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Climate change and green transitions in an agent-based integrated assessment model

Author

Listed:
  • G. Dosi

    (SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa])

  • F. Lamperti

    (SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa], EIEE - European Institute on Economics and the Environment)

  • Mauro Napoletano

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur, SKEMA Business School, OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po, SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa])

  • A. Roventini

    (SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa], OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

  • A. Sapio

    (PARTHENOPE - Università degli Studi di Napoli “Parthenope” = University of Naples, SSSUP - Scuola Universitaria Superiore Sant'Anna [Pisa])

Abstract

In this paper we employ an agent-based integrated assessment model to study the likelihood of transition to green, sustainable growth in presence of climate damages. The model comprises heterogeneous fossil-fuel and renewable plants, capital- and consumption-good firms and a climate box linking greenhouse gasses emission to temperature dynamics and microeconomic climate shocks affecting labour productivity and energy demand of firms. Simulation results show that the economy possesses two statistical equilibria: a carbon-intensive lock-in and a sustainable growth path characterized by better macroeconomic performances. Once climate damages are accounted for, the likelihood of a green transition depends on the damage function employed. While energy efficiency shocks (which raise the demand of energy) exert little effects on the macroeconomic performance compared to labour productivity impacts, they disproportionally harm the chances of an energy transition by exacerbating path-dependence in the process of technical change in favour of fossil-fuel technologies. Finally, we run a series of policy experiments on carbon (fossil fuel) taxes and green subsidies. We find that the effectiveness of such market-based instruments is limited, though it also depends upon the different channels climate change affects the economy through. Complementary policies might be required to avoid carbon-intensive lock-ins.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • G. Dosi & F. Lamperti & Mauro Napoletano & A. Roventini & A. Sapio, 2020. "Climate change and green transitions in an agent-based integrated assessment model," SciencePo Working papers Main halshs-03046932, HAL.
  • Handle: RePEc:hal:spmain:halshs-03046932
    DOI: 10.1016/j.techfore.2019.119806
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    6. Nieddu, Marcello & Bertani, Filippo & Ponta, Linda, 2021. "Sustainability transition and digital trasformation: an agent-based perspective," MPRA Paper 106943, University Library of Munich, Germany.
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    9. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    10. Jesse M. Keenan & Benjamin D. Trump & William Hynes & Igor Linkov, 2021. "Exploring the Convergence of Resilience Processes and Sustainable Outcomes in Post-COVID, Post-Glasgow Economies," Sustainability, MDPI, vol. 13(23), pages 1-12, December.
    11. Franzke, Christian L.E., 2021. "Towards the development of economic damage functions for weather and climate extremes," Ecological Economics, Elsevier, vol. 189(C).
    12. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2023. "Enter the MATRIX model:a Multi-Agent model for Transition Risks with application to energy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    13. Alessandro Taberna & Tatiana Filatova & Andrea Roventini & Francesco Lamperti, 2021. "Coping with increasing tides: technological change, agglomeration dynamics and climate hazards in an agent-based evolutionary model," LEM Papers Series 2021/44, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Lopolito, Antonio & Falcone, Pasquale Marcello & Sica, Edgardo, 2022. "The role of proximity in sustainability transitions: A technological niche evolution analysis," Research Policy, Elsevier, vol. 51(3).
    15. Taberna, Alessandro & Filatova, Tatiana & Roventini, Andrea & Lamperti, Francesco, 2022. "Coping with increasing tides: Evolving agglomeration dynamics and technological change under exacerbating hazards," Ecological Economics, Elsevier, vol. 202(C).
    16. de Moura, Fernanda Senra & Barbrook-Johnson, Peter, 2022. "Using data-driven systems mapping to contextualise complexity economics insights," INET Oxford Working Papers 2022-27, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    17. Enrico Turco & Davide Bazzana & Massimiliano Rizzati & Emanuele Ciola & Sergio Vergalli, 2022. "Energy price shocks and stabilization policies in a multi-agent macroeconomic model for the Euro Area," Working Papers 2022.25, Fondazione Eni Enrico Mattei.
    18. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    19. Dr. Christian Lutz & Dr. Marc Ingo Wolter, 2021. "Wege zur Klimaneutralität bis 2045 – Politische Handlungsfelder," GWS Discussion Paper Series 21-4, GWS - Institute of Economic Structures Research.
    20. Maruf Rahman Maxim & Kerstin K. Zander, 2020. "Green Tax Reform in Australia in the Presence of Improved Environment-Induced Productivity Gain: Does It Offer Sustainable Recovery from a Post-COVID-19 Recession?," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    21. Llopis-Albert, Carlos & Palacios-Marqués, Daniel & Simón-Moya, Virginia, 2021. "Fuzzy set qualitative comparative analysis (fsQCA) applied to the adaptation of the automobile industry to meet the emission standards of climate change policies via the deployment of electric vehicle," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    22. Parrado-Hernando, Gonzalo & Herc, Luka & Pfeifer, Antun & Capellán-Perez, Iñigo & Batas Bjelić, Ilija & Duić, Neven & Frechoso-Escudero, Fernando & Miguel González, Luis Javier & Gjorgievski, Vladimir, 2022. "Capturing features of hourly-resolution energy models through statistical annual indicators," Renewable Energy, Elsevier, vol. 197(C), pages 1192-1223.
    23. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2020. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," LEM Papers Series 2020/31, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    24. Filiou, Despoina & Kesidou, Effie & Wu, Lichao, 2023. "Are smart cities green? The role of environmental and digital policies for Eco-innovation in China," World Development, Elsevier, vol. 165(C).

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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