Multi-Period Corporate Failure Prediction with Stochastic Covariates
Darrell Duffie and
Ke Wang
No 10743, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: C41 E44 G33 (search for similar items in EconPapers)
Date: 2004-09
New Economics Papers: this item is included in nep-bec
Note: CF AP
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Citations: View citations in EconPapers (19)
Published as Duffie, Darrell, Leandro Saita and Ke Wang. "Multi-Period Corporate Default Prediction with Stochastic Covariates,." Journal of Financial Economics 83 (2007): 635-665.
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Working Paper: Multi-Period Corporate Failure Prediction With Stochastic Covariates (2004)
Working Paper: Multi-Period Corporate Failure Prediction With Stochastic Covariates (2004)
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