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The contribution of technological diffusion to climate change mitigation: a network-based approach

Author

Listed:
  • Antoine Mandel

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Solmaria Halleck Vega

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Dan-Xia Wang

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We propose a novel approach to quantify the contribution of technological diffusion to climate change mitigation. First, we use a parametric model of epidemic diffusion to estimate from micro-level data the determinants and the structure of the networks of diffusion for three key mitigation technologies: electro-mobility, renewable energy and agriculture. We then simulate the propagation of new technological vintages on these networks and quantify the reduction of emissions induced by the diffusion process using a tailored feedback centrality measure labelled "emission centrality". Finally, we investigate how new forms of international collaboration such as climate clubs can contribute to mitigation by catalysing the adoption of new technologies. Our approach can be used directly to measure the contribution of technological diffusion to mitigation or indirectly by providing estimates of global technological diffusion to integrated assessment models.

Suggested Citation

  • Antoine Mandel & Solmaria Halleck Vega & Dan-Xia Wang, 2020. "The contribution of technological diffusion to climate change mitigation: a network-based approach," Post-Print halshs-02334594, HAL.
    • Handle: RePEc:hal:journl:halshs-02334594
    DOI: 10.1007/s10584-019-02517-3
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    References listed on IDEAS

    as
    1. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    2. 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.
    3. Jon Hovi & Detlef F Sprinz & Håkon Sælen & Arild Underdal, 2016. "Climate change mitigation: a role for climate clubs?," Palgrave Communications, Palgrave Macmillan, vol. 2(1), pages 1-9, December.
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    5. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
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    9. 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.
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    Cited by:

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    2. Jochen Hinkel & Diana Mangalagiu & Alexander Bisaro & J. David Tàbara, 2020. "Transformative narratives for climate action," Climatic Change, Springer, vol. 160(4), pages 495-506, June.
    3. 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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    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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