Rubber Price History: Monthly Global Natural Rubber Price Since 1992

Natural rubber, tapped from trees across Southeast Asia, is essential to tyres and industrial goods. Because it competes with petroleum-derived synthetic rubber, its price tracks crude oil as well as plantation supply. This dataset tracks the IMF Primary Commodity Prices natural rubber benchmark (Ribbed Smoked Sheet basis), published monthly in US cents per pound and distributed via FRED under the code PRUBBUSDM, with continuous coverage since 1992. Thailand and Indonesia are the dominant producers.

Dataset: Rubber Price (1992–2026) · 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 PRUBBUSDM, sourced from the IMF Primary Commodity Prices dataset:

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

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/rubber-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/rubber-price.csv"
df = pd.read_csv(url, parse_dates=["date"])

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

df.plot(x="date", y="rubber_price", title="Rubber Price", legend=False)

Using the Dataset in R

library(readr)

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

head(df)
summary(df$rubber_price)

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

Methodology

The IMF reports the natural rubber price in US cents per pound, based on No.1 Ribbed Smoked Sheet (RSS) quoted in Singapore and Malaysia.

Values are monthly averages, which smooth the intra-month swings visible in daily futures and physical quotes. The series begins in 1992.

This dataset is updated monthly via an automated pull from the FRED API (series PRUBBUSDM) 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 in US cents per pound; exchange quotes (SICOM, Osaka, Shanghai) are usually in US dollars or cents per kilogram, so comparison requires conversion (1 kg ≈ 2.205 lb).

Historical Regimes

1992–2001 — Lows and the Asian crisis. The 1997-98 Asian financial crisis and ample supply held prices down.

2002–2008 — Oil-linked rise. Rising crude oil (lifting synthetic-rubber costs) and Chinese demand carried rubber higher into 2008.

2009–2011 — Record peak. Post-crisis Chinese tyre demand and Thai flooding drove rubber to a record in 2011, a multi-year high near $6 per kilogram.

2012–2020 — Decade-long decline. Expanding ASEAN supply, slowing Chinese growth, and cheaper synthetics dragged prices down by roughly 11% a year.

2021–2023 — Modest recovery. Post-pandemic auto demand and high freight costs lifted prices off their lows.

2024–2025 — Multi-year-high rally. Drought and flooding cut Thai and Indonesian output, leaf-fall disease spread, and the EU Deforestation Regulation tightened supply, pushing rubber above $2 per kilogram — a roughly seven-year high — before easing into early 2026.

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 Rubber
• Federal Reserve Bank of St. Louis — FRED database, series PRUBBUSDM
• Singapore Commodity Exchange (SICOM) RSS quotations — basis underlying the IMF series

Dataset Reference

Eco3min Research. (2026). Rubber Price — Global Monthly Price (1992-2026). Source: IMF Primary Commodity Prices via FRED.<br> https://eco3min.fr/en/rubber-price-history-dataset/