Rural-urban migration and house prices in China
Carlos Garriga (),
Yang Tang and
Regional Science and Urban Economics, 2021, vol. 91, issue C
This paper uses a dynamic competitive spatial equilibrium framework to evaluate the contribution of rural-urban migration induced by structural transformation to the behavior of Chinese housing markets. In the model, technological progress drives workers facing heterogeneous mobility costs to migrate from the rural agricultural sector to the higher paying urban manufacturing sector. Upon arrival to the city, workers purchase housing using long-term mortgages. Quantitatively, the model fits cross-sectional house price behavior across a representative sample of Chinese cities between 2003 and 2015. The model is then used to evaluate how changes to city migration policies and land supply regulations affect the speed of urbanization and house price appreciation. The analysis indicates that making migration policy more egalitarian or land policy more uniform would promote urbanization but also would contribute to larger house price dispersion.
Keywords: Spatial patterns of migration; Structural transformation; Housing booms; Land policy (search for similar items in EconPapers)
JEL-codes: O11 R23 R31 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Rural-Urban Migration and House Prices in China (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:91:y:2021:i:c:s0166046220302982
Access Statistics for this article
Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou
More articles in Regional Science and Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().