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| Forecasting Cross-Sections of Frailty-Correlated Default by Siem Jan Koopman of VU University Amsterdam & Tinbergen Institute, February 20, 2008 Abstract: We propose a novel econometric model for estimating and forecasting cross-sections of time-varying conditional default probabilities. The model captures the systematic variation in corporate default counts across e.g. rating and industry groups by using dynamic factors from a large panel of selected macroeconomic and financial data as well as common unobserved risk factors. All factors are statistically and economically significant and together capture a large part of the time-variation in observed default rates. In this framework we improve the out-of-sample forecasting accuracy associated with conditional default probabilities by about 10-35% in terms of Mean Absolute Error, particularly in years of default stress. Keywords: Non-Gaussian Panel Data, Common Factors, Unobserved Components, Forecasting Conditional Default Probabilities. Books Referenced in this Paper: (what is this?)
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