Forecasting Bankruptcy More Accurately: A Simple Hazard Model

Abstract

I argue that hazard models are more appropriate than single-period models for forecasting bankruptcy. Single-period models are inconsistent, while hazard models produce consistent estimates. I describe a simple technique for estimating a discrete-time hazard model. I find that about half of the accounting ratios that have been used in previous models are not statistically significant. Moreover, market size, past stock returns, and idiosyncratic returns variability are all strongly related to bankruptcy. I propose a model that uses both accounting ratios and market-driven variables to produce out-of-sample forecasts that are more accurate than those of alternative models. Copyright 2001 by University of Chicago Press.