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

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  • Lamperti, F.
  • Dosi, G.
  • Napoletano, M.
  • Roventini, A.
  • Sapio, A.

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.

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  • Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2020. "Climate change and green transitions in an agent-based integrated assessment model," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
  • Handle: RePEc:eee:tefoso:v:153:y:2020:i:c:s0040162518312460
    DOI: 10.1016/j.techfore.2019.119806
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    2. 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.
    3. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    4. Giovanni Dosi & Francesco Lamperti & Mariana Mazzucato & Mauro Napoletano & Andrea Roventini, 2021. "Mission-Oriented Policies and the “Entrepreneurial State” at Work: An Agent-Based Exploration," Sciences Po publications 14/2021, Sciences Po.
    5. 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).
    6. Ye, Liping, 2022. "The effect of climate news risk on uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    7. Franzke, Christian L.E., 2021. "Towards the development of economic damage functions for weather and climate extremes," Ecological Economics, Elsevier, vol. 189(C).
    8. 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.
    9. Nieddu, Marcello & Bertani, Filippo & Ponta, Linda, 2021. "Sustainability transition and digital trasformation: an agent-based perspective," MPRA Paper 106943, University Library of Munich, Germany.
    10. 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).
    11. 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.
    12. 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.
    13. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org.

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    More about this item

    Keywords

    Climate change; Agent based models; Transitions; Energy policy; Growth;
    All these keywords.

    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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