Research article

The measurement of financial support for real estate and house price bubbles and their dynamic relationship: An empirical study based on 31 major cities in China

  • Received: 30 December 2023 Revised: 27 March 2024 Accepted: 07 April 2024 Published: 16 April 2024
  • JEL Codes: JELCodes: C12, C23

  • In recent years, China's real estate prices have continued to rise, preventing the bursting of the house price bubble, and the various risks it triggers has become an important issue that governments at all levels have to face. In this paper, the backward sup ADF (BSADF) method was used to dynamically portray the evolution of real estate price bubbles in 31 large and medium-sized cities in China over a period of 11 years, from 2013 to 2021, and the dynamic relationship between the degree of financial support for real estate (hereinafter referred to as financial support) and house price bubbles in cities was investigated by employing a panel vector autoregressive (PVAR) model with panel data. The results showed that: Multiple cyclical bubbles significantly existed in the real estate markets of the cities during the study period, and in general, house price bubbles appeared earlier in the more economically developed regions than in the less economically developed regions and have spread to the less economically developed regions. Financial support contributed to house price bubbles, supporting the theory of excessive financial support. Furthermore, the results of the sub-sample showed that financial support contributed most strongly to house price bubbles in cities in the northern region.

    Citation: Ying Gao, Hui Yang. The measurement of financial support for real estate and house price bubbles and their dynamic relationship: An empirical study based on 31 major cities in China[J]. National Accounting Review, 2024, 6(2): 195-219. doi: 10.3934/NAR.2024009

    Related Papers:

  • In recent years, China's real estate prices have continued to rise, preventing the bursting of the house price bubble, and the various risks it triggers has become an important issue that governments at all levels have to face. In this paper, the backward sup ADF (BSADF) method was used to dynamically portray the evolution of real estate price bubbles in 31 large and medium-sized cities in China over a period of 11 years, from 2013 to 2021, and the dynamic relationship between the degree of financial support for real estate (hereinafter referred to as financial support) and house price bubbles in cities was investigated by employing a panel vector autoregressive (PVAR) model with panel data. The results showed that: Multiple cyclical bubbles significantly existed in the real estate markets of the cities during the study period, and in general, house price bubbles appeared earlier in the more economically developed regions than in the less economically developed regions and have spread to the less economically developed regions. Financial support contributed to house price bubbles, supporting the theory of excessive financial support. Furthermore, the results of the sub-sample showed that financial support contributed most strongly to house price bubbles in cities in the northern region.



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    [1] Allen F, Gale D (1998) Optimal financial crises. J Financ 53: 1245–1284. https://doi.org/10.1111/0022-1082.00052 doi: 10.1111/0022-1082.00052
    [2] Chen X, Funke M (2013) Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles. Natl Inst Econ Rev 223: R39–R48. https://doi.org/10.1177/002795011322300105 doi: 10.1177/002795011322300105
    [3] Guo WW (2016a) Study on the Measurement of China's Multi-Level House Price Bubble and Its Driving Factors-Along with the Effect of the Implementation of China's Real Estate Control Policies. Economist 10: 30–37.
    [4] Guo WW (2016b) Global stock market bubble measurement and its dependent structure analysis. Journal of Guangdong University of Finance and Economics 4: 61–71.
    [5] Homm U, Breitung J (2012) Testing for speculative bubbles in stock markets: a comparison of alternative methods. J Financ Econom 10: 198–231. https://doi.org/10.1093/jjfinec/nbr009 doi: 10.1093/jjfinec/nbr009
    [6] Han DZ (2005) An Empirical Study of Real Estate Bubbles Based on the West Model-Taking Beijing, Shanghai and Shenzhen as an Example. Modern Economic Science 27: 6–11+108.
    [7] Holtz-Eakin D, Newey W, Rosen HS (1988) Estimating vector autoregressions with panel data. Econometrica 56: 1371–1395. https://doi.org/10.2307/1913103 doi: 10.2307/1913103
    [8] Levin EJ, Wright RE (1997) The impact of speculation on house prices in the United Kingdom. Econ Model 14: 567–585. https://doi.org/10.1016/S0264-9993(97)00008-4 doi: 10.1016/S0264-9993(97)00008-4
    [9] Liu HY, Jiang PY (2014) Study on the formation mechanism of urban house price bubbles and inter-city differences in China. Price Theory and Practice 8: 20–25. https://doi.org/10.19851/j.cnki.cn11-1010/f.2014.08.006 doi: 10.19851/j.cnki.cn11-1010/f.2014.08.006
    [10] Liu Q (2023) Bank credit and property bubbles. https://doi.org/10.27270/d.cnki.gsxau.2022.000087
    [11] Liu TY, Chang HL, Su CW, et al. (2016) China's House Bubble Burst? Econ Transit 24: 361–389. https://doi.org/10.1111/ecot.12093 doi: 10.1111/ecot.12093
    [12] Li WZ, Qu B (2002) Research on the Construction of an Early Warning system of Land Bubble. Journal of Shanxi University of Finance and Economics 24: 99–101. https://doi.org/10.3969/j.issn.1007-9556.2002.04.027 doi: 10.3969/j.issn.1007-9556.2002.04.027
    [13] Mishkin FS (1996) Understanding financial crises: a developing country perspective. https://doi.org/10.3386/w5600
    [14] Phillips PCB, Wu Y, Yu J (2011) Explosive Behavior in the 1990s NASDAQ: When Did Exuberance Escalate Asset Values? Int Econ Rev 52: 201–226. https://doi.org/10.1111/j.1468-2354.2010.00625.x doi: 10.1111/j.1468-2354.2010.00625.x
    [15] Phillips PCB, Shi S, Yu J (2015a) Testing for Multiple Bubbles Ⅰ: Historical Episodes of Exuberance and Collapse in the SP500. Int Econ Rev 56: 1043–1078. https://doi.org/10.1111/iere.12132 doi: 10.1111/iere.12132
    [16] Phillips PCB, Shi S, Yu J (2015b) Testing for Multiple Bubbles: Limit Theory of Real Time Detectors. Int Econ Rev 56: 1079–1134. https://doi.org/10.1111/iere.12131 doi: 10.1111/iere.12131
    [17] Renaud B (1995) The 1985–1994 global real estate cycle: its causes and consequences.
    [18] Shi SP (2013) Specification sensitivities in the Markov-switching unit root test for bubbles. Empir Econ 45: 697–713. https://doi.org/10.1007/s00181-012-0635-8 doi: 10.1007/s00181-012-0635-8
    [19] Shen Y, Li BY, Zhang JY (2019) Urban house price bubbles and financial stability—An empirical study based on the PVAR model in 35 large and medium-sized cities in China. Contemporary Finance and Economics 4: 62–74.
    [20] Shi XJ, Zhou Y (2014) Switching AR model for property bubble testing. Systems Engineering Theory and Practice 34: 676–682.
    [21] Wang BJ, Feng ZH (2012) Excessive Financial Support, Property Price Bubble and Monetary Policy Effectiveness-Taking Beijing, Tianjin, Shanghai and Chongqing as Examples. Journal of Shanxi University of Finance and Economics 34: 48–57.
    [22] Wang JB, Xia BB, Li B (2022) Research on the Influence of Land Finance and Financial Support on House Price Bubbles—Based on the Dual Perspective of Institutional and Market Factors. Modernization of Management 42: 48–52.
    [23] Yuan DY, Song XN (2008) Measurement of regional house price bubbles and spatial contagion in China: An empirical analysis based on panel data of 35 large and medium-sized cities from 2001 to 2005. Journal of Shanghai University of Finance and Economics 10:80–87.
    [24] Zhou JK (2006) Research on excessive financial support and property bubble.
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