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Explaining the Persistence of Commodity Prices

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  • NG, Serena
  • RUGE-MURCIA, Francisco J.
Abstract
This paper extends the Competitive Storage Model by incorporating prominent features of the production process and financial markets. A major limitation of this basic model is that it cannot successfully explain the degree of serial correlation observed in actual data. The proposed extensions build on the observation that in order to generate a high degree of price persistence, a model must incorporate features such that agents are willing to hold stocks more often than predicted by the basic model. We therefore allow unique characteristics of the production and trading mechanisms to provide the required incentives. Specifically, the proposed models introduce (i) gestation lags in production with heteroskedastic supply shocks, (ii) multiperiod forward contracts, and (iii) a convenience return to inventory holding. The rational expectations solutions for twelve commodities are numerically solved. Simulations are then employed to assess the effects of the above extensions on the time series properties of commodity prices. Results indicate that each of the features above partially account for the persistence and occasional spikes observed in actual data. Evidence is presented that the precautionary demand for stocks might play a substantial role in the dynamics of commodity prices.

Suggested Citation

  • NG, Serena & RUGE-MURCIA, Francisco J., 1997. "Explaining the Persistence of Commodity Prices," Cahiers de recherche 9709, Universite de Montreal, Departement de sciences economiques.
    • Handle: RePEc:mtl:montde:9709
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    File URL: http://hdl.handle.net/1866/446
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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. Sklavos, Konstantinos & Dam, Lammertjan & Scholtens, Bert, 2013. "The liquidity of energy stocks," Energy Economics, Elsevier, vol. 38(C), pages 168-175.
    3. 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.
    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. Eyal Dvir & Ken Rogoff, 2009. "The Three Epochs of Oil," Boston College Working Papers in Economics 706, Boston College Department of Economics.
    6. 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.
    7. 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.
    8. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
    9. 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.
    10. Loening, Josef L. & Durevall, Dick & Ayalew Birru, Yohannes, 2009. "Inflation Dynamics and Food Prices in an Agricultural Economy: The Case of Ethiopia," Working Papers in Economics 347, University of Gothenburg, Department of Economics.
    11. 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.
    12. 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.
    13. Baur, Dirk G. & Dimpfl, Thomas, 2018. "The asymmetric return-volatility relationship of commodity prices," Energy Economics, Elsevier, vol. 76(C), pages 378-387.
    14. 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).
    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. Boschi, Melisso & Pieroni, Luca, 2009. "Aluminium market and the macroeconomy," Journal of Policy Modeling, Elsevier, vol. 31(2), pages 189-207.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Vivian, Andrew & Wohar, Mark E., 2012. "Commodity volatility breaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 395-422.
    23. 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).
    24. 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.
    25. 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.

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    More about this item

    Keywords

    nonlinear models; rsistence; gestation lags; convenience yield; ecautionary demand;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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