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Comparing Numerical Methods for Solving the Competitive Storage Model

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  • Christophe Gouel

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Abstract

This paper compares numerical methods for solving the competitive storage model. Because storage implies a nonnegativity constraint on stocks, the solution methods must be considered carefully. The model is solved using value function iteration and several projection approaches, including parameterised expectations and decision rules approximation. In considering a storage model with convenience yield, in which the inequality constraint is smoothed, perturbation methods are also applied. Parameterised expectations approximation proves to be the most accurate method, whereas perturbation techniques are shown inadequate for solving this highly nonlinear model. The endogenous grid method allows rapid solution if supply is assumed to be inelastic. Copyright Springer Science+Business Media, LLC. 2013

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  • 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.
    • Handle: RePEc:kap:compec:v:41:y:2013:i:2:p:267-295
    DOI: 10.1007/s10614-012-9318-y
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    Cited by:

    1. Pfuderer, Simone, 2015. "An Experimental Approach to Testing the Competitive Storage Model," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204297, Agricultural Economics Society.
    2. Zhou, Wei & Babcock, Bruce A., 2014. "Endogenous Price in a Dynamic Model for Agricultural Supply Analysis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170584, Agricultural and Applied Economics Association.
    3. Gouel, Christophe & Legrand, Nicolas, 2016. "Bayesian Estimation of the Storage Model using Information on Quantities," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235599, Agricultural and Applied Economics Association.
    4. Pfuderer, Simone, 2014. "Are stockholders rational? An experimental approach to testing the competitive storage model," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170537, Agricultural Economics Society.
    5. Gouel, Christophe, 2013. "Optimal food price stabilisation policy," European Economic Review, Elsevier, vol. 57(C), pages 118-134.
    6. Zhou, Wei & Babcock, Bruce A., 2014. "Pricing RINs and Corn in a Competitive Storage Model," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170581, Agricultural and Applied Economics Association.
    7. Zhou, Wei, 2015. "Three essays on modeling biofuel feedstock supply," ISU General Staff Papers 201501010800005728, Iowa State University, Department of Economics.
    8. Nicolas Legrand, 2019. "The Empirical Merit Of Structural Explanations Of Commodity Price Volatility: Review And Perspectives," Journal of Economic Surveys, Wiley Blackwell, vol. 33(2), pages 639-664, April.
    9. Bruce A. Babcock & Wei Zhou, 2013. "Impact on Corn Prices from Reduced Biofuel Mandates," Center for Agricultural and Rural Development (CARD) Publications 13-wp543, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    10. Zhou, Wei & Babcock, Bruce A., 2017. "Using the competitive storage model to estimate the impact of ethanol and fueling investment on corn prices," Energy Economics, Elsevier, vol. 62(C), pages 195-203.
    11. Kleppe, Tore Selland & Oglend, Atle, 2017. "Estimating the competitive storage model: A simulated likelihood approach," Econometrics and Statistics, Elsevier, vol. 4(C), pages 39-56.

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