IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/7579.html
   My bibliography  Save this paper

The Relationship between Crude and Refined Product Market: The Case of Singapore Gasoline Market using MOPS Data

Author

Listed:
  • Rao, Gyaneshwar

Abstract

Economic theory suggests that refined and crude oil prices should be interrelated as the refined products are a derivative of the crude product and hence the prices of the two categories must have a long run relationship. However any short term feedbacks between the two markets are also of interest. Any feedbacks which are significant between the markets will greatly improve our understanding of how the complex oil markets work and that the workings of both the markets are not as independent as some would want to believe. The Johansen and Julius VCEM technique and Granger causality tests using co-integrating methodology show there is a basis to conclude that there is a uni-directional causality running from crude market to the refined product market, confirming a long run relationship between the markets.

Suggested Citation

  • Rao, Gyaneshwar, 2008. "The Relationship between Crude and Refined Product Market: The Case of Singapore Gasoline Market using MOPS Data," MPRA Paper 7579, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:7579
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/7579/1/MPRA_paper_7579.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. B Bhaskara Rao & Gyaneshwar Rao, 2006. "The Rockets And Feathers Hypothesis: An Application To Gasoline Prices In Fiji," The IUP Journal of Applied Economics, IUP Publications, vol. 0(5), pages 67-71, September.
    2. Bacon, Robert W., 1991. "Rockets and feathers: the asymmetric speed of adjustment of UK retail gasoline prices to cost changes," Energy Economics, Elsevier, vol. 13(3), pages 211-218, July.
    3. Lance J. Bachmeier & James M. Griffin, 2003. "New Evidence on Asymmetric Gasoline Price Responses," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 772-776, August.
    4. Severin Borenstein & A. Colin Cameron & Richard Gilbert, 1997. "Do Gasoline Prices Respond Asymmetrically to Crude Oil Price Changes?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 305-339.
    5. B Bhaskara Rao & Gyaneshwar Rao, 2005. "Crude Oil and Gasoline Prices in Fiji: Is the Relationship Asymmetric?," Microeconomics 0510004, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jordi Perdiguero-García, 2010. "“Symmetric or asymmetric gasoline prices? A metaanalysis approach”," IREA Working Papers 201013, University of Barcelona, Research Institute of Applied Economics, revised Nov 2010.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jordi Perdiguero-García, 2010. "“Symmetric or asymmetric gasoline prices? A metaanalysis approach”," IREA Working Papers 201013, University of Barcelona, Research Institute of Applied Economics, revised Nov 2010.
    2. Perdiguero-García, Jordi, 2013. "Symmetric or asymmetric oil prices? A meta-analysis approach," Energy Policy, Elsevier, vol. 57(C), pages 389-397.
    3. Phaisan Pattanakooha & Pongsa Pornchaiwisetgul, 2015. "The Effect of Stock, Government Policy, and Monopoly on Asymmetric Price Transmission in Thailand," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 926-933.
    4. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the oil–gasoline price relationship: Do asymmetries help?," Energy Economics, Elsevier, vol. 46(S1), pages 44-56.
    5. Escribano, Álvaro & Wang, Dandan, 2021. "Mixed random forest, cointegration, and forecasting gasoline prices," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1442-1462.
    6. Noel, Michael D. & Qiang, Hongjie, 2019. "The role of information in retail gasoline price dispersion," Energy Economics, Elsevier, vol. 80(C), pages 173-187.
    7. Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.
    8. repec:ipg:wpaper:2014-569 is not listed on IDEAS
    9. Erich Muehlegger & Richard L. Sweeney, 2017. "Pass-Through of Own and Rival Cost Shocks: Evidence from the U.S. Fracking Boom," NBER Working Papers 24025, National Bureau of Economic Research, Inc.
    10. Kaufmann, Robert K. & Dees, Stephane & Mann, Micheal, 2009. "Horizontal and vertical transmissions in the US oil supply chain," Energy Policy, Elsevier, vol. 37(2), pages 644-650, February.
    11. Palazzi, Rafael Baptista & Meira, Erick & Klotzle, Marcelo Cabus, 2022. "The sugar-ethanol-oil nexus in Brazil: Exploring the pass-through of international commodity prices to national fuel prices," Journal of Commodity Markets, Elsevier, vol. 28(C).
    12. L. Bettendorf & S. A. van der Geest & G. H. Kuper, 2009. "Do daily retail gasoline prices adjust asymmetrically?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(4), pages 385-397.
    13. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    14. Cook, Steven & Fosten, Jack, 2019. "Replicating rockets and feathers," Energy Economics, Elsevier, vol. 82(C), pages 139-151.
    15. Szymon Wlazlowski & Monica Giulietti & Jane Binner & Costas Milas, 2008. "Smooth Transition Models in Price Transmission," Working Paper series 04_08, Rimini Centre for Economic Analysis.
    16. Jonathan E. Ogbuabor & Anthony Orji & Gladys C. Aneke & Manasseh O. Charles, 2019. "Did the global financial crisis alter the oil–gasoline price relationship?," Empirical Economics, Springer, vol. 57(4), pages 1171-1200, October.
    17. Chen, Hao & Sun, Zesheng, 2021. "International crude oil price, regulation and asymmetric response of China's gasoline price," Energy Economics, Elsevier, vol. 94(C).
    18. repec:dgr:rugsom:14027-eef is not listed on IDEAS
    19. Ederington, Louis H. & Fernando, Chitru S. & Hoelscher, Seth A. & Lee, Thomas K. & Linn, Scott C., 2019. "A review of the evidence on the relation between crude oil prices and petroleum product prices," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 1-15.
    20. Remer, Marc, 2015. "An empirical investigation of the determinants of asymmetric pricing," International Journal of Industrial Organization, Elsevier, vol. 42(C), pages 46-56.
    21. Blair, Benjamin F. & Rezek, Jon P., 2008. "The effects of Hurricane Katrina on price pass-through for Gulf Coast gasoline," Economics Letters, Elsevier, vol. 98(3), pages 229-234, March.
    22. Zhang, Tao & Ma, Guofeng & Liu, Guangsheng, 2015. "Nonlinear joint dynamics between prices of crude oil and refined products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 444-456.

    More about this item

    Keywords

    Crude Prices; Refined Prices; Long Run Relationship; Granger causality; Mean of Platts (MOPS);
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:7579. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.