ESGスコアを超えて：グリーンウォッシュ問題——格付不一致、測定の頑健性、持続可能金融における証拠の信頼性
Beyond ESG Scores: The Greenwashing Question — Rating Disagreement, Measurement Robustness and Evidence Reliability in Sustainable Finance (原題)
Stephen Kamran
🤖 gxceed AI 要約
日本語
中国上場377社・2019〜2024年の1,323社年観測を用い、ESG格付プロバイダー間の不一致とその時間的持続性を再現可能な形で分析した研究。平均絶対パーセンタイル順位不一致は0.2493、連続年Spearman相関は約0.493。不一致指標の選択が財務関連の探索的推定結果を左右することを示す。ただし不一致はグリーンウォッシュの立証ではないと明記している。
English
A reproducible compendium analyzing cross-provider ESG rating disagreement and its persistence across 1,323 firm-year observations from 377 Chinese listed firms (2019–2024). Mean absolute percentile-rank disagreement is 0.2493, with consecutive-year Spearman correlation around 0.493. It shows exploratory financial associations are sensitive to the choice of disagreement measure, while cautioning that disagreement alone does not establish greenwashing.
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
SSBJ基準・有報開示・統合報告書においてESG評価機関の格付を参照する日本企業・投資家にとって、格付不一致と測定手法の感応性を理解する実務的示唆がある。グリーンウォッシュ断定を避ける慎重な枠組みは国内のESG格付活用ガイドライン議論にも通じる。
In the global GX context
Speaks directly to global debates on ESG rating divergence, greenwashing detection, and the reliability of sustainability information under ISSB/CSRD disclosure regimes. Its emphasis on measurement robustness and reproducibility offers a methodological benchmark for disclosure-infrastructure scholarship.
👥 読者別の含意
🔬研究者:ESG格付不一致の測定手法選択が推定結果に与える影響を、再現可能な枠組みで検証する際の参照点となる。
🏢実務担当者:自社格付がプロバイダー間でばらつく理由と、開示情報の信頼性を説明する際の慎重な表現の根拠に使える。
🏛政策担当者:ESG格付の透明性・測定頑健性に関する規制議論で、不一致をグリーンウォッシュと混同しない枠組みの重要性を示す。
📄 Abstract（原文）
BEYOND-ESG: The Greenwashing Question is a reproducible research compendium examining cross-provider environmental, social, and governance (ESG) rating disagreement, temporal persistence, measurement robustness, and sustainability information reliability in Chinese listed companies. The underlying study comprises 1,323 firm-year observations from 377 Chinese listed companies during 2019–2024, drawn from secondary academic replication data. It reports a mean absolute percentile-rank disagreement of 0.2493 and a consecutive-year Spearman correlation of approximately 0.493 across 909 matched firm-year transitions. The research compares percentile-rank, absolute z-score, and absolute min-max disagreement measures, demonstrating the sensitivity of exploratory financial associations to alternative measurement choices. The analytical framework incorporates panel estimation, clustered statistical inference, and false discovery rate adjustments. Relationship to greenwashing: ESG rating disagreement can motivate scrutiny of corporate sustainability disclosures and information reliability, but disagreement alone does not establish greenwashing, corporate misconduct, or inaccurate provider ratings. This resource does not claim to identify or validate greenwashing events. The archive includes a reproducible Python notebook, aggregate statistical evidence, publication-quality figures, methodological documentation, computational verification materials, and source-provenance disclosures. This resource is a separately titled, manuscript-aligned research compendium building upon earlier ESG-DIVERGE computational work (DOI: 10.5281/zenodo.24144951). Original provider-level ESG ratings, historical rating timestamps, and redistribution permissions have not been independently verified. The package does not redistribute the underlying restricted firm-level ratings. Associated Kaggle notebook: https://www.kaggle.com/code/stephenkamran/beyond-esg-the-greenwashing-question-rating-dis Research purpose: To support transparent, measurement-aware, and evidence-based interpretation of ESG ratings in sustainable finance.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.24194194first seen 2026-11-15 05:29:48
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