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Introduction of subsidisation in nascent climate-friendly learning technologies and evaluation of its effectiveness

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  • Rout, Ullash K.
  • Akimoto, Keigo
  • Sano, Fuminori
  • Tomoda, Toshimasa

Abstract

Given its importance as a practical phenomenon underlying the progress of learning technologies, attention should be paid to the role of subsidisation in learning theory, particularly in the case of nascent climate-related sociable learning technologies, in order to examine its benefits. Thus, this study focuses on subsidy procurement of energy technologies in several economies in the context of the component learning track in endogenous global clusters in order to suggest improvements to the adoption mechanism and examine the climate stabilization constraint. At the same time, the study attempts to determine the global progress ratio of the lithium-ion battery in order to analyse various endogenous learning scenarios for hybrid technologies. An integrated energy system model with highly disaggregated global regions (DNE21+) is used to execute this research in a medium time frame. Subsidisation of the learning track of battery technology encourages greater development of plug-in hybrid vehicles, promotes early diffusion of hybrid technologies, and relieves heavy dependency on crude oil and biofuels. The subsidies in the common learning domains in few economies benefit the nearby economies because of the technology spillover that occurs through numerous cross-feedback learning mechanisms. Endogenous learning with subsidies augments diffusion potentials, abates emissions, and shifts sectoral emissions.

Suggested Citation

  • Rout, Ullash K. & Akimoto, Keigo & Sano, Fuminori & Tomoda, Toshimasa, 2010. "Introduction of subsidisation in nascent climate-friendly learning technologies and evaluation of its effectiveness," Energy Policy, Elsevier, vol. 38(1), pages 520-532, January.
  • Handle: RePEc:eee:enepol:v:38:y:2010:i:1:p:520-532
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    References listed on IDEAS

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    1. Rout, Ullash K. & Akimoto, Keigo & Sano, Fuminori & Oda, Junichiro & Homma, Takashi & Tomoda, Toshimasa, 2008. "Impact assessment of the increase in fossil fuel prices on the global energy system, with and without CO2 concentration stabilization," Energy Policy, Elsevier, vol. 36(9), pages 3477-3484, September.
    2. Larsen, Bjorn & Shah, Anwar & DEC, 1992. "World fossil fuel subsidies and global carbon emissions," Policy Research Working Paper Series 1002, The World Bank.
    3. Rout, Ullash K. & Fahl, Ulrich & Remme, Uwe & Blesl, Markus & Voß, Alfred, 2009. "Endogenous implementation of technology gap in energy optimization models--a systematic analysis within TIMES G5 model," Energy Policy, Elsevier, vol. 37(7), pages 2814-2830, July.
    4. Kamp, Linda M. & Smits, Ruud E. H. M. & Andriesse, Cornelis D., 2004. "Notions on learning applied to wind turbine development in the Netherlands and Denmark," Energy Policy, Elsevier, vol. 32(14), pages 1625-1637, September.
    5. Loiter, Jeffrey M. & Norberg-Bohm, Vicki, 1999. "Technology policy and renewable energy: public roles in the development of new energy technologies," Energy Policy, Elsevier, vol. 27(2), pages 85-97, February.
    6. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    7. Fisher-Vanden, Karen & Ho, Mun S., 2010. "Technology, development, and the environment," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 94-108, January.
    8. Akimoto, Keigo & Tomoda, Toshimasa & Fujii, Yasumasa & Yamaji, Kenji, 2004. "Assessment of global warming mitigation options with integrated assessment model DNE21," Energy Economics, Elsevier, vol. 26(4), pages 635-653, July.
    9. 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.
    10. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    11. Keigo Akimoto & Fuminori Sano & Junichiro Oda & Takashi Homma & Ullash Kumar Rout & Toshimasa Tomoda, 2008. "Global emission reductions through a sectoral intensity target scheme," Climate Policy, Taylor & Francis Journals, vol. 8(sup1), pages 46-59, December.
    12. Ad Seebregts & Tom Kram & Gerrit Jan Schaeffer & Alexandra Bos, 2000. "Endogenous learning and technology clustering: analysis with MARKAL model of the Western European energy system," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 289-319.
    13. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    14. Yasumasa Fujii & Kenji Yamaji, 1998. "Assessment of technological options in the global energy system for limiting the atmospheric CO 2 concentration," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 1(2), pages 113-139, December.
    15. Irwin, Douglas A & Klenow, Peter J, 1994. "Learning-by-Doing Spillovers in the Semiconductor Industry," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1200-1227, December.
    16. Hertel, Thomas, 1997. "Global Trade Analysis: Modeling and applications," GTAP Books, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, number 7685, December.
    17. Fuminori Sano, Keigo Akimoto, Takashi Homma and Toshimasa Tomoda, 2006. "Analysis of Technological Portfolios for CO2 Stabilizations and Effects of Technological Changes," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 141-162.
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