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安価な約束:企業の気候コミットメントはなぜ失敗するのか、グリーンボンドは役立つのか

Cheap Promises : Why Corporate Climate Commitments Fail, and Whether Green Bonds Can Help (原題)

Zi-Teng Zhang

Economics and Public Policy📚 査読済 / ジャーナル2026-10-22#SBT/SBTi経営インパクト: 資金調達対象セクター: cross_sector
DOI: 10.63313/epp.9056
原典: https://doi.org/10.63313/epp.9056
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🤖 gxceed AI 要約

日本語

企業の気候コミットメントが撤回されるメカニズムを不完備情報モデルで分析。均衡撤回率が検証基準の厳格さcと評判・財務的ペナルティR+Pの比c/(R+P)で決まることを示す。SBTiの15,304社(解決済み6,613社)のデータで検証し、上場企業は非上場企業より撤回確率が13.7ポイント低いことを発見。失敗時のコストが高いほどコミットの信頼性が高まるという予測と整合する。

English

An incomplete-information model explains why firms withdraw from climate commitments: the equilibrium removal rate equals c/(R+P), where c is verification strictness and R, P are reputational and financial penalties. Using SBTi data on 15,304 firms (6,613 resolved), listed firms are 13.7 pp less likely to have commitments removed than unlisted firms, against a 21.1% overall removal rate. Stronger consequences for failure raise commitment credibility.

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

SBTiの目標検証と撤回メカニズムを理論・実証両面から分析した研究で、SSBJや有報での目標開示、投資家の信頼性評価、トランジション・ファイナンス設計に直結する。日本企業のSBT認定取得・維持の戦略を考える上で示唆が大きい。

In the global GX context

Directly informs the credibility debate around SBTi validation and net-zero pledges central to TCFD/ISSB disclosure and transition finance. It offers a formal framework linking verification strictness and penalties to pledge integrity, relevant to regulators and standard-setters scrutinizing greenwashing.

👥 読者別の含意

🔬研究者:SBTiデータを用いたコミットメント撤回の実証と理論モデルを組み合わせた分析枠組みを提供する。

🏢実務担当者:SBTi目標の設定・維持における検証厳格さと失敗コストのバランスを経営判断に活かせる。

🏛政策担当者:検証基準と失敗ペナルティの設計が企業コミットの信頼性に与える影響を政策設計に反映できる。

📄 Abstract(原文)

Firms frequently announce public commitments to reduce carbon emissions but often fail to follow through on them. This paper studies why these commitments break down and whether financial instruments can make them more credible. I develop an incomplete-information model in which firms differ in their ability to reduce emissions and complete third-party verification. Because firms can withdraw from a commitment by accepting a reputational or financial penalty, even firms with low abatement ability may choose to commit initially when the cost of failure is limited. The model shows that the equilibrium removal rate equals c/(R+P), where c represents the strictness of the verification standard, while R and P represent the reputational and financial penalties associated with withdrawal. This implies that stricter verification requirements raise the removal rate, while stronger penalties for failure lower it. I test this prediction using data from the Science Based Targets initiative (SBTi), which covers 15,304 firms, focusing on the 6,613 firms whose commitment status has been resolved. Using a linear probability model, I find that publicly listed firms are 13.7 percentage points less likely than unlisted firms to have their commitments removed. This difference is substantial relative to the overall removal rate of 21.1 percent. Although this estimate should not be interpreted as causal, it is consistent with the model’s prediction that stronger consequences for failure increase the credibility of corporate climate commitments.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。