Using Prior Payment Behavior Variables for Small Enterprise Default Prediction Modelling


  •  Francesco Ciampi    

Abstract

This study aims to verify the potential of combining prior payment behavior variables and financial ratios for SE default prediction modelling. Logistic regression was applied to a sample of 980 Italian SEs in order to calculate and compare two categories of default prediction models, one exclusively based on financial ratios and the other based also on company payment behavior related variables. The main findings are: 1) using prior payment behavior variables significantly improves the effectiveness of SE default prediction modelling; ii) the longer the forecast horizon and/or the smaller the size of the firms which are the object of analysis, the higher  the improvements in prediction accuracy that can be obtained by using also prior payment behavior variables as default predictors; iii) SE default prediction modelling should be separately implemented for different size groups of firms.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1833-3850
  • ISSN(Online): 1833-8119
  • Started: 2006
  • Frequency: bimonthly

Journal Metrics

Google Scholar Citations

h-index: 174

i10-index: 1295

WoS Reviewer Recognition

Clarivate - Web of Science

IJBM partners with Web of Science to recognize our reviewers' contributions. You can forward your review thank-you email to reviews@webofscience.com to automatically log your certified credits on your Web of Science Researcher Profile.

Contact