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From Boom to Bust?: A Critical Look at US Shale Gas Projections

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  • Philipp M. Richter

Abstract

US shale gas production is generally expected to continue its fast rise. However, a cautious evaluation is needed. Shale gas resource estimates are potentially overoptimistic and it is uncertain to which extent they can be produced economically. Moreover, the adverse environmental effects of ever more wells to be drilled may lead to a fall in public acceptance and a strengthening of regulation. The objective of this paper is hence twofold: providing a critical look at current US shale gas projections, and investigating in a second step the implications of a less optimistic development by means of numerical simulation. In a world of declining US shale gas production after 2015, natural gas consumption outside the USA is reduced from its reference path by at least as much as US consumption. Trade flows are redirected, and the current US debate on LNG export capacity requirements becomes obsolete.

Suggested Citation

  • Philipp M. Richter, 2013. "From Boom to Bust?: A Critical Look at US Shale Gas Projections," Discussion Papers of DIW Berlin 1338, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1338
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Weijermars, Ruud, 2015. "Shale gas technology innovation rate impact on economic Base Case – Scenario model benchmarks," Applied Energy, Elsevier, vol. 139(C), pages 398-407.
    2. Egging, Ruud & Holz, Franziska, 2016. "Risks in global natural gas markets: Investment, hedging and trade," Energy Policy, Elsevier, vol. 94(C), pages 468-479.
    3. Egging, Ruud & Pichler, Alois & Kalvø, Øyvind Iversen & Walle–Hansen, Thomas Meyer, 2017. "Risk aversion in imperfect natural gas markets," European Journal of Operational Research, Elsevier, vol. 259(1), pages 367-383.
    4. Richter, Philipp M. & Holz, Franziska, 2015. "All quiet on the eastern front? Disruption scenarios of Russian natural gas supply to Europe," Energy Policy, Elsevier, vol. 80(C), pages 177-189.
    5. Huppmann, Daniel & Egging, Ruud, 2014. "Market power, fuel substitution and infrastructure – A large-scale equilibrium model of global energy markets," Energy, Elsevier, vol. 75(C), pages 483-500.
    6. Weijermars, Ruud, 2014. "US shale gas production outlook based on well roll-out rate scenarios," Applied Energy, Elsevier, vol. 124(C), pages 283-297.
    7. Ruud Egging & Franziska Holz, 2015. "Local Consequences of Global Uncertainty: Capacity Development and LNG Trade under Shale Gas and Demand Uncertainty and Disruption Risk," Discussion Papers of DIW Berlin 1498, DIW Berlin, German Institute for Economic Research.
    8. Langer, Lissy & Huppmann, Daniel & Holz, Franziska, 2016. "Lifting the US crude oil export ban: A numerical partial equilibrium analysis," Energy Policy, Elsevier, vol. 97(C), pages 258-266.
    9. Sheridan Few & Ajay Gambhir & Tamaryn Napp & Adam Hawkes & Stephane Mangeon & Dan Bernie & Jason Lowe, 2017. "The Impact of Shale Gas on the Cost and Feasibility of Meeting Climate Targets—A Global Energy System Model Analysis and an Exploration of Uncertainties," Energies, MDPI, Open Access Journal, vol. 10(2), pages 1-22, January.

    More about this item

    Keywords

    Natural Gas; Shale; USA; Scenarios; Equilibrium Modeling;

    JEL classification:

    • Q37 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Issues in International Trade
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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