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House Price Index Construction in the Nascent Housing Market: The Case of China

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  • Jing Wu

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  • Yongheng Deng
  • Hongyu Liu

Abstract

Most existing house price index construction methods are developed mainly based on transaction data from the secondary housing market, and are not necessarily suitable for the nascent housing markets where a predominant portion of housing transactions are new units. Using the booming market in China as an example, we evaluate and compare the performances of three most common house price measurement methods in the newly-built housing sector, including the simple average method without quality adjustment, the matching approach with the repeat sales modeling framework, and the hedonic modeling approach. Our analyses suggest that the simple average method fails to account for the substantial complex-level quality changes over time of sales during our sample period, and the matching model fails to control for the effect of developers’ pricing behaviors when adopted in the newly-built sector, hence both are downward biased. Based on this finding, we apply a hedonic method, which allows us to control for both quality changes over time of sales and developers’ pricing behaviors, to 35 major newly-built housing markets and provide the first multi-city constant-quality house price index in China. The new index reveals that the current Chinese housing market is facing a greater risk of mispricing than reported by the existing official metrics. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Jing Wu & Yongheng Deng & Hongyu Liu, 2014. "House Price Index Construction in the Nascent Housing Market: The Case of China," The Journal of Real Estate Finance and Economics, Springer, vol. 48(3), pages 522-545, April.
  • Handle: RePEc:kap:jrefec:v:48:y:2014:i:3:p:522-545
    DOI: 10.1007/s11146-013-9416-1
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    References listed on IDEAS

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    Cited by:

    1. Hanming Fang & Quanlin Gu & Wei Xiong & Li-An Zhou, 2016. "Demystifying the Chinese Housing Boom," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 105-166.
    2. Kaiji Chen & Yi Wen, 2017. "The Great Housing Boom of China," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(2), pages 73-114, April.
    3. Wu, Jing & Gyourko, Joseph & Deng, Yongheng, 2016. "Evaluating the risk of Chinese housing markets: What we know and what we need to know," China Economic Review, Elsevier, vol. 39(C), pages 91-114.
    4. Wu, Guiying Laura & Feng, Qu & Li, Pei, 2015. "Does local governments’ budget deficit push up housing prices in China?," China Economic Review, Elsevier, vol. 35(C), pages 183-196.
    5. Diewert, W. Erwin & Shimizu, Chihiro, 2016. "Hedonic regression models for Tokyo condominium sales," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 300-315.
    6. Wang, Zhi & Zhang, Qinghua, 2014. "Fundamental factors in the housing markets of China," Journal of Housing Economics, Elsevier, vol. 25(C), pages 53-61.
    7. Shi, Song & Yang, Zan & Tripe, David & Zhang, Huan, 2015. "Uncertainty and new apartment price setting: A real options approach," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 574-591.
    8. Gong, Yunlong & Hu, Jinxing & Boelhouwer, Peter J., 2016. "Spatial interrelations of Chinese housing markets: Spatial causality, convergence and diffusion," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 103-117.
    9. repec:eee:forpol:v:91:y:2018:i:c:p:84-93 is not listed on IDEAS
    10. Zhou, Zhengyi, 2016. "Overreaction to policy changes in the housing market: Evidence from Shanghai," Regional Science and Urban Economics, Elsevier, vol. 58(C), pages 26-41.
    11. Jia, Pengfei & Lim, King Yoong, 2018. "Tax Policy and Toxic Housing Bubbles in China," MPRA Paper 86576, University Library of Munich, Germany.
    12. Porfirio Guevara & Robert J. Hill & Michael Scholz, 2015. "Hedonic Indexes for Public and Private Housing in Costa Rica," Graz Economics Papers 2015-05, University of Graz, Department of Economics.
    13. Jing Wu & Yongheng Deng, 2015. "Intercity Information Diffusion and Price Discovery in Housing Markets: Evidence from Google Searches," The Journal of Real Estate Finance and Economics, Springer, vol. 50(3), pages 289-306, April.
    14. Yongheng Deng & Randall Morck & Jing Wu & Bernard Yeung, 2015. "China’s Pseudo-monetary Policy," Review of Finance, European Finance Association, vol. 19(1), pages 55-93.
    15. repec:bla:pacecr:v:22:y:2017:i:3:p:276-292 is not listed on IDEAS
    16. Wu, Jing & Gyourko, Joseph & Deng, Yongheng, 2015. "Real estate collateral value and investment: The case of China," Journal of Urban Economics, Elsevier, vol. 86(C), pages 43-53.
    17. Zhang, Lei & Yi, Yimin, 2017. "Quantile house price indices in Beijing," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 85-96.
    18. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    19. repec:eee:chieco:v:48:y:2018:i:c:p:205-222 is not listed on IDEAS
    20. Yongheng Deng & Eric Girardin & Roselyne Joyeux & Shuping Shi, 2017. "Did bubbles migrate from the stock to the housing market in China between 2005 and 2010?," Pacific Economic Review, Wiley Blackwell, vol. 22(3), pages 276-292, August.
    21. Cao, Xiaping & Huang, Bihong & Lai, Rose Neng, 2018. "The Impact of Exogenous Demand Shock on the Housing Market: Evidence from the Home Purchase Restriction Policy in the People’s Republic of China," ADBI Working Papers 824, Asian Development Bank Institute.

    More about this item

    Keywords

    House price index; Hedonic method; Quality change; Nascent housing market; C43; C81; R31;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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