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Optimal Clean Energy R&D Investments Under Uncertainty

Author

Listed:
  • Giacomo Marangoni

    (FEEM, CMCC and Politecnico di Milano)

  • Gauthier De Maere

    (FEEM)

  • Valentina Bosetti

    (FEEM, CMCC and Bocconi University)

Abstract

The availability of technology plays a major role in the feasibility and costs of climate policy. Nonetheless, technological change is highly uncertain and capital intensive, requiring risky efforts in research and development of clean energy technologies. In this paper, we introduce a two-track method that makes it possible to maintain the rich set of information produced by climate-economy models while introducing the dimension of uncertainty in innovation ef- forts, without succumbing to computation complexity. In particular, we solve the problem of an optimal R&D portfolio by employing Approximate Dynamic Programming, through multiple runs of an integrated assessment model (IAM) for the purpose of computing the value function, and expert elicitation data to quantify the relevant uncertainties. We exemplify the methodology with the problem of evaluating optimal near-term innovation investment portfolios in four key clean energy technologies (solar, biofuels, bioelectricity and personal electric vehicle batteries), taking into account the uncertainty surrounding the effectiveness of innovation to improve the performance of these technologies. We employ an IAM (WITCH) which has a fairly rich description of the energy technologies and experts’ beliefs on future costs for the above-mentioned technologies. Focusing on Europe and its short-term climate policy commitments, we find that batteries in personal transportation dominate the optimal public R&D portfolio. The resulting ranking across technologies is robust to changes in risk-aversion, R&D budget limitation and assump- tions on crowding out of other investments. These results suggest an important upscaling of R&D efforts compared to the recent past.

Suggested Citation

  • Giacomo Marangoni & Gauthier De Maere & Valentina Bosetti, 2017. "Optimal Clean Energy R&D Investments Under Uncertainty," Working Papers 2017.16, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2017.16
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    References listed on IDEAS

    as
    1. Derek Lemoine & Christian Traeger, 2014. "Watch Your Step: Optimal Policy in a Tipping Climate," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 137-166, February.
    2. Yongyang Cai & Kenneth L. Judd & Thomas S. Lontzek, 2013. "The Social Cost of Stochastic and Irreversible Climate Change," NBER Working Papers 18704, National Bureau of Economic Research, Inc.
    3. Elmar Kriegler & John Weyant & Geoffrey Blanford & Volker Krey & Leon Clarke & Jae Edmonds & Allen Fawcett & Gunnar Luderer & Keywan Riahi & Richard Richels & Steven Rose & Massimo Tavoni & Detlef Vuu, 2014. "The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies," Climatic Change, Springer, vol. 123(3), pages 353-367, April.
    4. Giacomo Marangoni & Massimo Tavoni, 2014. "The Clean Energy R&D Strategy For 2°C," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-23.
    5. Bosetti, Valentina & Marangoni, Giacomo & Borgonovo, Emanuele & Diaz Anadon, Laura & Barron, Robert & McJeon, Haewon C. & Politis, Savvas & Friley, Paul, 2015. "Sensitivity to energy technology costs: A multi-model comparison analysis," Energy Policy, Elsevier, vol. 80(C), pages 244-263.
    6. Nemet, Gregory F. & Anadon, Laura Diaz & Verdolini, Elena, 2016. "Quantifying the Effects of Expert Selection and Elicitation Design on Experts’ Confidence in their Judgments about Future Energy Technologies," MITP: Mitigation, Innovation and Transformation Pathways 249349, Fondazione Eni Enrico Mattei (FEEM).
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    Cited by:

    1. Elena Verdolini & Laura Díaz Anadón & Erin Baker & Valentina Bosetti & Lara Aleluia Reis, 2018. "Future Prospects for Energy Technologies: Insights from Expert Elicitations," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 133-153.
    2. Gu, Gaoxiang & Wang, Zheng, 2018. "Research on global carbon abatement driven by R&D investment in the context of INDCs," Energy, Elsevier, vol. 148(C), pages 662-675.

    More about this item

    Keywords

    Energy; Innovation; Technological Change; Uncertainty; Climate Policy;

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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