A Bayesian approach to hedonic price analysis

Auteur(s) et Affiliation(s)

WHEELER, D.C.

Dept. of Biostatistics, Virginia Commonwealth Univ., Richmond, Etats-Unis

PÁEZ, A.

School of Geography and Earth Sciences, McMaster Univ., Hamilton, Canada

SPINNEY, J.

Dept. of Geography, St. Mary's Univ., Halifax, Canada

WALLER, L.A

Dept. of Biostatistics and Bioinformatics, Emory Univ., Atlanta, Etats-Unis

Description :
In this paper, the AA. apply Bayesian models with spatially varying coefficients in an analysis of housing sale prices in the city of Toronto, Ontario to address these objectives. They evaluate model performance and identified patterns of submarkets indicated by the spatial coefficient processes. The results show that Bayesian spatial process models predict housing sale prices well, provide useful inference regarding heterogeneity in prices within a market, and may be specified to include expert market opinions.

Type de document :
Article de périodique

Source :
Papers in regional science, issn : 1056-8190, 2014, vol. 93, n°. 3, p. 663-683, nombre de pages : 21, Références bibliographiques : 2 p.

Date :
2014

Editeur :
Pays édition : Allemagne, Berlin, Springer

Langue :
Anglais