カーボンニュートラル目標と最適政策：多基準分析
Carbon neutrality targets and optimal policy: a multicriteria analysis (原題)
Simone Marsiglio, Fabio Privileggi
🤖 gxceed AI 要約
日本語
本研究は、公共政策と個人行動の相互作用を動的モデルで分析し、カーボンニュートラル目標達成のための最適な補助金構造を探る。完全な中立は最適ではなく、短期的コストと長期的持続可能性のバランスを取る制御された逸脱が社会的コストを最小化する。スカラー化とe制約法が同等の効率的フロンティアを生むことを示し、政策設計への方法論的貢献を提供する。
English
This study analyzes the interaction between public policy and individual behavior using a dynamic model to identify optimal subsidy structures for achieving carbon neutrality. It finds that complete neutrality is not optimal; a controlled deviation minimizes social cost. Scalarization and e-constraint methods yield equivalent efficient frontiers, offering methodological insights for policy design.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のGX政策（例：GX推進法、カーボンプライシング）において、補助金設計や社会受容性を考慮する際に、本モデルの多基準最適化アプローチが参考になる。特に、完全な脱炭素目標の非最適性は、現実的な政策目標設定に示唆を与える。
In the global GX context
This paper contributes to global climate policy scholarship by integrating behavioral dynamics into optimal policy design. Its finding that full carbon neutrality may not be socially optimal challenges rigid targets and supports flexible, cost-effective approaches, relevant for NDC updates and transition finance frameworks.
👥 読者別の含意
🔬研究者:Provides a novel methodological framework combining discrete choice and multicriteria optimization for climate policy analysis.
🏢実務担当者:Offers insights into designing subsidy schemes that account for social behavior, useful for corporate advocacy and policy engagement.
🏛政策担当者:Highlights the trade-offs in carbon neutrality targets and suggests that controlled deviations may be more efficient, informing policy design.
📄 Abstract（原文）
Purpose This study explores how public policy and individual behavior interact to achieve carbon neutrality targets, aiming to identify the optimal incentive structure that balances short-term mitigation costs and long-term sustainability goals. Design/methodology/approach A dynamic model integrates discrete choice and social interaction frameworks, where agents decide whether to act green and policymakers design subsidies accordingly. The multicriteria optimization problem is solved using both scalarization and e-constraint methods to compare their outcomes. Findings The optimal subsidy depends on social and individual factors such as conformism, time preference and sustainability concern. Complete carbon neutrality is not optimal; a controlled deviation minimizes overall social cost. The scalarization and e-constraint methods yield equivalent, convex efficient frontiers between short- and long-term objectives. Originality/value This paper is the first to couple optimal dynamic policymaking with a discrete choice model of green transition using the e-constraint method. It offers methodological and policy insights for designing realistic, efficiency-oriented climate strategies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/md-10-2025-3230first seen 2026-09-09 04:55:08
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