Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices

Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices Spatial dependence is often seen as a problem in econometrics rather than in economics. This study seeks to find an economic explanation for spatially correlated real estate prices. We posit spatial dependence as a process to discover price information from neighboring property transactions. Weaker spatial dependence is expected when price information in the immediate vicinity of a subject property is abundant. In the context of apartment buildings, in addition to the more commonly known horizontal dependence, there is also spatial dependence in the vertical dimension within the same building. Based on more than 18,000 transactions of highly homogeneous apartment units in Hong Kong, we found that the trading volume of a building depresses horizontal spatial dependence, but raises vertical spatial dependence. This not only confirmed the role of trading volume in the real estate price discovery process, but also questioned the validity of constant spatial autocorrelation assumption adopted in many studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Real Estate Finance and Economics Springer Journals

Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices

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Publisher
Springer US
Copyright
Copyright © 2012 by The Author(s)
Subject
Economics / Management Science; Regional/Spatial Science; Finance/Investment/Banking
ISSN
0895-5638
eISSN
1573-045X
D.O.I.
10.1007/s11146-012-9375-y
Publisher site
See Article on Publisher Site

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