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Towards agent-based integrated assessment models: examples, challenges, and future developments

Author

Listed:
  • Francesco Lamperti

    (Laboratory of Economics and Management (LEM) - SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa], SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa], Fondazione Eni Enrico Mattei (FEEM), Milan - affiliation inconnue)

  • 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)

  • Mauro Napoletano

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

  • Alessandro Sapio

    (DISAE - PARTHENOPE - Università degli Studi di Napoli “Parthenope” = University of Naples, SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa], Department of Business and Economics, Parthenope University of Naples)

  • Andrea Roventini

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, SSSUP - Scuola Universitaria Superiore Sant'Anna = Sant'Anna School of Advanced Studies [Pisa], OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

  • Tomas Balint

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

  • Igor Khorenzhenko

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

Abstract

Understanding the complex, dynamic, and non-linear relationships between human activities, the environment and the evolution of the climate is pivotal for policy design and requires appropriate tools. Despite the existence of different attempts to link the economy (or parts of it) to the evolution of the climate, results have often been disappointing and criticized. In this paper, we discuss the use of agent-based modeling for climate policy integrated assessment. First, we identify the main limitations of current mainstream models and stress how framing the problem from a complex system perspective might help, in particular when extreme climate conditions are at stake and general equilibrium effects are questionable. Second, we present two agent-based models that serve as prototypes for the analysis of coupled climate, energy, and macroeconomic dynamics. We argue that such models constitute examples of a promising approach for the integrated assessment of climate change and economic dynamics. They allow a bottom-up representation of climate damages and their cross-sectoral percolation, naturally embed distributional issues, and traditionally account for the role of finance in sustaining economic development and shaping the dynamics of energy transitions. All these issues are at the fore-front of the research in integrated assessment. Finally, we provide a careful discussion of testable policy exercises, modeling limitations, and open challenges for this stream of research. Notwithstanding great potential, there is a long way-to-go for agent-based models to catch-up with the richness of many existing integrated assessment models and overcome their major problems. This should encourage research in the area.

Suggested Citation

  • Francesco Lamperti & Antoine Mandel & Mauro Napoletano & Alessandro Sapio & Andrea Roventini & Tomas Balint & Igor Khorenzhenko, 2019. "Towards agent-based integrated assessment models: examples, challenges, and future developments," PSE-Ecole d'économie de Paris (Postprint) halshs-01905993, HAL.
  • Handle: RePEc:hal:pseptp:halshs-01905993
    DOI: 10.1007/s10113-018-1287-9
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    Citations

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    Cited by:

    1. Francesco Lamperti & Mariana Mazzucato & Andrea Roventini & Gregor Semieniuk, 2019. "The Green Transition: Public Policy, Finance, and the Role of the State," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 88(2), pages 73-88.
    2. 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).
    3. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    4. Tommaso Ciarli & Karolina Safarzynska, 2020. "Sustainability and Industrial Challenge: The Hindering Role of Complexity," SPRU Working Paper Series 2020-18, SPRU - Science Policy Research Unit, University of Sussex Business School.
    5. Zhang, Qi & Wu, Xifeng & Chen, Yu, 2022. "Is economic crisis an opportunity for realizing the low-carbon transition? A simulation study on the interaction between economic cycle and energy regulation policy," Energy Policy, Elsevier, vol. 168(C).
    6. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. 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.
    8. Naqvi, Asjad & Stockhammer, Engelbert, 2018. "Directed Technological Change in a Post-Keynesian Ecological Macromodel," Ecological Economics, Elsevier, vol. 154(C), pages 168-188.
    9. 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).
    10. 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).
    11. Rising, James A. & Taylor, Charlotte & Ives, Matthew C. & Ward, Robert E.t., 2022. "Challenges and innovations in the economic evaluation of the risks of climate change," LSE Research Online Documents on Economics 114941, London School of Economics and Political Science, LSE Library.
    12. Severin Reissl & Luca E. Fierro & Francesco Lamperti & Andrea Roventini, 2024. "The DSK-SFC stock-flow consistent agent-based integrated assessment model," LEM Papers Series 2024/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    13. Moya, Diego & Budinis, Sara & Giarola, Sara & Hawkes, Adam, 2020. "Agent-based scenarios comparison for assessing fuel-switching investment in long-term energy transitions of the India’s industry sector," Applied Energy, Elsevier, vol. 274(C).
    14. Rising, James A. & Taylor, Charlotte & Ives, Matthew C. & Ward, Robert E.T., 2022. "Challenges and innovations in the economic evaluation of the risks of climate change," Ecological Economics, Elsevier, vol. 197(C).
    15. Mellacher, Patrick, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," MPRA Paper 103661, University Library of Munich, Germany.

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