Abstract
This paper uses GIS data to develop variables representing the physical extent and visibility of surrounding land use/cover features in a hedonic model of a rural/suburban residential housing market. Three equations are estimated to determine if views affect property prices and, further, if omission of visibility variables leads to omitted variable biases. To improve efficiency, first-order spatial autoregressive models are estimated. Results indicate that the visibility measures are important determinants of prices and that their exclusion may lead to incorrect conclusions regarding the significance and signs of other environmental variables. (JEL Q21)
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