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

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

Abstract

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.
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    File URL: http://hdl.handle.net/10.1093/ajae/aau068
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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. 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.
    3. Albuquerque, Rui & de Araujo, Bruno & Brandao-Marques, Luis & Mosse, Gerivasia & de Vletter, Pippy & Zavale, Helder, 2024. "Market timing, farmer expectations, and liquidity constraints," Journal of Development Economics, Elsevier, vol. 168(C).
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. Nicolas Legrand, 2023. "“The empirical relevance of the competitive storage model” by Cafiero et al. (2011): Replication, robustness, and extension," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1493-1514, September.
    9. 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.
    10. Nicolas Legrand & Christophe Gouel, 2022. "The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data," Working Papers hal-03809825, HAL.
    11. Dalheimer, Bernhard & Fiankor, Dela-Dem Doe, 2022. "Food Production Shocks and Agricultural Supply Elasticities in Sub-Saharan Africa," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322168, Agricultural and Applied Economics Association.
    12. 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.
    13. 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.
    14. Fabio Gaetano Santeramo & Emilia Lamonaca, 2019. "On the drivers of global grain price volatility: an empirical investigation," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(1), pages 31-42.
    15. 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).
    16. 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.
    17. Sima Siami‐Namini, 2021. "U.S. Monetary Policy and Commodity Prices: A SVECM Approach," Economic Papers, The Economic Society of Australia, vol. 40(4), pages 288-312, December.
    18. 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.
    19. Juan R. A. Bobenrieth & Eugenio S. A. Bobenrieth & Andrés F. Villegas & Brian D. Wright, 2022. "Estimation of Endogenous Volatility Models with Exponential Trends," Mathematics, MDPI, vol. 10(15), pages 1-27, July.
    20. 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.
    21. 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.
    22. 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.

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