Spatial econometric issues in hedonic property value models: Model choice and endogenous land us

The dissertation consists of two major components on the topic of environmental valuation using spatial hedonic pricing models.;The first component deals with the specification of a spatial hedonic model. The focus is on how to include the spatial effects of observed house prices into a hedonic model and selecting a suitable spatial model. Several popular spatial models are considered. I argue that, based on theoretical grounds, the spatial error components (SEC) specification provides a better model for house price than the spatial lag model and the SAR error model. I also question the "convention" of row-standardizing the spatial weights matrix in practice and discuss its implications within each of these spatial models. An empirical application is conducted using a large dataset on house sales near three landfills. To illustrate and justify the arguments, I estimate the impacts that these different landfills have on nearby house prices using several spatial models. My claims are supported by the large-sample empirical evidence.;The second component investigates issues related to estimation of the impact of privately-owned and developable open space on nearby house prices. Because privately-owned and developable open space is considered as a part of the residential market, its level responds to area house prices. As a result, an endogeneity problem arises in the hedonic regression model of house price as the house price and surrounding open space are simultaneously determined. The usual approach to deal with this endogeneity is to use IV/2SLS estimation. I propose a new approach that improves on IV/2SLS in two ways. First, in addition to the hedonic modeling of house price, a dynamic process of open space conversion is modeled to include more information, resulting in a simultaneous-equation model. Second, based on the arguments made in the first component, the SEC specification is applied to both equations of the model to incorporate the spatial effects embedded in neighboring house prices and neighboring open spaces. As a result, a nonlinear spatial simultaneous-equation model is suggested to estimating the marginal implicit price of developable open spaces around properties. The estimation results show that the house buyers of the two areas have distinct preference of surrounding land uses of properties. In addition, people only appreciate the amenity effect of open space that is protected from future development.;These two components are related with each other in the sense that the first component establishes a methodology basis for estimating spatial hedonic property value model; the second one comes with an empirical application to modeling spatial effects of neighboring open space (and neighboring house price). Both are to contribute to the application of spatial econometrics in estimating hedonic pricing model.