DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

I Premachandra, Yao Chen, John Watson

    Research output: Contribution to journalArticleResearchpeer-review

    58 Citations (Scopus)

    Abstract

    Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman s bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991a??2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.
    Original languageEnglish
    Pages (from-to)620 - 626
    Number of pages7
    JournalOMEGA International Journal of Management Science
    Volume39
    Issue number6
    DOIs
    Publication statusPublished - 2011

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