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An age structured demographic theory of technological change

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  • J. -F. Mercure
Abstract
At the heart of technology transitions lie complex processes of social and industrial dynamics. The quantitative study of sustainability transitions requires modelling work, which necessitates a theory of technology substitution. Many, if not most, contemporary modelling approaches for future technology pathways overlook most aspects of transitions theory, for instance dimensions of heterogenous investor choices, dynamic rates of diffusion and the profile of transitions. A significant body of literature however exists that demonstrates how transitions follow S-shaped diffusion curves or Lotka-Volterra systems of equations. This framework is used ex-post since timescales can only be reliably obtained in cases where the transitions have already occurred, precluding its use for studying cases of interest where nascent innovations in protective niches await favourable conditions for their diffusion. In principle, scaling parameters of transitions can, however, be derived from knowledge of industrial dynamics, technology turnover rates and technology characteristics. In this context, this paper presents a theory framework for evaluating the parameterisation of S-shaped diffusion curves for use in simulation models of technology transitions without the involvement of historical data fitting, making use of standard demography theory applied to technology at the unit level. The classic Lotka-Volterra competition system emerges from first principles from demography theory, its timescales explained in terms of technology lifetimes and industrial dynamics. The theory is placed in the context of the multi-level perspective on technology transitions, where innovation and the diffusion of new socio-technical regimes take a prominent place, as well as discrete choice theory, the primary theoretical framework for introducing agent diversity.

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  • J. -F. Mercure, 2013. "An age structured demographic theory of technological change," Papers 1304.3602, arXiv.org, revised Nov 2014.
    • Handle: RePEc:arx:papers:1304.3602
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    Cited by:

    1. Pim Vercoulen & Soocheol Lee & Xu Han & Wendan Zhang & Yongsung Cho & Jun Pang, 2023. "Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with E3ME-FTT:Steel," Energies, MDPI, vol. 16(11), pages 1-24, June.
    2. 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.
    3. 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.
    4. Campiglio, Emanuele & Lamperti, Francesco & Terranova, Roberta, 2024. "Believe me when I say green! Heterogeneous expectations and climate policy uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
    5. Katariina Koistinen & Satu Teerikangas, 2021. "The Debate If Agents Matter vs. the System Matters in Sustainability Transitions—A Review of the Literature," Sustainability, MDPI, vol. 13(5), pages 1-32, March.
    6. Odenweller, Adrian, 2022. "Climate mitigation under S-shaped energy technology diffusion: Leveraging synergies of optimisation and simulation models," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    7. An, Kangxin & Wang, Can & Cai, Wenjia, 2023. "Low-carbon technology diffusion and economic growth of China: an evolutionary general equilibrium framework," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 253-263.
    8. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
    9. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    10. Mercure, Jean-François & Salas, Pablo, 2013. "On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities," Energy Policy, Elsevier, vol. 63(C), pages 469-483.
    11. J. -F. Mercure & H. Pollitt & A. M. Bassi & J. E Vi~nuales & N. R. Edwards, 2015. "Modelling complex systems of heterogeneous agents to better design sustainability transitions policy," Papers 1506.07432, arXiv.org, revised Feb 2016.
    12. Femke J. M. M. Nijsse & Jean-Francois Mercure & Nadia Ameli & Francesca Larosa & Sumit Kothari & Jamie Rickman & Pim Vercoulen & Hector Pollitt, 2023. "The momentum of the solar energy transition," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. F. Knobloch & J. -F. Mercure, 2016. "The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents," Papers 1603.06888, arXiv.org.
    14. Knobloch, Florian & Pollitt, Hector & Chewpreecha, Unnada & Lewney, Richard & Huijbregts, Mark A.J. & Mercure, Jean-Francois, 2021. "FTT:Heat — A simulation model for technological change in the European residential heating sector," Energy Policy, Elsevier, vol. 153(C).
    15. J.-F. Mercure & A. Lam & S. Billington & H. Pollitt, 2018. "Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 ∘C," Climatic Change, Springer, vol. 151(2), pages 109-129, November.

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