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The relationship between owner-occupied housing prices and rental housing rents: evidence from 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)

  • Zalejska-Jonsson, Agnieszka

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

Abstract

The relationship between housing prices or rents with other economic factors has been widely analysed. However, few studies use cross-sectional data to analyse the relationship between owner-occupied and rental housing sectors. This paper aims to develop a cross-sectional rent-price model and estimate the interconnected relationship between different market segments. Based on the transactional data of owner-occupied and rental housing in 2015–2018 in Beijing, China, we empirically conduct analyses of cross-sectional rent-price interconnectivity in total housing markets and segments such as housing size and school district. As expected, we find a bi-directional relationship between prices and rents in Beijing that goes in both directions, indicating that housing of different tenures substitute each other, and substitutional effects are significantly different across submarkets. Condominium prices have a more significant impact on rents than vice versa.

Suggested Citation

  • Song, Zisheng & Wilhelmsson, Mats & Zalejska-Jonsson, Agnieszka, 2022. "The relationship between owner-occupied housing prices and rental housing rents: evidence from Beijing, China," Working Paper Series 22/3, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    • Handle: RePEc:hhs:kthrec:2022_003
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    References listed on IDEAS

    as
    1. Dimitrios Staikos & Wenjun Xue, 2017. "What drives housing prices, rent and new construction in China," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 10(5), pages 662-686, October.
    2. Denise DiPasquale & William C. Wheaton, 1992. "The Markets for Real Estate Assets and Space: A Conceptual Framework," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(2), pages 181-198, June.
    3. Hill, Robert J. & Syed, Iqbal A., 2016. "Hedonic price–rent ratios, user cost, and departures from equilibrium in the housing market," Regional Science and Urban Economics, Elsevier, vol. 56(C), pages 60-72.
    4. Patrick Bayer & Kyle Mangum & James W. Roberts, 2021. "Speculative Fever: Investor Contagion in the Housing Bubble," American Economic Review, American Economic Association, vol. 111(2), pages 609-651, February.
    5. Lu, Xun & Su, Liangjun & White, Halbert, 2017. "Granger Causality And Structural Causality In Cross-Section And Panel Data," Econometric Theory, Cambridge University Press, vol. 33(02), pages 263-291, April.
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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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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