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Constructing a rental housing index and identifying market segmentation in the case of Beijing, China

Author

Listed:
  • Song, Zisheng

    (Department of Real Estate and Construction Management, Royal Institute of Technology)

  • Wilhelmsson, Mats

    (Department of Real Estate and Construction Management, Royal Institute of Technology)

  • Yang, Zan

    (Hang Lung Centre for Real Estate Studies Department of Construction Management Tsinghua University, Beijing, China)

Abstract

Although the rental market is relatively small in China, rental housing is an integral part of the housing market as a whole and plays a vital role in reducing pressure from the owner-occupied housing sector. In general, knowledge about the functioning of the rental market and rental dynamics over space and time is relatively limited. The rent index is a useful indicator of the variation of rent and the rental housing market dynamics. Therefore, the primary aim of this paper is to construct a rental-housing index by employing the hedonic model approach. Clustering analysis will be used to identify different rental housing market segmentations. The case study is the rental housing market in Beijing, China, over the period 2016-2018. In summary, we can conclude that a more scientific approach to segmenting the housing market better accounts for the heterogeneity in the market than traditional administrative boundaries.

Suggested Citation

  • Song, Zisheng & Wilhelmsson, Mats & Yang, Zan, 2020. "Constructing a rental housing index and identifying market segmentation in the case of Beijing, China," Working Paper Series 20/10, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    • Handle: RePEc:hhs:kthrec:2020_010
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    References listed on IDEAS

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    1. de Palma, Andre & Picard, Nathalie & Waddell, Paul, 2007. "Discrete choice models with capacity constraints: An empirical analysis of the housing market of the greater Paris region," Journal of Urban Economics, Elsevier, vol. 62(2), pages 204-230, September.
    2. Yong Tu & Hua Sun & Shi-Ming Yu, 2007. "Spatial Autocorrelations and Urban Housing Market Segmentation," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 385-406, April.
    3. Stephen Malpezzi, "undated". "Hedonic Pricing Models: A Selective and Applied Review," Wisconsin-Madison CULER working papers 02-05, University of Wisconsin Center for Urban Land Economic Research.
    4. Bradford Case & Henry O. Pollakowski & Susan M. Wachter, 1991. "On Choosing Among House Price Index Methodologies," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 286-307, September.
    5. Ghebreegziabiher Debrezion & Eric Pels & Piet Rietveld, 2007. "The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-analysis," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 161-180, August.
    6. Allen C. Goodman & Thomas G. Thibodeau, 2007. "The Spatial Proximity of Metropolitan Area Housing Submarkets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 35(2), pages 209-232, June.
    7. John F. Kain, 1962. "The Journey‐To‐Work As A Determinant Of Residential Location," Papers in Regional Science, Wiley Blackwell, vol. 9(1), pages 137-160, January.
    8. Craig A. Gallet, 2004. "Housing market segmentation: An application of convergence tests to Los Angeles region housing," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 38(3), pages 551-561, September.
    9. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    10. Ling-xiang HUANG & Li-jie CHEN & Jian-min HAO & Dong-chuan WANG? & Li-guo JIN & Di ZHAO, 2017. "Study On The Relationship Between Housing Price And Transportation Accessibility In Urban District Of Tianjin, China," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 12(2), pages 48-63, April.
    11. Ira Gary Peppercorn & Claude Taffin, 2013. "Rental Housing : Lessons from International Experience and Policies for Emerging Markets," World Bank Publications - Books, The World Bank Group, number 13117.
    12. Michael Brusco & Hans-Friedrich Köhn, 2009. "Clustering Qualitative Data Based on Binary Equivalence Relations: Neighborhood Search Heuristics for the Clique Partitioning Problem," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 685-703, December.
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    More about this item

    Keywords

    Rent Index; Hedonic Model; Cluster Analysis; Accessibility;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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