Treffer: Optimal threshold of data envelopment analysis in bankruptcy prediction
Title:
Optimal threshold of data envelopment analysis in bankruptcy prediction
Authors:
Source:
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Autònoma de Barcelona
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Publisher Information:
Institut d'Estadística de Catalunya, 2023.
Publication Year:
2023
Subject Terms:
validation, Classificació AMS::90 Operations research, Programming (Mathematics), mathematical programming::90C Mathematical programming, Operations research, Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, ROC curve, Management science, Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science, Threshold optimization, mathematical programming::90B Operations research and management science, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Data envelopment analysis, Validation, Optimització i investigació operativa, threshold optimization, Bankruptcy prediction, data envelopment analysis, Programació matemàtica, bankruptcy prediction
Document Type:
Fachzeitschrift
Article
File Description:
application/pdf
Language:
English
DOI:
10.57645/20.8080.02.3
Access URL:
Rights:
CC BY NC ND
Accession Number:
edsair.dedup.wf.002..ffccd30642e7e98bbcde17b1501f4d1e
Database:
OpenAIRE
Weitere Informationen
Data envelopment analysis is not typically used for bankruptcy prediction. However, this paper shows that a correctly set up a model for this approach can be very useful in that context. A superefficiency model was applied to classify bankrupt and actively manufactured companies in the European Union. To select an appropriate threshold, the Youden index and the distance from the corner were used in addition to the total accuracy. The results indicate that selecting a suitable threshold improves specificity visibly with only a small reduction in the total accuracy. The thresholds of the best models appear to be robust enough for predictions in different time and economic sectors.