Abstract

The study aimed to investigate the role of non-financial measures in predicting corporate financial distress in the Indian industrial sector. The proportion of independent directors on the board and the proportion of the promoters’ share in the ownership structure of the business were the non-financial measures that were analysed, along with ten financial measures. For this, sample data consisted of 82 companies that had filed for bankruptcy under the Insolvency and Bankruptcy Code (IBC). An equal number of matching financially sound companies also constituted the sample. Therefore, the total sample size was 164 companies. Data for five years immediately preceding the bankruptcy filing was collected for the sample companies. The data of 120 companies evenly drawn from the two groups of companies were used for developing the model and the remaining data were used for validating the developed model. Two binary logistic regression models were developed, M1 and M2, where M1 was formulated with both financial and non-financial variables, and M2 only had financial variables as predictors. The diagnostic ability of the model was tested with the aid of the receiver operating curve (ROC), area under the curve (AUC), sensitivity, specificity and annual accuracy. The results of the study show that inclusion of the two non-financial variables improved the efficacy of the financial distress prediction model. This study made a unique attempt to provide empirical evidence on the role played by non-financial variables in improving the efficiency of corporate distress prediction models.

Highlights

  • In a country, healthy and sick businesses coexist

  • The model resulting from the comparison is recommended for corporate financial distress prediction in the Indian industrial sector

  • Except for the debt to total assets ratio (DTAR) and cash flow to sales ratio (CSR), the mean values of all the variables were lower amongst the distressed companies

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Summary

Introduction

When businesses fail to maintain competitive efficiency, they get sick (Datta 2013). Sick businesses adversely affect the different stakeholder groups and the national economy at large. Consider the example of Enron, once the world’s largest energy company that ranked seventh in the fortune magazine in early 2001 but filed for bankruptcy in December 2001. Enron’s employees lost jobs, but its audit firm Arthur Anderson laid off thousands of its employees. The sharp and sudden decline in the stock price of Enron adversely affected the savings of ordinary investors, both direct and index-fund investors (Sridharan et al 2002)

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