The Impact of Wind Power Projects on Residential Property Values ...

3. Data Overview
<strong>The</strong> methods applied in the present work are intended to overcome many <strong>of</strong> the limitations <strong>of</strong> the
existing literature. First, a large amount <strong>of</strong> data is collected from residential transactions within
10 miles <strong>of</strong> 24 different wind projects in the U.S., allowing for a robust statistical analysis across
a pooled dataset that includes a diverse group <strong>of</strong> wind project sites. Second, all three potential
stigmas are investigated by exploring the potential impact <strong>of</strong> wind projects on home values based
both on the distance to and view <strong>of</strong> the projects from the homes. Third, field visits are made to
every home in the sample, allowing for a solid assessment <strong>of</strong> the scenic vista enjoyed by each
home and the degree to which the wind facility can be seen from the home, and to collect other
value-influencing data from the field (e.g., if the home is situated on a cul-de-sac). Finally, a
number <strong>of</strong> hedonic regression models are applied to the resulting dataset, as are repeat sales and
sales volume analyses, in order to assess the robustness <strong>of</strong> the results.
Testing for the three potential stigmas requires a significant sample <strong>of</strong> residential transactions
within close proximity to existing wind facilities. Unfortunately for the study, most wind power
projects are not located near densely populated areas. As a result, finding a single wind project
site with enough transaction data to rigorously analyze was not possible. Instead, the approach
was to collect data from multiple wind project sites, with the resulting data then pooled together
to allow for robust statistical analyses. 19 <strong>The</strong> remainder <strong>of</strong> this section describes the site
selection process that is used, and provides a brief overview <strong>of</strong> both the selected study areas and
the data that were collected from these areas. Also provided is a description <strong>of</strong> how scenic vista,
views <strong>of</strong> turbines, and distances from turbines were quantified for use in the hedonic analysis,
and a summary <strong>of</strong> the field data collection effort. <strong>The</strong> section ends with a brief summary <strong>of</strong> the
resulting dataset.
3.1. Site Selection
For the purpose <strong>of</strong> this study, an ideal wind project area would:
1) Have a large number <strong>of</strong> residential transactions both before and, more importantly, after wind
facility construction, and especially in close proximity (e.g., within 2 miles) <strong>of</strong> the facility;
2) Have comprehensive data on home characteristics, sales prices, and locations that are readily
available in electronic form; and
3) Be reasonably representative <strong>of</strong> the types <strong>of</strong> wind power projects being installed in the
United States.
To identify appropriate sites that met these criteria, and that also provided a diversity <strong>of</strong> locations,
the authors obtained from Energy Velocity, LLC a set <strong>of</strong> Geographic Information System (GIS)
coordinates representing 241 wind projects in the U.S. that each had a total nameplate capacity
greater than 0.6 megawatts (MW) and had gone online before 2006. 20 Also provided were
facility capacity, number <strong>of</strong> turbines, and announcement, construction, and operational dates.
<strong>The</strong>se data were cross-checked with a similar dataset provided by the American <strong>Wind</strong> Energy
Association (AWEA), which also included some turbine hub-height information.
19 A thorough discussion <strong>of</strong> this “pooled” approach is contained in Section 4.2 and in Appendix F.
20 Energy Velocity, LLC was owned at the time by Global Energy Decisions, which was later purchased by Ventyx.
<strong>The</strong> dataset is available as Velocity Suite 2008 from Ventyx.
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