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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2501.11988 |
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| _version_ | 1866914526648074240 |
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| author | Lavigne, Pierre Petit, Quentin Warin, Xavier |
| author_facet | Lavigne, Pierre Petit, Quentin Warin, Xavier |
| contents | This article introduces a novel mean-field game model for multi-sector economic growth in which a dynamically evolving externality, influenced by the collective actions of agents, plays a central role. Building on classical growth theories and integrating environmental considerations, the framework incorporates common noise to capture shared uncertainties among agents about the externality variable. We demonstrate the existence and uniqueness of a strong mean-field game equilibrium by reformulating the equilibrium conditions as a Forward-Backward Stochastic Differential Equation under the stochastic maximum principle and establishing a contraction argument to ensure a unique solution. We provide a numerical resolution for a specified model using a fixed-point approach combined with neural network approximations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_11988 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Growth model with externalities for energetic transition via MFG with common external variable Lavigne, Pierre Petit, Quentin Warin, Xavier Optimization and Control 91A16, 91-03, This article introduces a novel mean-field game model for multi-sector economic growth in which a dynamically evolving externality, influenced by the collective actions of agents, plays a central role. Building on classical growth theories and integrating environmental considerations, the framework incorporates common noise to capture shared uncertainties among agents about the externality variable. We demonstrate the existence and uniqueness of a strong mean-field game equilibrium by reformulating the equilibrium conditions as a Forward-Backward Stochastic Differential Equation under the stochastic maximum principle and establishing a contraction argument to ensure a unique solution. We provide a numerical resolution for a specified model using a fixed-point approach combined with neural network approximations. |
| title | Growth model with externalities for energetic transition via MFG with common external variable |
| topic | Optimization and Control 91A16, 91-03, |
| url | https://arxiv.org/abs/2501.11988 |