Abstract

http://ssrn.com/abstract=2029670
 


 



Competing Risks Models Using Mortgage Duration Data Under the Proportional Hazards Assumption


Mark Yuying An


Federal National Mortgage Association (Fannie Mae); Duke University

Zhikun Qi


affiliation not provided to SSRN

March 27, 2012

Journal of Real Estate Research, Vol. 34, No. 1, 2012

Abstract:     
This paper demonstrates two important results related to the estimation of a competing risks model under the proportional hazards assumption with grouped duration data, a model that has become the canonical model for the termination of mortgages with prepayment and default as two competing risks. First, the model with non-parametric baseline hazards is unidentifiable with only grouped mortgage duration data. Therefore, assumption on the functional form of the baseline hazard is necessary for any meaningful inference. Second, under some parametric assumptions such as piece-wise constant baseline hazards, the sample likelihood function has an explicit analytical form. Therefore, there is no need for the approximation formula widely adopted in the previous literature. Both Monte Carlo simulations and actual mortgage data are used to demonstrate the adverse impact of the approximation.

Number of Pages in PDF File: 26

Keywords: proportional hazards, competing risks

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Date posted: March 28, 2012  

Suggested Citation

An, Mark Yuying and Qi, Zhikun, Competing Risks Models Using Mortgage Duration Data Under the Proportional Hazards Assumption (March 27, 2012). Journal of Real Estate Research, Vol. 34, No. 1, 2012. Available at SSRN: http://ssrn.com/abstract=2029670

Contact Information

Mark Yuying An (Contact Author)
Federal National Mortgage Association (Fannie Mae) ( email )
3900 Wisconsin Avenue, NW
Mail Stop 1H3N-01
Washington, DC 20016-2892
United States
(202) 752-8442 (Phone)
(202) 752-5460 (Fax)
Duke University ( email )
Box 90097
207 Social Sciences
Durham, NC 27708-0097
United States
(919) 660-1809 (Phone)
(919) 684-8974 (Fax)
Zhikun Qi
affiliation not provided to SSRN ( email )
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