 House Prices and Spatial Dependence: Towards an Integrated Procedure to Model NeighborhoodF. Des Rosier and M. Theriault Working Papers from Laval - Faculte des sciences de administration Abstract: This paper deals with applying GIS and spatial statistics to hedonic modeling. More precisely, it looks at spatial autocorrelation and trend surface analysis (TSA) as devices that can be used to improve model performances. Empirical analysis is performed on the Charlesbourg 1986-87 bungalow (one-story, single-family detached unit) residential market segment. Charlesbourg is the third largest municipality in the Quebec Urban Community (QUC), with some 71 000 in population by 1991. Main findings first suggest that TSA may either be viewed as a proxy for, or a complement to, detailed neighborhood analysis. While best results are obtained using an array of space-related attributes, TSA proves to be an adequate, cost-efficient alternative to expensive data collection. Secondly, the study emphasizes the need for a strict analytical framework to be followed if any spurious conclusions about implicit prices are to be avoided. Keywords: HOUSING; MODELS (search for similar items in EconPapers) 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:fth:lavadm:99-002 Access Statistics for this paper More papers in Working Papers from Laval - Faculte des sciences de administration Canada; Universite Laval, Faculte des sciences de l'administration. Pavillon des sciences de l'administration. Universite laval, Quebec, Canada G1K 7P4. Contact information at EDIRC. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.