CHIU-LING LUYang, Ann ShawingAnn ShawingYangHuang, Jui FengJui FengHuang2019-10-022019-10-022015-07-0810550925https://scholars.lib.ntu.edu.tw/handle/123456789/425836© 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.enAir carrier industry | Bankruptcy prediction | Binary quantile regressionjournal article10.1007/s12197-014-9282-62-s2.0-84930477332https://api.elsevier.com/content/abstract/scopus_id/84930477332