Home Values Not Responsive to Statistical Analysis
The Boston Globe Magazine listing (2/9/14) of a Kingston home for $899,000 in the Country Club Way neighborhood reads like an ordinary upscale purchase until the last sentence: ” Cons A wind turbine is visible at street’s end.”
The 400+ foot turbine not only looms over the property, but would also be audible to the residents. In fact, all five turbines in Kingston are not very distant from the property location (approximately where the yellow pin appears in the middle of this map–which can be found on page 11 in the report “O’Donnell Wind Turbines Noise Analysis, Kingston, MA” by Allan Beaudry and Michael Bahtiarian).
This could be why the home, which originally listed for $949,900 in June 2013, has been on the market for 224 days and is now offered at a price reduction.
That a disclaimer is needed in a property listing contradicts the findings of the recent report commissioned by the MassCEC and performed by UConn and Lawrence Berkeley Lab (California) statisticians. The report had been prominent on the Kingston town website until residents complained that it was another misleading, pro-wind document similar to others the town had posted. Kathryn Gallerani reported on the concern in The Enterprise (Brockton), “Residents question decision to post turbine study on town website:”
KINGSTON – A study commissioned by the Massachusetts Clean Energy Center indicates that despite claims to the contrary it cannot be demonstrated statistically that wind turbines affect nearby home prices.
Critics say the findings of this new study are misleading. Some residents are angry that the study has been posted to the town’s website.
The misleading aspects of the study have to do with the methodology, which lumps together many years of property sale data and homes at various distances from turbine locations. Michael McCann, an appraiser who has been consulted as an expert in many wind turbine siting proposals, has said
The CEC/Hoen study is far from transparent. Not a single property sale is identified, and this of course makes it impossible to independently verify any of the facts or relevance of the data relied on by the author. Further, using 122,000 “sales” in an effort to claim the study is reliable is misleading. Only a minuscule number of those transactions are likely to have been affected by neighboring turbines, so the actual impacts get lost in the rounding of statistical analysis.