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Article: Exploring the ripple effect and spatial volatility in house prices in England and Wales: regressing interaction domain cross-correlations against reactive statistics

TitleExploring the ripple effect and spatial volatility in house prices in England and Wales: regressing interaction domain cross-correlations against reactive statistics
Authors
KeywordsCensus
Cross-correlation
House prices
Interaction
Migration
Network analysis
Regression
Ripple effect
Spatial data
Time series
Issue Date2013
Citation
Environment and Planning B, 2013, v. 40 n. 5, p. 763-782 How to Cite?
AbstractIn this study we conduct an exploratory spatiotemporal analysis of recent UK housing-market data 2000–06, fine grained both in space and in time. We present firstly the exploratory technique itself, and secondly an overview of patterns found in the dataset. A broadly scoped metamodel is created which points towards fruitful avenues for further investigation and understanding of the driving forces behind price propagation in the housing market. At the core of this model is an 8850 × 8850 cross-correlation matrix representing price linkage between different areas, which is analyzed by a custom regression engine. Hence this is the first study to unify both local and regional house-price modelling, and the first to look for a quantitative explanation of the structure of any house-price interaction matrix on a large scale. Findings corroborate existing research on the ripple effect and spatial volatility, and point towards mechanisms through which these might arise, as a combination of local interaction and market segmentation broken by lifecycle migration patterns.
Persistent Identifierhttp://hdl.handle.net/10722/184043
ISSN
2016 Impact Factor: 1.527
2019 SCImago Journal Rankings: 1.109
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCooper, Cen_US
dc.contributor.authorOrford, Sen_US
dc.contributor.authorWebster, CJen_US
dc.contributor.authorJones, Cen_US
dc.date.accessioned2013-06-20T08:27:33Z-
dc.date.available2013-06-20T08:27:33Z-
dc.date.issued2013en_US
dc.identifier.citationEnvironment and Planning B, 2013, v. 40 n. 5, p. 763-782en_US
dc.identifier.issn0265-8135-
dc.identifier.urihttp://hdl.handle.net/10722/184043-
dc.description.abstractIn this study we conduct an exploratory spatiotemporal analysis of recent UK housing-market data 2000–06, fine grained both in space and in time. We present firstly the exploratory technique itself, and secondly an overview of patterns found in the dataset. A broadly scoped metamodel is created which points towards fruitful avenues for further investigation and understanding of the driving forces behind price propagation in the housing market. At the core of this model is an 8850 × 8850 cross-correlation matrix representing price linkage between different areas, which is analyzed by a custom regression engine. Hence this is the first study to unify both local and regional house-price modelling, and the first to look for a quantitative explanation of the structure of any house-price interaction matrix on a large scale. Findings corroborate existing research on the ripple effect and spatial volatility, and point towards mechanisms through which these might arise, as a combination of local interaction and market segmentation broken by lifecycle migration patterns.-
dc.languageengen_US
dc.relation.ispartofEnvironment and Planning Ben_US
dc.subjectCensus-
dc.subjectCross-correlation-
dc.subjectHouse prices-
dc.subjectInteraction-
dc.subjectMigration-
dc.subjectNetwork analysis-
dc.subjectRegression-
dc.subjectRipple effect-
dc.subjectSpatial data-
dc.subjectTime series-
dc.titleExploring the ripple effect and spatial volatility in house prices in England and Wales: regressing interaction domain cross-correlations against reactive statisticsen_US
dc.typeArticleen_US
dc.identifier.emailWebster, CJ: cwebster@hku.hken_US
dc.identifier.authorityWebster, CJ=rp01747en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1068/b37062-
dc.identifier.scopuseid_2-s2.0-84885209625-
dc.identifier.spage763-
dc.identifier.epage782-
dc.identifier.isiWOS:000325755600002-
dc.identifier.issnl0265-8135-

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