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A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models

Andreeva, Galina and Calabrese, Raffaella and Osmetti, Silvia Angela (2016) 'A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models.' European Journal of Operational Research, 249 (2). pp. 506-516. ISSN 0377-2217

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This paper presents a cross-country comparison of significant predictors of small business failure between Italy and the UK. Financial measures of profitability, leverage, coverage, liquidity, scale and non-financial information are explored, some commonalities and differences are highlighted. Several models are considered, starting with the logistic regression which is a standard approach in credit risk modelling. Some important improvements are investigated. Generalised Extreme Value (GEV) regression is applied in contrast to the logistic regression in order to produce more conservative estimates of default probability. The assumption of non-linearity is relaxed through application of BGEVA, non-parametric additive model based on the GEV link function. Two methods of handling missing values are compared: multiple imputation and Weights of Evidence (WoE) transformation. The results suggest that the best predictive performance is obtained by BGEVA, thus implying the necessity of taking into account the low volume of defaults and non-linear patterns when modelling SME performance. WoE for the majority of models considered show better prediction as compared to multiple imputation, suggesting that missing values could be informative.

Item Type: Article
Uncontrolled Keywords: Decision support systems; Risk analysis; Credit Scoring; Small and Medium Sized Enterprises; Default prediction
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 18 Aug 2015 11:50
Last Modified: 06 Jan 2022 14:39

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