The determinants of loan loss and allowances for MENA banks
Notice bibliographique
Résumé
Purpose – This study aims to examine the determinants of the allowance for loan losses (ALL) and loan loss provisions (LLP) for banks in the Middle East and North African (MENA) region using both a two-stage approach and simultaneous equation system to address the potential problem of estimation bias introduced by estimating the ALL and LLP separately. The paper also tests three competing hypotheses: the earnings management hypothesis, the capital management hypothesis, and the signaling hypothesis. Design/methodology/approach – The authors adopt a simultaneous equation and three-stage approaches to test whether MENA banks jointly determine LLP and ALL and the determinants of the two accounts. The sample consists of all available electronic data for 75 banks (451 bank-year observations) in nine MENA countries over the period 2000-2008. Findings – Evidence suggests that the two accounts are jointly determined. The results support the earnings management hypothesis – meaning that MENA banks have engaged in year-to-year income smoothing. The authors also find that LLP and ALL provide signals about future earnings. Research limitations/implications – The authors acknowledge that the LLP account is only one of many accounts on the income statement that could be used for signaling or to manage earnings, and that the ALL is one of several accounts that could be used for signaling, earnings or capital management. Future studies could examine other accruals for their role in managing earnings, signaling and capital. Practical implications – The results indicate that bank managers use LLP and ALL accounts to manage earnings management, policy makers may want to limit the ability of banks to manipulate earnings. Originality/value – Prior research on the loan loss accounting practices has been based on single equation models of the determinants of LLP and ALL. An issue that has not been adequately addressed in this literature is that ALL and LLP may be interrelated and jointly determined by banks. If the two accounts are not independent of each other, failure to include one when estimating the other may lead to an omitted variable problem, while including both in the same equation induces a potential simultaneity bias. The study is the first empirical work examining whether ALL and LLP are jointly determined by banks. By jointly estimating LLP and ALL, the study permits an assessment of the magnitude of the potential error from adopting ordinary least squares estimation of a single equation model.
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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».