Chong Won Kim

Date of Graduation


Document Type



The United Nations Environment Programme and the World Health Organization (1994) reported that Seoul has serious problems with sulfur dioxide. The primary objective of this study is to improve the methodology for estimating hedonic price functions when the data are inherently spatial in nature. The secondary objective is to estimate the marginal value of air pollution abatement in the Seoul metropolitan area. The hedonic property value model is employed to achieve this goal. To attain the primary objective, this study explicitly considers the spatial effects of housing prices in estimating the hedonic property value price function. Spatial weight matrices are designed to capture the spatial effects. Two conceptual models are considered to capture spatial effects: the spatial lag and the spatial error hedonic property value model. The idea behind the spatial lag hedonic property value model is that the neighborhood housing prices directly affect to one's housing price. The idea of the spatial error hedonic property value model is that spatial dependencies are captured by the spatial error, which is similar to a first order moving average process in time series models. Estimation results showed that the spatial lag model with log-linear functional form is best in the Seoul housing market for both owner and renter households. Some important results are explored by deriving marginal benefits from the spatial lag property value model. The traditional hedonic housing price model without spatial considerations does not reflect the actual working of real estate markets. The spatial lag model enables both direct and induced effects of a neighborhood's housing characteristic changes to be captured through the spatial multiplier (1/1-{dollar}\\rho{dollar}). The marginal benefit estimations show that owner and renter households have large differences in WTP for air quality improvement. Marginal WTP for a marginal change of air quality (4% improvement) are about {dollar}3,000 {dollar} sim{dollar} \\{dollar}3,300 (1.2 {dollar}\\sim{dollar} 1.5% of mean housing price) for owner households and {dollar}370 {dollar} sim{dollar} \\{dollar}420 (0.7 {dollar}\\sim{dollar} 0.9% of mean rent price) for renter households. These results are interpreted as follows: The value of air quality capitalized into the price of the house is the present value of air quality the individual expects to receive while living there. Therefore, an owner is willing to pay more for the air quality improvement than a renter.