Detecting bubbles in China’s regional housing markets

Abstract

This study employs the supremum augmented Dicker–Fuller (SADF) and generalized supremum ADF (GSADF) tests to examine the Chinese housing market for the presence of bubbles from 2005 to 2016. We first employed a conventional right-tailed unit root test, and the results clearly suggest that housing prices showed no explosive behaviour in most cities. We further used SADF and GSADF, and the results suggest that most major cities in China experienced bubbles, with the longest bubble period from 2015 to the present, which is still ongoing. The SADF and GSADF results are robust after considering the effects of interest and mortgage rates. Moreover, the northern and southern regions experienced the largest number of bubbles, with over 1.1 bubbles for each city, while the western region experienced the fewest bubbles over the last decade. The western region had bubbles with the shortest durations, around 4 months, than other regions, where the average duration was at least 5 months. This study provides potentially valuable insights into the Chinese housing market and offers important policy implications.

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Notes

  1. 1.

    For full ranking, please visit http://www.knightfrank.com.hk/news/knight-frank-global-residential-cities-index-q1-2016-09625.aspx.

  2. 2.

    Engsted (2016) discuss Eugene Fama and Robert Shiller’s views on bubbles.

  3. 3.

    “Appendix” contains the detailed results for the other cities.

  4. 4.

    The minimum bubble lengths for Beijing, Hangzhou, Hohhot, Zhengzhou, and Xinning are 2.02, 2.03, 2.03, 2.03, and 2.00, respectively.

  5. 5.

    We understood there are still some factors, such as tax rates, maintenance costs, which could affect the fundamental value of house markets [see, e.g. the discussion in, e.g. Poterba (1992)]. Nonetheless, unavailability of data in Chinese house markets has restricted us to consider them in our analysis.

  6. 6.

    Following Caspi (2016), we use the difference between expected inflation and the People’s Bank of China rate.

  7. 7.

    We also compute the descriptive statistics for the bubbles in each city and report the results in Table 5 in “Appendix.” Interestingly, Zhengzhou experienced the most bubbles during the study period. This city does not have a major increase in its house prices, and policymakers do not frequently mention it about house price bubbles.

  8. 8.

    The “negative bubble” is defined as the average price during a given bubble period is smaller than the price at bubble start date, while the “positive bubble” is defined as the average price during a given bubble period is larger than the price at bubble start date.

References

  1. Allen F, Gale D (1999) Bubbles, crises, and policy. Oxf Rev Econ Policy 15(3):9–18

    Article  Google Scholar 

  2. Blanchard OJ, Watson MW (1982) Bubbles, rational expectations and financial markets. In: NBER Working Paper No. 945

  3. Campbell JY, Shiller RJ (1986) The dividend-price ratio and expectations of future dividends and discount factors. Rev Financ Stud 1(3):195–228

    Article  Google Scholar 

  4. Campbell J, Perron P (1991) Pitfalls and opportunities: what macroeconomists should know about unit roots. In: NBER Working Paper No. 100

  5. Case KE, Shiller RJ (2003) Is there a bubble in the housing market? Brookings Paper Econ Act 2:299–362

    Article  Google Scholar 

  6. Caspi I (2016) Testing for a housing bubble at the national and regional level: the case of Israel. Empir Econ 2:1–34

    Google Scholar 

  7. Clark SP, Coggin TD (2011) Was there a us house price bubble? an econometric analysis using national and regional panel data. Q Rev Econ Financ 51(2):189–200

    Article  Google Scholar 

  8. Diba BT, Grossman HI (1988) Explosive rational bubbles in stock prices? Am Econ Rev 78:520–530

    Google Scholar 

  9. Engsted T (2016) Fama on bubbles. J Econ Surv 30(2):370–376

    Article  Google Scholar 

  10. Engsted T, Nielsen B (2012) Testing for rational bubbles in a co-explosive vector autoregression. Economet J 15(2):226–254

    Article  Google Scholar 

  11. Etienne XL, Irwin SH, Garcia P (2014) Bubbles in food commodity markets: four decades of evidence. J Int Money Financ 42:129–155

    Article  Google Scholar 

  12. Evans GW (1991) Pitfalls in testing for explosive bubbles in asset prices. Am Econ Rev 81:922–930

    Google Scholar 

  13. Gilbert CL (2010) Speculative influences on commodity futures prices 2006–2008. In: United Nations conference on trade and development Discussion Paper No. 197

  14. Gómez-González JE, Ojeda-Joya JN, Rey-Guerra C, Sicard N (2015) Testing for bubbles in Colombian housing market: a new approach. Revista Desarrollo y Sociedad 75:197–222

    Article  Google Scholar 

  15. Gomez-Gonzalez JE, Ojeda-Joya JN, Franco JP, Torres JE (2017) Asset price bubbles: existence, persistence and migration. S Afr J Econ 85(1):52–67

    Article  Google Scholar 

  16. Gürkaynak R (2008) Econometric tests of asset price bubbles: taking stock. J Econ Surv 22(1):166–186

    Article  Google Scholar 

  17. Hamilton JD, Whiteman CH (1985) The observable implications of self-fulfilling expectations. J Monet Econ 16(3):353–373

    Article  Google Scholar 

  18. Himmelberg C, Mayer C, Sinai T (2005) Assessing high house prices: bubbles, fundamentals and misperceptions. J Econ Perspect 19(4):67–92

    Article  Google Scholar 

  19. Homm U, Breitung J (2012) Testing for speculative bubbles in stock markets: a comparison of alternative methods. J Financ Economet 10(1):198–231

    Article  Google Scholar 

  20. Igan D, Kang H (2011) Do loan-to-value and debt-to-income limits work? evidence from Korea. In: IMF Working Papers, vol: 1–34

  21. Jordà Ò, Schularick M, Taylor AM (2015) Leveraged bubbles. J Monet Econ 76:S1–S20

    Article  Google Scholar 

  22. Kivedal BK (2013) Testing for rational bubbles in the US housing market. J Macroecon 38:369–381

    Article  Google Scholar 

  23. Krainer J, Wei C (2004) House price and fundamental value. FRBSF Economic Letter, Federal Reserve Bank of San Francisco, Issue Oct1

  24. McCarthy J, Peach RW (2004) Are home prices the next bubbles. Federal Reserve Bank of New York. Econ Pol Rev 10:1–17

    Google Scholar 

  25. Okina K, Shirakawa M, Shiratsuka S (2001) The asset price bubbles and monetary policy: Japan’s experience in the late 1980s and the lessons. Monet Econ Stud (Spec Edit) 19(2):395–450

    Google Scholar 

  26. Ono A, Uchida H, Udell GF, Uesugi I (2016) Lending pro-cyclicality and macro-prudential policy: evidence from Japanese LTV ratios. In: HIT-REFINEWorking Paper Series 41, Institute of Economic Research, Hitotsubashi University

  27. Pavlidis E, Yusupova A, Paya I, Peel D, Martínez-García E, Mack A, et al. (2015) Episodes of exuberance in housing markets: in search of the smoking gun. J Real Estate Finance Econ: 1–31

  28. Phillips PCB, Yu J (2011) Dating the timeline of financial bubbles during the subprime crisis. Quant Econ 2:455–491

    Article  Google Scholar 

  29. 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

    Article  Google Scholar 

  30. Phillips PCB, Shi SP, Yu J (2012) Testing for multiple bubbles. Cowles Foundation for Research in Economics, Yale University, Paper No: 1843

  31. Phillips PCB, Shi S, Yu J (2015) Testing for multiple bubbles: historical episodes of exuberance and collapse in the S&P 500. Int Econ Rev 56(4):1043–1078

    Article  Google Scholar 

  32. Poterba JM (1992) Taxation and housing: old questions, new answers. Am Econ Rev 82(2):237–242

    Google Scholar 

  33. Ren Y, Xiong C, Yuan Y (2012) House price bubbles in China. China Econ Rev 23(4):786–800

    Article  Google Scholar 

  34. Shi S, Valadkhani A, Smyth R, Vahid F (2016) Dating the timeline of house price bubbles in Australian capital cities. Econ Rec 92(299):590–605

    Article  Google Scholar 

  35. Shiller RJ (2005) Irrational exuberance. Princeton University Press, Princeton

    Google Scholar 

  36. Smith VL, Suchanek GL, Williams AW (1988) Bubbles, crashes, and endogenous expectations in experimental spot asset markets. Econometrica 56(5):1119–1151

    Article  Google Scholar 

  37. Taipalus K (2012) Detecting asset price bubbles with time-series methods. Bank of Finland, Helsinki

    Google Scholar 

  38. Vissing-Jorgensen A (2003) Perspectives on behavioral finance: does “irrationality” disappear with wealth? evidence from expectations and actions. NBER Macroecon Ann 18:139–194

    Article  Google Scholar 

  39. Wong E, Fong T, Li K, Choi H (2011) Loan-to-value ratio as a macroprudential tool: Hong Kong’s experience and cross-country evidence. In: Hong Kong Monetary Authority Working Paper No. 01/2011

  40. Yiu MS, Yu J, Jin L (2013) Detecting bubbles in Hong Kong residential property market. J Asian Econ 28:115–124

    Article  Google Scholar 

Download references

Acknowledgements

The author is grateful to the coordinating editor, Robert M. Kunst, and to the two anonymous referees for their helpful comments and insights. Remaining errors, however, are my own.

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Correspondence to Wei-Fong Pan.

Appendix 1: Bubble periods for each regional city

Appendix 1: Bubble periods for each regional city

See Table 5.

Table 5 Bubble periods for 35 cities

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Pan, W. Detecting bubbles in China’s regional housing markets. Empir Econ 56, 1413–1432 (2019). https://doi.org/10.1007/s00181-017-1394-3

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Keywords

  • Real estate
  • Rational bubbles
  • Housing market
  • Recursive unit root

JEL Classification

  • C32
  • G01
  • R30