IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2602.15607.html

Agent-based macroeconomics for the UK's Seventh Carbon Budget

Author

Listed:
  • Tom Youngman
  • Tim Lennox
  • M. Lopes Alves
  • Pirta Palola
  • Brendon Tankwa
  • Emma Bailey
  • Emilien Ravigne
  • Thijs Ter Horst
  • Benjamin Wagenvoort
  • Harry Lightfoot Brown
  • Jose Moran
  • Doyne Farmer

Abstract

In June 2026, the UK government will set its carbon budget for the period 2038 to 2042, the seventh such carbon budget (CB7) since the Climate Change Act became law in 2008. For the first time, this carbon budget will be accompanied by a macroeconomic assessment of its impact on growth, employment, inflation and inequality. Researchers from the Institute of New Economic Thinking (INET) Oxford are working in partnership with the Department for Energy Security and Net Zero to deliver this assessment using our data-driven macroeconomic agent-based model (ABM). This extended abstract presents the work in progress towards this pioneering policymaking using our data-driven macroeconomic ABM. We are conducting our work in three work packages. By the time of the workshop, we hope to be able to present preliminary findings from the first two work packages. In WP1, we adapt an existing macro-ABM prototype and build a UK macroeconomic baseline. The main task for this is initialising the model with suitable UK household microdata. We present the options considered and the approach settled upon. In WP2, we conduct preliminary modelling that represents UK decarbonisation as an external shock to financial flows and technical coefficients. In order to present results in time to influence the June 2026 policy decision, this second work package exogenously forces the ABM to follow the CB7 green investment and associated technological change projections provided by the Climate Change Committee. Finally, we will implement more sophisticated social and technological learning packages in WP3, building our own projections of likely decarbonisation pathways that may diverge from UK government plans. For the workshop, we will present the progress of WP1 and WP2.

Suggested Citation

  • Tom Youngman & Tim Lennox & M. Lopes Alves & Pirta Palola & Brendon Tankwa & Emma Bailey & Emilien Ravigne & Thijs Ter Horst & Benjamin Wagenvoort & Harry Lightfoot Brown & Jose Moran & Doyne Farmer, 2026. "Agent-based macroeconomics for the UK's Seventh Carbon Budget," Papers 2602.15607, arXiv.org, revised Mar 2026.
  • Handle: RePEc:arx:papers:2602.15607
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2602.15607
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Baumgärtner, Lennart & Farmer, J. Doyne, 2025. "Will national renewable costs continue declining?," INET Oxford Working Papers 2025-12, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    2. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    3. Samuel Wiese & Jagoda Kaszowska-Mojsa & Joel Dyer & Jose Moran & Marco Pangallo & Francois Lafond & John Muellbauer & Anisoara Calinescu & J. Doyne Farmer, 2024. "Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model," Papers 2409.18760, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aldo Glielmo & Mitja Devetak & Adriano Meligrana & Sebastian Poledna, 2025. "BeforeIT.jl: High-Performance Agent-Based Macroeconomics Made Easy," Papers 2502.13267, arXiv.org.
    2. Samuel Wiese & Jagoda Kaszowska-Mojsa & Joel Dyer & Jose Moran & Marco Pangallo & Francois Lafond & John Muellbauer & Anisoara Calinescu & J. Doyne Farmer, 2024. "Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model," Papers 2409.18760, arXiv.org.
    3. Massimiliano Carlo Pietro Rizzati & Emanuele Ciola & Enrico Turco & Davide Bazzana & Sergio Vergalli, 2025. "Beyond Green Preferences: Demand-side and Supply-side Drivers in the Low-Carbon Transition," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 88(5), pages 1239-1295, May.
    4. Hosszú, Zsuzsanna & Borsos, András & Mérő, Bence & Vágó, Nikolett, 2025. "The optimal choice of scaling in economic agent-based models," Journal of Economic Behavior & Organization, Elsevier, vol. 232(C).
    5. Richiardi, Matteo & van de Ven, Justin, 2023. "Back to the future: agent-based modelling and dynamic microsimulation," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA8/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    6. Aldo Glielmo & Marco Favorito & Debmallya Chanda & Domenico Delli Gatti, 2023. "Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs," Papers 2302.11835, arXiv.org, revised Dec 2023.
    7. Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series wps115, Bank of Russia.
    8. Oswald, Yannick & Suchak, Keiran & Malleson, Nick, 2025. "Agent-based models of the United States wealth distribution with Ensemble Kalman Filter," Journal of Economic Behavior & Organization, Elsevier, vol. 229(C).
    9. Christian Kimmich & Klaus Weyerstraß & Thomas Czypionka & Norman FRM Fauster & Maurice Kinner & Elisabeth Laa & Liliana Mateeva & Kerstin Plank & Leonhard Ulrici & Hannes Zenz & Michael Miess & Sebast, 2025. "Economic impact of labor productivity losses induced by heat stress: an agent-based macroeconomic approach," Climatic Change, Springer, vol. 178(3), pages 1-21, March.
    10. Cameron Hepburn & Matthew C Ives & Sam Loni & Penny Mealy & Pete Barbrook-Johnson & J Doyne Farmer & Nicholas Stern & Joseph Stiglitz, 2025. "Economic models and frameworks to guide climate policy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 41(2), pages 616-652.
    11. Tankwa, Brendon & Barbrook-Johnson, Pete, 2025. "Who rides the renewable cost curve? Country evidence on prices, learning, and policy," INET Oxford Working Papers 2025-17, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    12. Martin Jaraiz, 2026. "Macroeconomic Forecasting from Input-Output Tables Alone: A Darwinian Agent-Based Approach with FIGARO Data," Papers 2603.12412, arXiv.org, revised Mar 2026.
    13. Ciola, Emanuele & Turco, Enrico Maria & Rizzati, Massimiliano Carlo Pietro & Bazzana, Davide & Vergalli, Sergio, 2025. "Taking the green pill: Macroeconomic and financial risks of the energy transition in the MATRIX model," Journal of Economic Behavior & Organization, Elsevier, vol. 239(C).
    14. Ciambezi, Leonardo & Guerini, Mattia & Napoletano, Mauro & Roventini, Andrea, 2025. "Accounting for the multiple sources of inflation: An agent-based model investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 178(C).
    15. Lux, Thomas, 2024. "Lack of identification of parameters in a simple behavioral macroeconomic model," Economics Working Papers 2024-02, Christian-Albrechts-University of Kiel, Department of Economics.
    16. Kirman, Alan & Armstrong, Angus & Hynes, William, 2026. "Forecasting and policy when “we simply do not know”," International Journal of Forecasting, Elsevier, vol. 42(1), pages 34-39.
    17. Berryman, Anna & Bücker, Joris & de Moura, Fernanda Senra & Barbrook-Johnson, Peter & Hanusch, Marek & Mealy, Penny & Farmer, J. Doyne & del Rio-Chanona, R. Maria, 2025. "Skill and spatial mismatches for sustainable development in Brazil," INET Oxford Working Papers 2025-08, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    18. Jean-Philippe Bouchaud, 2024. "Navigating through Economic Complexity: Phase Diagrams & Parameter Sloppiness," Papers 2412.11259, arXiv.org.
    19. Marcin Rzeszutek & Jørgen Vitting Andersen & Adam Szyszka & Szymon Talaga, 2024. "Subjective Well-Being of Chief Executive Officers and Its Impact on Stock Market Volatility During the COVID-19 Pandemic in Poland: Agent-Based Model Perspective," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04723512, HAL.
    20. Marcello Nieddu & Marco Raberto & Andrea Teglio, 2025. "The importance of being many: dynamics, interaction and aggregation in a multi-sector economy," Working Papers 2025: 04, Department of Economics, University of Venice "Ca' Foscari".

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2602.15607. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.