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Global Crisis and Financial Distress Likelihood of SMEs: Some Evidence From Panel Data Regression

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Andrea Quintiliani at Università degli Studi G. d'Annunzio Chieti e Pescara
Andrea Quintiliani
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Abstract

In the aftermath of the global financial crisis, this chapter sheds light on the determinants of the financial distress costs between Italian and German small and medium enterprises (SMEs). The authors propose an innovative formulation of the expected costs originated by financial distress expressed as the product of the expected financial distress likelihood times the total amount of the financial distress costs if insolvency does occur. The model is estimated using panel data methodology on samples from two European countries (Italy and Germany). The results indicate that the amount of ex-post costs depends on derivative financial instruments, intangible assets, and relation with local banks (small local banks rather than large banking groups).
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Chapter 5
DOI: 10.4018/978-1-5225-3767-0.ch005
ABSTRACT
In the aftermath of the global financial crisis, this chapter sheds light on the determinants of the finan-
cial distress costs between Italian and German small and medium enterprises (SMEs). The authors
propose an innovative formulation of the expected costs originated by financial distress expressed as the
product of the expected financial distress likelihood times the total amount of the financial distress costs
if insolvency does occur. The model is estimated using panel data methodology on samples from two
European countries (Italy and Germany). The results indicate that the amount of ex-post costs depends
on derivative financial instruments, intangible assets, and relation with local banks (small local banks
rather than large banking groups).
INTRODUCTION
This study is the continuation of a search (Quintiliani, 2017b) finalized to estimate the expected costs of
financial distress, quantified in terms of product among financial distress likelihood and costs sustained
by the insolvent society.
Compared with the previous one, the survey model analyzes SME samples from two European
countries, Italy and Germany, whose financial and entrepreneurial systems show significant differences.
Data were extracted from Amadeus (a high quality European database), BvD databases (Aida and
Mint Italy) and panel data methodology was used to control for potential endogeneity and unobservable
heterogeneity.
The results obtained for each country taken individually, empirically validate our model, revealing
that most parameters are significant and with the expected signs.
Global Crisis and Financial
Distress Likelihood of SMEs:
Some Evidence From Panel
Data Regression
Andrea Quintiliani
Pegaso Telematic University, Italy
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FINANCIAL CRISIS AND LOCAL BANKS: A REVIEW OF BANK-FIRM RELATIONSHIPS IN ITALY
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  • Apr 2017
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Financial distress cost of Italian small and medium enterprises: A predictive and interpretative model
Article
  • Oct 2017
  • J Risk Finance
Purpose This work proposes a theoretical model designed to predict the likelihood of financial distress of an enterprise and to quantify the damages whenever the financial crisis became full-blown. Design/methodology/approach Coherently with the objectives of the paper, the analysis considers the last seven exercises (period: 1999/2006) of a sample of 25.000 SMEs (volume of sales: < 20 mlns; number of employees: < 250) organized in the form of Ltd. The empirical investigation has been effected through the use of BvD database: Aida and Mint Italy. Findings The analysis shows that the ex-post costs of financial distress decrease in relation to the company’s increased ability to use intangible assets and in relation to the local roots of the banks (local banks rather than international banking groups) Research limitations/implications The instruments used for this study need to be subjected to more statistical tests in order to establish a more robust validity and reliability. Replication of this study using larger samples and a broader geographic base (extended at European level) is suggested. Practical implications The timely monitoring of investigated variables allows you to mitigate the costs of exit from the market. Originality/value Following the global financial crisis, this paper sheds new light on the financial distress cost of Italian SMEs.
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