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Prepayment Behavior of Dutch Mortgagors: An Empirical Analysis

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  • Erwin Charlier
  • Arjan Van Bussel

Abstract

The suboptimal exercise of the prepayment option in a mortgage is relevant for mortgage pricing and the management of a mortgage portfolio. Construction of an accurate prepayment model requires quantification of driving factors such as seasoning, seasonality, refinance incentive and burnout. We focus on Dutch mortgages but also discuss the Dutch market in a European setting. Within the euro‐denominated MBS market, the Dutch market is often referred to as the benchmark market. In our application we include typical Dutch market and contract characteristics such as the annual penalty‐free prepayment of 10 to 20% of the original loan amount. We use loan‐level historical data on mortgages originated between January 1989 and June 1999 to estimate separate models for two popular redemption types: savings mortgages and interest‐only mortgages. In both models we allow for suboptimal prepayment behavior. The results clearly indicate that prepayment rates depend on interest rates and the age of the mortgage contract. Moreover, we find that burnout is an important element in describing the prepayment behavior of Dutch mortgagors.

Suggested Citation

  • Erwin Charlier & Arjan Van Bussel, 2003. "Prepayment Behavior of Dutch Mortgagors: An Empirical Analysis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(2), pages 165-204, June.
    • Handle: RePEc:bla:reesec:v:31:y:2003:i:2:p:165-204
    DOI: 10.1111/1540-6229.00062
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    Cited by:

    1. Leonardo Perotti & Lech A. Grzelak & Cornelis W. Oosterlee, 2024. "Modeling and Replication of the Prepayment Option of Mortgages including Behavioral Uncertainty," Papers 2410.21110, arXiv.org.
    2. Richard Chamboko & Jorge Miguel Bravo, 2020. "A Multi-State Approach to Modelling Intermediate Events and Multiple Mortgage Loan Outcomes," Risks, MDPI, vol. 8(2), pages 1-29, June.
    3. Matteo Bissiri & Riccardo Cogo, 2017. "Behavioral Value Adjustments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-37, December.
    4. Linda A. Toolsema & Jan P. A. M. Jacobs, 2007. "Why do prices rise faster than they fall? With an application to mortgage rates," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 701-712.
    5. Irfan Ahmed & Shahid Mahmood & Umar Farooq, 2012. "Determinant Attributes of Customer Choice of Banks, Supplying Mortgage Products," Journal of Economics and Behavioral Studies, AMH International, vol. 4(5), pages 287-296.
    6. Ebner, André, 2013. "A micro view on home equity withdrawal and its determinants: Evidence from Dutch households," Journal of Housing Economics, Elsevier, vol. 22(4), pages 321-337.
    7. Stefan Groot & Arjan Lejour, 2017. "Tax arbitrage incentives for mortgage prepayment behavior: Evidence from Dutch micro data," CPB Discussion Paper 350, CPB Netherlands Bureau for Economic Policy Analysis.
    8. Groot, Stefan P.T. & Lejour, Arjan M., 2018. "Financial incentives for mortgage prepayment behavior: Evidence from Dutch micro data," Journal of Housing Economics, Elsevier, vol. 41(C), pages 237-250.
    9. Yeorim Kim & Mauro Mastrogiacomo, 2024. "Residual-debt insurance and mortgage repayments," Working Papers 823, DNB.
    10. Stefan Groot & Arjan Lejour, 2017. "Tax arbitrage incentives for mortgage prepayment behavior: Evidence from Dutch micro data," CPB Discussion Paper 350.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    11. Emanuele Casamassima & Lech A. Grzelak & Frank A. Mulder & Cornelis W. Oosterlee, 2021. "Pricing and Hedging Prepayment Risk in a Mortgage Portfolio," Papers 2109.14977, arXiv.org, revised Oct 2021.
    12. Liang, Te-Hsin & Lin, Jian-Bang, 2014. "A two-stage segment and prediction model for mortgage prepayment prediction and management," International Journal of Forecasting, Elsevier, vol. 30(2), pages 328-343.

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