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Enregistrement W7028232918

Essays in Corporate Finance, Shareholder Litigation, and Politics

2023· dissertation· en· W7028232918 sur OpenAlexfundno aff

Notice bibliographique

RevueSpectrum Research Repository (Concordia University) · 2023
Typedissertation
Langueen
DomaineMedicine
ThématiqueBiomedical and Chemical Research
Établissements canadiensnon disponible
Organismes subventionnairesConcordia UniversityUniversité du Québec à MontréalMcGill University
Mots-clésShareholderPoliticsCorporate governanceDismissalCampaign financeSupreme courtVotingIdeology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

When firms seek to curry the favor of politicians, it inevitably leads to political corruption. Political spending totaled US$14.4 Billion in the 2020 US election cycle—and this total does not include dark money donations. Firms naturally never donate to politicians without wanting a return on their investment, so clearly political corruption is a multi-billion-dollar problem in the United States. Recently, a strand of literature examines political corruption in the US from a corporate finance perspective. Another recent strand of finance literature concerns the effects of political ideology on the outcomes of US securities-related shareholder litigation. This thesis aims to first combine and expand upon these two emerging strands of literature by analyzing the relationships of a comprehensive variety of US political and judicial variables with the outcomes of securities fraud and related shareholder litigation. We then extend our framework to a refined exploration of corporate governance as it relates to shareholder litigation. 
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\nIn the first essay, we study the relationship between a number of political and judicial variables in the United States with the outcomes of litigation for firms that have been sued by their shareholders. Consistent with our hypothesis, we find that a crucial factor in shareholder litigation dismissal has been the passage of the Citizens United v. FEC Supreme Court campaign finance ruling of 2010. Furthermore, we find evidence that political campaign contributions afford firms the requisite connections that will benefit them in current or future lawsuits. Also, we quantify the impact of the size and timing of the political campaign contributions. In addition, we confirm hypotheses that the fate of shareholder class action litigation against these firms is also affected by the political ideologies of some of the trusted authorities who write, administer, and interpret the laws pertinent to firms facing such litigation. These authorities are federal politicians and judges, who are ideally independent arbiters—but the great powers they are given appear to create agency and bias issues, respectively.\t 
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\nIn the second essay, we use the knowledge and framework attained from our conclusions from the first essay to examine various corporate governance variables with respect to their role in shareholder litigation outcomes in this new light—variables which can be categorized as board, executive, and firm ownership characteristics. We confirm hypotheses generally based on the principle that variables reflecting better corporate governance will tend to be associated with a higher lawsuit dismissal likelihood. This likelihood tends to increase with a firm’s board of directors who are older, more independent, less busy, and have a larger network size. Furthermore, the likelihood of litigation dismissal increases with greater analyst coverage of the firm, with a firm’s CEO who is older than the board of directors, with greater institutional ownership, and with a larger number of blockholders owning stakes in the firm. As well as finding results consistent with such hypotheses for our corporate governance variables, we also find some novel, unexpected interactions between political variables and corporate governance variables.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,296
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,052
Tête enseignante GPT0,310
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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