The paper aims to jointly combine three diferent categories of variables (fnancial ratios, corporate governance data and bank-frm information) to predict SMEs’ default. To this end, a merged longitudinal predictive model was applied to a sample of 973 Italian SMEs that are clients of 36 diferent co-operative banks. The collected data (for a total of 23 variables included in the model) relate to the years 2012–2014. The main fndings reveal the high predictive power of leverage ratio, CEO tenure and ownership concentration, and the number of loans overdue for more than 180 days in the previous 12 months.
Financial ratios, corporate governance and bank-firm information: A Bayesian approach to predict SMEs’ default
Rosalia Santulli;
2022-01-01
Abstract
The paper aims to jointly combine three diferent categories of variables (fnancial ratios, corporate governance data and bank-frm information) to predict SMEs’ default. To this end, a merged longitudinal predictive model was applied to a sample of 973 Italian SMEs that are clients of 36 diferent co-operative banks. The collected data (for a total of 23 variables included in the model) relate to the years 2012–2014. The main fndings reveal the high predictive power of leverage ratio, CEO tenure and ownership concentration, and the number of loans overdue for more than 180 days in the previous 12 months.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
Gallucci2022_Article_FinancialRatiosCorporateGovern.pdf
accesso aperto
Tipologia:
Documento in versione editoriale
Dimensione
709.9 kB
Formato
Adobe PDF
|
709.9 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.