This research attempts to quantify the cumulative impacts of vehicle traffic, both passenger cars and trucks, by using the hedonic price analysis of the relationship between property values and the traffic along selected arterial corridors in Chicago, Illinois. The traffic characteristics are derived from the traffic counts data obtained from the City of Chicago and include average daily traffic, maximum daily peak, and nighttime volumes, calculated separately for trucks and for total traffic. Autoregressive models, with assessed property value as the dependent variable and traffic characteristics along with other determinants of property value as the independent variables, are constructed. The models include a spatial-lag term to control for the spatial autocorrelation and are estimated using the two-stage least squares. The regression results from the final models suggest that although the characteristics for total traffic have modest but statistically significant impact on property values, the traffic characteristics for trucks are statistically insignificant. Also, the strong evidence of spatial dependence in the data set underscores the importance of paying close attention to the model specification and controlling the autocorrelation in the hedonic price analysis.
Abstract