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Role of Comprehensive Income in Predicting Bankruptcy

Author

Listed:
  • Asyrofa Rahmi

    (National Central University)

  • Hung-Yuan Lu

    (California State University)

  • Deron Liang

    (National Central University)

  • Dinda Novitasari

    (National Central University)

  • Chih-Fong Tsai

    (National Central University)

Abstract

This study examines the role of comprehensive income and its components, in addition to net income, as inputs to forecast bankruptcy. Using a matched sample of 466 (233 pairs) U.S. bankrupt and non-bankrupt firms from 1993 to 2014, we build a bankruptcy prediction model using random forest classification. Compared with the benchmark model, our proposed model’s accuracy increases by 1.5% and the Type I error decreases by up to 3%. A variable importance analysis reveals that comprehensive income is consistently the most useful variable for bankruptcy prediction. A variable interaction analysis shows that the top interaction pair includes one Altman variable and comprehensive income. Finally, we analyze bankrupt firms that our model identifies but the benchmark model misclassifies; we find that such firm’ other comprehensive income is consistently negative, suggesting that firms’ macroeconomic risk exposure plays a key role in bankruptcy prediction.

Suggested Citation

  • Asyrofa Rahmi & Hung-Yuan Lu & Deron Liang & Dinda Novitasari & Chih-Fong Tsai, 2023. "Role of Comprehensive Income in Predicting Bankruptcy," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 689-720, August.
    • Handle: RePEc:kap:compec:v:62:y:2023:i:2:d:10.1007_s10614-022-10328-5
    DOI: 10.1007/s10614-022-10328-5
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