The use of accounting anomalies indicators to predict business failure

Carlos Serrano-Cinca, Begoña Gutiérrez-Nieto, Martha Bernate-Valbuena

Resultado de la investigación

1 Cita (Scopus)

Resumen

Most of the studies that try to predict business failure assume that accounts give a true and fair view of the financial position of a company, without considering that managers can discretionarily apply accounting rules or even perform accounting fraud. This paper takes a set of financial ratios especially designed to detect accounting anomalies as bankruptcy predictors. These ratios are not very common in bankruptcy prediction studies, but they come from creative accounting studies. The ratios try to identify abnormal depreciation figures, exaggerated receivables or deteriorating financial conditions preceding aggressive accounting practices. The empirical study has been performed from a sample of 51,337 public and private European companies, during the period 2012–2016. The analysis techniques applied were logistic regression and decision trees, allowing to obtain rules to predict the status of failed or non-failed. It is found that several indicators proposed in the literature as earnings management indicators present statistically significant differences between failed and non-failed firms, but they do not have enough predictive power to incorporate them into prediction models. However, an index developed to measure accounting anomalies exhibits high discriminatory power, similar to that of the classical financial ratios. The construction of the index and its application to private firm sample provide the main contribution of the paper, as the results suggest slightly better forecast accuracy only for the private firm sample. The inclusion of indicators to detect accounting anomalies should be considered when developing new models to predict bankruptcy, especially in private companies.

Idioma originalEnglish
Páginas (desde-hasta)353-375
Número de páginas23
PublicaciónEuropean Management Journal
Volumen37
N.º3
DOI
EstadoPublished - 1 jun 2019

All Science Journal Classification (ASJC) codes

  • Strategy and Management

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