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Editor's choice Empirical commodity storage model: the challenge of matching data and theory

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  • V. Ernesto Alex Guerra
  • Eugenio Sebastián Antonio Bobenrieth H.
  • Juan Rodrigo Andrés Bobenrieth H.
  • Carlo Cafiero

Abstract

The ability of the standard commodity storage model to replicate annual price serial correlation is a controversial issue. Calendar year averages of prices induce spurious smoothing of price spikes, a fact that has been surprisingly overlooked in several empirical estimations of the annual commodity storage model for agricultural commodities. We present the application of a maximum likelihood estimator of the storage model for maize prices, correcting for the spurious smoothing. We find, for this data set, serious differences in magnitudes of interest.

Suggested Citation

  • V. Ernesto Alex Guerra & Eugenio Sebastián Antonio Bobenrieth H. & Juan Rodrigo Andrés Bobenrieth H. & Carlo Cafiero, 2015. "Editor's choice Empirical commodity storage model: the challenge of matching data and theory," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(4), pages 607-623.
    • Handle: RePEc:oup:erevae:v:42:y:2015:i:4:p:607-623.
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    File URL: http://hdl.handle.net/10.1093/erae/jbu037
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    Citations

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    Cited by:

    1. Guerra Vallejos, Ernesto & Bobenrieth Hochfarber, Eugenio & Bobenrieth Hochfarber, Juan & Wright, Brian D., 2021. "Solving dynamic stochastic models with multiple occasionally binding constraints," Economic Modelling, Elsevier, vol. 105(C).
    2. Farhangdoost, Sara & Etienne, Xiaoli L., 2020. "Time-Varying Storage Announcement Effect in Natural Gas Market," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304476, 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. 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. Nicolas Legrand & Christophe Gouel, 2022. "The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data," Working Papers hal-03809825, HAL.
    6. Santeramo, Fabio Gaetano, 2017. "Market Fundamentals And International Grain Price Volatility," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 260908, European Association of Agricultural Economists.
    7. Berg, Ernst, 2017. "Impacts of Inventory Management on Price Volatility in Agricultural Commodity Markets: Insights from a System Dynamics Model," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261281, European Association of Agricultural Economists.
    8. V., Ernesto Guerra & H., Eugenio Bobenrieth & H., Juan Bobenrieth & Wright, Brian D., 2023. "Endogenous thresholds in energy prices: Modeling and empirical estimation," Energy Economics, Elsevier, vol. 121(C).
    9. Eugenio S.A. Bobenrieth & Juan R.A. Bobenrieth & Ernesto A. Guerra & Brian D. Wright & Di Zeng, 2021. "Putting the Empirical Commodity Storage Model Back on Track: Crucial Implications of a “Negligible” Trend," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1034-1057, May.
    10. Fabio Gaetano Santeramo & Emilia Lamonaca & Francesco Contò & Gianluca Nardone & Antonio Stasi, 2018. "Drivers of grain price volatility: a cursory critical review," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(8), pages 347-356.
    11. Oglend, Atle, 2022. "The commodities/equities beta term-structure," Journal of Commodity Markets, Elsevier, vol. 28(C).

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