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.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1072326
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 4
social impact