Estimating Default Probabilities of CMBS Loans With Clustering and Heavy Censoring

Journal of Real Estate Finance and Economics, Vol. 37, No. 2, 2008

27 Pages Posted: 16 Nov 2007 Last revised: 3 Feb 2011

See all articles by Yildiray Yildirim

Yildiray Yildirim

Zicklin School of Business, Baruch College - The City University of New York

Abstract

This paper provides a comprehensive default estimation of commercial real estate loans with a complete commercial mortgage backed securites (CMBS) loan history database. Standard survival models assume that eventually every observation will experience the event. However, often there is a high proportion of censored observation in the sample. A mixture model is proposed to disentangle the probability of long-term survivorship and the timing of default occurrence. Loans within the same geographical area and property type tend to exhibit correlation in default incidence. A multilevel model is proposed to capture this correlation within and between clusters.

Keywords: multilevel mixture model, credit risk, CMBS

Suggested Citation

Yildirim, Yildiray, Estimating Default Probabilities of CMBS Loans With Clustering and Heavy Censoring. Journal of Real Estate Finance and Economics, Vol. 37, No. 2, 2008 . Available at SSRN: https://ssrn.com/abstract=1029701

Yildiray Yildirim (Contact Author)

Zicklin School of Business, Baruch College - The City University of New York ( email )

55 Lexington Ave., Box B13-260
New York, NY 10010
United States

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