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How predictable are prices of agricultural commodities? The possibilities and constraints of forecasting wheat prices

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  • Holst, Carsten

Abstract

Wheat price forecasts are very important for traders, farmers and politicians as well. However, only quite accurate price predictions can guide these groups towards making the best decisions. Therefore the well-known wheat price projections of both the OECD and the FAPRI from 1996 on are tested for their predictive accuracy using Theil's inequality coefficient. Despite the fact that both models could not foresee the price peak which occurred in February 2008, their predictions offer more accurate values than a naive prediction of no price change. Nevertheless, precise price forecasts cannot be expected by the models of the OECD and the FAPRI since some short-run effects such as inappropriate weather are not predictable. Thus, our own econometric model is developed taking the previous price development, the stocks-to-use-ratio and the crude oil price into account. In comparison to the projections of both institutions the model, with rather simple assumptions, was able to generate forecasts more accurately. In a simulation study which takes different crude oil price levels and stochastic effects of the world wheat consumption and the average yields per hectare into account, the possible wheat price range is shown as large. Therefore, price predictions can only inform about general longrun trends.

Suggested Citation

  • Holst, Carsten, 2010. "How predictable are prices of agricultural commodities? The possibilities and constraints of forecasting wheat prices," IAMO Forum 2010: Institutions in Transition – Challenges for New Modes of Governance 52717, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
  • Handle: RePEc:zbw:iamo10:52717
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    References listed on IDEAS

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    1. Bernhard Brümmer & Ulrich Koester & Jens-Peter Loy, 2008. "Weltgetreidemarkt: Anhaltender Boom oder kurzfristige Spekulationsblase?," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 88(10), pages 654-662, October.
    2. Brümmer, Bernhard & Koester, Ulrich & Loy, Jens-Peter, 2008. "Tendenzen auf dem Weltgetreidemarkt: anhaltender Boom oder kurzfristige Spekulationsblase?," DARE Discussion Papers 0807, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    3. Dwight R. Sanders & Scott H. Irwin, 2010. "A speculative bubble in commodity futures prices? Cross‐sectional evidence," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 25-32, January.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, November.
    6. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, November.
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    Cited by:

    1. Pokorný, Jiří & Froněk, Pavel, 2021. "Price Forecasting Accuracy of the OECD-FAO's Agricultural Outlook and the European Commission DG AGRI's Medium-Term Agricultural Outlook Report," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 13(3), September.

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    More about this item

    Keywords

    wheat price forecasts; predictive accuracy; Theil's inequality coefficient;
    All these keywords.

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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