The article below references just a bite of the latest “PR” that you will find on the newest study that uses a rubber ruler to estimate home values. The web is riddled with copycats of this nonsense. Instead of using complex models/assumptions, nationally known property appraiser Mike McCann suggests that the old “paired analysis” technique using the Multiple Listing Service (MLS) is sufficient here. One of the benefits of such a paired study is that the data is transparent and the tests can be replicated and validated. However, neither of these things is true, below, in Hoen’s use of the “hedonic model” – called by Albert Wilson a “rubber ruler”.
What is a first reaction to the study below? It should serve as a great reason for BigWind to provide property value guarantees to all homeowners within a certain distance to a turbine! After all, BigWind says the report is “independent” – so there should be no risk to the developer, right? OOPS! Just last week testimony was provided in the Everpower Scioto Ridge hearing (Ohio) that . Why should BigWind be allowed to have their cake and eat it too?!
What does Mike McCann the noted property appraiser have to say?The remaining comments are his…
• 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 miniscule 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.
An analogy may be helpful to understand the lack of relevance of that large database used by the CEC study:
The Boston Marathon had over 23,000 runners start the race, and tens of thousands more were in attendance. When the terror bombs killed 3 people, this was an incredibly significant event. But using hedonic measurement of statistical significance against that large “data” background, a researcher could opine that the tragedy was not “statistically significant”.
Thus, the large database of the CEC study can be understood as obscuring the substantive significance of value impacts, by diluting the mathematical measurement with non-impacted data. In order for comparisons to be valid from an appraisal perspective, the impacts of near vs. far data must be measure on a 1:1 basis, i.e., paired sales methodology. However, 500:1 or 1,000:1 allows the research and conclusions to be manipulated.
• 8 years after his Thesis paper on this subject, Mr. Hoen still fails to use the industry standard data source; namely the Multiple Listing Service (MLS) data, which includes marketing time data and list to sale price ratio data, as well as expired and cancelled listing comparison for homes that no one would buy.
In summary, the deficiencies of the CEC study are numerous, and the report should not be relied upon for any public policy or siting purposes. Unless the data details are made available for independent and objective review and testing, there can be no assurance that fundamental errors in the prior work of the author have not been replicated in this latest endeavor to support wind turbine development in or near residential locations….
A quasi-public agency responsible for promoting clean-energy technologies in the Bay State has released a study that found no significant effect of wind turbines on home values.\”What we wanted to do was to help provide independent research to communities that are either dealing with questions about existing projects in their communities or communities that might be dealing with new projects,\” said Alicia Barton, CEO of the Massachusetts Clean Energy Center, which sponsored the study