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An Early Assessment of Residential Mortgage Performance in China
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An Early Assessment of Residential Mortgage Performance in China

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  • Yongheng Deng
  • Della Zheng
  • Changfeng Ling

Abstract

The residential mortgage market becomes a financial engine for the booming residential housing development and sustained economic growth in China. Our study provides the first rigorous empirical analysis on the earlier performance of residential mortgage market in China based on a unique micro dataset of mortgage loan history collected from a major residential mortgage lender in China. We found that while the option theory fails to explain prepayment and default behavior in the residential mortgage market in China, other non-option theory related financial economic factors play major roles in determining the prepayment and default risks in China. We also found that borrower’s characteristics are significant in determining prepayment behavior, hence may be used as an effective tool for screening potential high risk borrowers in the loan origination process. Adopting a risk-based pricing in residential mortgage lending in China can improve the efficiency of the market, and enhance the credit availability to the most needed households, i.e., the younger households, blue-collar workers, lower income households, and help them become homeowners.

Suggested Citation

  • Yongheng Deng & Della Zheng & Changfeng Ling, 2004. "An Early Assessment of Residential Mortgage Performance in China," Working Paper 8603, USC Lusk Center for Real Estate.
    • Handle: RePEc:luk:wpaper:8603
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    References listed on IDEAS

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    Cited by:

    1. Bardhan, Ashok Deo & Kroll, Cynthia A., 2007. "Globalization and Real Estate: Issues, Implications, Opportunities," Fisher Center for Real Estate & Urban Economics, Research Reports qt8fm5j003, Fisher Center for Real Estate & Urban Economics, UC Berkeley.
    2. Kenneth K. Chow & Matthew S. Yiu & Charles Ka Yui Leung & Dickson C. Tam, 2008. "Does the DiPasquale-Wheaton Model Explain the House Price Dynamics in China Cities?," Working Papers 212008, Hong Kong Institute for Monetary Research.
    3. Weida Kuang & Chunlin Liu & Qun Wu & Hongchao Zeng, 2021. "How do Interest Rate Changes Affect Mortgage Curtailments? Evidence from China," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(S2), pages 395-427, September.
    4. Jing Li & Ying Xu, 2016. "Evaluating restrictive measures containing housing prices in China: A data envelopment analysis approach," Urban Studies, Urban Studies Journal Limited, vol. 53(12), pages 2654-2669, September.
    5. Jianmei Zhao & Lin Liu & Ruihan Liu, 2018. "How house price appreciation affects homeowners' labour force participation : Evidence from urban China," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(2), pages 233-252, April.
    6. Wu, Wenjie, 2012. "Does public investment spur the land market?: evidence from transport improvement in Beijing," LSE Research Online Documents on Economics 57918, London School of Economics and Political Science, LSE Library.
    7. Ye, Guangliang & Deng, Guoying & Li, Zhigang, 2014. "Mortgage rate and choice of mortgage length: A quasi-experimental evidence from Chinese transaction-level data," Journal of Housing Economics, Elsevier, vol. 25(C), pages 96-103.
    8. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    9. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    10. Mark Stephens, 2010. "Locating Chinese Urban Housing Policy in an International Context," Urban Studies, Urban Studies Journal Limited, vol. 47(14), pages 2965-2982, December.
    11. Gyourko, Joseph & Shen, Yang & Wu, Jing & Zhang, Rongjie, 2022. "Land finance in China: Analysis and review," China Economic Review, Elsevier, vol. 76(C).
    12. Yongheng Deng & Peng Liu, 2009. "Mortgage Prepayment and Default Behavior with Embedded Forward Contract Risks in China’s Housing Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 214-240, April.
    13. Eickholt, Mathias & Entrop, Oliver & Wilkens, Marco, 2014. "What makes individual investors exercise early? Empirical evidence from the fixed-income market," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe 15, University of Passau, Faculty of Business and Economics.
    14. Iris Claus & Les Oxley & Jie Chen & Xuehui Han, 2014. "The Evolution Of The Housing Market And Its Socioeconomic Impacts In The Post-Reform People'S Republic Of China: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 28(4), pages 652-670, September.
    15. Zheng, Siqi & Wu, Jing & Kahn, Matthew E. & Deng, Yongheng, 2012. "The nascent market for “green” real estate in Beijing," European Economic Review, Elsevier, vol. 56(5), pages 974-984.
    16. Leung, Charles Ka Yui & Chow, Kenneth & Yiu, Matthew & Tam, Dickson, 2010. "House Market in Chinese Cities: Dynamic Modeling, In-Sampling Fitting and Out-of-Sample Forecasting," MPRA Paper 27367, University Library of Munich, Germany.
    17. Agarwal, Sumit & Chomsisengphet, Souphala & Hassler, Olivier, 2005. "The impact of the 2001 financial crisis and the economic policy responses on the Argentine mortgage market," Journal of Housing Economics, Elsevier, vol. 14(3), pages 242-270, September.
    18. 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.
    19. Eickholt, Mathias & Entrop, Oliver & Wilkens, Marco, 2018. "What makes individual investors exercise early? Empirical evidence from non-tradable fixed-income products," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 318-334.

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