Commodity forecast accuracy brochure

A recent assessment by the World Bank Group identified the Oxford Economics Model as a superior tool for forecasting commodity prices.  

Key takeaways:
  • In its analysis, the World Bank Group conducted an in-depth comparison of five well-known forecasting approaches to forecasting the prices of three key industrial commodities: aluminium, copper and crude oil over the period of 2015Q1 to 2022Q1. These commodities represent approximately 50% of global commodity exports, highlighting the significance of accurate forecasting.
  • The World Bank Group concluded that beyond one year, Oxford Economics Model and CE forecasts produce more accurate forecasts.
  • In addition, The World Bank Group highlighted that Oxford Economics Model ‘is particularly useful for scenario exercises that consider changes in policy variables, global growth, inflation, and structural variables.’
  • ‘Forecasts based on the OEM displayed a smaller difference in relative performance before and after the pandemic, as the model had been adapted to accommodate the pandemic shock.’
  • For lead, nickel, tin and zinc prices, ‘the OEM forecast showing the lowest bias and forecast error for forecast horizons of 12 months or more’.
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