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

Chiuling Lu, Ann Shawing Yang, Jui Feng Huang

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)574-589
Number of pages16
JournalJournal of Economics and Finance
Volume39
Issue number3
DOIs
Publication statusPublished - 2015 Jul 8

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics

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