IDEAS home Printed from
   My bibliography  Save this article

Maximum Likelihood Estimation of the Standard Commodity Storage Model: Evidence from Sugar Prices


  • Carlo Cafiero
  • Eugenio S.A. Bobenrieth H.
  • Juan R.A. Bobenrieth H.
  • Brian D. Wright


We present a Maximum Likelihood estimator for the standard commodity storage model with stockouts, based on prices only. While it imposes no additional assumptions on the model, the Maximum Likelihood estimator has small sample properties superior to those of the Pseudo Maximum Likelihood approach. We provide a proof that is crucial for applying our estimator to the model with normal harvests and possibly unbounded prices, thereby eliminating an inconsistency in the empirical storage model literature. Applying our Maximum Likelihood estimator to a series of annual sugar prices from 1921 to 2009 provides new evidence for the empirical relevance of the standard storage model. Our results imply a cutoff price at which discretionary stocks go to zero, which is higher than the price obtained by applying the Pseudo Maximum Likelihood estimator to the same data. The implied frequency of stockouts is lower, and price correlations, skewness, and kurtosis implied by the model closely match those seen in the annual sugar price data. We find the price of sugar to be highly responsive to small changes in consumption. When inventories are not available to buffer the effects of negative supply shocks on consumption, prices must increase sharply to induce the consumption changes needed to clear the market. Our results show why production shocks are not necessarily aligned with price spikes; the same production shock can give rise to very different price responses, depending on whether or not there are sufficient stocks to buffer its impact.

Suggested Citation

  • Carlo Cafiero & Eugenio S.A. Bobenrieth H. & Juan R.A. Bobenrieth H. & Brian D. Wright, 2015. "Maximum Likelihood Estimation of the Standard Commodity Storage Model: Evidence from Sugar Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 122-136.
  • Handle: RePEc:oup:ajagec:v:97:y:2015:i:1:p:122-136.

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Atle Oglend & Vesa-Heikki Soini, 2020. "Equilibrium Working Curves with Heterogeneous Agents," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 355-372, August.
    2. 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.
    3. 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.
    4. Gabriela Simonet & Julie Subervie & Driss Ezzine-de-Blas & Marina Cromberg & Amy Duchelle, 2015. "Paying smallholders not to cut down the Amazon forest: Impact evaluation of a REDD+ pilot project," Working Papers 15-14, LAMETA, Universtiy of Montpellier, revised Oct 2015.
    5. Gutierrez, Luciano & Piras, Francesco & Olmeo, Maria Grazia, 2015. "Forecasting Wheat Commodity Prices using a Global Vector Autoregressive model," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207264, Italian Association of Agricultural and Applied Economics (AIEAA).
    6. Christophe Gouel & Nicolas Legrand, 2017. "Estimating the Competitive Storage Model with Trending Commodity Prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 744-763, June.
    7. 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.
    8. Vorotnikova, Ekaterina, 2016. "Optimal Storage Capacity Allocation in Grain Merchandizing," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230128, Southern Agricultural Economics Association.
    9. Fabio G., Santeramo & Emilia, Lamonaca, 2018. "On the Drivers of Global Grain Price Volatility : an empirical investigation," MPRA Paper 86795, University Library of Munich, Germany.
    10. 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.
    11. Santeramo, Fabio Gaetano & Lamonaca, Emilia & Contò, Francesco & Stasi, Antonio & Nardone, Gianluca, 2017. "Drivers of grain price volatility: a cursory critical review," MPRA Paper 79427, University Library of Munich, Germany.
    12. 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.
    13. Oglend, Atle & Kleppe, Tore Selland, 2017. "On the behavior of commodity prices when speculative storage is bounded," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 52-69.
    14. Bobenrieth, Eugenio & Wright, Brian D. & Zeng, Di, 2014. "How Biofuels Policies Boosted Grain Staple Prices: A Counterfactual Analysis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170709, Agricultural and Applied Economics Association.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:ajagec:v:97:y:2015:i:1:p:122-136.. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press or Christopher F. Baum (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.