Estimating Estate-Specific Price-to-Rent Ratios in Shanghai and Shenzhen: A Bayesian Approach
Jie Chen and
Shawn Ni ()
Additional contact information
Jie Chen: HSBC (The Hong Kong and Shanghai Banking Corporation)
International Real Estate Review, 2011, vol. 14, issue 2, 208-239
Abstract:
The price-to-rent ratio, a common yardstick for the value of housing, is difficult to estimate when rental properties are poor substitutes of owner-occupied homes. In this study, we estimate price-to-rent ratios of residential properties in two major cities in China, where urban high-rises (estates) comprise both rental and owner-occupied units. We conduct Bayesian inference on estate-specific parameters by using information of rental units to elicit priors of the unobserved rents of units sold in the same estate. We find that the price-to-rent ratios tend to be higher for low-end properties. We discuss economic explanations for the phenomenon and the policy implications.
Keywords: Housing price; Rents; Heterogeneity; Bayesian analysis (search for similar items in EconPapers)
JEL-codes: L85 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.gssinst.org/irer/wp-content/uploads/20 ... hai-and-shenzhen.pdf Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ire:issued:v:14:n:02:2011:p:208-239
Ordering information: This journal article can be ordered from
Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850
https://www.gssinst.org/gssinst/index.html
Access Statistics for this article
International Real Estate Review is currently edited by Professor Sing Tien Foo and Professor Ko Wang
More articles in International Real Estate Review from Global Social Science Institute Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850.
Bibliographic data for series maintained by IRER Graduate Assistant/Webmaster ().