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Supply Flexibility in the Shale Patch: Evidence from North Dakota

Author

Listed:
  • Hilde C. Bjørnland

    (BI Norwegian Business School and Norges Bank (Central Bank of Norway))

  • Frode Martin Nordvik

    (BI Norwegian Business School and Norges Bank (Central Bank of Norway))

  • Maximilian Rohrer

    (BI Norwegian Business School)

Abstract

We analyse if supply exibility in oil production depends on the extraction technology. In particular, we ask to what extent shale oil producers respond to price incentives by changing completion of new wells as well as oil production from completed wells. Using a novel well-level monthly production data set covering more than 15,000 crude oil wells in North Dakota, we find large differences in response between conventional and unconventional (shale) extraction technology: While shale oil wells respond significantly to spot future spreads by changing both well completion and crude oil production, conventional wells do not. Our results suggest that firms using shale oil technology are more exible in allocating output intertemporally. We interpret such output pattern of shale oil wells to be consistent with the Hotelling theory of optimal extraction.

Suggested Citation

  • Hilde C. Bjørnland & Frode Martin Nordvik & Maximilian Rohrer, 2017. "Supply Flexibility in the Shale Patch: Evidence from North Dakota," Working Paper 2017/9, Norges Bank.
  • Handle: RePEc:bno:worpap:2017_09
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    File URL: http://www.norges-bank.no/en/Published/Papers/Working-Papers/2017/92017/
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    References listed on IDEAS

    as
    1. Lutz Kilian, 2016. "The Impact of the Shale Oil Revolution on U.S. Oil and Gasoline Prices," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(2), pages 185-205.
    2. repec:ucp:jpolec:doi:10.1086/697203 is not listed on IDEAS
    3. Pesaran, M Hashem, 1990. "An Econometric Analysis of Exploration and Extraction of Oil in the U.K. Continental Shelf," Economic Journal, Royal Economic Society, vol. 100(401), pages 367-390, June.
    4. Soren T. Anderson & Ryan Kellogg & Stephen W. Salant, 2018. "Hotelling under Pressure," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 984-1026.
    5. James L. Smith, 2009. "World Oil: Market or Mayhem?," Journal of Economic Perspectives, American Economic Association, vol. 23(3), pages 145-164, Summer.
    6. Harold Hotelling, 1931. "The Economics of Exhaustible Resources," Journal of Political Economy, University of Chicago Press, vol. 39, pages 137-137.
    7. Ramcharran, Harri, 2002. "Oil production responses to price changes: an empirical application of the competitive model to OPEC and non-OPEC countries," Energy Economics, Elsevier, vol. 24(2), pages 97-106, March.
    8. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    9. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    10. Carol Dahl & Mine Yucel, 1991. "Testing Alternative Hypotheses of Oil Producer Behavior," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 117-138.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Lutz Kilian & Zhou Xiaoqing, 2019. "Oil Prices, Exchange Rates and Interest Rates," CESifo Working Paper Series 7484, CESifo Group Munich.
    2. Christiane Baumeister & James D. Hamilton, 2017. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," CESifo Working Paper Series 6835, CESifo Group Munich.
    3. Ferriani, Fabrizio & Natoli, Filippo & Veronese, Giovanni & Zeni, Federica, 2018. "Futures risk premia in the era of shale oil," MPRA Paper 89097, University Library of Munich, Germany.
    4. Ferriani, Fabrizio & Veronese, Giovanni, 2018. "U.S. shale producers: a case of dynamic risk management?," MPRA Paper 88279, University Library of Munich, Germany.
    5. Rick van der Ploeg & Armon Rezai, 2018. "Climate Policy and Stranded Carbon Assets: a Financial Perspective," OxCarre Working Papers 206, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    6. Fernández, Andrés & González, Andrés & Rodríguez, Diego, 2018. "Sharing a ride on the commodities roller coaster: Common factors in business cycles of emerging economies," Journal of International Economics, Elsevier, vol. 111(C), pages 99-121.
    7. repec:pal:buseco:v:53:y:2018:i:4:d:10.1057_s11369-018-0098-9 is not listed on IDEAS
    8. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Structural Interpretation of Vector Autoregressions with Incomplete Information: Revisiting the Role of Oil Supply and Demand Shocks: Comment," CEPR Discussion Papers 13068, C.E.P.R. Discussion Papers.
    9. Hilde C. Bjørnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Gambetti, Luca & Moretti, Laura, 2017. "News, Noise and Oil Price Swings," Research Technical Papers 12/RT/17, Central Bank of Ireland.
    11. Lutz Kilian & Xiaoqing Zhou, 2018. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks: Comment," CESifo Working Paper Series 7166, CESifo Group Munich.
    12. repec:aea:aecrev:v:109:y:2019:i:5:p:1873-1910 is not listed on IDEAS

    More about this item

    Keywords

    Oil extraction; crude oil prices; US oil shale boom; Hotelling theory;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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