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Seasonal prediction of European cereal prices: good forecasts using bad models?

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  • Adusei Jumah

    (Institute for Advanced Studies and University of Vienna, Austria)

  • Robert M. Kunst

    (Institute for Advanced Studies and University of Vienna, Austria)

Abstract

Because of their natural adherence to the climate and pronounced seasonal cycles, prices of field crops constitute an interesting field for exploring seasonal time series models. We consider quarterly prices of two major cereals: barley and wheat. Using traditional in-sample fit and moving-window techniques, we investigate whether seasonality is deterministic or unit-root stochastic and whether seasonal cycles have converged over time. We find that seasonal cycles in the data are mainly deterministic and that evidence on common cycles across countries differs for the two commodities. Out-of-sample prediction experiments, however, yield a ranking with respect to accuracy that does not match the statistical in-sample evidence. Parametric bootstrap experiments establish that the observed mismatch is indeed an inherent and systematic feature. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Adusei Jumah & Robert M. Kunst, 2008. "Seasonal prediction of European cereal prices: good forecasts using bad models?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 391-406.
    • Handle: RePEc:jof:jforec:v:27:y:2008:i:5:p:391-406
    DOI: 10.1002/for.1062
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    Cited by:

    1. Martin-Rodriguez, Gloria & Caceres-Hernandez, Jose Juan, 2012. "Forecasting weekly Canary tomato exports from annual surface data," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126364, International Association of Agricultural Economists.
    2. Tao XIONG & Chongguang LI & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
    3. Yuehjen E. Shao & Jun-Ting Dai, 2018. "Integrated Feature Selection of ARIMA with Computational Intelligence Approaches for Food Crop Price Prediction," Complexity, Hindawi, vol. 2018, pages 1-17, July.
    4. Tiwari, Aviral Kumar & Dutta, Subhendu & Dash, Aruna Kumar, 2017. "Testing of the Seasonal Unit Root Hypothesis in the Price Indices of Agricultural Commodities in India," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 14(2), December.
    5. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022. "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, vol. 28(C).
    6. Adusei Jumah & Robert M. Kunst, 2016. "Optimizing time-series forecasts for inflation and interest rates using simulation and model averaging," Applied Economics, Taylor & Francis Journals, vol. 48(45), pages 4366-4378, September.
    7. Isengildina-Massa, Olga & MacDonald, Stephen, 2009. "U.S. Cotton Prices and the World Cotton Market: Forecasting and Structural Change," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49324, Agricultural and Applied Economics Association.

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