.
• LME aluminum price, explained - how the settlement behind the aluminum column actually forms.
• Best diversified metals mining datasets - where this record ranks within the slice and what beats it for other jobs.

Within the sixteen-dataset diversified-metals-mining pool, the Pink Sheet is the price-history spine and the neighbors add axes it deliberately lacks. Production volumes across 168 producer countries come from World Mining Data; EU structural business statistics from Eurostat - Mining and Quarrying Statistics; country-level copper detail including daily prices and exchange inventories from Cochilco - Chilean Copper Statistics; mine-safety operational records from MSHA Mine Data Retrieval System & Reports; Canadian production and trade flows from NRCan Mineral Statistics.

For precious metals specifically, intraday-grade benchmark alternatives live in LBMA Precious Metal Benchmark Prices and Kitco Precious Metals Market - shorter histories, finer ticks. Where geology matters more than price, the split is drawn in Pink Sheet vs Geoscience Australia Minerals Data: prices against deposit-level GIS. Nothing else matches 805 monthly observations per commodity.