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Modelling and forecasting rig rates on the Norwegian Continental Shelf

Author

Listed:
  • Terje Skjerpen

  • Halvor Briseid Storrøsten

    (Statistics Norway)

  • Knut Einar Rosendahl

  • Petter Osmundsen

Abstract

Knowledge about rig markets is crucial for understanding the global oil market. In this paper we first develop a simple bargaining model for rig markets. Then we examine empirically the most important drivers for rig rate formation of floaters operating at the Norwegian Continental Shelf in the period 1991q4 to 2013q4. We use reduced form time series models with two equations and report conditional point and bootstrapped interval forecasts for rig rates and capacity utilization. We then consider two alternative simulations to examine how the oil price and remaining petroleum reserves influence rig rate formation of floaters. In the first alternative simulation we assume a relatively high crude oil price equal to 100 USD (2010) per barrel for the entire forecast period, whereas the reference case features the actual oil price with extrapolated values for the last quarters in the forecast period. According to our results, the rig rates will be about 34 percent higher in 2016q4 with the higher oil price. In the second alternative simulation we explore the effects of opening the Barents Sea and areas around Jan Mayen for petroleum activity. This contributes to dampening the fall in the rig rates and capacity utilization over the last part of the forecast period.

Suggested Citation

  • Terje Skjerpen & Halvor Briseid Storrøsten & Knut Einar Rosendahl & Petter Osmundsen, 2015. "Modelling and forecasting rig rates on the Norwegian Continental Shelf," Discussion Papers 832, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:832
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    References listed on IDEAS

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    Cited by:

    1. Storrøsten, Halvor Briseid, 2024. "U.S. light tight oil supply flexibility - A multivariate dynamic model for production and rig activity," Energy Economics, Elsevier, vol. 131(C).
    2. Halvor B. Storrøsten, 2020. "Emission Regulation of Markets with Sluggish Supply Structures," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(1), pages 1-33, September.
    3. Hiorth, Aksel & Osmundsen, Petter, 2020. "Petroleum taxation. The effect on recovery rates," Energy Economics, Elsevier, vol. 87(C).
    4. 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.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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