To simplify it, there are three main ways to analyze house prices, in decreasing accuracy. This is a very quick recap of them.
First, you could study houses within audible distance (i.e. one mile) that sold (or perhaps independently appraised) fairly recently before the project was known about and then sold after the project went in. As long as the sales are “arms-length” and the proper adjustments made for area house price trends, this is the best indication of property value changes. This is sometimes called a “matched sales” analysis. Obviously timing is critical – you must find properties that first sold before even a hint of the project was in the wind, and subsequently sold after the project was built. One major problem is the number of homes remaining unsold in these area is quite high. In many cases the full extent of the devaluation won’t show up until the current residents die and the home must be sold, regardless of price.
Second, you could study just the house prices within audible distance of a turbine and compare them with similar houses (aka “comps”) further away, like 10 miles. This technique is commonly used in the Real Estate industry to estimate property values. The trick here is finding enough homes with similar enough characteristics to be able to draw solid conclusions. Sometimes this technique is called “matched pairs”.
Third, you could use regression analysis. You start by taking all the sales within a certain distance of a wind project (5 miles is typical) and assign a series of descriptors to each house within that group – things like size of the house, number of bathrooms, distance from the wind project and so on. You then look for correlations between the different descriptors and the price, trying to assign the contribution of each. Obviously the descriptor of most interest is distance from the project. With enough computer processing you can assign the effect of each of these on the final price.
The two most recent industry-sponsored studies (Hoen and Canning) used regression, and neither of these studies found a statistically significant difference between homes “close” to a project and those “not close”. However, the main reason for this was the wide variances of the prices and the lack of explanatory power of the results, not the differences in the prices – which did exist.