Copper Price History: Monthly Global Price Since 1992

This dataset tracks the monthly global copper price in US dollars per metric ton, as published by the World Bank in its Commodity Price Data (the Pink Sheet), since January 1992. The series is the monthly average of the London Metal Exchange (LME) settlement price for grade A copper and serves as a standard reference for industrial-metal economics. Often nicknamed “Dr. Copper” for its perceived ability to diagnose global manufacturing health, the metal is widely used in business-cycle analysis and energy-transition demand modeling.

Dataset: Copper Price History (1992–2026) · Updated 2026-10-01

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

Source: World Bank, Commodity Price Data (The Pink Sheet) · CC BY 4.0

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns.

Column names match the CSV headers exactly.

Download the Complete Dataset

The full dataset is available in CSV and Excel formats.

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

Source Data Access: World Bank Pink Sheet

The underlying series is the “Copper” column of the Monthly Prices sheet in the World Bank’s Commodity Price Data, known as the Pink Sheet. The World Bank publishes it as a monthly Excel workbook on its commodity markets page, under a CC BY 4.0 licence that requires attribution to the World Bank.

The Eco3min dataset reproduces that column unmodified from January 1992, in US dollars per metric ton, in a stable CSV with a fixed column name for direct use in Python, R or any data pipeline. The URL never changes, which makes it suitable for automated scripts.

Direct CSV Access: Eco3min Structured Dataset

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

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

Using the Dataset in R

library(readr)

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

head(df)
summary(df$copper_price_usd)

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

Methodology

The series is the “Copper” column of the World Bank Pink Sheet: the London Metal Exchange (LME) settlement price for grade A copper (minimum 99.9935% purity, cathodes and wire bar shapes), averaged over each calendar month. It is quoted in US dollars per metric ton, the LME’s own unit, without conversion. The Pink Sheet column starts in January 1960; the Eco3min file keeps observations from January 1992 onward. For how copper exposure is actually obtained, see our reading of the commodity access paths.

An Eco3min pipeline on GitHub Actions reads the Pink Sheet workbook after each monthly release, keeps the column unmodified and regenerates the CSV, Excel and JSON files and the page metadata. The World Bank updates the Pink Sheet on the second business day of each month. Values are nominal US dollars, not seasonally adjusted and not adjusted for inflation. Monthly averaging smooths daily LME volatility: daily analysis requires LME or COMEX HG data.

Data Quality & Provider Notes

The series comes from the World Bank Pink Sheet and reflects the monthly average of LME copper settlement prices. A few provider-specific points matter when using it.

• Release latency. The World Bank publishes the Pink Sheet on the second business day of each month, with the average of the month just ended. Eco3min refreshes the file after each release. The series is not a real-time price.
• Revisions. Prices are market-derived and are not revised like survey-based macro series, but the World Bank can correct recent months or replace a series, and it lists those changes in the notes of the Pink Sheet workbook.
• Source change on 30 September 2026. Until that date this file reproduced another publisher’s series; the whole history was then rebuilt from the Pink Sheet column, so figures downloaded earlier can differ slightly.
• Alternative sources. The London Metal Exchange (LME) provides daily settlement and intraday tick data under paid licenses. COMEX copper futures (Bloomberg HG1, CME ticker HG) offer a US-dollar-denominated US-settled alternative with its own term-structure dynamics. Bloomberg’s LMCADS03 ticker and the BIS commodity database publish institutional-grade LME references with paid access.
• Known gaps. Monthly granularity only, no daily observations. The Pink Sheet copper column starts in January 1960, but observations before January 1992 are not part of this file. Prices are in US dollars per metric ton throughout. One metric ton is about 2,204.6 pounds, so a price per pound is the price per ton divided by that factor.

For macro modeling, check the latest observation date before joining the copper series to monthly industrial production or PMI data. A month’s average reaches the Pink Sheet on the second business day of the next month, so misaligned dates produce stale readings.

Common Pitfalls When Using Copper Price Data

The Pink Sheet copper price is one of the most widely cited industrial-metal series, but its monthly aggregation and global pricing scope produce several recurring interpretation errors.

1. Confusing the monthly average with daily LME settlement or COMEX HG. The Pink Sheet copper price is a monthly average of LME settlements, in US dollars per metric ton. Daily LME copper settlements and COMEX HG futures can diverge from the monthly average over short periods, and COMEX HG is quoted per pound: $10,000 per ton is about $4.54 per pound. Daily backtests run on this series operate on smoothed monthly data and miss the intra-month volatility that drives most trading P&L. For daily analysis, LME or COMEX series are required.
2. Treating copper as a pure China demand proxy. The “Dr. Copper” framing is convenient but incomplete. The copper price reacts to USD strength, real interest rates, energy-transition orders (EVs, grid build-out), and supply-side disruptions in Chile and Peru (which together produce ~40% of global copper). Attributing every copper move to Chinese manufacturing data misses these channels and produces misleading conclusions during USD strength regimes or major supply shocks. The underlying dynamic is traced in copper challenged by iron ore.
3. Reading nominal copper levels across decades without real adjustment. The series is quoted in nominal US dollars. The April 2008 peak of $8,685 per ton and the 2024 average of about $9,140 per ton look close, but US inflation and global production costs shifted in between. Joint analysis with US CPI and the dollar index is required for cross-decade comparison.
4. Ignoring the structural demand shift from the energy transition. Copper-intensive technologies (battery EVs, renewable generation, grid transmission upgrades) have added a structural demand floor since approximately 2020 that prior cyclical regimes did not face. Treating copper cycles as purely demand-cyclical without accounting for this structural channel can produce overconfident mean-reversion predictions.

Historical Regimes

The copper price’s 1992–2026 history decomposes into six regimes, each driven by distinct combinations of global demand, supply constraints, and macro forces.

1992–1999: Low and range-bound ($1,400–3,100 per ton). An eight-year regime of subdued global manufacturing growth, ample mine supply, and stable USD conditions. The monthly average peaked at $3,076 in July 1995 and fell to $1,378 in March 1999, after the Asian crisis cut demand.

2000–2008: China supercycle. China’s WTO accession (2001) and infrastructure-led growth model drove copper from $1,377 per ton in October 2001, the lowest month in the file, to $8,685 in April 2008. That roughly 6.3x move took six and a half years. This regime defined the “BRIC commodity supercycle” narrative and tracked closely with parallel moves in WTI and Brent crude.

2008–2009: GFC collapse and recovery. Copper fell from $8,685 per ton in April 2008 to $3,072 in December 2008, a 65% drop in eight months. The recovery, driven by China’s 4 trillion RMB stimulus and global central bank coordination, lifted the price to $9,868 by February 2011, above the 2008 peak.

2011–2016: Structural decline. A five-year bear market took copper from $9,868 per ton in February 2011 to $4,472 in January 2016, a 55% fall. China’s slowdown, the USD strengthening cycle initiated by Fed tapering (May 2013) and the exhaustion of the broader commodity supercycle drove it. The 2016 low marked the end of the cyclical bear regime.

2017–2019: Range-bound ($5,600–7,100 per ton). A three-year stabilization phase with global manufacturing modestly expanding and the 2018 US-China trade tensions creating two-way volatility. Joint reading with the US industrial production and ISM Manufacturing PMI tracks the cyclical signal closely in this regime.

2020–2026: Post-COVID and energy-transition regime. COVID stimulus, supply-chain disruption, and structural energy-transition demand drove copper from $5,058 per ton in April 2020 to $10,231 in March 2022, roughly double. After a softer 2023 (annual average $8,490), the price passed its March 2022 peak in October 2025 and reached $14,326 in August 2026, above every earlier month in the file. Unlike the 2003–2008 cycle, this regime added an energy-transition demand component (EV manufacturing, grid build-out, renewable generation) alongside the cyclical one. Joint reading with the natural gas and gold series helps decompose the commodity-wide versus copper-specific signals during this regime.

Related Macroeconomic Datasets

Copper sits at the intersection of industrial demand, USD dynamics, and the energy-transition structural shift. The datasets below place the copper price within the broader commodity and macro framework.

Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Explore the Eco3min Dataset Hub

Sources

• World Bank: Commodity Price Data (The Pink Sheet), Monthly Prices, column “Copper” (CC BY 4.0)
• London Metal Exchange (LME) settlement price, the market basis of the Pink Sheet series
• Board of Governors of the Federal Reserve System: Nominal Broad U.S. Dollar Index (DTWEXBGS), used for the dollar correlation above

Dataset Reference

Eco3min Research. (2026). Copper Price History (1992–2026). Source: World Bank, Commodity Price Data (The Pink Sheet), CC BY 4.0.<br> https://eco3min.fr/en/copper-price-history-dataset/