Abstract
With novel microdata from a household survey of China, we find that migrants decide to move out of destination cities experiencing housing booms, even after controlling for various factors and address potential endogeneity issues that may affect households’ migration decisions. Moreover, we present new evidence that housing booms have no effect on the decisions of homeowners but affect renters through a negative income effect. Next, we use big data on population flows from Tencent to confirm the effects of housing booms on households’ actual out-migration. The results suggest that an affordable home is a primary factor in attracting migrant households and maintaining a healthy economy.
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Notes
News from People.cn: http://politics.people.com.cn/n1/2016/0315/c1001-28198984.html.
Hukou location is a concept specific to the Chinese context. It refers to the place where Chinese citizens are registered with the national population administration. It may not be the place where citizens live for a long time, but it is often related to many components of citizens’ welfare.
Specifically, willingness to move is assigned 1 if the respondent answered “no” or “undecided.” Thank to the anonymous referee’s suggestion, we assign willingness to move to 1 if the respondent answered “no” and 0 otherwise. The estimated results are similar. We provide the these estimations by request.
Given the low WTM in each year, it is not clear that a linear model is appropriate. However, estimations from the probit and IV models yield similar results. We report those estimations as a robustness check in Table A2 in the Appendix, but we keep the linear probability model coefficients due to their ease of interpretation.
Local land unavailability is calculated by ArcGIS 10.3 using elevation data obtained from the United States Geographic Service (USGS) SRTM 90 m Digital Elevation Database v4.1 (website: https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/).
We access the time-series data of the historical interest rate from the website of the Bank of China: http://www.bankofchina.com/fimarkets/lilv/fd32/
An increasing in housing prices by a one standard deviation (0.424) boosts in the labor’s willingness to move by 0.091 × 0.424/0.408 = 9.45%.
The second-hand housing transactions data is provided by Xitai, http://www.cityre.cn/credata.html
The southern coastal provinces include Jiangsu, Zhejiang, Fujian, Shanghai, Guangdong and Hainan. The northern coastal province include Tianjin, Hebei and Liaoning. The southern inland provinces are Anhui, Jiangxi, Hubei, Hunan, Chongqing, Sichuan, Yunnan, Guizhou, Xizang and Guangxi, and the remaining provinces are northern-inland provinces, including Shanxi, Inner Mongolia, Jilin, Heilongjiang, Henan, Shaanxi, Gansu, Ningxia, Qinghai and Xinjiang.
Data from the China Industry Statistical Yearbook (2011, 2020) shows that, since 2010, over 150 thousand and 12 thousand of firms above the designated size have move to southern coastal regions and southern inland regions, respectively.
The policy entitled Notice of the State Council on Adjusting the Standards for Categorizing City Sizes was issued in 2014. Megacity refers to cities with urban resident population of 10 million and above. Supercity refers to cities with urban resident population between 5 million and 10 million. Large city refers to cities with urban resident population between 1 million and 5 million. Medium city refers to cities with urban resident population 0.5 million and 1 million. And the rest prefecture cities are small cities here. Urban resident population data is collected from China City Construction Statistical Yearbook.
The coefficient of housing prices in subsample of aged 40 – 49 is marginally significant at a 10% level. And the coefficients of housing prices between subsamples aged 40 – 49 and aged >50 are indifferent, verified by Fisher’s Permutation Test (Cleary, 1999).
We thank the referee for pointing out that a positive shock to rent is likely to increase the housing price. To address this concern, we conduct a Granger causality test between housing prices and rent using the Chinese city-level panel data. The unreported results (available on request) show that housing price changes one-way Granger-cause housing rent changes. This finding is consistent with that of Wang et al. (2020c).
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Acknowledgements
The authors thank James B. Kau (the editor), two anonymous referees, and workshop participants of 2018 Asia-Pacific Real Estate Research Symposium. We also gratefully acknowledge financial supports from the National Natural Science Foundation of China (71871195 and 71988101), Chinese National Social Science Foundation (19ZDA060), the Humanities and Social Sciences grant of the Chinese Ministry of Education (18YJA790121), and the Fundamental Research Funds for the Central Universities (2072021049).
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Meng, L., Xiao, X. & Zhou, Y. Housing Boom and Household Migration Decision: New Evidence from China. J Real Estate Finan Econ 67, 453–479 (2023). https://doi.org/10.1007/s11146-021-09856-y
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DOI: https://doi.org/10.1007/s11146-021-09856-y