Industrial sector and financial distress
Emerald Group Publishing Limited
Faculty of Business and Law
School of Accounting, Finance and Economics
Purpose: A number of authors have noted that industrial sector is a significant factor in the design and construction of failure prediction models, suggesting that organisational structures dictate the construction of separate models for different sectors. However, most modellers have been content to amalgamate sub‐sectors of the “manufacturing” classification (often because of otherwise facing sample size difficulties) to produce a single manufacturing sector model. This paper seeks to examine the differences that exist across the manufacturing sector to identify those sub‐sectors for which such amalgamation is inadvisable. Design/methodology/approach: The paper examines the correlation of traditional financial ratios with sector performance for a large sample of UK companies. A proprietary Z‐score failure prediction model is used to evaluate the solvency of 340 manufacturing companies, in order to determine the pattern of misclassification errors, and their association with industrial sector. Findings: The paper identifies sub‐sectors whose inclusion would make traditional models vulnerable to error, and makes suggestions regarding their continued inclusion for modelling purposes. Research limitations/implications: The paper makes suggestions for data selection in the construction of failure prediction models. Practical implications: The classificatory ability of failure prediction models should be improved, notably through a reduction in the incidence of Type 2 errors. Users of financial models for evaluating companies as investments and/or their worthiness as suppliers or creditors will have more reliable information at their disposal. Originality/value: Contribution to knowledge of the explanatory factors associated with corporate failure.