![Sample our Area Studies journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5922/TOC-Subject-Sample-2021-Area-Studies.jpg"})
ABSTRACT
China has experienced very rapid house price inflation in recent years – by some 10% per annum relative to consumer price inflation. Existing house-owners have benefited from capital gain and have been able to climb the housing ladder. Young household heads – wanting to own a house and facing rising house prices relative to their incomes – have found it increasingly difficult to get onto the housing ladder. However, their difficulty is eased by the strength of family support and the developing market for housing loans. The China Household Income Project (CHIP) surveys of 2002 and 2013 are analysed to test the hypothesis that the age distributions of house ownership and of housing wealth have moved against the young. Probits, tobits, and difference-in-difference analyses measure these effects. There is indeed evidence indicating a receding housing ladder, and evidence that waiting longer to own a house is positively associated with house price inflation.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. More detailed accounts of the data are available in the text and data appendices of Knight, Shi, and Haiyuan (Citation2020, 2022).
2. National Population Census, 2000, 2015.
3. China General Social Survey.
4. The other possible proxy for the increasing difficulty of young people to acquire a house is the increase in the house value/income ratio over our period. However, because the data set is not a panel, the change in the ratio is not available at sampled locality level.
5. Various other specifications were attempted but this one produced the strongest positive association. House price in 2013 and the ratio of house price to income in 2013 also produced positive coefficients but each was dominated when included with house price inflation.
6. We lack some of the potential explanatory variables that are discussed in sections 4 and 5, such as extent of family support and access to loans. Marriage and number of children are excluded because they might be consequences rather than causes of house ownership.
7. We choose household real housing wealth as the dependent variable because the logarithm of household real housing wealth would eliminate households with zero housing wealth, and because household housing wealth per capita results would be confounded by sharp changes of household size in some age-groups.
8. As a further robustness test, we confined the sample to house-owners and compared the OLS results with housing wealth or ln. housing wealth as the dependent variable. In both estimations and in each sample except the rural, the coefficient on age-group 35–44 was positive, significant and greater in 2013 than in 2002. The choice of ln. housing wealth would make no difference to the story.
Additional information
Notes on contributors
John Knight
John Knight is emeritus professor in the University of Oxford and emeritus fellow of St Edmund Hall, Oxford. He is also academic director of the Oxford Chinese Economy Programme. He has conducted research on the Chinese economy for thirty years. Recent books include Towards a Labour Market in China, 2005, and China’s Remarkable Economic Growth, 2012 (both OUP).
Haiyuan Wan
Haiyuan Wan, at the Beijing Normal University Business School, is a researcher in the China Institute for Income Distibution, and a member of the CHIP team.