Abstract:
Transportation system has a great impact on the land uses of an urban area. Many
transportation researchers used hedonic price models to understand the relationship
between transportation and land uses. Hedonic price model studies are commonly
focused on the impact of transportation system on land uses, particularly on land
values. This study was an attempt following hedonic price model approach to
provide empirical evidence regarding the nature and magnitude of accessibility
impacts of transportation system on asking rental price of residential properties. It
also investigated and compared impacts of structural attributes and neighborhood
attributes on residential property values with that of transportation system.
Accessibility to transportation infrastructure, central business district, wholesale
markets, shopping centers and primary schools were considered as the transportation
attributes that might have significant impact on residential property values at
Rajshahi City. Both linear and semi-log model specifications were estimated based
on data collected by field visual inspection of advertisements for rent during May
2004. The study used Geographical Information System (GIS) as a tool for the
determination of hedonic models. It was facilitated by a large GIS dataset collected
by the Rajshahi Master Plan Project.
The study revealed that the semi-log specification provides better results than simple
linear hedonic models. Again, omission of transportation attributes in the hedonic
price models caused four percent reduction in explaining the overall variability of
the property values.
In the study, stepwise regression technique was used to determine best-reduced
model. Moran's J and Geary's c were estimated to identify the effects of spatial
autocorrelation in the residuals of predicted property values. The final model
explained 58.8 percent of the variability in the residential asking rental prices.
Structural attributes are the most significant determinants for property value
variations at Rajshahi. Number of bedrooms proved to be the highest contributor as
a predictor with a standardized coefficient of 0.427.
One of the most interesting findings was that increase in network distance to CBD
from the residential properties increases property values in the study area, as the
corresponding explanatory variable constituted a positive coefficient of 0.34.
However, Accessibility effects of the transportation infrastructure, which was
measured by the network distance from the properties to the major arterials, found to
be negative coefficient indicating that the rent of house decreases with the increase
of distance to the major roads. The estimated hedonic model suggested that moving
0.5-mile closer to the major arterials adds 585.858 Taka premiums, all else held
equal, on residential asking rental price at Rajshahi City.
