Notice bibliographique
Résumé
capital structure has been done in the US context and finds puzzlingevidence that the US MNCs have lower leverage ratio compared to their domestic peers (see for example, Fatemi (1988), Burgman (1996), Chen, Cheng, He and Kim (i997) and Doukas and Pantzalis ( 2003)).Several explanations, such as higher agency costs of debt, higher business and political risk of MNCs, have been offered for the US evidence but there is no consensus on which factors drive this puzzlingevidence.I compare the capital structure difference between Canadian MNCs and DCs, and also compare the Canadian sample with a US matched sample for the period of 1998-2002.I contribute to the MNCs capital structure literature in three ways.First, contrary to the US evidence, I find that Canadian MNCs display higher leverage than DCs.Second, the higher leverage of Canadian MNCs is associated largely with their US operations, and is explained by their larger firm size and better access to the US capital market.I also show that the negative impact of agency costs of debt and business risk on leverage is more pronounced for Canadian MNCs' non-IJS operations compared to their US operations, and the agency costs of debt is the dominant factor.Third, to minimize the sample variation between Canada and the US, I construct a US sample that is matched with the Canadian sample based on year, industry and firm size.I show that the sensitivity of leverage to the firm-specific factors also differs between the two country samples.Overall, Chapter 2 shows that the capital structure of MNCs is influenced by a complex interaction of home and host country factors as well as the differences in the leverage determinants across countries.It also suggests that future research on MNCs' capital structure should differentiate between MNCs' regional and global expansions.Chapter 3 examines the impact of bond market access on Canadian firms' capital structure during the period of 1990-2003.Access to the public bond market could be very important for firms' capital structure decisions as it can change the maturity as well as the costs of debt.The traditional capital structure literature, however, largely focuses on the capital demand-side effects (e.g. firms with larger size, lower growth opportunity and lower business risk could have higher debt ratios), implicitly assuming that supply-side effects do not matter.In a recent study, Faulkender and Petersen (2006) examine whether the source of capital affects frrms' capital structure and show that the US firms with bond market access, as measured by having a credit rating, have signif,rcantly higher leverage ratios than firms without access.I show two main f,rndings in Chapter 3. First, I test the impact of supply-side effects on leverage by comparing the leverage difference between Canadian firms with and without bond market access, after controlling for demand-side effects.My evidence REFERBNCES
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 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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,008 | 0,004 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».