Forecasting Bankruptcy More Accurately: A Simple Hazard Model

Keywords

bankruptcy forecasting, hazard models, market-driven variables

Abstract

I argue that hazard models are more appropriate for forecasting bankruptcy than the single-period models used previously. Single-period bankruptcy models give biased and inconsistent probability estimates while hazard models produce consistent estimates. I describe a simple technique for estimating a discrete-time hazard model with a logit model estimation program.

Applying my technique, I find that about half of the accounting ratios that have been used in previous models are not statistically significant bankruptcy predictors. Moreover, several market-driven variables are strongly related to bankruptcy probability, including market size, past stock returns, and the idiosyncratic standard deviation of stock returns. I propose a model that uses a combination of accounting ratios and market-driven variables to produce more accurate out-of-sample forecasts than alternative models.

Original Publication Citation

Forecasting Bankruptcy More Accurately: A Simple Hazard Model 2001, Journal of Business

Document Type

Peer-Reviewed Article

Publication Date

1999

Publisher

Journal of Business

Language

English

College

Marriott School of Business

Department

Finance

University Standing at Time of Publication

Full Professor

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