Forecasting International Sugar Prices: A Bayesian Model Average Analysis

Abstract

This paper examines the relative importance of key variables for the prediction of international sugar prices. Understanding movements in world sugar prices helps policy-makers and participants in the sugar value chain to formulate effective investment strategies and forecast the effects of market shocks more accurately. We combine a Bayesian model averaging (BMA) technique to address specification uncertainty with an out-of-sample analysis to evaluate price predictability. Results show that world sugar quotations are mostly influenced by their own dynamics, changes in international staple food prices, sugar production costs, and macroeconomic variables. The predictability of the BMA is found to be generally high, compared with a sample of benchmark time series approaches.

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Source: Authors’ calculations and FAO

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Source: Authors’ calculations

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Notes

  1. 1.

    The world reference quotation for sugar is the International Sugar Agreement (ISA) Daily Prices, which is based on the first three futures positions of the New York ICE, Contract No. 11.

  2. 2.

    The forecasts of the predictors are obtained with the assumption that they follow an ARIMA-based process.

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Acknowledgements

This research was partially funded by European Union’s Horizon 2020 Research Project SUSFANS under Grant Agreement No. 633692.

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Correspondence to El Mamoun Amrouk.

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Amrouk, E.M., Heckelei, T. Forecasting International Sugar Prices: A Bayesian Model Average Analysis. Sugar Tech 22, 552–562 (2020). https://doi.org/10.1007/s12355-020-00815-0

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Keywords

  • Sugar prices
  • Bayesian model averaging (BMA)
  • Forecast
  • Parameter priors
  • Model priors

JEL Classification

  • Q13
  • C13
  • G11
  • G01