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

6. Repeat Sales Analysis
In general, the Base and Alternative Hedonic Models presented in previous sections come to the
same basic conclusion: wind power facilities in this sample have no demonstrable, widespread,
sizable, and statistically significant affect on residential property values. <strong>The</strong>se hedonic models
contain 29 or more controlling variables (e.g., house and site characteristics) to account for
differences in home values across the sample. Although these models perform well and explain
nearly 80% <strong>of</strong> the variation in sales prices among homes in the sample, it is always possible that
variables not included in (i.e., “omitted from”) the hedonic models could be correlated with the
variables <strong>of</strong> interest, therefore biasing the results.
A common method used to control for omitted variable bias in the home assessment literature is
to estimate a repeat sales model (Palmquist, 1982). This technique focuses on just those homes
that have sold on more than one occasion, preferably once before and once after the introduction
<strong>of</strong> a possible disamenity, and investigates whether the price appreciation between these
transactions is affected by the presence <strong>of</strong> that disamenity. In this section a repeat sales analysis
is applied to the dataset, investigating in a different way the presence <strong>of</strong> the three possible
property value stigmas associated with wind facilities, and therefore providing an important
cross-check to the hedonic model results. <strong>The</strong> section begins with a brief discussion <strong>of</strong> the
general form <strong>of</strong> the Repeat Sales Model and a summary <strong>of</strong> the literature that has employed this
approach to investigate environmental disamenities. <strong>The</strong> dataset and model used in the analysis
is then described, followed by a summary <strong>of</strong> the results from that analysis.
6.1. Repeat Sales Models and Environmental Disamenities Literature
Repeat sales models use the annual sales-price appreciation rates <strong>of</strong> homes as the dependent
variable. Because house, home site, and neighborhood characteristics are relatively stable over
time for any individual home, many <strong>of</strong> those characteristics need not be included in the repeat
sales model, thereby increasing the degrees <strong>of</strong> freedom and allowing sample size requirements to
be significantly lower and coefficient estimates to be more efficient (Crone and Voith, 1992). A
repeat sales analysis is not necessarily preferred over a traditional hedonic model, but is rather an
alternative analysis approach that can be used to test the robustness <strong>of</strong> the earlier results (for
further discussion see Jackson, 2003). <strong>The</strong> repeat sales model takes the basic form:
Annual Appreciation Rate (AAR) = f (TYPE OF HOUSE, OTHER FACTORS)
where
TYPE OF HOUSE provides an indication <strong>of</strong> the segment <strong>of</strong> the market in which the house is
situated (e.g., high end vs. low end), and
OTHER FACTORS include, but are not limited to, changes to the environment (e.g., proximity
to a disamenity).
<strong>The</strong> dependent variable is the adjusted annual appreciation rate and is defined as follows:
ln P 1/ P2
AAR exp 1
t1
t2
where
(10)
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