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Financing housing and house prices in China

Author

Listed:
  • Philip Arestis
  • Maggie Mo Jia

Abstract

Purpose - This paper aims to examine the evolution of house prices in China and especially the effects of different financing channels on China’s house prices. Design/methodology/approach - The author use the own theoretical framework and proceed to test the testable hypotheses by using the autoregressive distributed lag bounds test approach for cointegration analysis and the unrestricted error correction model. Quarterly time series data from Q1 2002 to Q2 2016 are used. Findings - The results suggest that in the short run, bank loans to real estate development and scale of shadow banking have significant positive effects on house prices. In the long run, the scale of shadow banking and disposable income affects house prices positively and significantly. Originality/value - This study provides more insights into how and to the extent different financing channels affect China’s house prices, particularly the impact of shadow banking on the house prices.

Suggested Citation

  • Philip Arestis & Maggie Mo Jia, 2019. "Financing housing and house prices in China," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 12(4), pages 445-461, December.
    • Handle: RePEc:eme:jfeppp:jfep-04-2019-0072
    DOI: 10.1108/JFEP-04-2019-0072
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    More about this item

    Keywords

    Central banking; Time-series models; Econometric modelling; China’s house prices; Shadow banking; Dual channel of housing finance; Time series analysis; C22; R31;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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