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Innovation subsidies versus consumer subsidies: A real options analysis of solar energy

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  • Torani, Kiran
  • Rausser, Gordon
  • Zilberman, David

Abstract

Given the interest in the commercialization of affordable, clean energy technologies, we examine the prospects of solar photovoltaics (PV). We consider the question of how to transition to a meaningful percentage of solar energy in a sustainable manner and which policies are most effective in accelerating adoption. This paper develops a stochastic dynamic model of the adoption of solar PV in the residential and commercial sector under two sources of uncertainty – the price of electricity and cost of solar. The analytic results suggest that a high rate of innovation may delay adoption of a new technology if the consumer has rational price expectations. We simulate the model across alternative rates technological change, electricity prices, subsidies and carbon taxes. It is shown that there will be a displacement of incumbent technologies and a widespread shift towards solar PV in under 30 years – and that this can occur without consumer incentives and carbon pricing. We show that these policies have a modest impact in accelerating adoption, and that they may not be an effective part of climate policy. Instead, results demonstrate that further technological change is the crucial determinant and main driver of adoption. Further, results indicate that subsidies and taxes become increasingly ineffective with higher rates of technological change.

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  • Torani, Kiran & Rausser, Gordon & Zilberman, David, 2016. "Innovation subsidies versus consumer subsidies: A real options analysis of solar energy," Energy Policy, Elsevier, vol. 92(C), pages 255-269.
    • Handle: RePEc:eee:enepol:v:92:y:2016:i:c:p:255-269
    DOI: 10.1016/j.enpol.2015.07.010
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    1. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    2. Fleten, S.-E. & Maribu, K.M. & Wangensteen, I., 2007. "Optimal investment strategies in decentralized renewable power generation under uncertainty," Energy, Elsevier, vol. 32(5), pages 803-815.
    3. Pindyck, Robert S., 2000. "Irreversibilities and the timing of environmental policy," Resource and Energy Economics, Elsevier, vol. 22(3), pages 233-259, July.
    4. Derek M. Lemoine, 2010. "Valuing Plug-In Hybrid Electric Vehicles' Battery Capacity Using a Real Options Framework," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 113-144.
    5. Michael Greenstone & Elizabeth Kopits & Ann Wolverton, 2011. "Estimating the Social Cost of Carbon for Use in U.S. Federal Rulemakings: A Summary and Interpretation," NBER Working Papers 16913, National Bureau of Economic Research, Inc.
    6. Kenneth J. Arrow & Anthony C. Fisher, 1974. "Environmental Preservation, Uncertainty, and Irreversibility," Palgrave Macmillan Books, in: Chennat Gopalakrishnan (ed.), Classic Papers in Natural Resource Economics, chapter 4, pages 76-84, Palgrave Macmillan.
    7. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    8. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    9. Brennan, Michael J & Schwartz, Eduardo S, 1985. "Evaluating Natural Resource Investments," The Journal of Business, University of Chicago Press, vol. 58(2), pages 135-157, April.
    10. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    11. Schmit, T.M. & J., Luo & Conrad, J.M., 2011. "Estimating the influence of U.S. ethanol policy on plant investment decisions: A real options analysis with two stochastic variables," Energy Economics, Elsevier, vol. 33(6), pages 1194-1205.
    12. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    13. Jon M. Conrad, 1980. "Quasi-Option Value and the Expected Value of Information," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 94(4), pages 813-820.
    14. Janis M. Carey & David Zilberman, 2002. "A Model of Investment under Uncertainty: Modern Irrigation Technology and Emerging Markets in Water," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 171-183.
    15. 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.
    16. Chakravorty, Ujjayant & Roumasset, James & Tse, Kinping, 1997. "Endogenous Substitution among Energy Resources and Global Warming," Journal of Political Economy, University of Chicago Press, vol. 105(6), pages 1201-1234, December.
    17. McDonald, Robert L & Siegel, Daniel R, 1985. "Investment and the Valuation of Firms When There Is an Option to Shut Down," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(2), pages 331-349, June.
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