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Spatio-Temporal Hedonic Price Model to Investigate the Dynamics of Housing Prices in Contexts of Urban Form and Transportation Services in Toronto

Spatio-Temporal Hedonic Price Model to Investigate the Dynamics of Housing Prices in Contexts of... A spatio-temporal hedonic price model is developed for the Greater Toronto area to examine the effects of urban configurations and proximity to transit services on housing price. A spatial Durbin panel model is utilized to account for both spatial and temporal autocorrelation. This model is shown to have advantages through its ability to reduce the number of explanatory variables required to obtain a strong fit with empirical data. Analysis is completed for the period of 1996 to 2017 and distinctions are made in housing stock between single-family houses, townhouses, and condominiums. It is shown that heterogeneities exist between the hedonic representations of each dwelling type and that separate models should be employed for each. In all cases, the average income of the community, its distance to the central business district (CBD), and population and employment density are found to be significant factors in the determination of price. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportation Research Record SAGE

Spatio-Temporal Hedonic Price Model to Investigate the Dynamics of Housing Prices in Contexts of Urban Form and Transportation Services in Toronto

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References (34)

Publisher
SAGE
Copyright
© National Academy of Sciences: Transportation Research Board 2018
ISSN
0361-1981
eISSN
2169-4052
DOI
10.1177/0361198118774153
Publisher site
See Article on Publisher Site

Abstract

A spatio-temporal hedonic price model is developed for the Greater Toronto area to examine the effects of urban configurations and proximity to transit services on housing price. A spatial Durbin panel model is utilized to account for both spatial and temporal autocorrelation. This model is shown to have advantages through its ability to reduce the number of explanatory variables required to obtain a strong fit with empirical data. Analysis is completed for the period of 1996 to 2017 and distinctions are made in housing stock between single-family houses, townhouses, and condominiums. It is shown that heterogeneities exist between the hedonic representations of each dwelling type and that separate models should be employed for each. In all cases, the average income of the community, its distance to the central business district (CBD), and population and employment density are found to be significant factors in the determination of price.

Journal

Transportation Research Record – SAGE

Published: Dec 1, 2018

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