Default Estimation, Correlated Defaults, and Expert Information

Nicholas Kiefer ()

Working Papers from Cornell University, Center for Analytic Economics

Abstract: Capital allocation decisions are made on the basis of an assessment of creditworthiness. Default is a rare event for most segments of a bank's portfolio and data information can be minimal. Inference about default rates is essential for efficient capital allocation, for risk management and for compliance with the requirements of the Basel II rules on capital standards for banks. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using prior distributions assessed from industry experts. A maximum entropy approach is used to represent expert information. The binomial model, most common in applications, is extended to allow correlated defaults yet remain consistent with Basel II. The application shows that probabilistic information can be elicited from experts and econometric methods can be useful even when data information is sparse.

Date: 2008-04
New Economics Papers: this item is included in nep-ban, nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://cae.economics.cornell.edu/08-02.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ecl:corcae:08-02

Access Statistics for this paper

More papers in Working Papers from Cornell University, Center for Analytic Economics Contact information at EDIRC.
Bibliographic data for series maintained by ().