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The Perils of the Learning Model for Modeling Endogenous Technological Change

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Cited by:

  1. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
  2. Grafström, Jonas & Lindman, Åsa, 2017. "Invention, innovation and diffusion in the European wind power sector," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 179-191.
  3. Elizabeth Baldwin & Yongyang Cai & Karlygash Kuralbayeva, 2018. "To Build or Not to Build? Capital Stocks and Climate Policy," CESifo Working Paper Series 6884, CESifo.
  4. Grafström, Jonas & Poudineh, Rahmat, 2021. "A review of problems associated with learning curves for solar and wind power technologies," Ratio Working Papers 347, The Ratio Institute.
  5. Christopher L Benson & Christopher L Magee, 2015. "Quantitative Determination of Technological Improvement from Patent Data," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-23, April.
  6. Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  7. 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.
  8. 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.
  9. Sommerfeldt, Nelson & Madani, Hatef, 2017. "Revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: Part one – Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1379-1393.
  10. Verdolini, Elena & Anadon, Laura Diaz & Lu, Jiaqi & Nemet, Gregory F., 2015. "The effects of expert selection, elicitation design, and R&D assumptions on experts' estimates of the future costs of photovoltaics," Energy Policy, Elsevier, vol. 80(C), pages 233-243.
  11. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
  12. Aguilera, Roberto F. & Ripple, Ronald D., 2012. "Technological progress and the availability of European oil and gas resources," Applied Energy, Elsevier, vol. 96(C), pages 387-392.
  13. Littlejohn, Christina & Proost, Stef, 2022. "What role for electric vehicles in the decarbonization of the car transport sector in Europe?," Economics of Transportation, Elsevier, vol. 32(C).
  14. Funk, Jeffrey L. & Magee, Christopher L., 2015. "Rapid improvements with no commercial production: How do the improvements occur?," Research Policy, Elsevier, vol. 44(3), pages 777-788.
  15. Magee, C.L. & Basnet, S. & Funk, J.L. & Benson, C.L., 2016. "Quantitative empirical trends in technical performance," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 237-246.
  16. Bento, Nuno & Gianfrate, Gianfranco & Groppo, Sara Virginia, 2019. "Do crowdfunding returns reward risk? Evidences from clean-tech projects," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 107-116.
  17. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
  18. Bergesen, Joseph D. & Suh, Sangwon, 2016. "A framework for technological learning in the supply chain: A case study on CdTe photovoltaics," Applied Energy, Elsevier, vol. 169(C), pages 721-728.
  19. 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.
  20. Stephen Murray & Cesar Aguado & Victor M. Castaño, 2022. "In-Company Technical Training in Developing Countries," Journal of Education and Training, Macrothink Institute, vol. 9(2), pages 82-99, August.
  21. Seck, Gondia S. & Hache, Emmanuel & Sabathier, Jerome & Guedes, Fernanda & Reigstad, Gunhild A. & Straus, Julian & Wolfgang, Ove & Ouassou, Jabir A. & Askeland, Magnus & Hjorth, Ida & Skjelbred, Hans , 2022. "Hydrogen and the decarbonization of the energy system in europe in 2050: A detailed model-based analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  22. Bhardwaj, Chandan & Axsen, Jonn & McCollum, David, 2022. "Which “second-best” climate policies are best? Simulating cost-effective policy mixes for passenger vehicles," Resource and Energy Economics, Elsevier, vol. 70(C).
  23. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
  24. Lafond, François & Greenwald, Diana & Farmer, J. Doyne, 2022. "Can Stimulating Demand Drive Costs Down? World War II as a Natural Experiment," The Journal of Economic History, Cambridge University Press, vol. 82(3), pages 727-764, September.
  25. Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013. "Statistical Basis for Predicting Technological Progress," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
  26. Aguilera, Roberto F., 2014. "Production costs of global conventional and unconventional petroleum," Energy Policy, Elsevier, vol. 64(C), pages 134-140.
  27. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2023. "Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning," Applied Energy, Elsevier, vol. 340(C).
  28. Mauleón, Ignacio & Hamoudi, Hamid, 2017. "Photovoltaic and wind cost decrease estimation: Implications for investment analysis," Energy, Elsevier, vol. 137(C), pages 1054-1065.
  29. Baldwin, Elizabeth & Cai, Yongyang & Kuralbayeva, Karlygash, 2020. "To build or not to build? Capital stocks and climate policy∗," Journal of Environmental Economics and Management, Elsevier, vol. 100(C).
  30. Lion Hirth, 2015. "The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
  31. Michael Grubb & Jean-Francois Mercure & Pablo Salas & Rutger-Jan Lange & Ida Sognnaes, 2018. "Systems Innovation, Inertia and Pliability: A mathematical exploration with implications for climate change abatement," Working Papers EPRG 1808, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  32. Clas‐Otto Wene, 2016. "Future energy system development depends on past learning opportunities," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(1), pages 16-32, January.
  33. Newbery, David & Pollitt, Michael G. & Ritz, Robert A. & Strielkowski, Wadim, 2018. "Market design for a high-renewables European electricity system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 695-707.
  34. Mauleón, Ignacio, 2019. "Assessing PV and wind roadmaps: Learning rates, risk, and social discounting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 71-89.
  35. Mauleón, Ignacio, 2019. "Optimizing individual renewable energies roadmaps: Criteria, methods, and end targets," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  36. Ovaere, Marten & Proost, Stef, 2022. "Cost-effective reduction of fossil energy use in the European transport sector: An assessment of the Fit for 55 Package," Energy Policy, Elsevier, vol. 168(C).
  37. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
  38. Moglianesi, Andrea & Keppo, Ilkka & Lerede, Daniele & Savoldi, Laura, 2023. "Role of technology learning in the decarbonization of the iron and steel sector: An energy system approach using a global-scale optimization model," Energy, Elsevier, vol. 274(C).
  39. Paul Lehmann & Patrik Söderholm, 2018. "Can Technology-Specific Deployment Policies Be Cost-Effective? The Case of Renewable Energy Support Schemes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(2), pages 475-505, October.
  40. 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.
  41. Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
  42. Edenhofer, Ottmar & Hirth, Lion & Knopf, Brigitte & Pahle, Michael & Schlömer, Steffen & Schmid, Eva & Ueckerdt, Falko, 2013. "On the economics of renewable energy sources," Energy Economics, Elsevier, vol. 40(S1), pages 12-23.
  43. Thomas Boucher & Yuchen Li, 2016. "Technical note: systematic bias in stochastic learning," International Journal of Production Research, Taylor & Francis Journals, vol. 54(11), pages 3452-3463, June.
  44. Newbery, David, 2018. "Evaluating the case for supporting renewable electricity," Energy Policy, Elsevier, vol. 120(C), pages 684-696.
  45. Enrica Cian & Valentina Bosetti & Massimo Tavoni, 2012. "Technology innovation and diffusion in “less than ideal” climate policies: An assessment with the WITCH model," Climatic Change, Springer, vol. 114(1), pages 121-143, September.
  46. Bello, S. & Reiner, 2024. "Experience Curves for Electrolysis Technologies," Cambridge Working Papers in Economics 2476, Faculty of Economics, University of Cambridge.
  47. Dosi, Giovanni & Grazzi, Marco & Mathew, Nanditha, 2017. "The cost-quantity relations and the diverse patterns of “learning by doing”: Evidence from India," Research Policy, Elsevier, vol. 46(10), pages 1873-1886.
  48. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
  49. Enrica De Cian & Johannes Buhl & Samuel Carrara & Michela Bevione & Silvia Monetti & Holger Berg, 2016. "Knowledge Creation between Integrated Assessment Models and Initiative-Based Learning - An Interdisciplinary Approach," Working Papers 2016.66, Fondazione Eni Enrico Mattei.
  50. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
  51. 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).
  52. Ek, Kristina & Söderholm, Patrik, 2010. "Technology learning in the presence of public R&D: The case of European wind power," Ecological Economics, Elsevier, vol. 69(12), pages 2356-2362, October.
  53. Li, Xin, 2014. "The Demographic Structure and Export Strategy in Emerging Economies," Conference papers 332502, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
  54. 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.
  55. 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).
  56. Bistline, John & Blanford, Geoffrey & Mai, Trieu & Merrick, James, 2021. "Modeling variable renewable energy and storage in the power sector," Energy Policy, Elsevier, vol. 156(C).
  57. repec:sae:envval:v:25:y:2016:i:1:p:7-28 is not listed on IDEAS
  58. Gawel, Erik & Lehmann, Paul & Purkus, Alexandra & Söderholm, Patrik & Witte, Katherina, 2017. "Rationales for technology-specific RES support and their relevance for German policy," Energy Policy, Elsevier, vol. 102(C), pages 16-26.
  59. Anuraag Singh & Giorgio Triulzi & Christopher L. Magee, 2020. "Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description," Papers 2004.13919, arXiv.org.
  60. Yicong Lin & Hanno Reuvers, 2020. "Cointegrating Polynomial Regressions with Power Law Trends: Environmental Kuznets Curve or Omitted Time Effects?," Papers 2009.02262, arXiv.org, revised Dec 2021.
  61. Ritchie, Justin & Dowlatabadi, Hadi, 2017. "Evaluating the Learning-by-Doing Theory of Long-Run Oil, Gas, and Coal Economics," RFF Working Paper Series 17-14, Resources for the Future.
  62. Gawel, Erik & Lehmann, Paul & Purkus, Alexandra & Söderholm, Patrik & Witte, Katherina, 2016. "The rationales for technology-specific renewable energy support: Conceptual arguments and their relevance for Germany," UFZ Discussion Papers 4/2016, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
  63. Newbery, David M., 2016. "Towards a green energy economy? The EU Energy Union’s transition to a low-carbon zero subsidy electricity system – Lessons from the UK’s Electricity Market Reform," Applied Energy, Elsevier, vol. 179(C), pages 1321-1330.
  64. Narbel, Patrick André & Hansen, Jan Petter, 2014. "Estimating the cost of future global energy supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 91-97.
  65. Shayegh, Soheil & Sanchez, Daniel L. & Caldeira, Ken, 2017. "Evaluating relative benefits of different types of R&D for clean energy technologies," Energy Policy, Elsevier, vol. 107(C), pages 532-538.
  66. Wiebe, Kirsten S. & Lutz, Christian, 2016. "Endogenous technological change and the policy mix in renewable power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 739-751.
  67. 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.
  68. 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).
  69. Ding, H. & Zhou, D.Q. & Liu, G.Q. & Zhou, P., 2020. "Cost reduction or electricity penetration: Government R&D-induced PV development and future policy schemes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
  70. Yuichiro Kamada & Fuhito Kojima, 2013. "Voter Preferences, Polarization, and Electoral Policies," Discussion Papers 12-021, Stanford Institute for Economic Policy Research.
  71. Salvador Pueyo, 2019. "Limits to green growth and the dynamics of innovation," Papers 1904.09586, arXiv.org, revised May 2019.
  72. 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.
  73. Gao, Xue & Rai, Varun & Nemet, Gregory F., 2022. "The roles of learning mechanisms in services: Evidence from US residential solar installations," Energy Policy, Elsevier, vol. 167(C).
  74. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2017. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry’s Low Carbon Future," The Energy Journal, , vol. 38(6), pages 1-24, November.
  75. Partridge, Ian, 2013. "Renewable electricity generation in India—A learning rate analysis," Energy Policy, Elsevier, vol. 60(C), pages 906-915.
  76. John W. Anderson & Gordon W. Leslie & Frank A. Wolak, 2019. "Measuring the Impact of Own and Others’ Experience on Project Costs in the U.S. Wind Generation Industry," NBER Working Papers 26114, National Bureau of Economic Research, Inc.
  77. Schmid, Eva & Knopf, Brigitte, 2015. "Quantifying the long-term economic benefits of European electricity system integration," Energy Policy, Elsevier, vol. 87(C), pages 260-269.
  78. Narbel, Patrick A. & Hansen, Jan Petter, 2014. "Estimating the cost of future global energy supply," Discussion Papers 2014/14, Norwegian School of Economics, Department of Business and Management Science.
  79. Eskeland, Gunnar S. & Rive, Nathan A. & Mideksa, Torben K., 2012. "Europe’s climate goals and the electricity sector," Energy Policy, Elsevier, vol. 41(C), pages 200-211.
  80. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
  81. Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
  82. Matthias Weitzel, 2017. "The role of uncertainty in future costs of key CO2 abatement technologies: a sensitivity analysis with a global computable general equilibrium model," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 153-173, January.
  83. Amavilah, Voxi Heinrich, 2014. "Human Knowledge and a Commonsensical Measure of Human Capital: A Proposal," MPRA Paper 57670, University Library of Munich, Germany.
  84. Benson, Christopher L. & Magee, Christopher L., 2014. "On improvement rates for renewable energy technologies: Solar PV, wind turbines, capacitors, and batteries," Renewable Energy, Elsevier, vol. 68(C), pages 745-751.
  85. Saheed Bello & David M Reiner, 2024. "Experience curves for electrolysis technologies," Working Papers EPRG2420, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  86. 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.
  87. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
  88. Amavilah, Voxi Heinrich, 2011. "The Full Value of the Nobel Prize - Part 1: Mining “Data Without Theory”," MPRA Paper 33483, University Library of Munich, Germany.
  89. Odam, Neil & de Vries, Frans P., 2020. "Innovation modelling and multi-factor learning in wind energy technology," Energy Economics, Elsevier, vol. 85(C).
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