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Estimating a Nonlinear Rational Expectations Commodity Price Model with Unobservable State Variables

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  • Deaton, Angus
  • Laroque, Guy

Abstract

This paper is concerned with the estimation of a model in which a possibly serially correlated stochastic process, the "harvest" of an agricultural commodity, generates a competitive price in a market comprising both final consumers and risk-neutral speculators who can store the commodity at a cost in the anticipation of profit. Because storage cannot be negative, the relationship between prices and harvests is inherently nonlinear and is an unpromising candidate for a linear-quadratic model, or for linearization more generally. Instead, we calculate numerically a policy function in which price is a function of two unobservable state variables, the harvest and current availability, and we use the result to fit the price data. Copyright 1995 by John Wiley & Sons, Ltd.

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  • Deaton, Angus & Laroque, Guy, 1995. "Estimating a Nonlinear Rational Expectations Commodity Price Model with Unobservable State Variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(S), pages 9-40, Suppl. De.
  • Handle: RePEc:jae:japmet:v:10:y:1995:i:s:p:s9-40
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    Cited by:

    1. Christophe Gouel, 2012. "Agricultural Price Instability: A Survey Of Competing Explanations And Remedies," Journal of Economic Surveys, Wiley Blackwell, vol. 26(1), pages 129-156, February.
    2. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    3. Ivanic, Maros & Martin, Will, 2014. "Implications of domestic price insulation for global food price behavior," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 272-288.
    4. Michaelides, Alexander & Ng, Serena, 2000. "Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators," Journal of Econometrics, Elsevier, vol. 96(2), pages 231-266, June.
    5. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    6. repec:eee:ecosta:v:4:y:2017:i:c:p:39-56 is not listed on IDEAS
    7. Ghoshray, Atanu, 2011. "A reexamination of trends in primary commodity prices," Journal of Development Economics, Elsevier, vol. 95(2), pages 242-251, July.
    8. Oglend, Atle & Kleppe, Tore Selland, 2017. "On the behavior of commodity prices when speculative storage is bounded," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 52-69.
    9. Colin A. Carter & Gordon C. Rausser & Aaron Smith, 2011. "Commodity Booms and Busts," Annual Review of Resource Economics, Annual Reviews, vol. 3(1), pages 87-118, October.
    10. Pietola, Kyösti & Liu, Xing & Robles, Miguel, 2010. "Price, inventories, and volatility in the global wheat market," IFPRI discussion papers 996, International Food Policy Research Institute (IFPRI).
    11. Christophe Gouel, 2013. "Comparing Numerical Methods for Solving the Competitive Storage Model," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 267-295, February.
    12. Scandizzo, Pasquale Lucio & Savastano, Sara & Vezzani, Antonio, 2010. "The deterministic and speculative component of the terms of trade of primary commodities: An “Eclectic” Real Option value approach," 114th Seminar, April 15-16, 2010, Berlin, Germany 61086, European Association of Agricultural Economists.
    13. Gronwald, Marc, 2016. "Explosive oil prices," Energy Economics, Elsevier, vol. 60(C), pages 1-5.
    14. Brunetti, Celso & Gilbert, Christopher L., 1995. "Metals price volatility, 1972-1995," Resources Policy, Elsevier, vol. 21(4), pages 237-254, December.

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