Empirical comparison of hazard models in predicting SMEs failure

Jairaj Gupta, Andros Gregoriou, Tahera Ebrahimi

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


This study aims to shed light on the debate concerning the choice between discrete-time and continuous-time hazard models in making bankruptcy or any binary prediction using interval censored data. Building on the theoretical suggestions from various disciplines, we empirically compare widely used discrete-time hazard models (with logit and clog-log links) and the continuous-time Cox Proportional Hazards (CPH) model in predicting bankruptcy and financial distress of the United States Small and Medium-sized Enterprises (SMEs). Consistent with the theoretical arguments, we report that discrete-time hazard models are superior to the continuous-time CPH model in making binary predictions using interval censored data. Moreover, hazard models developed using a failure definition based jointly on bankruptcy laws and firms’ financial health exhibit superior goodness of fit and classification measures, in comparison to models that employ a failure definition based either on bankruptcy laws or firms’ financial health alone.

Original languageEnglish
Pages (from-to)437-466
Number of pages30
JournalQuantitative Finance
Issue number3
Early online date16 Jun 2017
Publication statusPublished - 4 Mar 2018
Externally publishedYes


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