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Review of Categorical Models for Classification Issues in Accounting and Finance

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  • Barniv, Ran
  • McDonald, James B

Abstract

Recent studies have extensively used the logit or probit models for classification problems in accounting and finance. More than 289 articles in prestigious journals have used these or similar methods from 1989 through 1996. This paper reviews several categorical techniques and compares the performance of logit or probit with alternative procedures. Intuitive and mathematical explanations of how the models examined differ in terms of underlying assumptions and other attributes are provided. The alternative techniques are applied to two substantive research questions: predicting bankruptcy and auditors' consistency judgements. Four empirical criteria provide some evidence that the exponential generalized beta of the second kind (EGB2), lomit, and burrit (all new to the accounting and finance literature) improve the log-likelihood functions, and the explanatory power, compared with logit and other models. EGB2, lomit and burrit also provide significantly better classifications and predictions than logit and other techniques. Copyright 1999 by Kluwer Academic Publishers

Suggested Citation

  • Barniv, Ran & McDonald, James B, 1999. "Review of Categorical Models for Classification Issues in Accounting and Finance," Review of Quantitative Finance and Accounting, Springer, vol. 13(1), pages 39-62, July.
  • Handle: RePEc:kap:rqfnac:v:13:y:1999:i:1:p:39-62
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    Cited by:

    1. Willem Karel M. Brauers & Romualdas Ginevičius & Askoldas Podviezko, 2014. "Development of a Methodology of Evaluation of Financial Stability of Commercial Banks," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 61(3), pages 349-367, June.
    2. Steven Caudill & Norman Godwin, 2002. "Heterogeneous skewness in binary choice models: Predicting outcomes in the men's NCAA basketball tournament," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 991-1001.
    3. Fotios Pasiouras & Chrysovalantis Gaganis & Michael Doumpos, 2007. "A multicriteria discrimination approach for the credit rating of Asian banks," Annals of Finance, Springer, vol. 3(3), pages 351-367, July.
    4. Michael J. Peel, 2014. "Addressing unobserved endogeneity bias in accounting studies: control and sensitivity methods by variable type," Accounting and Business Research, Taylor & Francis Journals, vol. 44(5), pages 545-571, October.
    5. Becchetti, Leonardo & Castelli, Annalisa & Hasan, Iftekhar, 2008. "Investment-cash flow sensitivities, credit rationing and financing constraints," Research Discussion Papers 15/2008, Bank of Finland.
    6. Marco Alf˜ & Giovanni Trovato & Stefano Caiazza, 2004. "Extending Logistic Approach to Risk Modelling Through Semiparametric Mixing," CEIS Research Paper 47, Tor Vergata University, CEIS.
    7. Pasiouras, Fotios & Gaganis, Chrysovalantis & Zopounidis, Constantin, 2007. "Multicriteria decision support methodologies for auditing decisions: The case of qualified audit reports in the UK," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1317-1330, August.
    8. Leonardo Becchetti & Annalisa Castelli & Iftekhar Hasan, 2010. "Investment–cash flow sensitivities, credit rationing and financing constraints in small and medium-sized firms," Small Business Economics, Springer, vol. 35(4), pages 467-497, November.
    9. Lis Bettina & Nessler Christian & Retzmann Jan, 2011. "The Proposition Value Of Corporate Ratings - A Reliability Testing Of Corporate Ratings By Applying Roc And Cap Techniques," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 6(2), pages 60-90, August.
    10. João Fernandes, 2005. "Corporate Credit Risk Modeling: Quantitative Rating System And Probability Of Default Estimation," Finance 0505013, EconWPA.
    11. Pasiouras, Fotios & Tanna, Sailesh & Zopounidis, Constantin, 2007. "The identification of acquisition targets in the EU banking industry: An application of multicriteria approaches," International Review of Financial Analysis, Elsevier, vol. 16(3), pages 262-281.

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