IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v49y2015icp430-439.html
   My bibliography  Save this article

Understanding rig rate formation in the Gulf of Mexico

Author

Listed:
  • Osmundsen, Petter
  • Rosendahl, Knut Einar
  • Skjerpen, Terje

Abstract

We examine the largest cost component in offshore development projects, rig rates. High rig rates in recent years have restricted development of new oil and gas fields, as well as IOR projects and thus increased the cost for importing countries. Thus, it is important to understand developments in rig rates. Using econometric analysis, we examine the effects on jackup rig rates from gas and oil prices, rig capacity utilisation, contract length and lead time, and rig-specific characteristics like drilling depth capacities and rig classification. Having access to a unique data set from the Gulf of Mexico (GoM), containing contract information, we are able to estimate how contract parameters crucial to the relative bargaining power between rig owners and oil and gas companies affect rig rates. We find that increasing lead times and contract lengths enhance the bargaining power of the rig companies and are likely to be associated with higher rates for new contracts. Further, we find that gas prices are more important for jackup rig rates in the GoM area than oil prices — ten percent increase in gas prices leads to nine percent increase in rig rates in the long run, according to our results.

Suggested Citation

  • Osmundsen, Petter & Rosendahl, Knut Einar & Skjerpen, Terje, 2015. "Understanding rig rate formation in the Gulf of Mexico," Energy Economics, Elsevier, vol. 49(C), pages 430-439.
  • Handle: RePEc:eee:eneeco:v:49:y:2015:i:c:p:430-439
    DOI: 10.1016/j.eneco.2015.03.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988315000900
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohn, Klaus & Osmundsen, Petter, 2008. "Exploration economics in a regulated petroleum province: The case of the Norwegian Continental Shelf," Energy Economics, Elsevier, vol. 30(2), pages 303-320, March.
    2. Alexander Kemp & Sola Kasim, 2003. "An Econometric Model of Oil and Gas Exploration Development and Production in the UK Continental Shelf: A Systems Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 113-141.
    3. Ringlund, Guro Bornes & Rosendahl, Knut Einar & Skjerpen, Terje, 2008. "Does oilrig activity react to oil price changes An empirical investigation," Energy Economics, Elsevier, vol. 30(2), pages 371-396, March.
    4. Lin, C.-Y. Cynthia, 2009. "Estimating strategic interactions in petroleum exploration," Energy Economics, Elsevier, vol. 31(4), pages 586-594, July.
    5. Dixit, Avinash K & Stiglitz, Joseph E, 1977. "Monopolistic Competition and Optimum Product Diversity," American Economic Review, American Economic Association, vol. 67(3), pages 297-308, June.
    6. Farzin, Y. H., 2001. "The impact of oil price on additions to US proven reserves," Resource and Energy Economics, Elsevier, vol. 23(3), pages 271-292, July.
    7. Iledare, Omowumi O., 1995. "Simulating the effect of economic and policy incentives on natural gas drilling and gross reserve additions," Resource and Energy Economics, Elsevier, vol. 17(3), pages 261-279, November.
    8. Boyce, John R. & Nøstbakken, Linda, 2011. "Exploration and development of U.S. oil and gas fields, 1955-2002," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 891-908, June.
    9. Aune, Finn Roar & Mohn, Klaus & Osmundsen, Petter & Rosendahl, Knut Einar, 2010. "Financial market pressure, tacit collusion and oil price formation," Energy Economics, Elsevier, vol. 32(2), pages 389-398, March.
    10. Ryan Kellogg, 2011. "Learning by Drilling: Interfirm Learning and Relationship Persistence in the Texas Oilpatch," The Quarterly Journal of Economics, Oxford University Press, vol. 126(4), pages 1961-2004.
    11. Klaus Mohn, 2008. "Efforts and Efficiency in Oil Exploration: A Vector Error-Correction Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 53-78.
    12. Emile J. Brinkmann & Ramon Rabinovitch, 1995. "Regional Limitations on the Hedging Effectiveness of Natural Gas Futures," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 113-124.
    13. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
    14. Modjtahedi, Bagher & Movassagh, Nahid, 2005. "Natural-gas futures: Bias, predictive performance, and the theory of storage," Energy Economics, Elsevier, vol. 27(4), pages 617-637, July.
    15. Osmundsen, Petter & Roll, Kristin Helen & Tveteras, Ragnar, 2012. "Drilling speed—the relevance of experience," Energy Economics, Elsevier, vol. 34(3), pages 786-794.
    16. Kenneth S. Corts, 2008. "Stacking the Deck: Idling and Reactivation of Capacity in Offshore Drilling," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 17(2), pages 271-294, June.
    17. Osmundsen, Petter & Roll, Kristin Helen & Tveterås , Ragnar, 2009. "Exploration drilling productivity at the Norwegian Shelf," UiS Working Papers in Economics and Finance 2009/34, University of Stavanger.
    18. Kenneth S. Corts, 2004. "The Effect of Repeated Interaction on Contract Choice: Evidence from Offshore Drilling," Journal of Law, Economics, and Organization, Oxford University Press, vol. 20(1), pages 230-260, April.
    19. Osmundsen, Petter, 1999. "Risk sharing and incentives in norwegian petroleum extraction," Energy Policy, Elsevier, vol. 27(9), pages 549-555, September.
    20. Robert S. Pindyck, 2001. "The Dynamics of Commodity Spot and Futures Markets: A Primer," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-30.
    21. Serroyen, Jan & Molenberghs, Geert & Verbeke, Geert & Davidian, Marie, 2009. "Nonlinear Models for Longitudinal Data," The American Statistician, American Statistical Association, vol. 63(4), pages 378-388.
    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. Dahl, Roy Endre & Lorentzen, Sindre & Oglend, Atle & Osmundsen, Petter, 2016. "Pro-Cyclical Petroleum Investments and Cost Overruns in Norway by Roy Endré Dahl, Sindre Lorentzen, Atle Oglend, and Petter Osmundsen," UiS Working Papers in Economics and Finance 2016/7, University of Stavanger.
    2. Smith, James L. & Lee, Thomas K., 2017. "The price elasticity of U.S. shale oil reserves," Energy Economics, Elsevier, vol. 67(C), pages 121-135.
    3. Osmundsen, Petter & Roll, Kristin Helen, 2016. "Rig rates and drilling speed: reinforcing effects," UiS Working Papers in Economics and Finance 2016/4, University of Stavanger.
    4. Skjerpen, Terje & Storrøsten, Halvor Briseid & Rosendahl, Knut Einar & Osmundsen, Petter, 2018. "Modelling and forecasting rig rates on the Norwegian Continental Shelf," Resource and Energy Economics, Elsevier, vol. 53(C), pages 220-239.
    5. Dahl, Roy Endré & Lorentzen, Sindre & Oglend, Atle & Osmundsen, Petter, 2017. "Pro-cyclical petroleum investments and cost overruns in Norway," Energy Policy, Elsevier, vol. 100(C), pages 68-78.
    6. Dahl, Roy Endré & Lorentzen, Sindre & Oglend, Atle & Osmundsen, Petter, 2017. "Pro-cyclical petroleum investments and cost overruns in Norway," Energy Policy, Elsevier, vol. 100(C), pages 68-78.

    More about this item

    Keywords

    Rig rates; Oil and gas drilling; Oil and gas prices; Contract length;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:eee:eneeco:v:49:y:2015:i:c:p:430-439. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.