Bankruptcy predictions for U.S. air carrier operations: a study of financial data
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 reg...
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| Veröffentlicht in: | Journal of economics and finance 2015-07, Vol.39 (3), p.574-589 |
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| container_end_page | 589 |
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| container_title | Journal of economics and finance |
| container_volume | 39 |
| creator | Lu, Chiuling Yang, Ann Shawing Huang, Jui-Feng |
| description | 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. |
| doi_str_mv | 10.1007/s12197-014-9282-6 |
| format | Article |
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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.</description><identifier>ISSN: 1055-0925</identifier><identifier>EISSN: 1938-9744</identifier><identifier>DOI: 10.1007/s12197-014-9282-6</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Accuracy ; Adultery ; Aircraft ; Aircraft carriers ; Airline industry ; Alliances ; Aviation ; Bankruptcy ; Bankruptcy reorganization ; Bayesian analysis ; Book value ; Credit scoring ; Discriminant analysis ; Economics ; Economics and Finance ; Equity ; Finance ; Financial analysis ; Insolvency ; Macroeconomics/Monetary Economics//Financial Economics ; Operating leases ; Predictions ; Probability ; Profitability ; Profits ; Quick assets ; Retained earnings ; Studies ; Terrorism ; Travel ; Variables ; Working capital</subject><ispartof>Journal of economics and finance, 2015-07, Vol.39 (3), p.574-589</ispartof><rights>Springer Science+Business Media New York 2014</rights><rights>Copyright Springer Science & Business Media Jul 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3346-abe21ae1989451b6a11c30c5f230352a695dab5f7d6c36cd0eeaf0fba3bfb9153</citedby><cites>FETCH-LOGICAL-c3346-abe21ae1989451b6a11c30c5f230352a695dab5f7d6c36cd0eeaf0fba3bfb9153</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12197-014-9282-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12197-014-9282-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Lu, Chiuling</creatorcontrib><creatorcontrib>Yang, Ann Shawing</creatorcontrib><creatorcontrib>Huang, Jui-Feng</creatorcontrib><title>Bankruptcy predictions for U.S. air carrier operations: a study of financial data</title><title>Journal of economics and finance</title><addtitle>J Econ Finan</addtitle><description>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. 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Yang, Ann Shawing ; Huang, Jui-Feng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3346-abe21ae1989451b6a11c30c5f230352a695dab5f7d6c36cd0eeaf0fba3bfb9153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accuracy</topic><topic>Adultery</topic><topic>Aircraft</topic><topic>Aircraft carriers</topic><topic>Airline industry</topic><topic>Alliances</topic><topic>Aviation</topic><topic>Bankruptcy</topic><topic>Bankruptcy reorganization</topic><topic>Bayesian analysis</topic><topic>Book value</topic><topic>Credit scoring</topic><topic>Discriminant analysis</topic><topic>Economics</topic><topic>Economics and Finance</topic><topic>Equity</topic><topic>Finance</topic><topic>Financial analysis</topic><topic>Insolvency</topic><topic>Macroeconomics/Monetary Economics//Financial Economics</topic><topic>Operating leases</topic><topic>Predictions</topic><topic>Probability</topic><topic>Profitability</topic><topic>Profits</topic><topic>Quick assets</topic><topic>Retained earnings</topic><topic>Studies</topic><topic>Terrorism</topic><topic>Travel</topic><topic>Variables</topic><topic>Working capital</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lu, Chiuling</creatorcontrib><creatorcontrib>Yang, Ann Shawing</creatorcontrib><creatorcontrib>Huang, Jui-Feng</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>BPIR.com Limited</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>DELNET Management Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>Healthcare Administration Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Journal of economics and finance</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lu, Chiuling</au><au>Yang, Ann Shawing</au><au>Huang, Jui-Feng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bankruptcy predictions for U.S. air carrier operations: a study of financial data</atitle><jtitle>Journal of economics and finance</jtitle><stitle>J Econ Finan</stitle><date>2015-07-01</date><risdate>2015</risdate><volume>39</volume><issue>3</issue><spage>574</spage><epage>589</epage><pages>574-589</pages><issn>1055-0925</issn><eissn>1938-9744</eissn><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. 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| ispartof | Journal of economics and finance, 2015-07, Vol.39 (3), p.574-589 |
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| source | Business Source Complete; SpringerLink Journals - AutoHoldings |
| subjects | Accuracy Adultery Aircraft Aircraft carriers Airline industry Alliances Aviation Bankruptcy Bankruptcy reorganization Bayesian analysis Book value Credit scoring Discriminant analysis Economics Economics and Finance Equity Finance Financial analysis Insolvency Macroeconomics/Monetary Economics//Financial Economics Operating leases Predictions Probability Profitability Profits Quick assets Retained earnings Studies Terrorism Travel Variables Working capital |
| title | Bankruptcy predictions for U.S. air carrier operations: a study of financial data |
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