Abstract

This dissertation research focuses on understanding benefits or costs of some urban amenities and disamenities using the Hedonic Pricing (HP) method. It includes three Southern California case studies where different hedonic models (fixed effects, spatial Durbin model, and geographically weighted regression) are estimated to obtain unbiased and consistent parameter estimates. In the first case study, I analyze 20,660 transactions of single family detached houses sold in 2003 and 2004 in the city of Los Angeles, CA, to estimate the value of urban trees, irrigated grass, and non-irrigated grass areas. I rely on fine-grained hedonic models with many covariates to control for unobserved neighborhood characteristics. I find that Angelenos like lawns: 78 percent of the properties examined would gain value with additional irrigated grass in their neighborhood and even more (83 percent) on their parcel. However, additional parcel trees would decrease the value of almost half (46 percent) of the properties examined and they would have only a small positive impact on most of the others. By contrast, additional neighborhood trees would slightly increase the value of over 80 percent of the properties analyzed. This suggests that while Los Angeles residents may want additional trees, they are unwilling to pay for them. These results have implications for urban tree planting programs that rely primarily on private property owners. The second case study quantifies the impact of urban green spaces on the value of 1,197 multifamily buildings sold in 2003-2004 in the city of Los Angeles, California; these green spaces are either on their parcels or in their vicinity (an area 200 meters outward of each parcel boundary). It is necessary to examine multifamily houses separately because they belong to a different market. To assess the robustness of the results, I contrast a spatial Durbin model with a geographically weighted regression model and conduct an extensive sensitivity analysis. I find that increases in grassy areas either on the parcels of multifamily buildings or in their vicinity would typically not enhance their value, and neither would more parcel tree canopy cover (TCC); by contrast, most multifamily properties would benefit from an increase in vicinity TCC. These results suggest that most multifamily building owners have no incentives to increase the tree canopy cover or the grassy areas on their properties. In the third case study, I investigate the impact of freeway traffic on property values using hedonic pricing models, with a particular interest for truck traffic. I analyze 4,715 sales of single family houses that took place in 2003 and 2004 in part of the busy transportation corridor that links the Ports of Los Angeles and Long Beach to downtown Los Angeles. These houses are located at least 200 meters from the nearest arterial road to filter out the impact of traffic on arterial roads. In order to minimize the risk of omitted variable bias and spatial autocorrelation, I estimate a fine-grained fixed effects model. I find that a one percent increase in the proportion of truck traffic could decrease the value of a $420,000 house located between 100 and 400 meters from the nearest freeway by between $2,000 and $2,750. These results are important for policy makers and owners of single family houses located close to freeways as the ports of Los Angeles and Long Beach are forecasting sharp increases in drayage truck activity as the economy recovers.