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

Chiuling Lu, Ann Yang () and Jui-Feng Huang

Journal of Economics and Finance, 2015, vol. 39, issue 3, 574-589

Abstract: 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. Copyright Springer Science+Business Media New York 2015

Keywords: Air carrier industry; Bankruptcy prediction; Binary quantile regression; G33; L93; C11 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12197-014-9282-6

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