Failure Prediction in the Condition of Information Asymmetry: Tax Arrears as a Substitute When Financial Ratios Are Outdated

Abstract

This paper aims to study the usefulness of applying tax arrears in failure prediction, when annual reports to calculate financial ratios are outdated. Three known classification methods from the failure prediction literature are applied to the whole population dataset from Estonia, incorporating various tax arrears variables and financial ratios. The results indicate that accuracies remarkably exceeding those of models based on financial ratios can be obtained with variables portraying the average, maximum, and duration contexts of tax arrears. The main contribution of the current study is that it provides a proof of concept that accounting for the dynamics of payment defaults can lead to useful prediction models in cases in which up-to-date financial reports are not available.