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Quantile Regression Estimates of Hong Kong Real Estate Prices

Author

Listed:
  • Stephen Mak

    (Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, bssmak@inet.polyu.edu.hk)

  • Lennon Choy

    (Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, bslennon@polyu.edu.hk)

  • Winky Ho

    (Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, trswinky@inet.polyu.edu.hk)

Abstract

Linear regression is a statistical tool used to model the relation between a set of housing characteristics and real estate prices. It estimates the mean value of the response variable, given levels of the predictor variables. The quantile regression approach complements the least squares by identifying how differently real estate prices respond to a change in one unit of housing characteristic at different quantiles, rather than estimating the constant regression coefficient representing the change in the response variable produced by a one-unit change in the predictor variable associated with that coefficient. It estimates the implicit price for each characteristic across the distribution of prices and allows buyers of higher-priced properties to behave differently from buyers of lower-priced properties, even if they are within one single housing estate. Thus, it provides a better explanation of the real-world phenomenon and offers a more comprehensive picture of the relationship between housing characteristics and prices.

Suggested Citation

  • Stephen Mak & Lennon Choy & Winky Ho, 2010. "Quantile Regression Estimates of Hong Kong Real Estate Prices," Urban Studies, Urban Studies Journal Limited, vol. 47(11), pages 2461-2472, October.
    • Handle: RePEc:sae:urbstu:v:47:y:2010:i:11:p:2461-2472
    DOI: 10.1177/0042098009359032
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Lei, 2016. "Flood hazards impact on neighborhood house prices: A spatial quantile regression analysis," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 12-19.
    2. Zahirovich-Herbert, Velma & Gibler, Karen M., 2014. "The effect of new residential construction on housing prices," Journal of Housing Economics, Elsevier, vol. 26(C), pages 1-18.
    3. Hyung-Gun Kim & Kwong-Chin Hung & Sung Park, 2015. "Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(2), pages 270-287, February.
    4. Yang, Linchuan & Chau, K.W. & Wang, Xu, 2019. "Are low-end housing purchasers more willing to pay for access to basic public services? Evidence from China," Research in Transportation Economics, Elsevier, vol. 76(C).
    5. Zhang, Lei & Leonard, Tammy, 2014. "Neighborhood impact of foreclosure: A quantile regression approach," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 133-143.
    6. Lin, Jen-Jia & Cheng, Yu-Chun, 2016. "Access to jobs and apartment rents," Journal of Transport Geography, Elsevier, vol. 55(C), pages 121-128.
    7. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    8. Marcelo Cajias & Philipp Freudenreich & Anna Heller & Wolfgang Schaefers, 2018. "Censored Quantile Regressions and the Determinants of Real Estate Liquidity," ERES eres2018_203, European Real Estate Society (ERES).
    9. Heiko Kirchhain & Jan Mutl & Joachim Zietz, 2020. "The Impact of Exogenous Shocks on House Prices: the Case of the Volkswagen Emissions Scandal," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 587-610, May.
    10. Haizhen Wen & Zaiyuan Gui & Chuanhao Tian & Yue Xiao & Li Fang, 2018. "Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China," Sustainability, MDPI, vol. 10(7), pages 1-23, June.
    11. Alan T. K. Wan & Shangyu Xie & Yong Zhou, 2017. "A varying coefficient approach to estimating hedonic housing price functions and their quantiles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(11), pages 1979-1999, August.
    12. Zhang, Lei & Yi, Yimin, 2017. "Quantile house price indices in Beijing," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 85-96.
    13. repec:grz:wpaper:2015-09 is not listed on IDEAS

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