|Title:||Bankruptcy predictions for U.S. air carrier operations: a study of financial data||Authors:||CHIU-LING LU
Yang, Ann Shawing
Huang, Jui Feng
|Keywords:||Air carrier industry | Bankruptcy prediction | Binary quantile regression||Issue Date:||8-Jul-2015||Journal Volume:||39||Journal Issue:||3||Source:||Journal of Economics and Finance||Abstract:||
© 2014, Springer Science+Business Media New York. 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.
|Appears in Collections:||國際企業學系|
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