Abstract
Over the past two decades, Chinese cities have experienced real estate booms displaying clear signs of “bubble” elements, including, inter allia, prohibitive residential prices, an accumulation of debt, and severe overbuilding. In 2014, many media commentators claimed that Chinese property markets were about to burst. Yet house prices have started to rise again in major cities, and no significant slowdown has been recorded to date. This chapter addresses the challenges posed by China’s residential market dynamics to the bubble theory. Adopting a political economy perspective that breaks with the approaches of real estate economics, it highlights the self-fulfilling logic of the housing booms, resulting from pervasive practices of land value capture by local governments. The paper stresses the inadequacy of the bubble framework to distinguish speculative and “fundamental” explanatory factors of price increases, and provides an alternative reading based on André Orléan’s theory of conventions. It is argued that the asymmetric nature of the State’s regulation of housing markets—a failure to rein in housing price hikes, yet efficiency in managing downturns—has played a crucial role in shaping the common representation of the market by investors. Beyond the challenge to bubble theory, China’s experience of housing booms opens the way for the recognition of alternative paths to finance-led regimes of capital accumulation in the built environment.
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Notes
- 1.
An asset is a resource with economic value that an entity owns or controls, with the expectation that it will generate income.
- 2.
This figure is taken from China Banking News, July 6, 2017. http://www.chinabankingnews.com/2017/07/06/housing-price-income-ratio-exceeds-10-across-16-chinese-cities/ (checked on September 20, 2018)
- 3.
The decentralization process operated in the 1980s conferred great freedom on local governments to manage their economies. In 1998, the sale of land-use rights was put under their jurisdiction. The same year, the public residence allocation system was converted into a system of marketization.
- 4.
Wu et al. developed an independent data set using hedonic prices to control for housing quality. This dataset covers indices based on sales of newly built housing units in 35 major Chinese cities.
- 5.
China’s cities are divided into four categories. The first tier includes the four most developed metropolitan areas: Beijing, Shanghai, Shenzhen, and Guangzhou; the second tier includes most provincial capitals and some very developed prefecture cities. Tier 3 cities include prefecture cities that have medium to high levels of income, while Tier 4 cities are further behind economic development and smaller in size.
- 6.
The number of workers in SOEs stood at 122 million in 1998, and fell thereafter to 76 million in 2006. The remaining SOEs account for 30% of the total assets in the secondary and tertiary sectors. They are bigger, more competitive and more profitable than were former SOEs (Ren 2013).
- 7.
The “big four” state-owned banks are the Industrial and Commercial Bank of China, the Bank of China, the China Construction Bank, and the Agricultural Bank of China.
- 8.
The Trust industry is a unique financial system that has very little in common with Western trusts industries. It is primarily engaged in two main categories of services: private placement investment banking (for both high-net-worth individuals and corporate investors), and conduit business (operating as a conduit to allow banks investing in forbidden asset class). The trust industry has grown rapidly after the GFC. The total value of its assets under management rose from 960 billion 2007 into 23 trillion in mid-2017. Chinese policy-makers are actively working to normalize this industry.
- 9.
https://www.prometeia.it/atlante/China-government-debt. Checked on September 3, 2018.
- 10.
This figure does not consider consumption loans that are used to circumvent regulations for housing investment.
- 11.
https://www.ceicdata.com/en/indicator/china/household-debt--of-nominal-gdp. Checked in Sept. 2018.
- 12.
Hong Kong developers are by far the main ‘foreign’ players in the Mainland. Some groups manage a large number of buildings in major cities and hold extensive landbanks. However, unlike Western operators, they seldom invest in property trough financial vehicles.
- 13.
China Daily, “8 cities with a lottery system for housing sales”, June 4, 2018. http://www.chinadaily.com.cn/a/201806/04/WS5b147119a31001b82571de20.html. Checked on November 15, 2018.
- 14.
South China Morning Post, “Shanghai authorities get more involved in supervising lottery system used by developers to allocate properties”, May 5, 2017. https://www.scmp.com/property/hong-kong-china/article/2093036/shanghai-vows-crack-down-home-sales-irregularities. Checked on November 15, 2018.
- 15.
Derecet News business, October 18, 2011, https://www.deseretnews.com/article/700189099/Debt-panic-in-Chinas-Wenzhou-may-auger-wider-woes.html. Checked on September 25, 2018.
- 16.
JLL Global Research, China 12: China’s cities go global 2018. This figure includes investment in Hong Kong.
- 17.
CHFS Data Talks, Trend in the housing market and Housing vacancy rate in urban China, 2004. This survey was based on interviews of some 28,000 households, carried out in 262 counties and 29 provinces.
- 18.
A PPP is a partnership between a public authority and a private operator aimed at providing a public project or infrastructure, in which there is a transfer of significant risk to the private party.
- 19.
Reuters, Business news, November 17, 2017. https://www.reuters.com/article/us-china-economy-ppp/china-overhauls-2-69-trillion-public-private-projects-as-debt-fears-rise-idUSKBN1DH0DE. Check on September 20, 2018.
- 20.
Nikkei Asian Review, May 17, 2018. https://asia.nikkei.com/Opinion/China-must-put-the-private-into-PPP2, checked on September 20, 2018.
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Aveline-Dubach, N. (2020). China’s Housing Booms: A Challenge to Bubble Theory. In: Pumain, D. (eds) Theories and Models of Urbanization. Lecture Notes in Morphogenesis. Springer, Cham. https://doi.org/10.1007/978-3-030-36656-8_11
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