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Pricing and Storage of Field Crops: A Quarterly Model Applied to Soybeans

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  • Mark Lowry
  • Joseph Glauber
  • Mario Miranda
  • Peter Helmberger

Abstract

This paper considers the role of competitive storage in markets for annually harvested field crops. A quarterly model is presented that considers the allocative role of storage both within and between crop years. Rational price expectations are endogenous variables calculated by a recursive method. Forward stochastic simulations using the model generate data that can be used to characterize the distributions of the variables. In the base case, the model is assigned parameter values from a quarterly econometric model of the U.S. soybean market. The results shed light on the distributions of the quarterly variables, including the rational price expectations, and show how these distributions are affected by changes in the carrying charge.

Suggested Citation

  • Mark Lowry & Joseph Glauber & Mario Miranda & Peter Helmberger, 1987. "Pricing and Storage of Field Crops: A Quarterly Model Applied to Soybeans," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(4), pages 740-749.
    • Handle: RePEc:oup:ajagec:v:69:y:1987:i:4:p:740-749.
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    File URL: http://hdl.handle.net/10.2307/1242183
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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. Holt, Matthew T., 1989. "Risk, Rational Expectations, and Price Stabilization in the U.S. Corn Market," Staff Papers 200480, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    3. 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.
    4. 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.
    5. Huang, Wen-Yuan & Hyberg, Bengt & Segarra, Eduardo, 1990. "A Variable Price Support Farm Program: A Transition Tool To A Free Market," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 22(1), pages 1-11, July.
    6. Park, Hwanil & Fortenbery, T. Randall, 2007. "The Effect of Ethanol Production on the U.S. National Corn Price," 2007 Conference, April 16-17, 2007, Chicago, Illinois 37565, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Anna Kormilitsina, 2013. "Solving Rational Expectations Models with Informational Subperiods: A Perturbation Approach," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 525-555, April.
    8. Miranda, Mario J & Glauber, Joseph W, 1993. "Estimation of Dynamic Nonlinear Rational Expectations Models of Primary Commodity Markets with Private and Government Stockholding," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 463-470, August.
    9. Chaton, Corinne & Creti, Anna & Villeneuve, Bertrand, 2008. "Some economics of seasonal gas storage," Energy Policy, Elsevier, vol. 36(11), pages 4235-4246, November.
    10. 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.
    11. Nicolas Legrand & Christophe Gouel, 2022. "The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data," Working Papers hal-03809825, HAL.
    12. repec:dau:papers:123456789/5365 is not listed on IDEAS
    13. Sophie Mitra & Jean‐Marc Boussard, 2012. "A simple model of endogenous agricultural commodity price fluctuations with storage," Agricultural Economics, International Association of Agricultural Economists, vol. 43(1), pages 1-15, January.
    14. Serena Ng & Francisco J. Ruge-Murcia, 2000. "Explaining the Persistence of Commodity Prices," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 149-171, October.
    15. Stephen E. Miller, 1990. "Some empirical evidence for production smoothing in the agribusiness sector," Agribusiness, John Wiley & Sons, Ltd., vol. 6(1), pages 41-52.
    16. Chen, Dean T. & Bessler, David A., 1988. "Impulse Responses and Intertemporal Pricing of Cotton," Staff Reports 257914, Texas A&M University, Agricultural and Food Policy Center.
    17. Chambers, Robert G. & Pope, Rulon D., 1989. "What Do Aggregate Agricultural Supply and Demand Curves Mean?," Working Papers 197605, University of Maryland, Department of Agricultural and Resource Economics.
    18. Chaudhry, Muhammad Imran & Katchova, Ani & Miranda, Mario Javier, 2016. "Examining pricing mechanics in the poultry value chain - empirical evidence from Pakistan," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235953, Agricultural and Applied Economics Association.
    19. Chambers, Robert G. & Pope, Rulon D., 1989. "What Do Aggregate Agricultural Supply and Demand Curves Mean?," 1990 Conference (34th), February 13-15, 1990, Brisbane, Australia 144922, Australian Agricultural and Resource Economics Society.
    20. Hélyette Geman & Vu-Nhat Nguyen, 2005. "Soybean Inventory and Forward Curve Dynamics," Management Science, INFORMS, vol. 51(7), pages 1076-1091, July.

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