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A territorial perspective of SME’s default prediction models

A territorial perspective of SME’s default prediction models 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/approachThe 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.FindingsIncluding variables regarding the relationships between firms and their territory, the accuracy rates of the default prediction model are significantly improved.Research limitations/implicationsThe 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 implicationsThe 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/valueThe 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Economics and Finance Emerald Publishing

A territorial perspective of SME’s default prediction models

Studies in Economics and Finance , Volume 35 (4): 22 – Oct 24, 2018

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1086-7376
DOI
10.1108/sef-08-2016-0207
Publisher site
See Article on Publisher Site

Abstract

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/approachThe 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.FindingsIncluding variables regarding the relationships between firms and their territory, the accuracy rates of the default prediction model are significantly improved.Research limitations/implicationsThe 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 implicationsThe 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/valueThe 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.

Journal

Studies in Economics and FinanceEmerald Publishing

Published: Oct 24, 2018

Keywords: SMEs; Logistic regression; Default prediction modelling; Firm-territory relationships

References