INSOLVENCY PREDICTION IN COMPANIES: AN EMPIRICAL STUDY IN ITALY

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Elisa Giacosa ORCID logo, Alberto Mazzoleni ORCID logo, Claudio Teodori ORCID logo, Monica Veneziani ORCID logo

https://doi.org/10.22495/cocv12i4c1p6

Abstract

The study stems from the relevance of the global economic crisis which is affecting companies to an increasing extent. The objective of the paper is to test the degree of effectiveness of the insolvency prediction models, most widely used in the literature, including recent works (Jackson and Wood, 2013), with reference to Lombardy, the most important Italian region in terms of industrialization rate. The following models were used, selected according to their diffusion and the statistical technique used: 1) Discriminant analysis (Altman, 1983), (Taffler, 1983); 2) Logit Analysis (Ohlson, 1980). The study identifies the state of health of companies in 2012, using the financial reporting data of the three previous years. The research sample consists of 58,750 companies (58,367 non-failed and 383 failed). Among the main results, it is observed that, for all the models, a prediction of default is often erroneously made for companies which are solvent, whereas failed companies are classified with a lower degree of error. The objective of the paper is preparatory to the second part of the research in progress in which, on the basis of the results presented here, some modifications will be made to the insolvency prediction models selected, significant for the Italian context, with the aim of identifying a company insolvency “alert model” which can be used by the various stakeholders. The results are interpreted in the light of the Stakeholder Theory.

Keywords: Prediction Models, Economic Crisis, Financial Reporting Data, Italian Companies, Stakeholder Theory

How to cite this paper: Giacosa, E., Mazzoleni, A., Teodori, C., & Veneziani, M. (2015). Insolvency prediction in companies: An empirical study in Italy. Corporate Ownership & Control, 12(4-1), 232-250. https://doi.org/10.22495/cocv12i4c1p6