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Forecasting food prices: The case of corn, soybeans and wheat

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  • Ahumada, H.
  • Cornejo, M.

Abstract

Given the high correlations observed among food prices, we analyse whether the forecasting accuracies of individual food price models can be improved by considering their cross-dependence. We focus on three strongly correlated food prices: corn, soybeans and wheat. We analyse an unstable forecasting period (2008–2014) and apply robust approaches and recursive schemes. Our results indicate forecast improvements from using models that include price interactions.

Suggested Citation

  • Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
  • Handle: RePEc:eee:intfor:v:32:y:2016:i:3:p:838-848
    DOI: 10.1016/j.ijforecast.2016.01.002
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    References listed on IDEAS

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    1. Shahnoushi, Naser & Sayed, Saghaian & Hezareh, Reza & Tirgari Seraji, Mohammad, 2017. "Investigation of Relationship Between World Food Prices and Energy Price: A Panel SUR Approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252782, Southern Agricultural Economics Association.

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