E-resources
Peer reviewed
-
Hohenstatt, Ralf; Kaesbauer, Manuel
The Journal of real estate research, 04/2014, Volume: 36, Issue: 2Journal Article
This study follows the stream of research identifying sentiment trends by using online search query data. The potential of the Google data series for the U.K. housing market on a disaggregated level is analyzed in a panel VAR framework. Our findings confirm research based on U.S. samples that Google subcategories, especially “Real Estate Agency,” serve as an indicator of transaction volume. Our main contribution is the detection of contrary dynamics within the Google “Home Financing” subcategory, which to date yields empirically mixed evidence (Hohenstatt, Kaesbauer, and Schaefers, 2011). Sensitivity analysis yields that transaction volume responds twice as sensitively as house prices due to a standard deviation increase of the stress indicator. Most importantly, the derived stress indicator of housing market (un-)soundness works at least as well as in downturns, as opposed to “Real Estate Agency,” which is primarily a suitable indicator during upturns.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.