Influence of Public Conservation Acquisition on Surrounding Residential Property Values in Gainesville, Florida

摘要

This study uses a hedonic price model to examine the relationship between proximity to newly purchased conservation lands and single-family property values. Specifically, a variant of the hedonic price model is used that addresses changing market values of neighborhood and locational attributes during a given period. Fixed effects are included to control spatial autocorrelation and year and month influences under three variants of an ordinary least-squares (OLS) model, which are double-log, semi-log, and linear model. In addition to the traditional OLS model to explain residential values, a geographically weighted regression (GWR) model is used to study the local difference of coefficient values for each primary variable. An empirical study using a single-family house market-price data set from 2002 to 2010 and 104 newly purchased conservation lands in Alachua County, Florida, is also conducted. To account for the impact of the housing market crash around 2006, the researchers break the data set into two groups (precrash and postcrash), and compare them. The results indicate that sales price increases 0.04% for every percent decrease in distance to the nearest conservation land in general, while the positive influences from conservation lands are larger precrash compared to those afterward. In addition, time from acquisition is not significant precrash; however, it has a negative influence on property values after the housing market crash in 2006. The result is that the purchase of environmentally sensitive lands has an immediate and positive influence on neighboring property values. The influence, however, decreases as time from purchase increases. The results of this study support the government policy of protecting environmentally sensitive lands through their purchase. In addition, coefficient surfaces generated from GWR models can also be used as a guideline for making these purchases in terms of location. (C) 2017 American Society of Civil Engineers.