IDEAS home Printed from https://ideas.repec.org/p/umc/wpaper/1015.html
   My bibliography  Save this paper

Estimating Estate-Specific Price-to-Rent Ratios in Shanghai and Shenzhen: A Bayesian Approach

Author

Abstract

The price-to-rent ratio, a common yardstick for the value of housing, is difficult to estimatewhen rental properties are poor substitutes of owner-occupied homes. In this study weestimate price-to-rent ratios of residential properties in two major cities in China, where urbanhigh-rises (estates) comprise both rental and owner-occupied units. We conduct Bayesianinference on estate-specific parameters, using information of rental units to elicit priors of theunobserved rents of units sold in the same estate. We find that the price-to-rent ratios tendto be higher for low-end properties. We discuss economic explanations for the phenomenonand the policy implications.

Suggested Citation

  • 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.
  • Handle: RePEc:umc:wpaper:1015
    as

    Download full text from publisher

    File URL: https://economics.missouri.edu/working-papers/2010/wp1015_ni.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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 815-843, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Housing price; rents; heterogeneity; Bayesian analysis;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • G00 - Financial Economics - - General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:umc:wpaper:1015. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Valerie Kulp). General contact details of provider: http://edirc.repec.org/data/edumous.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.