“Birds of a Feather” Fail Together: Exploring the Nature of Dependency in SME Defaults

Abstract

This article studies the effects of incorporating the interdependence among London small business defaults into a risk analysis framework using the data just before the financial crisis. We propose an extension from standard scoring models to take into account the spatial dimensions and the demographic characteristics of small and medium-sized enterprises (SMEs), such as legal form, industry sector, and number of employees. We estimate spatial probit models using different distance matrices based only on the spatial location or on an interaction between spatial locations and demographic characteristics. We find that the interdependence or contagion component defined on spatial and demographic characteristics is significant and that it improves the ability to predict defaults of non-start-ups in London. Furthermore, including contagion effects among SMEs alters the parameter estimates of risk determinants. The approach can be extended to other risk analysis applications where spatial risk may incorporate correlation based on other aspects.

The impact of geographical positioning on agri‐food businesses' failure considering nonlinearities

“…Logistic estimations are widely utilized in business‐failure literature (Calabresse et al, 2017). These models are based on variations of the formula below: where E( Y ) is the expected value of the variable Y , and is the linear combination of different explanatory variables , with unknown coefficients and f represents the functional form relating both sides of the Equation ().…”

The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics

“…However, both these numbers have been set in a rather arbitrary way, or based upon some empirical but not published procedure [17]. This interdependency has been proven to be a significant factor amongst small and medium-sized enterprises [18]. One of the key challenges in understanding network effects or default propagation in credit scoring concerns the definition of the network itself.…”

Advances in Spatial Risk Analysis

“…Calabrese, Andreeva, and Ansell () propose a method for detecting the risk of small and medium enterprises’ defaults by considering the enterprises’ location and their demographic characteristics. They found that taking into account this information helped to improve the ability to predict defaults of non‐startups in London.…”