Journal of Economics and Finance

, Volume 39, Issue 3, pp 574–589

Bankruptcy predictions for U.S. air carrier operations: a study of financial data


DOI: 10.1007/s12197-014-9282-6

Cite this article as:
Lu, C., Yang, A.S. & Huang, JF. J Econ Finan (2015) 39: 574. doi:10.1007/s12197-014-9282-6


We applied the binary quantile regression, a Bayesian quantile regression, and logit models to identify optimal bankruptcy prediction accuracy for U.S. air carriers for the period from 1990 to 2011. We used accuracy ratio and Brier scores as standards of comparison and a Bayesian binary quantile regression with optimal bankruptcy prediction accuracy for both healthy and bankrupt air carriers. Total assets positively and significantly influenced bankruptcy probability for air carriers. Operational variables consisted of quick assets to expenditures for operation, increase in sales, and working capital to assets; however, these variables negatively and significantly influenced air carriers’ bankruptcy probability.


Air carrier industry Bankruptcy prediction Binary quantile regression 

JEL Classification

G33 L93 C11 

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Chiuling Lu
    • 1
  • Ann Shawing Yang
    • 2
  • Jui-Feng Huang
    • 1
  1. 1.Department of International BusinessNational Taiwan UniversityTaipeiRepublic of China
  2. 2.Institute of International Management, National Cheng Kung UniversityTainanRepublic of China

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