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Accelerating diffusion of climate-friendly technologies: A network perspective

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  • Halleck-Vega, Solmaria
  • Mandel, Antoine
  • Millock, Katrin

Abstract

We introduce a methodology to estimate the determinants of the formation of technology diffusion networks from the patterns of technology adoption. We apply this methodology to wind energy, which is one of the key technologies in climate change mitigation. Our results emphasize that, in particular, long-term relationships as measured by economic integration are key determinants of technological diffusion. Specific support measures are less relevant, at least to explain the extensive margin of diffusion. Our results also highlight that the scope of technological diffusion is much broader than what is suggested by the consideration of CDM projects alone, which are particularly focused on China and India. Finally, the network of technological diffusion inferred from our approach highlights the central role of European countries in the diffusion process and the absence of large hubs among developing countries.

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  • Halleck-Vega, Solmaria & Mandel, Antoine & Millock, Katrin, 2018. "Accelerating diffusion of climate-friendly technologies: A network perspective," Ecological Economics, Elsevier, vol. 152(C), pages 235-245.
    • Handle: RePEc:eee:ecolec:v:152:y:2018:i:c:p:235-245
    DOI: 10.1016/j.ecolecon.2018.05.007
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    2. Antoine Mandel & Solmaria Halleck Vega & Dan-Xia Wang, 2020. "The contribution of technological diffusion to climate change mitigation: a network-based approach," Climatic Change, Springer, vol. 160(4), pages 609-620, June.
    3. Fadly, Dalia & Fontes, Francisco, 2019. "Geographical proximity and renewable energy diffusion: An empirical approach," Energy Policy, Elsevier, vol. 129(C), pages 422-435.
    4. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2024. "Global climate change mitigation technology diffusion: A network perspective," Energy Economics, Elsevier, vol. 133(C).
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    7. Garsous, Grégoire & Worack, Stephan, 2022. "Technological expertise as a driver of environmental technology diffusion through trade: Evidence from the wind turbine manufacturing industry," Energy Policy, Elsevier, vol. 162(C).
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    10. Monasterolo, Irene & Roventini, Andrea & Foxon, Tim J., 2019. "Uncertainty of climate policies and implications for economics and finance: An evolutionary economics approach," Ecological Economics, Elsevier, vol. 163(C), pages 177-182.

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    More about this item

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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