Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk

27 Pages Posted: 3 Mar 2006

See all articles by Matthew T. Jones

Matthew T. Jones

International Monetary Fund (IMF) - Monetary and Exchange Affairs Department

Date Written: November 2005

Abstract

This paper outlines a way to estimate transition matrices for use in credit risk modeling with a decades-old methodology that uses aggregate proportions data. This methodology is ideal for credit-risk applications where there is a paucity of data on changes in credit quality, especially at an aggregate level. Using a generalized least squares variant of the methodology, this paper provides estimates of transition matrices for the United States using both nonperforming loan data and interest coverage data. The methodology can be employed to condition the matrices on economic fundamentals and provide separate transition matrices for expansions and contractions, for example. The transition matrices can also be used as an input into other credit-risk models that use transition matrices as a basic building block.

Keywords: Markov transition matrix, credit risk, nonperforming loans, interest coverage

JEL Classification: C13

Suggested Citation

Jones, Matthew Thomas, Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk (November 2005). IMF Working Paper No. 05/219, Available at SSRN: https://ssrn.com/abstract=888088

Matthew Thomas Jones (Contact Author)

International Monetary Fund (IMF) - Monetary and Exchange Affairs Department ( email )

700 19th Street NW
Washington, DC 20431
United States

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