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Reviving the Competitive Storage Model: A Holistic Approach to Food Commodity Prices

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  • Mr. Norbert Funke
  • Weifeng Wu
  • Yanliang Miao

Abstract

We revive in this paper the empirical relevance of the competitive storage model by taking a holistic approach to food commodity prices. We augment the seminal Deaton and Laroque (1992, 1996) model by incorporating more comprehensive and realistic supply and demand factors: output and demand trends, shocks to the yield, and time-varying interest rates. While the computational burden increases exponentially, the augmented model succeeds in replicating all four key patterns of food commodity prices. Our simulation and comparative statics also show that (i) the long-run declining trend of food prices may come to a halt or even reverse due to the shifting balance between supply and demand; (ii) short-run price fluctuations are mainly attributable to sizeable, though low-probability, shocks to output such as inclement weather; and (iii) the impact of monetary policy, though small in normal times, is nonlinear and asymmetric, and can become large if the real rate passes a certain threshold.

Suggested Citation

  • Mr. Norbert Funke & Weifeng Wu & Yanliang Miao, 2011. "Reviving the Competitive Storage Model: A Holistic Approach to Food Commodity Prices," IMF Working Papers 2011/064, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2011/064
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    References listed on IDEAS

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    1. Carroll, Christopher D., 2006. "The method of endogenous gridpoints for solving dynamic stochastic optimization problems," Economics Letters, Elsevier, vol. 91(3), pages 312-320, June.
    2. Deaton, Angus & Laroque, Guy, 2003. "A model of commodity prices after Sir Arthur Lewis," Journal of Development Economics, Elsevier, vol. 71(2), pages 289-310, August.
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    Cited by:

    1. Hirbod Assa & Amal Dabbous & Nikolay Gospodinov, 2013. "A staggered pricing approach to modeling speculative storage: implications for commodity price dynamics," FRB Atlanta Working Paper 2013-08, Federal Reserve Bank of Atlanta.
    2. 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.
    3. Nader Karimi & Hirbod Assa & Erfan Salavati & Hojatollah Adibi, 2023. "Calibration of Storage Model by Multi-Stage Statistical and Machine Learning Methods," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1437-1455, December.
    4. Ahmed, Shamseddin Musa, 2020. "Impacts of drought, food security policy and climate change on performance of irrigation schemes in Sub-saharan Africa: The case of Sudan," Agricultural Water Management, Elsevier, vol. 232(C).
    5. David M Arseneau & Sylvain Leduc, 2013. "Commodity Price Movements in a General Equilibrium Model of Storage," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 61(1), pages 199-224, April.
    6. 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.
    7. Shrimali, Gireesh & Tirumalachetty, Sumala, 2013. "Renewable energy certificate markets in India—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 702-716.
    8. Tore S. Kleppe & Atle Oglend, 2019. "Can limits‐to‐arbitrage from bounded storage improve commodity term‐structure modeling?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 865-889, July.
    9. Chavas, Jean-Paul & Li, Jian, 2016. "On the Economics of Commodity Price Dynamics and Price Volatility," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235070, Agricultural and Applied Economics Association.

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