In financial literature there are many contributions aim to measure default risk of credit borrowers. This work explores the application of a survival model to reach this purpose. The data were provided by a broker and it refers to Small and Medium Enterprises (SMEs) of the South Italy. In particular, we analysed the companies’ credit lines, in order to assess death rate of the credit intended as insolvency risk of the enterprises. The sample collects information about 5.322 credit lines, referred to the 2011. The paper attempts to direct an exploratory investigation about risk factors for default prediction, using financial and some non-financial information that are available from public sources. Among non standard risk factors that can prevent a lending decision, we focused the attention on quality-of-life indicators of the municipalities where the monitored Small and Medium Enterprises are located. Such indicators have been built considered several different sides of the local territory, that vary from geographical to socio-economic environment. They are used as explanatory variables in a set of survival models in order to verify the existence of significant correlation between location of the company and the default probability. We expect to show interesting evidences for the defaulted companies, although the efficiency of the environment has different impact to the companies’ performances that can be very variable.
Liberati, C., Marletta, A. (2019). Quality of life indicators for Italian municipalities: are they risk factors for default probabilities?. Intervento presentato a: Nesputt 2019, Milano, Italy.
Quality of life indicators for Italian municipalities: are they risk factors for default probabilities?
Liberati, C;Marletta, A
2019
Abstract
In financial literature there are many contributions aim to measure default risk of credit borrowers. This work explores the application of a survival model to reach this purpose. The data were provided by a broker and it refers to Small and Medium Enterprises (SMEs) of the South Italy. In particular, we analysed the companies’ credit lines, in order to assess death rate of the credit intended as insolvency risk of the enterprises. The sample collects information about 5.322 credit lines, referred to the 2011. The paper attempts to direct an exploratory investigation about risk factors for default prediction, using financial and some non-financial information that are available from public sources. Among non standard risk factors that can prevent a lending decision, we focused the attention on quality-of-life indicators of the municipalities where the monitored Small and Medium Enterprises are located. Such indicators have been built considered several different sides of the local territory, that vary from geographical to socio-economic environment. They are used as explanatory variables in a set of survival models in order to verify the existence of significant correlation between location of the company and the default probability. We expect to show interesting evidences for the defaulted companies, although the efficiency of the environment has different impact to the companies’ performances that can be very variable.File | Dimensione | Formato | |
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