Abstract

Purpose The purpose of this paper is to investigate whether International Financial Reporting Standards (IFRS)-based data improve bankruptcy prediction over Australian Generally Accepted Accounting Principles (AGAAP)-based data. In doing so, this paper focuses on intangibles because conservative accounting rules for intangibles under IFRS required managers to write off substantial amounts of intangibles previously capitalized and revalued upwards under AGAAP. The focus on intangibles is also motivated by empirical evidence that financially distressed firms are more likely to voluntarily capitalize and make upward revaluations of intangibles compared with healthy firms. Design/methodology/approach This paper analyses a sample of 46 bankrupt firms and 46 non-bankrupt (healthy) firms using a matched-pair design over the period 1991 to 2004. The authors match control firms on fiscal year, size (total assets), Global Industry Classification Standard-based industry membership and principal activities. Using Altman’s (1968) model, this paper compares the bankruptcy prediction results between bankrupt and non-bankrupt firms for up to five years before bankruptcy. In the tests, the authors use financial statements as reported under AGAAP and two IFRS-based data sets. The IFRS-based datasets are created by considering the adjustments on the AGAAP data required to implement the requirements of IAS 38, IFRS 3 and IAS 36. Findings This paper finds that, under IFRS, Altman’s (1968) model consistently predicts bankruptcy for bankrupt firms more accurately than under AGAAP for all of the five years prior to bankruptcy. This greater prediction accuracy emanates from smaller values of the inputs to Altman’s model due to conservative accounting rules for intangibles under IFRS. However, this greater accuracy in bankruptcy prediction comes with larger Type II errors for healthy firms. Overall, the results provide evidence that the switch from AGAAP to IFRS improves the quality of information contained in the financial statements for predicting bankruptcy. Research limitations/implications Small sample size and having data available over the required period may limit generalizability of findings. Originality/value Although bankruptcy prediction is one of the primary uses of accounting information, the burgeoning literature on the benefits of IFRS adoption has so far neglected the role of IFRS data in bankruptcy prediction. Thus, this paper documents a new benefit of IFRS adoption. In this paper, the authors demonstrate how the restrictions on the ability to capitalize and revalue intangibles enhance the quality of information used to predict bankruptcy. These results provide evidence to international standard setters of what they can expect if their efforts to remove non-restrictive accounting practices for intangibles are abandoned.

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