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Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach

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  • Hyung-Gun Kim
  • Kwong-Chin Hung
  • Sung Park

Abstract

This paper analyzes the determinants of housing prices in Hong Kong by using property transaction data of condominium units from Taikoo Shing, one of the largest real estate properties in Hong Kong. We use a hedonic pricing model for the empirical analysis and estimate the model by using the Box-Cox quantile regression method. The empirical results show that this method provides a more comprehensive description of housing price determinants. Housing prices and characteristics have a nonlinear relationship, and this relationship varies across all quantiles. In addition, the response of housing prices to various housing characteristics varies across quantiles. For example, an increase in the size of the gross floor area is more valued at higher quantiles. Other variables have differential effects on housing prices across the distribution of housing prices. We also perform a simple simulation for model predictability and show that our model outperforms other models which have been frequently used in the previous studies. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • 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.
    • Handle: RePEc:kap:jrefec:v:50:y:2015:i:2:p:270-287
    DOI: 10.1007/s11146-014-9456-1
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    Cited by:

    1. Ming Li & Guojun Zhang & Yunliang Chen & Chunshan Zhou, 2019. "Evaluation of Residential Housing Prices on the Internet: Data Pitfalls," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    2. Wilmar Alexander Cabrera-Rodríguez & Juan Sebastián Mariño-Montaña & Carlos Andrés Quicazán-Moreno, 2019. "Modelos hedónicos con efectos espaciales: una aproximación al cálculo de índices de precios de vivienda para Bogotá," Borradores de Economia 1072, Banco de la Republica de Colombia.
    3. 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.
    4. Cupal Martin & Sedlačík Marek & Michálek Jaroslav, 2019. "The Assessment of a Building’s insurable Value using Multivariate Statistics: The Case of the Czech Republic," Real Estate Management and Valuation, Sciendo, vol. 27(3), pages 81-96, September.
    5. 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.
    6. Antonio Nesticò & Marianna La Marca, 2020. "Urban Real Estate Values and Ecosystem Disservices: An Estimate Model Based on Regression Analysis," Sustainability, MDPI, vol. 12(16), pages 1-15, August.

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    More about this item

    Keywords

    Housing price; Hedonic price function; Box-Cox quantile regression; Model comparison; R31; C21; C29;
    All these keywords.

    JEL classification:

    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other

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