Evaluating policy mix strategies for the energy transition using an agent-based macroeconomic model

被引:1
|
作者
Nieddu, Marcello [1 ]
Raberto, Marco [1 ]
Ponta, Linda [1 ]
Teglio, Andrea [2 ]
Cincotti, Silvano [1 ]
机构
[1] Univ Genoa, DIME DOGE, via Opera Pia 15, I-16145 Genoa, Italy
[2] Univ CaFoscari Venice, Dept Econ, Cannaregio 873, I-30121 Venice, Italy
关键词
Energy transition; Climate and the economy; Carbon tax; Feed-in tariff; Policy mix; Agent-based modelling and simulation; CLIMATE-CHANGE; COMPLEXITY; INNOVATION; IMPACTS; TAX;
D O I
10.1016/j.enpol.2024.114276
中图分类号
F [经济];
学科分类号
02 ;
摘要
Climate policy analysis has traditionally focused on evaluating individual policy instruments or comparing different instruments, but an increasing number of scholars are emphasizing the advantages of employing a policy mix. In this study, we investigate the combination of a carbon tax and a feed-in tariff policy using the Eurace agent-based model, addressing two primary issues: understanding the interactions between individual instruments within the policy mix and identifying the optimal combination to facilitate the energy transition. To evaluate the effects of each policy, we first examine policies in isolation and then analyse their combined impact. The results indicate that the feed-in tariff policy generally outperforms the carbon tax when considering both climate and economic indicators. Furthermore, when physical climate feedback is not included in the model, the combined policy approach outperforms the individual policies. However, for higher values of the carbon tax and feed-in tariff, the benefits of the policy mix decrease, and this reduction becomes more pronounced when physical climate feedback is considered.
引用
收藏
页数:27
相关论文
共 50 条
  • [21] Policy Comparisons and Causality in an Agent-Based Model
    Furtado, Bernardo Alves
    Nadalin, Vanessa
    ADVANCES IN SOCIAL SIMULATION, ESSA 2023, 2024, : 95 - 106
  • [22] Using realistic trading strategies in an agent-based stock market model
    Llacay, Barbara
    Peffer, Gilbert
    COMPUTATIONAL AND MATHEMATICAL ORGANIZATION THEORY, 2018, 24 (03) : 308 - 350
  • [23] Using realistic trading strategies in an agent-based stock market model
    Bàrbara Llacay
    Gilbert Peffer
    Computational and Mathematical Organization Theory, 2018, 24 : 308 - 350
  • [24] Extending and Evaluating Agent-based Models of Algorithmic Trading Strategies
    Ponomareva, Natalia
    Calinescu, Anisoara
    2012 17TH INTERNATIONAL CONFERENCE ON ENGINEERING OF COMPLEX COMPUTER SYSTEMS (ICECCS), 2012, : 351 - 360
  • [25] The sustainability transition and the digital transformation: two challenges for agent-based macroeconomic models
    Nieddu M.
    Bertani F.
    Ponta L.
    Review of Evolutionary Political Economy, 2022, 3 (1): : 193 - 226
  • [26] Using Agent-based VM Placement Policy
    Al-Ou'n, Ashraf
    Kiran, Mariam
    Kouvatsos, Demetres D.
    2015 3RD INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD (FICLOUD) AND INTERNATIONAL CONFERENCE ON OPEN AND BIG (OBD), 2015, : 272 - 281
  • [27] Credit Money and Macroeconomic Instability in the Agent-based Model and Simulator Eurace
    Cincotti, Silvano
    Raberto, Marco
    Teglio, Andrea
    ECONOMICS-THE OPEN ACCESS OPEN-ASSESSMENT E-JOURNAL, 2010, 4
  • [28] A basic macroeconomic agent-based model for analyzing monetary regime shifts
    Peters, Florian
    Neuberger, Doris
    Reinhardt, Oliver
    Uhrmacher, Adelinde
    PLOS ONE, 2022, 17 (12):
  • [29] Micro-Foundations of Macroeconomic Dynamics: The Agent-Based BAM Model
    Platas-Lopez, Alejandro
    Guerra-Hernandez, Alejandro
    Cecconi, Federico
    Paolucci, Mario
    Grimaldo, Francisco
    ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT, 2019, 319 : 319 - 328
  • [30] The effects of interbank networks on efficiency and stability in a macroeconomic agent-based model
    Gurgone, Andrea
    Iori, Giulia
    Jafarey, Saqib
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2018, 91 : 257 - 288