Predictive Modelling for Financial Distress amongst Manufacturing Companies in India

Dr. Jyoti Nair, and Dr. JK Sachdeva

Journal of Global Economy, 2022, vol. 18, issue 4, 261-276

Abstract: This study develops a model predicting financial distress amongst manufacturing companies in India using logistic regression. 18 financial ratios of 574 companies from 34 industries in manufacturing sector were examined for the period 2005 – 2019 to develop and validate the model. The study can be considered as one of the very few which has examined the financial distress indicators of manufacturing sector in India. EBIT margin, Interest coverage, quick ratio, Cash flow from operations to Sales, Debtors Turnover, Working Capital to Total Assets, Fixed Assets to Total Assets are important determinants of financial health of a business. This study provides useful insights to business managers and lenders to review and monitor financial soundness of business. The findings can also help policy makers to design policies and programs to support distressed industries in India. This study also addresses the urgent need for a country specific model for distress prediction. The model developed shows high predictive ability.

Keywords: Financial distress; Indian manufacturing sector; distress prediction; logistic regression; distress indicators (search for similar items in EconPapers)
JEL-codes: D8 I2 (search for similar items in EconPapers)
Date: 2022
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