Predicting Corporate Failure: Empirical Evidence for the UK

Posted: 25 Jun 2004

See all articles by Christakis Charalambous

Christakis Charalambous

University of Cyprus - Department of Public and Business Administration

Andreas Charitou

University of Cyprus

Evi Neophytou

Athens University of Economics and Business - Department of Accounting and Finance

Abstract

The main purpose of this study is to examine the incremental information content of operating cash flows in predicting financial distress and thus develop reliable failure prediction models for UK public industrial firms. Neural networks and logit methodology were employed to a dataset of 51 matched pairs of failed and nonfailed UK public industrial firms over the period 1988-97. The final models are validated using an out-of-sample-period ex-ante test and the Lachenbruch jackknife procedure. The results indicate that a parsimonious model that includes three financial variables, a cash flow, a profitability and a financial leverage variable, yielded an overall correct classification accuracy of 83% one year prior to the failure. In summary, our models can be used to assist investors, creditors, managers, auditors and regulatory agencies in the UK to predict the probability of business failure.

JEL Classification: M41, G33

Suggested Citation

Charalambous, Christakis and Charitou, Andreas and Neophytou, Evi, Predicting Corporate Failure: Empirical Evidence for the UK. European Accounting Review, Vol. 13, No. 3. Available at SSRN: https://ssrn.com/abstract=558523

Christakis Charalambous

University of Cyprus - Department of Public and Business Administration ( email )

75 Kallipoleos Street
P.O. Box 20537
Nicosia CY-1678
CYPRUS
00357-2-892258 (Phone)
00357-2-339063 (Fax)

Andreas Charitou (Contact Author)

University of Cyprus ( email )

75 Kallipoleos Street
P.O. Box 20537
Nicosia CY-1678
Cyprus
+357 2 893624 (Phone)
+357 2 895030 (Fax)

Evi Neophytou

Athens University of Economics and Business - Department of Accounting and Finance ( email )

76 Patission Street
GR-104 34 Athens
Greece
+30 210 8203960 (Phone)

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