Predicting Bankruptcy Resolution

24 Pages Posted: 17 May 2002

See all articles by Ran Barniv

Ran Barniv

Kent State University - Department of Accounting

Anurag Agarwal

University of Florida

Robert L. Leach

University of South Carolina at Aiken

Abstract

This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed.

Suggested Citation

Barniv, Ran and Agarwal, Anurag and Leach, Robert L., Predicting Bankruptcy Resolution. Available at SSRN: https://ssrn.com/abstract=312717

Ran Barniv (Contact Author)

Kent State University - Department of Accounting ( email )

P.O. Box 5190
Kent, OH 44242-0001
United States
330-672-1112 (Phone)
330-672-2548 (Fax)

Anurag Agarwal

University of Florida ( email )

Gainesville, FL 32610-0496
United States

Robert L. Leach

University of South Carolina at Aiken ( email )

171 University Parkway
Aiken, SC 29801
United States

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