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Oil and price dynamics in international petroleum markets

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  • A. Lanza
  • M. Manera
  • M. Giovannini

Abstract

In this paper we investigate crude oil and products price dynamics. We present a comparison among ten prices series of crude oils and fourteen price series of petroleum products, considering four distinct market areas (Mediterranean, North Western Europe, Latin America and North America) over the period 1994-2002. We provide first a complete analysis of crude oil and product price dynamics using cointegration and error correction models. Subsequently we use the error correction specification to predict crude oil prices over the horizon January 2002-June 2002.The main findings of the paper can be summarized as follows - a) differences in quality are crucial to understand the behaviour of crudes; b) prices of crude oils whose physical characteristics are more similar to the marker show the following regularities - b1) they converge more rapidly to the long-run equilibrium; b2) there is an almost monotonic relation between Mean Absolute Percentage Error values and crude quality, measured by API° gravity and sulphur concentration; c) the price of the marker is the driving variable of the crude price also in the short-run, irrespective of the specific geographical area and the quality of the crude under analysis.

Suggested Citation

  • A. Lanza & M. Manera & M. Giovannini, 2003. "Oil and price dynamics in international petroleum markets," Working Paper CRENoS 200306, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    • Handle: RePEc:cns:cnscwp:200306
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    References listed on IDEAS

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    2. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    3. Asche, Frank & Gjolberg, Ole & Volker, Teresa, 2003. "Price relationships in the petroleum market: an analysis of crude oil and refined product prices," Energy Economics, Elsevier, vol. 25(3), pages 289-301, May.
    4. Gjolberg, Ole & Johnsen, Thore, 1999. "Risk management in the oil industry: can information on long-run equilibrium prices be utilized?," Energy Economics, Elsevier, vol. 21(6), pages 517-527, December.
    5. Adrangi, Bahram & Chatrath, Arjun & Raffiee, Kambiz & D. Ripple, Ronald, 2001. "Alaska North Slope crude oil price and the behavior of diesel prices in California," Energy Economics, Elsevier, vol. 23(1), pages 29-42, January.
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    Cited by:

    1. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
    2. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," Post-Print hal-01411687, HAL.
    3. Mario Denni & G. Frewer, 2006. "New evidence on the relationship beetween crude oil and petroleum product prices," Departmental Working Papers of Economics - University 'Roma Tre' 0061, Department of Economics - University Roma Tre.
    4. Zavaleta, Armando & Walls, W.D. & Rusco, Frank W., 2015. "Refining for export and the convergence of petroleum product prices," Energy Economics, Elsevier, vol. 47(C), pages 206-214.

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    More about this item

    Keywords

    oil prices; product prices; error correction models;
    All these keywords.

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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