 Spatially Disaggregated Real Estate IndicesIversen, Edwin S, Journal of Business & Economic Statistics, 2001, vol. 19, issue 3, 341-57 Abstract: A spatial-temporal Markov random-field model is used to produce indices for residential real estate from repeat home sale data. A set of regions is represented by a graph in which neighboring regions are linked. This graph, repeated consecutively a number of times, with each region linked to the same region at adjacent times, defines a spatial-temporal graph that connects regions over space and time in which each node represents a region at a particular time. An index is defined at each node to be the rate of appreciation of log sale price in a region during the preceding time interval. The indices are estimated from data consisting of repeat home sales. The Markov random-field model specifies spatial and temporal correlations between neighboring indices and relations between indices and individual repeat sales. A method is proposed for estimating various parameters in the model and for obtaining real-estate indices. Following this prescription, indices are calculated for the Dade County, Florida, residential real-estate market. Results are compared to those obtained using competing space-only models. Date: 2001 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:19:y:2001:i:3:p:341-57 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano More articles in Journal of Business & Economic Statistics from American Statistical Association |
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