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Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Northern Cyprus, Turkey; Department of Economics, University of Pretoria, Pretoria, South Africa; Montpellier Business School, Montpellier, France.)

  • Elie Bouri

    (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha, Omaha, USA, and School of Business and Economics, Loughborough University, Leicestershire, UK.)

Abstract

Recent evidence, based on a linear framework, tend to suggest that while mortgage default risks can predict weekly and monthly housing returns of the United States, the same does not hold at the daily frequency. We however indicate that, the relationship between daily housing returns with mortgage default risks is in fact nonlinear, and hence a linear predictive model is misspecified. Given this, we use a k-th order nonparametric causality-in-quantiles test, which in turn, allows us to test for predictability over the entire conditional distribution of not only housing returns, but also volatility, by controlling for misspecification due to nonlinearity. Based on this model, we show that mortgage default risks do indeed predict housing returns and volatility, barring at the extreme upper end of the respective conditional distributions.

Suggested Citation

  • Mehmet Balcilar & Elie Bouri & Rangan Gupta & Mark E. Wohar, 2018. "Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration," Working Papers 201875, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201875
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    References listed on IDEAS

    as
    1. Nyakabawo, Wendy & Miller, Stephen M. & Balcilar, Mehmet & Das, Sonali & Gupta, Rangan, 2015. "Temporal causality between house prices and output in the US: A bootstrap rolling-window approach," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 55-73.
    2. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2014. "Housing and the Great Depression," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2966-2981, August.
    3. Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2016. "Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1005-1025, September.
    4. Plakandaras, Vasilios & Gupta, Rangan & Gogas, Periklis & Papadimitriou, Theophilos, 2015. "Forecasting the U.S. real house price index," Economic Modelling, Elsevier, vol. 45(C), pages 259-267.
    5. Norman Miller & Liang Peng, 2006. "Exploring Metropolitan Housing Price Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 33(1), pages 5-18, August.
    6. Lasse Bork & Stig V. Møller, 2018. "Housing Price Forecastability: A Factor Analysis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 46(3), pages 582-611, September.
    7. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    8. Kui-Wai Li, 2012. "A study on the volatility forecast of the US housing market in the 2008 crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 22(22), pages 1869-1880, November.
    9. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    10. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    11. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.
    12. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    13. Furkan Emirmahmutoglu & Mehmet Bacilar & Nicholas Apergis & Beatrice D. Simo-Kengne & Tsangyao Chang & Rangan Gupta, 2016. "Causal Relationship between Asset Prices and Output in the United States: Evidence from the State-Level Panel Granger Causality Test," Regional Studies, Taylor & Francis Journals, vol. 50(10), pages 1728-1741, October.
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    More about this item

    Keywords

    Mortgage Default Risks; Housing Returns and Volatility; Higher-Order Nonparametric Causality in Quantiles Test;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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