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A DYNAMIC DISCRETE CHOICE MODEL OF REVERSE MORTGAGE BORROWER BEHAVIOR
Authors:Jason R Blevins  Wei Shi  Donald R Haurin  Stephanie Moulton
Institution:1. Department of Economics, The Ohio State University, U.S.A.;2. Institute for Economic and Social Research, Jinan University, China;3. John Glenn College of Public Affairs, The Ohio State University, U.S.A.

The authors acknowledge funding from The MacArthur Foundation, “Aging in Place: Analyzing the Use of Reverse Mortgages to Preserve Independent Living,” 2012–14, Stephanie Moulton, PI, and also from the Department of Housing and Urban Development, “Aging in Place: Managing the Use of Reverse Mortgages to Enable Housing Stability,” 2013–2015, Stephanie Moulton, PI. Shi acknowledges financial support from the National Natural Science Foundation of China under grant no. 71803062 and the 111 Project of China under grant no. B18026. We also thank Yonghong An, Peter Arcidiacono, Thomas Davidoff, Juan Carlos Escanciano, Paul Grieco, Phil Haile, Sukjin Han, Ashley Langer, Lance Lochner, Salvador Navarro, Joris Pinkse, David Rivers, Mark Roberts, Joseph Rossetti, Daniel Sacks, Kamila Sommer, Mauricio Varela, Tiemen Woutersen, and Ruli Xiao, and attendees of the 2016 Calgary Empirical Microeconomics conference, the 2017 AREUEA-ASSA Annual Meeting, 2017 Midwest Econometrics Group meeting, and the 2018 Asian Meeting of the Econometric Society as well as seminar participants at Indiana University, Ohio State Glenn College of Public Affairs, the Office of the Comptroller of the Currency, Pennsylvania State University, University of Arizona, University of Maryland, University of Texas at Austin, and University of Western Ontario for useful 4. comments.

Abstract:Using unique data on reverse mortgage borrowers in the Home Equity Conversion Mortgage (HECM) program, we semiparametrically estimate a dynamic discrete choice model of borrower behavior. Our estimator is based on a new identification result we develop for models with multiple terminating actions. We show that the per-period utility functions and discount factor are identified without restrictive, ad hoc identifying restrictions that lead to incorrect counterfactual implications. Our estimates provide insights about factors that influence HECM refinance, default, and termination decisions and allow us to quantify the trade-offs involved for proposed program modifications, such as income and credit requirements.
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