Prediction of default probability for construction firms using the logit model
Recently, the high incidence of construction firm bankruptcies has underlined the importance of forecasting defaults in the construction industry. Early warning systems need to be developed to prevent or avert contractor default; additionally, this evaluation result could facilitate the selection o...
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doaj-f84b6b6624ca4812851fd17b7fc64bff2021-07-02T17:32:09ZengVilnius Gediminas Technical UniversityJournal of Civil Engineering and Management1392-37301822-36052014-04-0120210.3846/13923730.2013.801886Prediction of default probability for construction firms using the logit modelH. Ping Tserng0Po-Cheng Chen1Wen-Haw Huang2Man Cheng Lei3Quang Hung Tran4Department of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanLong Reign Development Co., 16F-2, No. 76, Sec. 2 Dunhua S. Road, Taipei, TaiwanDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, Taiwan Recently, the high incidence of construction firm bankruptcies has underlined the importance of forecasting defaults in the construction industry. Early warning systems need to be developed to prevent or avert contractor default; additionally, this evaluation result could facilitate the selection of firms as collaboration or investment partners. Financial statements are considered one of the key basic evaluation tools for demonstrating firm strength. This investigation provides a framework for assessing the probability of construction contractor default based on financial ratios by using the Logit model. A total of 21 ratios, gathered into five financial groups, are utilized to perform univariate logit analysis and multivariate logit analysis for assessing contractor default probability. The empirical results indicate that using multivariate analysis by adding market factor to the liquidity, leverage, activity and profitability factors can increase the accuracy of default prediction more than using only four financial factors. While considering the market factor in the multivariate Logit model, clear incremental prediction performance appears in 1-year evaluation. This study thus suggests that the market factor comprises important information to increase the prediction performance of the model when applied to construction contractors, particularly in short-term evaluation. http://journals.vgtu.lt/index.php/JCEM/article/view/3120default probabilityfinancial ratiosLogit modelbankruptcy prediction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Ping Tserng Po-Cheng Chen Wen-Haw Huang Man Cheng Lei Quang Hung Tran |
spellingShingle |
H. Ping Tserng Po-Cheng Chen Wen-Haw Huang Man Cheng Lei Quang Hung Tran Prediction of default probability for construction firms using the logit model Journal of Civil Engineering and Management default probability financial ratios Logit model bankruptcy prediction |
author_facet |
H. Ping Tserng Po-Cheng Chen Wen-Haw Huang Man Cheng Lei Quang Hung Tran |
author_sort |
H. Ping Tserng |
title |
Prediction of default probability for construction firms using the logit model |
title_short |
Prediction of default probability for construction firms using the logit model |
title_full |
Prediction of default probability for construction firms using the logit model |
title_fullStr |
Prediction of default probability for construction firms using the logit model |
title_full_unstemmed |
Prediction of default probability for construction firms using the logit model |
title_sort |
prediction of default probability for construction firms using the logit model |
publisher |
Vilnius Gediminas Technical University |
series |
Journal of Civil Engineering and Management |
issn |
1392-3730 1822-3605 |
publishDate |
2014-04-01 |
description |
Recently, the high incidence of construction firm bankruptcies has underlined the importance of forecasting defaults in the construction industry. Early warning systems need to be developed to prevent or avert contractor default; additionally, this evaluation result could facilitate the selection of firms as collaboration or investment partners. Financial statements are considered one of the key basic evaluation tools for demonstrating firm strength. This investigation provides a framework for assessing the probability of construction contractor default based on financial ratios by using the Logit model. A total of 21 ratios, gathered into five financial groups, are utilized to perform univariate logit analysis and multivariate logit analysis for assessing contractor default probability. The empirical results indicate that using multivariate analysis by adding market factor to the liquidity, leverage, activity and profitability factors can increase the accuracy of default prediction more than using only four financial factors. While considering the market factor in the multivariate Logit model, clear incremental prediction performance appears in 1-year evaluation. This study thus suggests that the market factor comprises important information to increase the prediction performance of the model when applied to construction contractors, particularly in short-term evaluation.
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topic |
default probability financial ratios Logit model bankruptcy prediction |
url |
http://journals.vgtu.lt/index.php/JCEM/article/view/3120 |
work_keys_str_mv |
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1721325304345001984 |