Abstract
AbstractThis paper emphasises the inappropriateness of continuous measure predictors for both the logit and MDA models when dealing with the measurement errors that exist in much of the private company data used to model financial distress in that sector. Also, it is argued that the step function logit model that we get as a consequence of the necessity to categorise the predictors, may be more appropriate in explaining underlying nonlinear behaviour of firms at risk than the usual continuous response linear function. Within this context, the two models are compared using data from 140 private Australian companies. A logit model based on only three discrete‐valued ratios gave an overall accuracy rate comparable to that of an existing continuous‐valued multiple discriminant analysis (MDA) model based on six ratios. Of interest is the very different order of significance of the predictor ratios in the two models although neither model remains trustworthy for predictive purposes.
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