Distressed Firm and Bankruptcy Prediction in an International Context: A Review and Empirical Analysis of Altman's Z-Score Model

47 Pages Posted: 11 Dec 2014

See all articles by Edward I. Altman

Edward I. Altman

New York University (NYU) - Salomon Center; New York University (NYU) - Department of Finance

Malgorzata Iwanicz-Drozdowska

Warsaw School of Economics, Institute of Finance

Erkki K. Laitinen

University of Vaasa - Department of Accounting and Finance

Arto Suvas

University of Vaasa - Department of Accounting and Finance

Date Written: August 10, 2014

Abstract

The purpose of this paper is firstly to review the literature on the efficacy and importance of the Altman Z-Score bankruptcy prediction model globally and its applications in finance and related areas. This review is based on an analysis of 33 scientific papers published from the year 2000 in leading financial and accounting journals. Secondly, we use a large international sample of firms to assess the classification performance of the model in bankruptcy and distressed firm prediction. In all, we analyze its performance on firms from 31 European and three non-European countries. This kind of comprehensive international analysis has not been presented thus far. Except for the U.S. and China, the firms in the sample are primarily private and cover non-financial companies across all industrial sectors. Thus, the version of the Z-Score model developed by Altman (1983) for private manufacturing and non-manufacturing firms (Z"-Score Model) is used in our testing. The literature review shows that results for Z-Score Models have been somewhat uneven in that in some studies the model has performed very well, whereas in others it has been outperformed by competing models. None of the reviewed studies is based on a comprehensive international comparison, which makes the results difficult to generalize. The analysis in this study shows that while a general international model works reasonably well, for most countries, with prediction accuracy levels (AUC) of about 75%, and exceptionally well for some (above 90%), the classification accuracy may be considerably improved with country-specific estimation especially with the use of additional variables. In some country models, the information provided by additional variables helps boost the classification accuracy to a higher level.

Keywords: Z-Score, bankruptcy, failure, default, financial distress

JEL Classification: G15, G32, G33

Suggested Citation

Altman, Edward I. and Iwanicz-Drozdowska, Malgorzata and Laitinen, Erkki K. and Suvas, Arto, Distressed Firm and Bankruptcy Prediction in an International Context: A Review and Empirical Analysis of Altman's Z-Score Model (August 10, 2014). Available at SSRN: https://ssrn.com/abstract=2536340 or http://dx.doi.org/10.2139/ssrn.2536340

Edward I. Altman

New York University (NYU) - Salomon Center ( email )

44 West 4th Street
New York, NY 10012
United States
212-998-0709 (Phone)
212-995-4220 (Fax)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

Malgorzata Iwanicz-Drozdowska

Warsaw School of Economics, Institute of Finance ( email )

Warsaw
Poland

Erkki K. Laitinen

University of Vaasa - Department of Accounting and Finance ( email )

P.O. Box 700
FIN-65101 Vaasa, FI-65101
Finland
+358 61 324 8275 (Phone)
+358 61 324 8344 (Fax)

Arto Suvas (Contact Author)

University of Vaasa - Department of Accounting and Finance ( email )

P.O. Box 700
FIN-65101 Vaasa, FI-65101
Finland
(358) 61 327-8111 (Phone)
(358) 61 324-8465 (Fax)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
3,149
Abstract Views
8,249
rank
3,709
PlumX Metrics