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Experiments with a methodology to model the role of R&D expenditures in energy technology learning processes; first results

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Cited by:

  1. Uyterlinde, Martine A. & Junginger, Martin & de Vries, Hage J. & Faaij, Andre P.C. & Turkenburg, Wim C., 2007. "Implications of technological learning on the prospects for renewable energy technologies in Europe," Energy Policy, Elsevier, vol. 35(8), pages 4072-4087, August.
  2. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
  3. Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
  4. Fertig, Emily, 2018. "Rare breakthroughs vs. incremental development in R&D strategy for an early-stage energy technology," Energy Policy, Elsevier, vol. 123(C), pages 711-721.
  5. Gunther Glenk & Rebecca Meier & Stefan Reichelstein, 2021. "Cost Dynamics of Clean Energy Technologies," Schmalenbach Journal of Business Research, Springer, vol. 73(2), pages 179-206, June.
  6. Avril, S. & Mansilla, C. & Busson, M. & Lemaire, T., 2012. "Photovoltaic energy policy: Financial estimation and performance comparison of the public support in five representative countries," Energy Policy, Elsevier, vol. 51(C), pages 244-258.
  7. Ahmadi, Esmaeil & McLellan, Benjamin & Tezuka, Tetsuo, 2020. "The economic synergies of modelling the renewable energy-water nexus towards sustainability," Renewable Energy, Elsevier, vol. 162(C), pages 1347-1366.
  8. Yi Zhou & Alun Gu, 2019. "Learning Curve Analysis of Wind Power and Photovoltaics Technology in US: Cost Reduction and the Importance of Research, Development and Demonstration," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
  9. Bointner, Raphael, 2014. "Innovation in the energy sector: Lessons learnt from R&D expenditures and patents in selected IEA countries," Energy Policy, Elsevier, vol. 73(C), pages 733-747.
  10. Gupta, Sandeep Kumar & Purohit, Pallav, 2013. "Renewable energy certificate mechanism in India: A preliminary assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 380-392.
  11. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng & Vaz-Serra, Paulo, 2022. "Economic and environmental impacts of public investment in clean energy RD&D," Energy Policy, Elsevier, vol. 168(C).
  12. Lin, Boqiang & He, Jiaxin, 2016. "Learning curves for harnessing biomass power: What could explain the reduction of its cost during the expansion of China?," Renewable Energy, Elsevier, vol. 99(C), pages 280-288.
  13. Harashima, Taiji, 2009. "A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element," MPRA Paper 15508, University Library of Munich, Germany.
  14. David MacLaughlin & Steffanie Scott, 2010. "Overcoming latecomer disadvantage through learning processes: Taiwan’s venture into wind power development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 12(3), pages 389-406, June.
  15. Apetrei, Cristina I. & Strelkovskii, Nikita & Khabarov, Nikolay & Javalera Rincón, Valeria, 2024. "Improving the representation of smallholder farmers’ adaptive behaviour in agent-based models: Learning-by-doing and social learning," Ecological Modelling, Elsevier, vol. 489(C).
  16. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2017. "Inter-temporal R&D and capital investment portfolios for the electricity industrys low carbon future," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
  17. Kobos, Peter H. & Erickson, Jon D. & Drennen, Thomas E., 2006. "Technological learning and renewable energy costs: implications for US renewable energy policy," Energy Policy, Elsevier, vol. 34(13), pages 1645-1658, September.
  18. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
  19. Taghizadeh-Hesary, Farhad & Yoshino, Naoyuki & Inagaki, Yugo, 2018. "Empirical Analysis of Factors Influencing Price of Solar Modules," ADBI Working Papers 836, Asian Development Bank Institute.
  20. Yiqing Li & Weiguo Yang & Lixin Tian & Jie Yang, 2018. "An Evaluation of Investment in a PV Power Generation Project in the Gobi Desert Using a Real Options Model," Energies, MDPI, vol. 11(1), pages 1-16, January.
  21. Liu, Qiang & Shi, Minjun & Jiang, Kejun, 2009. "New power generation technology options under the greenhouse gases mitigation scenario in China," Energy Policy, Elsevier, vol. 37(6), pages 2440-2449, June.
  22. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
  23. Jeon, Chanwoong & Shin, Juneseuk, 2014. "Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case," Energy, Elsevier, vol. 66(C), pages 447-457.
  24. Gregory F. Nemet & Erin Baker, 2009. "Demand Subsidies Versus R&D: Comparing the Uncertain Impacts of Policy on a Pre-commercial Low-carbon Energy Technology," The Energy Journal, , vol. 30(4), pages 49-80, October.
  25. Nemet, Gregory F., 2006. "How well does Learning-by-doing Explain Cost Reductions in a Carbon-free Energy Technology?," Climate Change Modelling and Policy Working Papers 12051, Fondazione Eni Enrico Mattei (FEEM).
  26. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  27. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  28. Raphael Bointner & Simon Pezzutto & Gianluca Grilli & Wolfram Sparber, 2016. "Financing Innovations for the Renewable Energy Transition in Europe," Energies, MDPI, vol. 9(12), pages 1-16, November.
  29. Liu, Jiangfeng & Zhang, Qi & Li, Hailong & Chen, Siyuan & Teng, Fei, 2022. "Investment decision on carbon capture and utilization (CCU) technologies—A real option model based on technology learning effect," Applied Energy, Elsevier, vol. 322(C).
  30. Glenk, Gunther & Meier, Rebecca & Reichelstein, Stefan, 2021. "Cost dynamics of clean energy technologies," ZEW Discussion Papers 21-054, ZEW - Leibniz Centre for European Economic Research.
  31. Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.
  32. Mathias Mier & Jacqueline Adelowo & Valeriya Azarova, 2022. "Endogenous Technological Change in Power Markets," ifo Working Paper Series 373, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  33. Takanobu Kosugi, 2010. "Assessments of ‘Greenhouse Insurance’: A Methodological Review," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 17(4), pages 345-363, December.
  34. Albrecht, Johan & Laleman, Ruben & Vulsteke, Elien, 2015. "Balancing demand-pull and supply-push measures to support renewable electricity in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 267-277.
  35. Criqui, P. & Mima, S. & Menanteau, P. & Kitous, A., 2015. "Mitigation strategies and energy technology learning: An assessment with the POLES model," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 119-136.
  36. 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.
  37. Choi, Donghyun & Kim, Yeong Jae, 2023. "Local and global experience curves for lumpy and granular energy technologies," Energy Policy, Elsevier, vol. 174(C).
  38. Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
  39. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
  40. Zeyringer, Marianne & Fais, Birgit & Keppo, Ilkka & Price, James, 2018. "The potential of marine energy technologies in the UK – Evaluation from a systems perspective," Renewable Energy, Elsevier, vol. 115(C), pages 1281-1293.
  41. Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
  42. Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
  43. Manne, Alan & Richels, Richard, 2004. "The impact of learning-by-doing on the timing and costs of CO2 abatement," Energy Economics, Elsevier, vol. 26(4), pages 603-619, July.
  44. Clarke, Leon & Weyant, John & Edmonds, Jae, 2008. "On the sources of technological change: What do the models assume," Energy Economics, Elsevier, vol. 30(2), pages 409-424, March.
  45. Iman Miremadi & Yadollah Saboohi, 2018. "Planning for Investment in Energy Innovation: Developing an Analytical Tool to Explore the Impact of Knowledge Flow," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 7-19.
  46. Wiser, Ryan & Millstein, Dev, 2020. "Evaluating the economic return to public wind energy research and development in the United States," Applied Energy, Elsevier, vol. 261(C).
  47. Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
  48. Hernandez-Negron, Christian G. & Baker, Erin & Goldstein, Anna P., 2023. "A hypothesis for experience curves of related technologies with an application to wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  49. Tooraj Jamasb, 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Working Papers EPRG 0608, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  50. Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.
  51. Fischer, Carolyn & Hübler, Michael & Schenker, Oliver, 2021. "More birds than stones – A framework for second-best energy and climate policy adjustments," Journal of Public Economics, Elsevier, vol. 203(C).
  52. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
  53. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
  54. Nemet, Gregory F., 2009. "Demand-pull, technology-push, and government-led incentives for non-incremental technical change," Research Policy, Elsevier, vol. 38(5), pages 700-709, June.
  55. Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
  56. Qiu, Yueming & Anadon, Laura D., 2012. "The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization," Energy Economics, Elsevier, vol. 34(3), pages 772-785.
  57. Zhang, Mingming & Zhou, Dequn & Zhou, Peng, 2014. "A real option model for renewable energy policy evaluation with application to solar PV power generation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 944-955.
  58. Shafiei, Ehsan & Saboohi, Yadollah & Ghofrani, Mohammad B., 2009. "Impact of innovation programs on development of energy system: Case of Iranian electricity-supply system," Energy Policy, Elsevier, vol. 37(6), pages 2221-2230, June.
  59. Harashima, Taiji, 2014. "Division of Work and Fragmented Information: An Explanation for the Diminishing Marginal Product of Labor," MPRA Paper 56301, University Library of Munich, Germany.
  60. Esmaeil Ahmadi & Benjamin McLellan & Seiichi Ogata & Behnam Mohammadi-Ivatloo & Tetsuo Tezuka, 2020. "An Integrated Planning Framework for Sustainable Water and Energy Supply," Sustainability, MDPI, vol. 12(10), pages 1-37, May.
  61. Chi, Chunjie & Ma, Tieju & Zhu, Bing, 2012. "Towards a low-carbon economy: Coping with technological bifurcations with a carbon tax," Energy Economics, Elsevier, vol. 34(6), pages 2081-2088.
  62. Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
  63. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry's Low Carbon Future," CESifo Working Paper Series 5139, CESifo.
  64. Ardito, Lorenzo & Ernst, Holger & Messeni Petruzzelli, Antonio, 2020. "The interplay between technology characteristics, R&D internationalisation, and new product introduction: Empirical evidence from the energy conservation sector," Technovation, Elsevier, vol. 96.
  65. Miremadi, I. & Saboohi, Y. & Arasti, M., 2019. "The influence of public R&D and knowledge spillovers on the development of renewable energy sources: The case of the Nordic countries," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 450-463.
  66. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
  67. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry’s Low Carbon Future," NBER Working Papers 20783, National Bureau of Economic Research, Inc.
  68. Raphael Bointner & Simon Pezzutto & Wolfram Sparber, 2016. "Scenarios of public energy research and development expenditures: financing energy innovation in Europe," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(4), pages 470-488, July.
  69. Harashima, Taiji, 2011. "A Model of Total Factor Productivity Built on Hayek’s View of Knowledge: What Really Went Wrong with Socialist Planned Economies?," MPRA Paper 29107, University Library of Munich, Germany.
  70. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  71. Taghizadeh-Hesary, Farhad & Yoshino, Naoyuki & Inagaki, Yugo & Morgan, Peter J., 2021. "Analyzing the factors influencing the demand and supply of solar modules in Japan – Does financing matter," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 1-12.
  72. Svensson, Elin & Berntsson, Thore, 2011. "Planning future investments in emerging energy technologies for pulp mills considering different scenarios for their investment cost development," Energy, Elsevier, vol. 36(11), pages 6508-6519.
  73. Harashima, Taiji, 2012. "A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence," MPRA Paper 43151, University Library of Munich, Germany.
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