Predicting the Risk of Insolvency in Small Enterprises: Critical Analysis of the Predictive Model Associated with the New Italian Code of Business Crisis

Anna Maria Arcari and Daniele Grechi

International Journal of Business and Management, 2023, vol. 16, issue 7, 41

Abstract: Numerous studies have been conducted to verify whether, and under what conditions, Altman's Z-Score model can also be applied to unlisted, non-US companies. The response of numerous studies confirms the substantial validity of this algorithm. However, in Italy, the legislator, in launching the new Business Crisis Code in 2019, in adherence to an important European recommendation, did not adopt the aforementioned model but approved a different one. In order to find a justification for this choice, the present work intends to test the effectiveness of the warning indices that will be adopted in Italy by comparing them with the Altman predictive model in the Z'' Score version. To this end, the two models were applied to the balance sheets of 789 Italian firms that went bankrupt in the period 2016-2018 and, at the same time, to a control sample, equal in number and composition, of non-bankrupt firms. The results of this analysis produced two distinct findings. The Italian method proved to be less effective in predicting a crisis than the Z'' score. but more effective in determining whether a firm is truly healthy. This evidence is useful to confirm once again the effectiveness of the Z'' Score in a non-American context but also, and above all, to provide suggestions to the Italian legislator so that it can refine the predictive model currently in force.

Date: 2023
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