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Solving Stochastic Models of Competitive Storage and Trade by Chebychev Collocation Methods

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  • Miranda, Mario J.
  • Glauber, Joseph W.

Abstract

We show how to solve the stochastic spatial-temporal price equilibrium model numerically using the Chebychev collocation method. We then use the model to analyze the joint and interactive stabilizing effects of competitive storage and trade.

Suggested Citation

  • Miranda, Mario J. & Glauber, Joseph W., 1995. "Solving Stochastic Models of Competitive Storage and Trade by Chebychev Collocation Methods," Agricultural and Resource Economics Review, Cambridge University Press, vol. 24(1), pages 70-77, April.
    • Handle: RePEc:cup:agrerw:v:24:y:1995:i:01:p:70-77_00
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    Cited by:

    1. Brockhaus, Jan & Kalkuhl, Matthias, 2015. "Grain emergency reserve cooperation – A theoretical analysis of benefits from a common emergency reserve," 2015 Conference, August 9-14, 2015, Milan, Italy 212767, International Association of Agricultural Economists.
    2. Makki, Shiva S. & Tweeten, Luther G. & Miranda, Mario J., 2001. "Storage-trade interactions under uncertainty: Implications for food security," Journal of Policy Modeling, Elsevier, vol. 23(2), pages 127-140, February.
    3. 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.
    4. Christophe Gouel & Sébastien Jean, 2015. "Optimal Food Price Stabilization in a Small Open Developing Country," The World Bank Economic Review, World Bank, vol. 29(1), pages 72-101.
    5. Kornher, Lukas & Kalkuhl, Matthias, 2013. "Food Price Volatility in Developing Countries and its Determinants," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 52(4), pages 1-32, November.
    6. Donald F. Larson & Julian Lampietti & Christophe Gouel & Carlo Cafiero & John Roberts, 2014. "Food Security and Storage in the Middle East and North Africa," The World Bank Economic Review, World Bank, vol. 28(1), pages 48-73.
    7. Li, J. & Chavas, J.-P., 2018. "How Have China s Agricultural Price Support Policies Affected Market Prices?: A Quantile Regression Evaluation," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277557, International Association of Agricultural Economists.
    8. 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.
    9. Chen, Bowen & Villoria, Nelson B., "undated". "Food Price Variability and Import Dependence: A Country Panel Analysis," 2018 Annual Meeting, August 5-7, Washington, D.C. 274285, Agricultural and Applied Economics Association.
    10. Santeramo, Fabio, 2021. "Price dynamics, LOP and quantile regressions," MPRA Paper 107454, University Library of Munich, Germany.
    11. Scheitrum, Daniel P. & Carter, Colin A. & Revoredo-Giha, Cesar, 2018. "WTI and Brent futures pricing structure," Energy Economics, Elsevier, vol. 72(C), pages 462-469.
    12. Mario J. Miranda & Joseph W. Glauber, 2022. "A model of asynchronous bi‐hemispheric production in global agricultural commodity markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(2), pages 812-830, March.
    13. Christophe Gouel, 2020. "The Value of Public Information in Storable Commodity Markets: Application to the Soybean Market," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 846-865, May.

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