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

Hildegart Ahumada () and Magdalena Cornejo

International Journal of Forecasting, 2016, vol. 32, issue 3, 838-848

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.

Keywords: Forecast; Food prices; Equilibrium correction; Joint models; Breaks; Robust devices (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207016300073
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:3:p:838-848

DOI: 10.1016/j.ijforecast.2016.01.002

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().