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USGS · 70101061

Effects of environmental amenities and locational disamenities on home values in the Santa Cruz watershed: a hedonic analysis using census data

Abstract

For this study, we used the hedonic pricing method to measure the effects of natural amenities on home prices in the U.S-side of the Santa Cruz Watershed. We employed multivariate spatial regression techniques to estimate how difference factors affect median home values in 613 census block groups of the 2000 Census, accounting for spatial autocorrelation, spatial lags, and/or spatial heterogeneity in the data. Diagnostic tests suggest that failure to account for the hedonic model can be classified as (1) physical features of the housing stock, (2) neighborhood characteristics, and (3) environmental attributes. Census data was combined with GIS data for vegetation and land cover, land administration, measures of species richness and open space, and proximity to amenities and disamenities. Census block groups close to the US-Mexico border of airports/air bases were negative. Results suggest that policies to maintain biodiversity and open space provide economic benefits to homeowners, reflected in higher home values. Future research will quantify the marginal effects of regression explanatory variables on home values to assess their economic and policy significant. These marginal effects will be used as input indicators to discern potential economic impacts of various scenarios in the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM). Future research will also expand this effort into the Mexican-portion of the watershed.

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90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 31.332177° to 31.731819° latitude; -111.36689° to -110.45172° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

Gaurav Arora, George Frisvold, Laura Norman. 2014. Effects of environmental amenities and locational disamenities on home values in the Santa Cruz watershed: a hedonic analysis using census data. https://pubs.usgs.gov/publication/70101061

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