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(Article of periodic en Anglais - 2014)

Document title

A Bayesian approach to hedonic price analysis

Authors(s) and Affiliation(s)

WHEELER D.C. (1) ; PÁEZ A. (2) ; SPINNEY J. (3) ; WALLER L.A (4) ;
(1) Dept. of Biostatistics, Virginia Commonwealth Univ., Richmond, ETATS-UNIS
(2) School of Geography and Earth Sciences, McMaster Univ., Hamilton, CANADA
(3) Dept. of Geography, St. Mary's Univ., Halifax, CANADA
(4) Dept. of Biostatistics and Bioinformatics, Emory Univ., Atlanta, ETATS-UNIS

Abstract

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.

Source

Article of periodic

published at : Papers in regional science / ISSN 1056-8190

Editor : Springer, Berlin - ALLEMAGNE (1991)

Millesime : 2014, vol. 93, no3 [pp. 663-683]

Bibliographic references : 2 p.

Collation : 5 fig., 2 tabl.

Language

Anglais

Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 2014
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