Multi-Period Corporate Failure Prediction with Stochastic Covariates

43 Pages Posted: 12 Jan 2005

See all articles by Darrell Duffie

Darrell Duffie

Stanford University - Graduate School of Business; National Bureau of Economic Research (NBER)

Ke Wang

Board of Governors of the Federal Reserve System

Multiple version iconThere are 2 versions of this paper

Date Written: December 17, 2003

Abstract

We provide maximum likelihood estimators of term structures of conditional probabilities of bankruptcy over relatively long time horizons, incorporating the dynamics of firm-specific and macroeconomic covariates. We find evidence in the U.S. industrial machinery and instruments sector, based on over 28,000 firm-quarters of data spanning 1971 to 2001, of significant dependence of the level and shape of the term structure of conditional future bankruptcy probabilities on a firm's distance to default (a volatility-adjusted measure of leverage) and on U.S. personal income growth, among other covariates. Variation in a firm's distance to default has a greater relative effect on the term structure of future failure hazard rates than does a comparatively sized change in U.S. personal income growth, especially at dates more than a year into the future.

Suggested Citation

Duffie, James Darrell and Wang, Ke, Multi-Period Corporate Failure Prediction with Stochastic Covariates (December 17, 2003). AFA 2005 Philadelphia Meetings Paper. Available at SSRN: https://ssrn.com/abstract=647862 or http://dx.doi.org/10.2139/ssrn.647862

James Darrell Duffie (Contact Author)

Stanford University - Graduate School of Business ( email )

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National Bureau of Economic Research (NBER)

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Ke Wang

Board of Governors of the Federal Reserve System ( email )

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