By Jones S., Hensher D.A. (eds.)
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Additional resources for Advances in credit risk modelling and corporate bankruptcy prediction
E. degrees of unobserved heterogeneity) and also to be correlated. We would want to be able to take this into account in some way in recognition that we are unlikely to capture all sources of explanation through the observed explanatory variables. , uncorrelated) parts. 5) (ignoring the t subscript for the present). À Á Uiq ¼ ß0 Xiq þ iq þ "iq ð2:5Þ where iq is a random term with zero mean whose distribution over firms and alternative outcomes depends in general on underlying parameters and observed data relating to outcome i and firm q; and "iq is a random term with zero mean that is IID over alternative outcomes and does not depend on underlying parameters or data.
1 if only checking account, 0 else. ¼ 1 if both savings and checking, 0 else. Derogatories and Other Credit Data MAJORDRG ¼ count of major derogatory reports (long delinquencies) from credit bureau. MINORDRG ¼ count of minor derogatories from credit bureau. TRADACCT ¼ number of open, active trade lines. ) Credit Bureau Data CREDOPEN CREDACTV CREDDEL30 CRED30DLNQ AVGRVBAL AVBALINC ¼ number of open and current trade accounts. ¼ number of active trades lines. ¼ number of trade lines 30 days past due at the time of the report.
Random utility theory (RUT) is a very general theory of how the analyst represents the preferences of agents where elements of information (known to the agents) are not observed by the analyst. While RUT has gained particular recognition within discrete-choice theory in recent years, RUT is not restricted to choice theory and can be implemented in a wide range of possible decision contexts. 4 However, econometric techniques to model heterogeneity have taken time to develop, despite a long-standing recognition that failure to do so can result in inferior model specification, spurious test results and invalid conclusions (Louviere et al.