Dealing with spatial data pooled over time in statistical models

DC FieldValueLanguage
dc.contributor.authorDubé, Jean-
dc.contributor.authorLegros, Diègo-
dc.coverage.spatialLucas County (Ohio)fr_CA
dc.coverage.temporal20e sièclefr_CA
dc.description.abstractRecent developments in spatial econometrics have been devoted to spatiotemporal data and how spatial panel data structure should be modeled. Little effort has been devoted to the way one must deal with spatial data pooled over time. This paper presents the characteristics of spatial data pooled over time and proposes a simple way to take into account unidirectional temporal effect as well as multidirectional spatial effect in the estimation process. An empirical example, using data on 25,357 single family homes sold in Lucas County, OH (USA), between 1993 and 1998 (available in the MatLab library), is used to illustrate the potential of the approach proposed.fr_CA
dc.subjectSpatio-temporal datafr_CA
dc.subjectWeights matrixfr_CA
dc.subjectSpatial econometricsfr_CA
dc.titleDealing with spatial data pooled over time in statistical modelsfr_CA
dc.typeCOAR1_1::Texte::Périodique::Revue::Contribution à un journal::Article::Article de recherche-
dcterms.bibliographicCitationLetters in Spatial and Resource Sciences, Vol. 6 (1), 1–18 (2013)fr_CA
dc.audienceProfesseurs (Enseignement supérieur)fr_CA
dc.subject.rvmDonnées spatio-temporellesfr_CA
dc.subject.rvmModèles économétriquesfr_CA
dc.subject.rvmMicroéconomie--Modèles mathématiquesfr_CA
rioxxterms.versionVersion of Recordfr_CA
Collection:Articles publiés dans des revues avec comité de lecture

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