Abstract

Despite several studies that have estimated the economic value of beach proximity on housing values, previous linear hedonic pricing models (HPMs) have yet to explore the spatially heterogeneous beach premiums for housing prices. To address the issue, this study demonstrated the feasibility of spatial HPM (S-HPM) using geographically weighted regression (GWR) analysis of 152 properties in Jacksonville Beach, Florida. Specifically, this study (1) investigated the spatial associations between multiple beach proximity attributes and housing values, (2) explored local variations in modeling housing values, and (3) assessed whether GWR-based S-HPM outperformed previous linear HPM. Results indicated that the GWR-based S-HPM revealed spatially heterogeneous beach premiums for housing values, with improvements in model performance over the corresponding linear HPM. Findings of this study can contribute to understanding the local patterns of beach premiums for housing prices, ultimately providing guidelines for location-based beach access planning and management.

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