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Tag Archives: University of Guelph

Realtors dispute economist study on wind farm neighbour property values

31 Wednesday Dec 2014

Posted by ottawawindconcerns in Renewable energy, Wind power

≈ 1 Comment

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Canadian Journal of Agricultural Economics, Canadian Real Estate Wealth, Melancthon, mortgage financing, property value, property value loss, property values, real estate appraisers, real estate value, Realtor, Richard Vyn, University of Guelph, wind farm property value, wind farms, wind turbine, wind turbines

Wind farm “monsters bad for Ontario: Realtors shoot back at property value study

Looks like a great place to live!!
Looks like a great place to live!!

Jennifer Paterson, Canadian Real Estate Wealth, December 18, 2014

A recent study by the University of Guelph, which found wind turbines do not have an impact on nearby property values, might have earned a big sigh of relief from investors – but the study’s results have been strongly criticized by members of the real estate industry.

“I have had several deals fall apart in this area because, in the appraisal report, it has been mentioned that there are windmills visible or adjacent to the property and, once a lender gets wind of that (forgive the pun), they will not fund a mortgage,” said Angela Jenkins, a mortgage agent at Dominion Lending Centres, who lives and works in the Melancthon region, where the study was conducted.

“If a person cannot get financing due to windmills, then how can this be a positive thing?”

The study, which was published this month in the Canadian Journal of Agricultural Economics, analyzed more than 7,000 home and farm sales in the area, and found that at least 1,000 of these were sold more than once, some several times.*

John Leonard Goodwin, who has been a real estate broker for more than 10 years in the Grand Bend, Ont. market, asserted that wind turbines absolutely do affect property values. “Turbines complicate your property enjoyment, period,” he said. “That alone spells depreciated value(s).

“Turbines should be in remote, unpopulated locations. To all the folks who have turbines on their property: Enjoy your $18,000 per turbine per year, because you will be giving most of the lease payments back (in much lower property value) when you sell.

“These monsters are very bad for Ontario,” he continued. “We all pay to subsidize the electricity they produce and they will also cause a significant loss of real estate value.”

Lynn Stein, a sales representative at Hartford and Stein Real Estate, lives and sells real estate in Prince Edward County, where a large-scale wind turbine project is slated to begin.

“The turbines that are proposed here are quite large,” she said. “The majority of the population here very clearly doesn’t want them.

“Put simply, if you were to buy your future home, given the choice, would you buy where you would have noise, shadow flicker, an industrial view, potential health issues caused by the turbines, and the possibility of a very difficult resale, or would you spend your money elsewhere?”

Read the full story and comments here.

*Wind Concerns Ontario Editor’s note– The writer is incorrect: Vyn had a data set of 5,414 residences but very few, 124, were within 5 km of a turbine. Several were as far as 50 km from a turbine. This is a tactic designed to “dilute” any actual effect. Author Richard Vyn himself said that the limitations of this study (sponsored by MPAC, perhaps to buttress their own disastrous study on this issue earlier this year) were significant and should not be overlooked. Toward the end of his paper he admits, “…while the results indicate a general lack of significantly negative effects across properties examined in this study, this does not preclude any negative effects occurring on individual properties.”

The Realtors and financing professionals contacted for this article also did not note that Vyn failed to include expired listings, i.e., properties that were listed for sale, but never sold.

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Wind farm property value study should not have been published: Queens prof

09 Tuesday Dec 2014

Posted by ottawawindconcerns in Renewable energy, Wind power

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Andrejs Skasburskis, regression analysis, Richard Vyn, University of Guelph, wind farm effects on property values, wind farm locations, wind farm neighbours, wind farm property values, wind farm research

You may have seen the Canadian Press story that surfaced on Sunday and Monday about a study done by a University of Guelph agricultural economics teacher, which was published in the Journal of Agricultural Economics. While the headlines said wind turbines caused NO effect on property value, the real study said otherwise: the co-authors noted that they had very little data, that expired listings (houses listed for sale that never sold) were not included, and neither were sales not on the open market, such as the properties purchased by wind power developers.

So the situation was: very few sales, houses not selling at all, and some houses that did sell changed hands many times. What’s wrong with that picture?

Well, plenty. Here’s a letter to the editor of the journal that published the study, released today. Too bad the damage has been done by the headline writers.

Letter to the Editors of Canadian Journal of Agricultural Economics:

The paper by Vyn and McCullough (2014) should not have been published in its current form as the results are being misinterpreted and highly publicized in the press and in radio broadcasts. The core issue is the lack of power in the statistical tests, a problem partially acknowledged by the authors but then dismissed by their focusing attention on tests for the sensitivity of their model specification. The article appears to encourage the misinterpretation of its statistical findings.

Out of the 5414 sales, only 79 post-turbine sales are of properties within a 5 kilometer radius and the rest are within a 50 kilometer radius. The diversity of the houses in the sample is very large as indicated by their price range of ten thousand to two million dollars and by the relatively low R-squares (0.57) in the hedonic regressions. Given the small number of properties that may have been adversely affected and the great diversity of properties in the sample, it is not at all surprising that the regressions yield no ‘statistically significant’ results. The shortage of observations on properties close to the turbines cannot be overcome by extensive sensitivity testing of model form. The problem is with the lack of data not with model form and focusing on the form tends to obfuscate the issue.

The authors do recognize the data problem: “Unfortunately, there are relatively few observations in the post-turbine periods that are in close proximity to turbines” (p 375) and “Hence, these numbers of observations are likely too few to detect significant effects, which represents a major limitation of this analysis” (p 387). But there are three problems that should have been picked up and corrected through the peer review and editorial decision process.

First, the authors conclude:

“The empirical results generated by the hedonic models, using three different measures to account for disamenity effects, suggest that these turbines have not impacted the value of surrounding properties” (p 388). This is wrong for two reasons. First they could not discern an impact which is different from not having an impact. Second, they misuse the term ‘value’. If you have a choice between two identical properties, identical in all respects except that one is close to a turbine while the other is not and if you choose the far one, then the turbine has an effect on the value of the property. This hypothetical example tests the paper’s hypothesis using common sense rather than a statistical measure.

Second, the authors claim:

“The findings of this paper will provide evidence that may help to resolve the controversy that exists in Ontario regarding the impacts of wind turbines on property values” (p 369) and then proceed to do all they can to make a non-finding appear important and repeat the general statement that they found no significant impact. They correctly said in the CBC interview this morning that their study did not find a statistically significant price effect but the public and reporters, not being familiar with statistical terms interpret this as saying that there was no price effect. Not finding a statistically significant impact due to a data shortage does not mean that there was no significant (i.e. important) impact. This distinction was not made clear enough in the paper nor in the follow up interviews and newspaper articles.

Third, the reviewers and finally the editors should have insisted on the power of the statistical tests to be calculated and reported. I understand that editors in the major health science journals insist on this as their readers, doctors and other clinicians, are not always aware of statistical fine-points but they need to be fully aware of the qualifications before using the results to change their practice. Given the potential impact a misinterpretation of the findings could generate, the test of the power should be reported even in the abstract. The reader should be told how big an impact would have to be before it can be detected by a statistical test with this number of observations. Had the price of properties near the turbines been 10 percent lower than they actually were, would the model have yielded a statistically significant finding of a price decrease at say the 0.05 probability level? What about a 20 percent decrease, would it have been ‘statistically significant’? Answers to this type of question would have been easy to produce and far more relevant that sensitivity tests of the model form.

The paper deals with an important issue that can have serious policy implications affecting the wellbeing of many people. The results can affect the location of wind turbine farms and the compensation claims of affected parties. Incorrect information or interpretations can be very hard to correct. In such cases, it is the journal editors’ responsibility to ensure that results are presented in a manner that, at the very least, does not encourage the misinterpretation of the findings.

Sincerely,

Andrejs Skaburskis, Professor Emeritus

North American Editor: Urban Studies,

School of Urban and Regional Planning,

Queen’s University,

Kingston Ontario, Canada

 

___________________________________________________

Richard J. Vyn and Ryan M. McCullough (2014), The Effects of Wind Turbines on Property Values in Ontario: Does Public Perception Match Empirical Evidence? Canadian Journal of Agricultural Economics 62 p. 365–392

 

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