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Climate change and optimal energy technology R&D policy

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  • Baker, Erin
  • Solak, Senay

Abstract

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.

Suggested Citation

  • Baker, Erin & Solak, Senay, 2011. "Climate change and optimal energy technology R&D policy," European Journal of Operational Research, Elsevier, vol. 213(2), pages 442-454, September.
  • Handle: RePEc:eee:ejores:v:213:y:2011:i:2:p:442-454
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    References listed on IDEAS

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    9. Valentina Bosetti & Laurent Drouet, 2005. "Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model," Working Papers 2005.147, Fondazione Eni Enrico Mattei.
    10. Baker, Erin & Shittu, Ekundayo, 2006. "Profit-maximizing R&D in response to a random carbon tax," Resource and Energy Economics, Elsevier, vol. 28(2), pages 160-180, May.
    11. Baker, Erin & Adu-Bonnah, Kwame, 2008. "Investment in risky R&D programs in the face of climate uncertainty," Energy Economics, Elsevier, vol. 30(2), pages 465-486, March.
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    Citations

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    Cited by:

    1. Popp, David & Santen, Nidhi & Fisher-Vanden, Karen & Webster, Mort, 2013. "Technology variation vs. R&D uncertainty: What matters most for energy patent success?," Resource and Energy Economics, Elsevier, vol. 35(4), pages 505-533.
    2. Guo, Jian-Xin & Zhu, Lei & Fan, Ying, 2016. "Emission path planning based on dynamic abatement cost curve," European Journal of Operational Research, Elsevier, vol. 255(3), pages 996-1013.
    3. Laura Diaz Anadon & Valentina Bosetti & Gabe Chan & Gregory Nemet & Elena Verdolini, 2014. "Energy Technology Expert Elicitations for Policy: Workshops, Modeling, and Meta-analysis," Working Papers 2014.91, Fondazione Eni Enrico Mattei.
    4. Pillai, Unni & McLaughlin, Jamison, 2013. "A model of competition in the solar panel industry," Energy Economics, Elsevier, vol. 40(C), pages 32-39.
    5. Wang, Yong & Li, Lin, 2016. "Critical peak electricity pricing for sustainable manufacturing: Modeling and case studies," Applied Energy, Elsevier, vol. 175(C), pages 40-53.
    6. Bistline, John E., 2016. "Energy technology R&D portfolio management: Modeling uncertain returns and market diffusion," Applied Energy, Elsevier, vol. 183(C), pages 1181-1196.
    7. Heutel, Garth & Moreno-Cruz, Juan & Shayegh, Soheil, 2018. "Solar geoengineering, uncertainty, and the price of carbon," Journal of Environmental Economics and Management, Elsevier, vol. 87(C), pages 24-41.
    8. Chen, Liang & Kettunen, Janne, 2017. "Is certainty in carbon policy better than uncertainty?," European Journal of Operational Research, Elsevier, vol. 258(1), pages 230-243.
    9. Olaleye, Olaitan & Baker, Erin, 2015. "Large scale scenario analysis of future low carbon energy options," Energy Economics, Elsevier, vol. 49(C), pages 203-216.
    10. repec:eee:ejores:v:269:y:2018:i:1:p:132-145 is not listed on IDEAS
    11. Heutel, Garth & Moreno-Cruz, Juan & Shayegh, Soheil, 2016. "Climate tipping points and solar geoengineering," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 19-45.
    12. Mort Webster & Karen Fisher-Vanden & David Popp & Nidhi Santen, 2015. "Should We Give Up After Solyndra? Optimal Technology R&D Portfolios under Uncertainty," NBER Working Papers 21396, National Bureau of Economic Research, Inc.
    13. Mort D. Webster & Karen Fisher-Vanden & David Popp & Nidhi R. Santen, 2015. "Should We Give Up After Solyndra? Optimal Technology R&D Portfolios under Uncertainty," CESifo Working Paper Series 5448, CESifo Group Munich.
    14. Santen, Nidhi R. & Anadon, Laura Diaz, 2016. "Balancing solar PV deployment and RD&D: A comprehensive framework for managing innovation uncertainty in electricity technology investment planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 560-569.
    15. Baker, Erin & Olaleye, Olaitan & Aleluia Reis, Lara, 2015. "Decision frameworks and the investment in R&D," Energy Policy, Elsevier, vol. 80(C), pages 275-285.
    16. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    17. Massol, Olivier & Tchung-Ming, Stéphane & Banal-Estañol, Albert, 2015. "Joining the CCS club! The economics of CO2 pipeline projects," European Journal of Operational Research, Elsevier, vol. 247(1), pages 259-275.
    18. repec:aen:journl:ej38-6-santen is not listed on IDEAS
    19. Kurth, Margaret & Keisler, Jeffrey M. & Bates, Matthew E. & Bridges, Todd S. & Summers, Jeffrey & Linkov, Igor, 2017. "A portfolio decision analysis approach to support energy research and development resource allocation," Energy Policy, Elsevier, vol. 105(C), pages 128-135.
    20. repec:eee:ejores:v:267:y:2018:i:1:p:304-314 is not listed on IDEAS
    21. Barry ANDERSON & Emanuele BORGONOVO & Marzio GALEOTTI & Roberto ROSON, 2012. "Uncertainty in climate change modelling: can global sensitivity analysis be of help?," Departmental Working Papers 2012-18, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

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