Estimating Estate-Specific Price-to-Rent Ratios in Shanghai and Shenzhen: A Bayesian Approach
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Asian Real Estate Society in its journal International Real Estate Review.
Volume (Year): 14 (2011)
Issue (Month): 2 ()
Contact details of provider:
Postal: Asia Real Estate Society, 51 Monroe Street, Plaza E-6, Rockville, MD 20850, USA
Web page: http://www.asres.org/
Postal: Asian Real Estate Society, 51 Monroe Street, Plaza E-6, Rockville, MD 20850, USA
Other versions of this item:
- Shawn Ni & Jie Chen, 2010. "Estimating Estate-Specific Price-to-Rent Ratios in Shanghai and Shenzhen: A Bayesian Approach," Working Papers 1015, Department of Economics, University of Missouri.
- L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005.
"Assessing High House Prices: Bubbles, Fundamentals and Misperceptions,"
Journal of Economic Perspectives,
American Economic Association, vol. 19(4), pages 67-92, Fall.
- Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005. "Assessing High House Prices: Bubbles, Fundamentals, and Misperceptions," NBER Working Papers 11643, National Bureau of Economic Research, Inc.
- Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005. "Assessing high house prices: bubbles, fundamentals, and misperceptions," Staff Reports 218, Federal Reserve Bank of New York.
- Dufour, Jean-Marie & Jasiak, Joann, 2001. "Finite Sample Limited Information Inference Methods for Structural Equations and Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(3), pages 815-43, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (IRER Graduate Assistant/Webmaster).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.