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A staggered pricing approach to modeling speculative storage: implications for commodity price dynamics

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Abstract

This paper embeds a staggered price feature into the standard speculative storage model of Deaton and Laroque (1996). Intermediate goods inventory speculators are added as an additional source of intertemporal linkage, which helps us to replicate the stylized facts of the observed commodity price dynamics. Incorporating this type of friction into the model is motivated by its ability to increase price stickiness which, gives rise to a higher degree of persistence in the first two conditional moments of commodity prices. The structural parameters of our model are estimated by the simulated method of moments using actual prices for four agricultural commodities. Simulated data are then employed to assess the effects of our staggered price approach on the time series properties of commodity prices. Our results lend empirical support to the possibility of staggered prices.

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  • 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.
    • Handle: RePEc:fip:fedawp:2013-08
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    1. Michaelides, Alexander & Ng, Serena, 2000. "Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators," Journal of Econometrics, Elsevier, vol. 96(2), pages 231-266, June.
    2. Newbery, David M, 1984. "Commodity Price Stabilization in Imperfect or Cartelized Markets," Econometrica, Econometric Society, vol. 52(3), pages 563-578, May.
    3. Lee, Bong-Soo & Ingram, Beth Fisher, 1991. "Simulation estimation of time-series models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 197-205, February.
    4. 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.
    5. Taylor, John B, 1980. "Aggregate Dynamics and Staggered Contracts," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 1-23, February.
    6. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    7. repec:vuw:vuwscr:19065 is not listed on IDEAS
    8. Williams,Jeffrey C. & Wright,Brian D., 2005. "Storage and Commodity Markets," Cambridge Books, Cambridge University Press, number 9780521023399, January.
    9. Mr. Norbert Funke & Weifeng Wu & Yanliang Miao, 2011. "Reviving the Competitive Storage Model: A Holistic Approach to Food Commodity Prices," IMF Working Papers 2011/064, International Monetary Fund.
    10. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    11. Mitraille, Sébastien & Thille, Henry, 2009. "Monopoly behaviour with speculative storage," Journal of Economic Dynamics and Control, Elsevier, vol. 33(7), pages 1451-1468, July.
    12. 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.
    13. Evans, Lewis & Guthrie, Graeme, 2007. "Commodity Price Behavior With Storage Frictions," Working Paper Series 3966, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    14. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    15. Cafiero, Carlo & Bobenrieth H., Eugenio S.A. & Bobenrieth H., Juan R.A. & Wright, Brian D., 2011. "The empirical relevance of the competitive storage model," Journal of Econometrics, Elsevier, vol. 162(1), pages 44-54, May.
    16. Gilbert, Christopher L., 1987. "International commodity agreements: Design and performance," World Development, Elsevier, vol. 15(5), pages 591-616, May.
    17. Brenner, Robin J. & Harjes, Richard H. & Kroner, Kenneth F., 1996. "Another Look at Models of the Short-Term Interest Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(1), pages 85-107, March.
    18. Beck, Stacie E, 1993. "A Rational Expectations Model of Time Varying Risk Premia in Commodities Futures Markets: Theory and Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(1), pages 149-168, February.
    19. Evans, Lewis & Guthrie, Graeme, 2007. "Commodity Price Behavior With Storage Frictions," Working Paper Series 19065, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    20. Rotemberg, Julio J., 1996. "Prices, output, and hours: An empirical analysis based on a sticky price model," Journal of Monetary Economics, Elsevier, vol. 37(3), pages 505-533, June.
    21. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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    More about this item

    Keywords

    commodity price determination; staggered pricing; high persistence; conditional heteroskedasticity; simulated method of moments;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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