Support for the Task Force on Climate-Related Financial Disclosures (TCFD) and Impact on Non-Renewable Energy Sector Investments in United States Public Pension Funds
Notice bibliographique
Résumé
The recommendations of the Task Force on Climate-Related Financial Disclosures (TCFD) are \nexpected to play an important role in advancing the transition towards a climate target-aligned \neconomy. However, the impact of the TCFD framework on investment decisions in sectors \nvulnerable to climate-related risks, such as the non-renewable energy sector, has yet to be \nstudied. Applying the lens of institutional theory, this study investigates whether normative \npressures stemming from voluntary support for the TCFD influence non-renewable energy sector \ninvestment decisions by public pension funds in the United States. This study employs a \nquantitative approach to pursue three interconnected objectives. First, identify the public pension \nfunds in the United States that support the TCFD, and among those, identify their stage of \nimplementation of the TCFD’s recommendations. Second, assess whether fund size and location \nare influential in determining TCFD support or implementation stage. Third, examine whether \nthe exposure to non-renewable energy sector investments before and after the release of the \nTCFD recommendations in 2017 significantly differs depending on whether a fund supports the \nTCFD or not. The study’s findings reveal that 8 of 191 sampled public pension funds in the \nUnited States support the TCFD and are at various stages of implementation of the \nrecommendations. Fund size was identified as a significant predictor of both TCFD support and \nstage of implementation, with larger funds more likely to be supporters and more advanced in \nimplementation. California and New York were the only states with public pension funds that \nsupport the TCFD. Location, specifically whether a fund is in California or New York, emerged \nas a significant predictor of TCFD implementation stage, with funds in these two states being \nmore advanced in implementation. Lastly, no significant differences in exposure to non-renewable \nenergy sector investments before and after the TCFD recommendations were released \nbetween TCFD supporters and non-supporters were found. These findings contribute to the \nliterature on the implementation of the TCFD framework and its impacts on investment decision-making. \nThey also apply institutional theory in a new context and demonstrate that normative \npressures resulting from voluntary TCFD support have not redirected institutional investments \naway from the non-renewable energy sector, despite its significant climate-related risks. These \nfindings may be of interest to policymakers working towards a climate target-aligned economy \nand considering regulatory measures to influence institutional investment decisions. They also may be of interest to public and private pension funds seeking to understand market engagement \nwith the TCFD and its impact on investment decisions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,083 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».