The aim of this paper is to evaluate the contribution of several aspects of the (hard) bank-firm relationship in anticipating the corporate default event in a model including firms’ specific balance sheets characteristics. Using a unique dataset on a sample of 113 co-operative credit banks and about 12,000 firms operating in Italy between 2012 and 2014, this paper documents that private-hard information, coming from checking accounts activities and long-term loan performances, provides an additional explanatory power to public-hard information, gathered from balance sheets, in predicting the likelihood of default. Estimating a pooled probit model, it finds that usage of credit lines and credit lines limits violations on checking accounts, as well as credit lines limit violations and payments overdue on long-term loans, increase the accuracy prediction of default events by about ten percent one year before and by six percent two years before.

Estimating the additional predictive power of bank-firm hard information in default models. An analysis on a sample of Italian firms

Michele Modina;Filomena Pietrovito
2017-01-01

Abstract

The aim of this paper is to evaluate the contribution of several aspects of the (hard) bank-firm relationship in anticipating the corporate default event in a model including firms’ specific balance sheets characteristics. Using a unique dataset on a sample of 113 co-operative credit banks and about 12,000 firms operating in Italy between 2012 and 2014, this paper documents that private-hard information, coming from checking accounts activities and long-term loan performances, provides an additional explanatory power to public-hard information, gathered from balance sheets, in predicting the likelihood of default. Estimating a pooled probit model, it finds that usage of credit lines and credit lines limits violations on checking accounts, as well as credit lines limit violations and payments overdue on long-term loans, increase the accuracy prediction of default events by about ten percent one year before and by six percent two years before.
2017
978-88-942687-0-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/89159
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