Volume 27, Number 1, 2005 of the Journal of Real Estate Research
Apartment Rent
Prediction Using Spatial Modeling
James Valente
Manager, Research
SSR Realty Advisers, Inc.
(973) 355-4560
jvalente@ssrrealty.com |
ShanShan Wu
Ph.D. Candidate
Department of Statistics
University of Connecticut |
Alan Gelfand
Institute for Statistics and Decision Sciences
Duke University |
C.F. Sirmans
Director, Center for Real Estate and Urban Economic Studies
University of Connecticut
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Abstract: This paper
provides a new model to explain local variation in apartment rents by
introducing the notion of a spatial process. This model differs from
those in the literature by explicitly specifying spatial association
between pairs of locations as a function of distance between them. Data
on apartment rents for the eight markets are used to illustrate the
spatial model. Results indicate significant prediction improvement over
traditional hedonic rent models that only include indicator variables to
capture spatial effects.
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