Climatic Change

, Volume 136, Issue 3–4, pp 677–691 | Cite as

Expert views - and disagreements - about the potential of energy technology R&D

  • Laura Diaz Anadon
  • Erin BakerEmail author
  • Valentina Bosetti
  • Lara Aleluia Reis


Mitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations.


Mitigate Climate Change Test Question Funding Decision Funding Level Improvement Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank Max Henrion for his help creating the aggregate distributions for each study and the combined distributions across studies using Analytica and Gabriel Chan (CCS) and Stephen Elliott (solar) for contributions in data processing at Harvard. The authors are also grateful to four anonymous referees for their constructive input. Anadon acknowledges funding from the Science, Technology, and Public Policy program at the Harvard Kennedy School and grants from the Doris Duke Charitable Foundation and BP to the Energy Technology Innovation Policy research group. Baker’s research was partially supported by NSF under award number SES-0745161. Bosetti acknowledges funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement n 240895 - project ICARUS “Innovation for Climate Change Mitigation: a Study of energy R&D, its Uncertain Effectiveness and Spillovers”; and under the European Community’s Programme “Ideas” - Call identifier: ERC-2013-StG / ERC grant agreement n 336703–project RISICO “RISk and uncertainty in developing and Implementing Climate change pOlicies.”

Supplementary material

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  1. Abdulla A, Azevedo I, Morgan MG (2013) Expert assessments of the cost of light water small modular reactor. PNAS 110(39):686–9691Google Scholar
  2. Anadon LD, Bosetti V, Bunn M, Catenacci M, Lee A (2012) Expert judgments about rd&d and the future of nuclear energy. Environ Sci Technol 46(11):497–504Google Scholar
  3. Anadon LD, Nemet G, Verdolini E (2013) The future costs of nuclear power using multiple expert elicitations: effects of rd&d and elicitation design. Environ Res Lett 8:034.020CrossRefGoogle Scholar
  4. Anadon LD, Chan G, Lee A (2014) Transforming U.S. energy innovation, chap. Expanding and better targeting U.S. Investment in energy innovation: an analytical approach. Cambridge University Press, CambridgeGoogle Scholar
  5. Baker E, Keisler J (2011) Cellulosic biofuels expert views on prospects for advancement. Energy 36:595–605CrossRefGoogle Scholar
  6. Baker E, Solak S (2014) Management of energy technology for sustainability: how to fund energy technology research and development. Prod Oper Manag 23:348–365CrossRefGoogle Scholar
  7. Baker E, Chon H, Keisler JM (2008) Advanced nuclear power: combining economic analysis with expert elicitations to inform climate policyGoogle Scholar
  8. Baker E, Chon H, Keisler J (2009) Advanced solar r&d: combining economic analysis with expert elicitations to inform climate policy. Energy Econ 31:S37–S49CrossRefGoogle Scholar
  9. Baker E, Chon H, Keisler J (2009) Carbon capture and storage: combining economic analysis with expert elicitations to inform climate policy. Clim Chang 96:379–408CrossRefGoogle Scholar
  10. Baker E, Bosetti V, Anadon LD, Henrion M, Reis LA (2015) Future costs of key low-carbon energy technologies: harmonization and aggregation of energy technology expert elicitation data. Energy Policy 80:219–232Google Scholar
  11. Bolger F, Rowe G (2014) The aggregation of expert judgment: do good things come to those who weight? Risk AnalGoogle Scholar
  12. Bosetti V, Catenacci M, Fiorese G, Verdolini E (2012) The future prospect of pv and csp solar technologies: an expert elicitation survey. Energy Policy 49:308–317CrossRefGoogle Scholar
  13. Chan G, Anadon LD, Chan M, Lee A (2011) Expert elicitation of cost, performance, and rd&d budgets for coal power with ccs. Energy Procedia:2685–2692Google Scholar
  14. Chung T, Patio-Echeverri D, Johnson TL (2011) Expert assessments of retrofitting coal-fired power plants with carbon dioxide capture technologies. Energy Policy 39:5609–5620CrossRefGoogle Scholar
  15. Clarke L, Baker E (2011) Workshop report: Rd&d portfolio analysis tools and methodologies. Tech. rep.
  16. Cooke RM (2015) Messaging climate change uncertainty. Nat Clim Chang 5(8–10)Google Scholar
  17. Cooke RM, Goossens LHJ (2008) Tu delft expert judgment data base. special issue on expert judgment. Reliab Eng Syst Safe 93:657–674CrossRefGoogle Scholar
  18. Curtright A, Morgan M, Keith D (2008) Expert assessment of future photovoltaic technology. Environ Sci Technol 42:9031–9038CrossRefGoogle Scholar
  19. Fiorese G, Catenacci M, Verdolini E, Bosetti V (2013) Advanced biofuels: future perspectives from an expert elicitation survey. Energy Policy 56:293–311CrossRefGoogle Scholar
  20. Fiorese G, Catenacci M, Bosetti V, Verdolini E (2014) The power of biomass: experts disclose the potential for success of bioenergy technologies. Energy Policy 65:94–114CrossRefGoogle Scholar
  21. Gallagher KS, Anadon LD (2014) DOE budget authority for energy research, development, & demonstration database. Tech. rep., Energy Technology Innovation Policy research group, Belfer Center for Science and International Affairs, Harvard Kennedy School.
  22. Goulder LH, Schneider Stephen H (1999) Induced technological change and the attractiveness of co2 emissions abatement. Resour Energy Econ 21:211–253CrossRefGoogle Scholar
  23. Hall BH (2007) Measuring the returns to r&d: the depreciation problem nber working paper no. w13473. Tech. rep. National Bureau of Economic Research, CambridgeGoogle Scholar
  24. Henrion M, Granger Morgan M (1990) Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge University Press, New YorkGoogle Scholar
  25. Hoffert MI, Caldeira K, Benford G, Criswell DR, Green C, Herzog H, Jain AK, Kheshgi HS, Lackner KS, Lewis JS, Lightfoot HD, Manheimer W, Mankins JC, Mauel ME, Perkins LJ, Schlesinger ME, Volk T, Wigley TML (2002) Advanced technology paths to global climate stability: energy for a greenhouse planet. Science 298:981–987CrossRefGoogle Scholar
  26. IPCC (2011) Special report of the intergovernmental panel on climate change on renewable energy sources and climate change mitigation. Tech. rep. Cambridge University PressGoogle Scholar
  27. IRENA (2015) Renewable power generation costs in 2014 international renewable energy agencyGoogle Scholar
  28. Jaffe AB, Newell RG, Stavins RN (2005) A tale of two market failures: technology and environmental policy. Ecol Econ 54:164–174CrossRefGoogle Scholar
  29. Jamasb T (2007) Technical change theory and learning curves: patterns of progress in energy technologies. Energy J 28(3):51–71CrossRefGoogle Scholar
  30. Jenni K, Baker E, Nemet G (2013) Expert elicitations of energy penalties for carbon capture. Int J Greenh Gas Control 12:136–145CrossRefGoogle Scholar
  31. Jones CI (1995) R & d-based models of economic growth. J Polit Econ 103:759–784CrossRefGoogle Scholar
  32. Klaassen G, Miketa A, Larsen K, Sundqvist T (2005) The impact of r&d on innovation for wind energy in Denmark, Germany and the United Kingdom. Ecol Econ 54(2–3):227–240CrossRefGoogle Scholar
  33. Elmar K, Blanford GJ, Weyant JP, Volker K, Clarke L, Edmonds J, Fawcett A, Gunnar L, Riahi K, Richels R, Steven KR, Tavoni M, Vuuren DP (2014) The role of technology for achieving climate policy objectives: overview of the emf 27 study on global technology and climate policy strategies. Clim Chang:1–15Google Scholar
  34. Nemet GF, Anadon LD, Verdolini E (2016) Quantifying the effects of expert selection and elicitation design on experts confidence in their judgments about future energy technologies. Risk Anal. ForthcomingGoogle Scholar
  35. NRC (2007) Prospective evaluation of applied energy research and development at doe (phase two). Tech. rep. NRCGoogle Scholar
  36. Popp D, Newell R (2012) Where does energy r&d come from? Examining crowding out from energy r&d. Energy Econ 34(4):980–991CrossRefGoogle Scholar
  37. Qiu Y, Anadon LD (2012) The price of wind power in china during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization. Energy Econ 34(3):772–785CrossRefGoogle Scholar
  38. Rao A, Rubin E, Keith D, Morgan M (2006) Evaluation of potential cost reductions from improved amine-based co2 capture systems. Energy Policy 34:3765–3772CrossRefGoogle Scholar
  39. Rogelj J, McCollum LD, ONeill BC, Riahi K (2013) 2020 emissions levels required to limit warming to below 2c. Nat Clim Chang 3:405–12CrossRefGoogle Scholar
  40. Tversky A, Kahneman D (1974) 1974 judgment under uncertainty: Heuristics and biases. Science 185(4157):1124–1131CrossRefGoogle Scholar
  41. USEPA (2011) Expert elicitation task force, white paper. Tech. rep., U.S. Environmental Protection AgencyGoogle Scholar
  42. Usher W, Strachan N (2013) An expert elicitation of climate, energy and economic uncertainties. Energy Policy 61:811–821CrossRefGoogle Scholar
  43. Verdolini E, Anadon LD, Lu J, Nemet G (2015) The effects of expert selection, elicitation design and r&d assumptions on experts’ estimates of the future costs of photovoltaics. Energy Policy 80:233–243. SubmittedCrossRefGoogle Scholar
  44. Zickfeld K, Morgan M, Frame D, Keith D (2010) Expert judgments about transient climate response to alternative future trajectories of radiative forcing. Proc Natl Acad Sci 107(28):12,451–12,456CrossRefGoogle Scholar
  45. Zubaryeva A, Thiel C (2013) Analyzing potential lead markets for hydrogen fuel cell vehicles in europe: expert views and spatial perspective. Int J Hydrog Energy 38:5878–15,886CrossRefGoogle Scholar
  46. Zubaryeva A., Thiel C, Barbone E, Mercier A (2012) Assessing factors for the identification of potential lead markets for electrified vehicles in europe: expert opinion elicitation. Technol Forecast Soc Chang 79:1622–1637CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Laura Diaz Anadon
    • 2
    • 6
  • Erin Baker
    • 1
    Email author
  • Valentina Bosetti
    • 3
    • 4
    • 5
  • Lara Aleluia Reis
    • 4
    • 5
  1. 1.Department of Mechanical and Industrial EngineeringUniversity of Massachusetts AmherstAmherstUSA
  2. 2.Harvard Kennedy SchoolHarvard UniversityCambridgeUSA
  3. 3.Department of EconomicsBocconi UniversityMilanoItaly
  4. 4.Fondazione Eni Enrico MatteiMilanoItaly
  5. 5.Centro Euro-Mediterraneo sui Cambiamenti ClimaticiLecceItaly
  6. 6.Department of Science, Technology, Engineering & Public PolicyUniversity College LondonLondonUK

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