CRB Index rose to 378.33 Index Points on December 1, 2025, up 0.45% from the previous day. Over the past month, CRB Index's price has fallen 0.80%, but it is still 10.95% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

Time series of major commodity prices and indices including iron, cooper, wheat, gold, oil. Data comes from the International Monetary Fund (IMF).

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Data

Dataset contains Monthly prices for 53 commodities and 10 indexes, starting from 1980 to 2016, Last updated on march 17, 2016. The reference year for indexes are 2005 (meaning the value of indexes are 100 and all other values are relative to that year).

License

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Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.

Orange Juice fell to 147.99 USd/Lbs on December 2, 2025, down 0.38% from the previous day. Over the past month, Orange Juice's price has fallen 15.22%, and is down 71.10% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Orange Juice - values, historical data, forecasts and news - updated on December of 2025.

Time series data for the commodity Primary Commodity Prices, Coffee index . Indicator Definition:Primary Commodity Prices, Coffee index The indicator "Primary Commodity Prices, Coffee index " stands at 223.80 as of 8/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 11.39 percent compared to the value the year prior.The 1 year change in percent is 11.39.The 3 year change in percent is 55.61.The 5 year change in percent is 146.61.The 10 year change in percent is 132.43.The Serie's long term average value is 93.49. It's latest available value, on 8/31/2025, is 139.38 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 10/31/2001, to it's latest available value, on 8/31/2025, is +638.31%.The Serie's change in percent from it's maximum value, on 2/28/2025, to it's latest available value, on 8/31/2025, is -18.14%.

Time series data for the commodity Primary Commodity Prices, Groundnuts . Indicator Definition:Primary Commodity Prices, Groundnuts The indicator "Primary Commodity Prices, Groundnuts " stands at 2.66 Thousand as of 8/31/2025, the highest value since 8/31/2023. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.14 percent compared to the value the year prior.The 1 year change in percent is 6.14.The 3 year change in percent is 10.15.The 5 year change in percent is 37.86.The 10 year change in percent is 30.10.The Serie's long term average value is 1.42 Thousand. It's latest available value, on 8/31/2025, is 87.57 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 5/31/2002, to it's latest available value, on 8/31/2025, is +353.38%.The Serie's change in percent from it's maximum value, on 7/31/2023, to it's latest available value, on 8/31/2025, is -1.65%.

Graph and download economic data for Producer Price Index by Commodity: All Commodities (PPIACO) from Jan 1913 to Sep 2025 about commodities, PPI, inflation, price index, indexes, price, and USA.

Context

Time series of major commodity prices and indices including iron, cooper, wheat, gold, oil

Content

Dataset contains Monthly prices for 53 commodities and 10 indexes, starting from 1980 to 2016, Last updated on march 17, 2016. The reference year for indexes are 2005 (meaning the value of indexes are 100 and all other values are relative to that year).

Inspiration

This is a challenging dataset with a fair share of NaN values. Some really good potential for EDA and also Time Series Analysis!

This paper investigates the role of commodity price information when evaluating inflation risk. Using a model averaging approach, we provide strong evidence of in-sample and out-of-sample predictive ability from commodity prices and convenience yields to inflation, establishing clear point and density forecast performance gains when incorporating disaggregated commodities price information. The resulting forecast densities are used to calculate the (ex-ante) risk of inflation breaching defined thresholds that broadly characterize periods of high and low inflation. We find that information in commodity prices significantly enhances our ability to pick out tail inflation events and to characterize the level of risks associated with periods of high volatility in commodity prices.

Coffee fell to 408.66 USd/Lbs on December 2, 2025, down 0.95% from the previous day. Over the past month, Coffee's price has risen 0.50%, and is up 38.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on December of 2025.

Time series data for the commodity Primary Commodity Prices, Vegetables, Tomato. Indicator Definition:Primary Commodity Prices, Vegetables, TomatoThe indicator "Primary Commodity Prices, Vegetables, Tomato" stands at 3.90 as of 08/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 12.86 percent compared to the value the year prior.The 1 year change in percent is 12.86.The 3 year change in percent is 42.51.The 5 year change in percent is 22.99.The 10 year change in percent is 38.59.

Australia Commodity Price Index: 2011-12=100: All Items: US$ data was reported at 78.873 2011-2012=100 in Feb 2014. This records a decrease from the previous number of 79.689 2011-2012=100 for Jan 2014. Australia Commodity Price Index: 2011-12=100: All Items: US$ data is updated monthly, averaging 27.627 2011-2012=100 from Jul 1982 (Median) to Feb 2014, with 380 observations. The data reached an all-time high of 111.341 2011-2012=100 in Jul 2011 and a record low of 20.479 2011-2012=100 in Jul 1986. Australia Commodity Price Index: 2011-12=100: All Items: US$ data remains active status in CEIC and is reported by Reserve Bank of Australia. The data is categorized under Global Database’s Australia – Table AU.I048: Commodity Price Index: 2011-12=100. The Commodity Price Index is intended to provide a timely indicator of the prices received by Australian commodity exporters. It is based on the prices of 22 major commodities exported by Australia. Commodity Price Index is a Laspeyres index, which means that it is a weighted average of recent changes in commodity prices, where the weight given to each commodity reflects its importance in total commodity export values in a base period. The index, including its rural, non-rural and base metals components, is published monthly in terms of US dollars, Australian dollars and Special Drawing Rights (SDRs).

Abstract

A survey of select rural markets in Rwanda captured monthly data on price and availability of a basket of 68 goods. Data was captured every month from January 2017 to November 2020 for 130 markets; 18 additional markets have data from 2017 and 2018 only. The markets are not a random sample and were selected based on their proximity to roads scheduled for rehabilitation by the Government of Rwanda. Markets are spread across 21 districts in Rwanda, covering all 4 provinces.

This is a panel dataset of monthly price data from a selected sample of rural markets in Rwanda, with data points starting in January 2017 and ending in November 2020.

Geographic coverage

The dataset includes markets in 21 districts of Rwanda, covering all 4 provinces.

Analysis unit

Product (one observation per product per month per market).

Kind of data

Sample survey data [ssd]

Sampling procedure

Markets were purposively sampled, based on proximity to roads prioritized for rehabilitation by the Government of Rwanda.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

2-3 price points were taken per product at each market per month. In order to deal with outliers, prices were logged and averaged to get mean monthly prices, then exponentiated to be interpretable. Where a product was not available, there is no price data. However, there are cases where a product was available but price data was not available. Indicators other than availability and price are embargoed and not included in the dataset at this time.

Summary of Commodity Price Relationships Across Data Sources.

Beef traded flat at 321.60 BRL/15KG on December 1, 2025. Over the past month, Beef's price has risen 0.44%, but it is still 8.58% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Beef - values, historical data, forecasts and news - updated on December of 2025.

In 2024, the average annual London Metal Exchange (LME) price for tin was approximately ** U.S. dollars per pound, making it the highest-priced base metal that year. Nickel had the *******highest price out of the base metals at that time, with an average annual LME price of approximately **** U.S. dollars per pound in 2024. Although there is no clear-cut definition of the term, base metals usually refer to metals that oxidize easily, and is most commonly categorized as including tin, nickel, copper, zinc, lead, and aluminum.

International merchandise trade price and volume indexes, grouped by North American Product Classification System (NAPCS) section. Users have the option of selecting Imports or Exports, as well as Paasche or Laspeyres price indexes, or Laspeyres volume indexes. Data are unadjusted and seasonally adjusted, on a Customs and Balance of Payments basis, at a monthly frequency.

Country-specific commodity price indices, including export, import, and terms-of-trade indices. For each country, the change in the international price of up to 45 individual commodities is weighted using commodity-level trade data. See "Commodity Terms of Trade: A New Database" by Bertrand Gruss and Suhaib Kebhaj, for further details.

The country-specific indices are constructed using, alternatively, time-varying weights (using average trade flows over the preceding three years) and fixed weights (based on average trade flows over several decades).

Time series data for the commodity Primary Commodity Prices, Legumes, Chickpea. Indicator Definition:Primary Commodity Prices, Legumes, ChickpeaThe indicator "Primary Commodity Prices, Legumes, Chickpea" stands at 69.52 as of 08/31/2025. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -21.67 percent compared to the value the year prior.The 1 year change in percent is -21.67.The 3 year change in percent is 15.89.The 5 year change in percent is 13.91.The 10 year change in percent is -3.35.The Serie's long term average value is 64.55. It's latest available value, on 08/31/2025, is 7.71 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 03/31/2009, to it's latest available value, on 08/31/2025, is +66.53%.The Serie's change in percent from it's maximum value, on 10/31/2016, to it's latest available value, on 08/31/2025, is -55.84%.

This paper shows that rare disaster concern, defined as the news implied volatility, performs very well at predicting the return of index commodity futures throughout the whole century (1926-2016). This result holds after controlling for the current business cycle conditions, the macroeconomic variables, and the VIX. We also find that rare disaster concern performs very well at predicting index commodity futures returns out-of-sample. The results remain robust while considering different macroeconomic conditions, such as recession (expansion), contango (backwardation), or inflation up (down).This excel document contains the main data for the paper: "One Hundred Years of Rare Disaster Concerns and Commodity Prices". Commodity returns data is from Levine, Ooi, Richardson, and Sasseville (2018), https://doi.org/10.2469/faj.v74.n2.4The Matlab code for result replication is available at Qunzi Zhang's website:https://sites.google.com/site/zhangqunzi/