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Housing Price in Urban China as Determined by Demand and Supply

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Listed:
  • Gregory Chow

    (Princeton University)

  • Linlin Niu

    (Xiamen University)

Abstract

This paper studies the demand for and supply of residential housing in urban China since the late 1980s when the urban housing market became commercialized. Using aggregated annual data from 1987 to 2012 in a simultaneous equations framework we show that the rapid increase in the urban residential housing price can be well explained by the forces of demand and supply, with income determining demand and cost of construction affecting supply. We find the income elasticity of demand for urban housing to be about 1, the price elasticity of demand about -1.1, and the price elasticity of supply of the total housing stock about 0.5. The resulting long-run effect of income on urban housing price in elasticity terms is about 0.7, because the increase in income has shifted the demand curve outward more rapidly than the supply curve.

Suggested Citation

  • Gregory Chow & Linlin Niu, 2015. "Housing Price in Urban China as Determined by Demand and Supply," Working Papers 2015-03-09, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:002251
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    References listed on IDEAS

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    Cited by:

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    2. Weizeng Sun & Siqi Zheng & Yuming Fu, 2016. "Local Public Service Provision and Spatial Inequality in Chinese Cities," ERSA conference papers ersa16p799, European Regional Science Association.
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    4. John J. García & Daniel Mateo Cossio & Ricardo Mesa Urhan, 2017. "Efectos de mecanismos institucionales en el precio de la vivienda nueva en Medellín," Documentos de Trabajo de Valor Público 15658, Universidad EAFIT.
    5. Chunping Liu & Zhirong Ou, 2021. "What determines China's housing price dynamics? New evidence from a DSGE‐VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3269-3305, July.
    6. Bator Anne & Hervé Blanchard, 2024. "The housing price index and the number of housing units: a surprising co-movement in France," Economics Bulletin, AccessEcon, vol. 44(1), pages 490-499.
    7. García Rendon, John Jairo & Cossio Sepúlveda, Daniel Mateo & Mesa Urhan, Ricardo, 2018. "Efectos del canal del crŽdito sobre el precio de la vivienda nueva en Medell’n - Colombia || Credit channel effects on new residential property prices: Evidence from Medell’n, Colombia," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 104-127, Diciembre.
    8. Feng, Qu & Wu, Guiying Laura, 2015. "Bubble or riddle? An asset-pricing approach evaluation on China's housing market," Economic Modelling, Elsevier, vol. 46(C), pages 376-383.
    9. Shulin Shen & Yiyi Zhao & Jindong Pang, 2024. "Local Housing Market Sentiments and Returns: Evidence from China," The Journal of Real Estate Finance and Economics, Springer, vol. 68(3), pages 488-522, April.
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    11. Huifu Nong, 2024. "Integration and risk transmission across supply, demand, and prices in China’s housing market," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-28, June.
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    13. Wei Tian & Liugang Sheng & Hongyan Zhao, 2016. "Special Section: China's Growing Trade and its Role to the World Economy," Pacific Economic Review, Wiley Blackwell, vol. 21(1), pages 84-101, February.
    14. Chunping Liu & Zhirong Ou, 2017. "What determines China's housing price dynamics? New evidence from a DSGE-VAR," NBS Discussion Papers in Economics 2017/04, Economics, Nottingham Business School, Nottingham Trent University.
    15. John García Rendón & Carlos Esteban Posada Posada, 2022. "Determinantes de los precios relativos de la vivienda: Bogotá versus Medellín," Coyuntura Económica, Fedesarrollo, vol. 52, pages 93-105, December.
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    17. Yadi Zhu & Feng Chen & Ming Li & Zijia Wang, 2018. "Inferring the Economic Attributes of Urban Rail Transit Passengers Based on Individual Mobility Using Multisource Data," Sustainability, MDPI, vol. 10(11), pages 1-17, November.

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    More about this item

    Keywords

    housing demand; housing supply; urban housing price; China;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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