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Explaining the Persistence of Commodity Prices

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  • Serena Ng
  • Francisco J. Ruge-Murcia

Abstract

This paper extends the Competitive Storage Model by incorporating prominent features of the production process and financial markets. This extension seems necessary since the basic model does not successfully explain the degree of serial correlation observed in actual data. To generate a high degree of price persistence, the model must incorporate agents that are willing to hold stocks more often than predicted by the basic model, so we include characteristics of the production and trading mechanisms to provide the required incentives. Specifically, we introduce (i) gestation lags in production with heteroskedastic supply shocks, (ii) multiperiod forward contracts, and (iii) a convenience return to inventory holding. Rational expectations solutions for twelve commodities are solved numerically. Simulations are then used to assess the effects of these extensions on the time-series properties of commodity prices. The results indicate that each feature accounts partly for the persistence as well as the occasional spikes observed in actual data. Evidence is also presented that the precautionary demand for stocks might play a substantial role in the dynamics of commodity prices.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:16:y:2000:i:1/2:p:149-171
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    Cited by:

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    3. Chavas, Jean-Paul & Li, Jian, 2017. "The Effects of Private Stocks versus Public Stocks on Food Price Volatility," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259185, Agricultural and Applied Economics Association.
    4. 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.
    5. Pieroni, Luca & Ricciarelli, Matteo, 2008. "Modelling dynamic storage function in commodity markets: Theory and evidence," Economic Modelling, Elsevier, vol. 25(5), pages 1080-1092, September.
    6. Nzuma, Jonathan M. & Karugia, T.J. & Wanjiku, J. & Wambua, J. & Kirui, Oliver K., 2013. "Staple Food Price Volatility and Its Policy Implications in Kenya," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 161525, African Association of Agricultural Economists (AAAE).
    7. Moledina, Amyaz A. & Roe, Terry L. & Shane, Mathew, 2004. "Measuring Commodity Price Volatility And The Welfare Consequences Of Eliminating Volatility," 2004 Annual meeting, August 1-4, Denver, CO 19963, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. 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.
    9. 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.
    10. Loening, Josef L. & Durevall, Dick & Birru, Yohannes A., 2009. "Inflation dynamics and food prices in an agricultural economy : the case of Ethiopia," Policy Research Working Paper Series 4969, The World Bank.
    11. Vivian, Andrew & Wohar, Mark E., 2012. "Commodity volatility breaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 395-422.
    12. Ashima Goyal & Shruti Tripathi, 2012. "Regulations and price discovery: oil spot and futures markets," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-016, Indira Gandhi Institute of Development Research, Mumbai, India.
    13. 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.
    14. 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.
    15. Nishimura, Kazuo & Stachurski, John, 2009. "Equilibrium storage with multiple commodities," Journal of Mathematical Economics, Elsevier, vol. 45(1-2), pages 80-96, January.
    16. Baur, Dirk G. & Dimpfl, Thomas, 2018. "The asymmetric return-volatility relationship of commodity prices," Energy Economics, Elsevier, vol. 76(C), pages 378-387.
    17. 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.
    18. Kindie Getnet & Wim Verbeke & Jacques Viaene, 2005. "Modeling spatial price transmission in the grain markets of Ethiopia with an application of ARDL approach to white teff," Agricultural Economics, International Association of Agricultural Economists, vol. 33(s3), pages 491-502, November.
    19. Sklavos, Konstantinos & Dam, Lammertjan & Scholtens, Bert, 2013. "The liquidity of energy stocks," Energy Economics, Elsevier, vol. 38(C), pages 168-175.
    20. Boschi, Melisso & Pieroni, Luca, 2009. "Aluminium market and the macroeconomy," Journal of Policy Modeling, Elsevier, vol. 31(2), pages 189-207.
    21. Power, Gabriel J. & Turvey, Calum G., 2008. "On Term Structure Models of Commodity Futures Prices and the Kaldor-Working Hypothesis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37608, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    22. 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.
    23. 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.
    24. Nader Karimi & Erfan Salavati & Hirbod Assa & Hojatollah Adibi, 2023. "Sensitivity Analysis of Optimal Commodity Decision Making with Neural Networks: A Case for COVID-19," Mathematics, MDPI, vol. 11(5), pages 1-15, February.
    25. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.

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    More about this item

    Keywords

    commodity prices; persistence; speculative storage;
    All these keywords.

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • G1 - Financial Economics - - General Financial Markets
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture

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