Survival Analysis and Financial Distress Prediction: Finnish Evidence

Survival analysis is statistical technique that uses longitudinal data to model the process that allows an individual or firm to survive to a particular point in time. Despite a large number of studies that use survival analysis to model the duration of time that precedes financial distress, some criticism has suggested that the application of survival analysis to financial distress research provides limited incremental knowledge. This study uses survival analysis to model the duration of time that precedes a firm's initial payment default. The data set consists of firm financial information obtained from a large credit information company in Finland for a five‐year period split into estimation and holdout samples. Financial ratios, size, industry, and age are used as covariates to model the survival process preceding the initial payment default. The hazard is compared to a logistic risk measure estimated from data one year prior to default. The proportional hazards model is shown to give a more accurate forecast of default for the earlier years prior to the onset of financial distress.

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