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Dynamics of Switching from Polluting Resources to Green Technologies

Author

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  • Supratim Das Gupta

    (University of South Carolina, Columbia, SC, USA and University of Guanajuato, Guanajuato, Mexico.)

Abstract

We have total energy produced by a firm using a non-renewable resource and a perfect substitute backstop. The average cost of the backstop is significantly higher relative to the non-renewable resource initially; average backstop costs are modeled to fall with investments in knowledge. Investments in knowledge are thought to bring about more efficient techniques to use alternative energies (better technical know-how for wind, solar) reducing their average costs. The knowledge stock is modeled as an impure public good such that an individual firm only partially benefits from its own knowledge accumulation. We find a firm in equilibrium invests less in the backstop relative to the social planner and that the planner solution also leads to faster exhaustion of the depletable resource. Introducing flow pollution, we find the time of switch to the backstop in the planner solution depends on the relative magnitudes of the average pollution cost and the average cost of the backstop. An increase in the pollution cost implies slower extraction of the exhaustible resource and a later switch (compared to the case without pollution); however for a very high pollution cost, the extraction rate rises and switch to the backstop is made sooner leaving some of the exhaustible resource in the ground. We solve both the models explicitly and use sophisticated numerical techniques in Mathematica.

Suggested Citation

  • Supratim Das Gupta, 2015. "Dynamics of Switching from Polluting Resources to Green Technologies," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 1109-1124.
  • Handle: RePEc:eco:journ2:2015-04-24
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    References listed on IDEAS

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    More about this item

    Keywords

    Exhaustible Resources; Backstop; Knowledge Stock; Investment; Pollution; Numerical Methods;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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