Empirical comparison of hazard models in predicting SMEs failure

Jairaj Gupta, Andros Gregoriou and Tahera Ebrahimi

Quantitative Finance, 2018, vol. 18, issue 3, 437-466

Abstract: 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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:18:y:2018:i:3:p:437-466

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DOI: 10.1080/14697688.2017.1307514

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