The consequences and management of ambiguity for long-term investors
Notice bibliographique
Résumé
This thesis responds to the question 'how can sovereign wealth funds manage ambiguity in their decision-making so as to implement substantive long-term investment programmes?' The rapid growth of sovereign wealth funds (SWFs) over the past decade, due largely to booming commodity prices, has inspired optimism among many for their potential to contribute to the sustainability goals of society. SWFs are unconstrained by many of the factors that have kept pension funds from realising their potential as long-term investors and so they are well placed to make significant investments in sustainable projects with positive externalities such as infrastructure and to act as effective monitors of corporate behaviour. But many obstacles stand in the way. At the institutional level, transparency has replaced tight financial market regulation, resulting in entrenched short-termism. At the organisational level, many problems facing long-term investors are too complex to fit into traditional models of decision-making. Decentralisation is necessary to respond to this complexity but it conflicts with the coordination necessary to achieve economies of scale and scope. There may not even be an ideal outcome to coerce or incentivise agents to achieve. Taken together, these problems are understood in this thesis as ambiguity, which results from differences in interpretation and irreconcilable conflict. In contrast, most governance frameworks focus on problems of uncertainty and risk, due to missing information. This thesis has three aims. The first is to reframe the governance challenge for longterm investing in terms of managing ambiguity. Second, this thesis aims to reconcile ambiguity with legitimacy that depends on expert decision-making and provides one right answer to a clearly specified problem. Third, it provides specific examples of how ambiguity, if managed, can improve decision-making. That is, ambiguity forces us to engage with subjective reality but also provides us with a framework to do so. Ambiguity can act as a built-in adaptation mechanism to hold a coalition of diverse interests together in a rapidly changing environment, to identify synergies where others see only trade-offs and to overcome collective action problems. These constructive properties of ambiguity are explored in the four substantive chapters of this thesis, alongside specific recommendations for changes to SWF governance structures to transcend barriers to long-term investing. The first half of the thesis focuses on the earlier stages of the investment process and draws on specific examples of two SWFs. Chapter III investigates ambiguity in the Alberta Heritage Fund's inter-generational equity mandate. If managed in the form of self-reflexivity, ambiguity can contribute to overcoming the time inconsistency problem in the context of sub-national resource wealth funds. Chapter IV focuses on the irreconcilable conflict in the Norwegian Fund's ethical investment policy. It argues that agents use their discretion to interpret the policy and, in doing so, are able to align it more closely to the Fund's long-term investing mandate. The second half of the thesis extends consideration to long-term investors more broadly. Chapter V explores the delegation of shareholder engagement to portfolio managers to leverage synergies in an investment management firm. It finds that introducing ambiguity into incentive design can overcome the multi-task incentive problem. Chapter VI brings concepts explored in earlier chapters to bear on its analysis of a new market for public infrastructure assets. It argues that ambiguity provides the space necessary to bring diverse actors together to transcend collective action problems and create new institutional arrangements to support a more efficient market structure. Taken as a whole, this thesis is optimistic that, as those claiming to have the one right answer are increasingly proven wrong, ambiguity will earn its rightful place in the study and practice of finance.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| 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 | 0,002 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».