Do internal migrants suffer from housing extreme overcrowding in urban China?

Abstract

Housing deprivation is central to economic deprivation. Identifying disadvantaged group(s) suffering from housing deprivation is a necessary step before the government can design effective housing assistance programmes. Using a nationwide micro-level data-set from the Chinese Family Panel Studies, we evidence the disadvantage that internal migrants face related to extreme overcrowding. We find that renters, whether natives or internal migrants, are more likely to suffer extreme overcrowding than homeowners, nationally and in most Chinese regions. However, both rural and urban migrants are less likely to be owner-occupiers than native residents. By comparing homeowners vs. renters, we further discover that migrant homeowners are less likely to suffer extreme overcrowding than the native residents of China’s cities. Conversely internal migrant renters face the highest odds to live in extremely overcrowded dwellings. Overall, findings suggest that the Chinese government needs pay special attention to improve internal migrant tenants’ living condition, particularly so for those renting.

Keywords:

• Extreme overcrowding
• internal migrant
• homeowner
• renter
• China

Acknowledgement

We are grateful to Prof. John Flint and three anonymous referees for helpful comments and suggestions. We also thank participants of The Global Chinese Real Estate Congress (GCREC) 2013 for providing insightful discussions and comments. All errors remain ours.

Notes

1. For some cities, the requirement of holding local urban Hukou was released in application for Gong Zu Fang after year 2012, but it has not been released in the application for Lian Zu Fang.

2. Data source: Chinese Statistic Yearbook 2012.

3. The area represents the built up area of a dwelling, including walls, halls, bathroom, kitchen, porches and average shared common area in the residential communities. This definition of ‘area’ is widely used for housing transactions and evaluations in the housing market in China.

4. For the criteria of overcrowding, we thank one of the anonymous referees for providing very helpful comments. She/he points out that the ‘threshold for overcrowding has not risen proportionally with the average space per capita’ in China. The 8-square-meter is probably a too low threshold with average floor area per capita was 31.6 square meters in year 2010, as compared with the 4-square-meter overcrowding threshold with average floor area per capita of 10 square meters in 1985. We guess that this ‘disproportion’ might be due to land management practiced by local governments in China. In order to maximize financial gains from selling land use rights, local governments in China has strategically controlled land supply for commercial and residential development, which in turn, may hold back the growth rate of housing space consumption in this country (Su & Tao, 2017).

5. Source: http://www.whfg.gov.cn/upload_files/whfcj/contents/990/25316.html.

6. Source: http://www.hrbfdc.gov.cn/start/newsview.asp?n_id=196.

7. For instance, the overcrowding standard defined by the U.S. Department of Housing and Urban Development in year 2007 was 165 square feet per person, or over 15 square metres per person (Blake et al., 2007). Please note that different countries may use different protocols for measuring ‘area’.

8. 'Renters’ in the analysis include those paying market rents, subsidized rents in the public sector or living rent-free.

9. Liaoning is one of the old industrial base of China. With the declining of old industries, worker settlements gradually turn into shantytown. Liaoning thus has the largest number and highest density Shantytown in China.

10. Unfortunately, no enough region-level samples can support the independent empirical research on housings with shared property rights. Instead, we take housings with full and shared property rights as a whole.

11. We have examined the correlation among independent variables. No strong correlation is found.

12. We notice that both ratios of housing overcrowding are lower than the ratios provided by the National Bureau of Statistics of China. The survey conducted by the National Bureau of Statistics of China covers all 32 provinces and autonomous regions. But CFPS covers 25 provinces and autonomous regions, not including Tibet, Qinghai, Xinjiang, Ningxia, Inner Mongolia, and Hainan. The different statistical scope may cause the difference.

13. The average annual USD/RMB exchange rate is 100:683.1, and the EUR/RMB exchange rate is 100:952.7 in 2009.

14. For the baseline model, we tried to divide a household head’s age into several cohorts. However, this caused a multicollinearity problem, and so we decided to include the simple AGE variable instead.

15. Given the limited space, results of ordered logistic regression are not reported in the paper.

16. IV approach is widely used in econometrics. Due to endogeneity, there exist possibility of inconsistent parameter estimation. The regression estimates measure only the magnitude of association, rather than the magnitude and direction of causation. IV approach can provide a way to nonetheless obtain consistent parameter estimates (Greene, 2008).