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

5.1.1. Dataset and Model Form
<strong>The</strong> same dataset is used as in the Base Model, focusing again on post-construction transactions
(n = 4,937). To investigate DISTANCE effects alone the following model is estimated:
(2)
0 1 2 3 5
ln P N S X DISTANCE
s k d
where
P represents the inflation-adjusted sales price,
N is the spatially weighted neighbors’ predicted sales price,
S is the vector <strong>of</strong> s Study Area fixed effects variables (e.g., WAOR, OKCC, etc.),
X is a vector <strong>of</strong> k home and site characteristics (e.g., acres, square feet, number <strong>of</strong> bathrooms,
condition <strong>of</strong> the home, age <strong>of</strong> home, VISTA, etc.),
DISTANCE is a vector <strong>of</strong> d categorical distance variables (e.g., less than 3000 feet, between one
and three miles, etc.),
0 is the constant or intercept across the full sample,
1 is a parameter estimate for the spatially weighted neighbor’s predicted sales price,
2 is a vector <strong>of</strong> s parameter estimates for the study area fixed effects as compared to transactions
<strong>of</strong> homes in the WAOR study area,
3 is a vector <strong>of</strong> k parameter estimates for the home and site characteristics,
5 is a vector <strong>of</strong> d parameter estimates for the DISTANCE variables as compared to transactions
<strong>of</strong> homes situated outside <strong>of</strong> five miles, and
is a random disturbance term.
<strong>The</strong> parameters <strong>of</strong> primary interest are 5 , which represent the marginal differences between
home values at various distances from the wind turbines as compared to the reference category
<strong>of</strong> homes outside <strong>of</strong> five miles. <strong>The</strong>se coefficients can then be compared to the same coefficients
estimated from the Base Model.
Alternatively, to investigate the VIEW effects alone, the following model is estimated:
(3)
0 1 2 3 4
ln P N S X VIEW
s k v
where
VIEW is a vector <strong>of</strong> v categorical view variables (e.g., MINOR, MODERATE, etc.),
4 is a vector <strong>of</strong> v parameter estimates for the VIEW variables, and
all other components are as defined in equation (2).
<strong>The</strong> parameters <strong>of</strong> primary interest in this model are 4 , which represent the marginal differences
between home values for homes with varying views <strong>of</strong> wind turbines at the time <strong>of</strong> sale as
compared to the reference category <strong>of</strong> homes without a view <strong>of</strong> those turbines. Again, these
coefficients can then be compared to the same coefficients estimated from the Base Model.
Our expectation for both <strong>of</strong> the models described here is that the results will not be dramatically
different from the Base Model, given the distribution <strong>of</strong> VIEW values across the DISTANCE
values, and vice versa, as shown in Table 11. Except for EXTREME view, which is
34