IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Price Discovery in Time and Space: The Course of Condominium Prices in Singapore

  • Hwang, Min
  • Quigley, John M.

A random walk in time and independence in space are maintained hypotheses in traditional empirical models of housing prices. However, there is increasing evidence in the context of hedonic models that housing prices are predictable over time and space. This paper examines the price discovery process in individual dwellings by relaxing both assumptions, using a unique body of data from the Singapore private condominium market in a repeat sales framework. We develop a formal model that tests directly the hypotheses that the prices of individual dwellings follow a random walk over time and that the price of an individual dwelling is independent of the price of a neighboring dwelling. The empirical results clearly support mean reversion in housing prices and also diffusion of innovations over space. This predictability may suggest that excess returns are possible. When aggregate returns are computed from models that assume a random walk and spatial independence, we find that they are strongly autocorrelated. However, when they are calculated from models permitting mean reversion and spatial autocorrelation, predictability in investment returns is completely absent. Despite this, an extensive simulation of investor performance, over different time horizons and with different investment rules, indicates quite clearly that recognition of the spatial and autocorrelated nature of prices substantially improves investor returns. The magnitude of deviations from standard models of price dynamics are small, but their economic implications are quite large in the housing market.

If 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.

File URL: http://www.escholarship.org/uc/item/1wn5v55d.pdf;origin=repeccitec
Download Restriction: no

Paper provided by Berkeley Program on Housing and Urban Policy in its series Berkeley Program on Housing and Urban Policy, Working Paper Series with number qt1wn5v55d.

as
in new window

Length:
Date of creation: 13 Sep 2007
Date of revision:
Handle: RePEc:cdl:bphupl:qt1wn5v55d
Contact details of provider: Postal: F502 Haas, Berkeley CA 94720-1922
Phone: (510) 642-1922
Fax: (510) 642-5018
Web page: http://www.escholarship.org/repec/iber_bphup/
Email:


More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:cdl:bphupl:qt1wn5v55d. 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: (Lisa Schiff)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.