Working Paper: NBER ID: w11962
Authors: Darrell Duffie; Ke Wang; Leandro Saita
Abstract: We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of firm-specific and macroeconomic covariates. For U.S. Industrial firms, based on over 390,000 firm-months of data spanning 1979 to 2004, the level and shape of the estimated term structure of conditional future default probabilities depends on a firm's distance to default (a volatility-adjusted measure of leverage), on the firm's trailing stock return, on trailing S&P 500 returns, and on U.S. interest rates, among other covariates. Distance to default is the most influential covariate. Default intensities are estimated to be lower with higher short-term interest rates. The out-of-sample predictive performance of the model is an improvement over that of other available models.
Keywords: Corporate Default; Stochastic Covariates; Maximum Likelihood Estimation
JEL Codes: C41; G33; E44
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| distance to default (Y20) | default risk (G33) |
| short-term interest rates (E43) | default risk (G33) |
| distance to default (Y20) | default intensity (Y20) |
| variations in distance to default (C29) | future default hazard rates (E43) |
| leverage targeting and mean reversion in macroeconomic performance (E61) | term structure of default probabilities (G33) |