A territorial perspective of SME’s default prediction models
Studies in Economics and Finance
ISSN: 1086-7376
Article publication date: 17 October 2018
Issue publication date: 24 October 2018
Abstract
Purpose
The purpose of this paper is to test whether the qualitative variables regarding the territory and the firm–territory relationship can improve the accuracy rates of small business default prediction models.
Design/methodology/approach
The authors apply a logistic regression to a sample of 141 small Italian enterprises located in the Marche region, and the authors build two different default prediction models: one using only financial ratios and one using jointly financial ratios and variables related to the relationship between firm and territory.
Findings
Including variables regarding the relationships between firms and their territory, the accuracy rates of the default prediction model are significantly improved.
Research limitations/implications
The qualitative variables data collected are affected by subjective judgments of respondents of the firms studied. In addition, neither other qualitative variables (such as those regarding competitive strategies, or managerial skills) are included nor those variables regarding the relationships between firms and financial institutions are included.
Practical implications
The study suggests that financial institutions should include territory qualitative variables, and, above all, qualitative variables regarding the firm–territory relationship, when constructing business default prediction models. Including this type of variables, it could be able to reduce the tendency to place unnecessary restrictions on credit.
Originality/value
The field of business failure prediction modeling using variables regarding the relationship between firm–territory is a unexplored area as it count of a very few studies.
Keywords
Citation
Gabbianelli, L. (2018), "A territorial perspective of SME’s default prediction models", Studies in Economics and Finance, Vol. 35 No. 4, pp. 542-563. https://doi.org/10.1108/SEF-08-2016-0207
Publisher
:Emerald Publishing Limited
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