Northern NY Property Values

I.               The effect of wind turbines on Northern New York property values

Due to recent concerns of climate change, renewable energy sources such as solar power, wind energy, and geothermal energy have become more popular. Although these energy sources have very few environmental impacts, there are several problems. These renewable energy services are not cost competitive with traditional fossil fuels, to be used effectively they would require major changes to infrastructure, and they are often met with resistance from locals.

Wind power is the fastest growing renewable energy in the United States and this growth is expected to continue. There are several areas of concern with wind energy including wildlife, human health effects, and aesthetics. When perceived in such a negative light, it is possible that wind farms may have a negative affect on property values in surrounding areas. Individuals who are willing to let turbines be built on their property receive payments directly from the developer. This money helps to offset the impacts to the owner’s property values. However, property owners that are in close proximity to the turbines have no control over the effects to their property values. Local residents must deal with any negative health repercussions and aesthetic impacts, which as a consequence could possibly affect property values.

There is very little literature that analyzes and  discusses the relationship between wind turbines and property values. This analysis used data on 6 wind farms and 11,369 residential and agricultural property transactions between 2000 and 2009 in the Clinton, Franklin, and Lewis Counties in Northern New York.

Data and Methodology

This report uses a repeat sales fixed-effects hedonic analysis. There are several difficulties in measuring the effect of wind turbines. The first is when the turbine is said to exist. The planning and approval process for turbines is long, and resident know before the turbine is actually built something of how many there will be and where they are going. To compensate for this, this report includes three assumptions about the date of the wind turbine. The data was run separately using the dates of when the draft environmental impact statement was submitted, the date the final environmental impact statement was approved, and the date when the turbine became operational. Another issue is how to measure proximity to the turbine. For this report the inverse of the distance to the nearest turbine was used. Also, the fact that this study deals with wind farms and not single turbines means that if a property is near one turbine it is near many. This has been accounted for. Other variables include distance to the nearest major road, the value of any personal property included in the transaction, whether or not the home is in the village, and standard home characteristics.

Wind turbines are likely to be located on cheaper properties, which is a concern because if this selection effect was ignored correlation may be confused with causation. To avoid this, repeat sales, parcel level, and fixed effects analysis are all used. Time varying factors are the proximity of turbines, the age of any home on the parcel, and the year in which the sale takes place.

Results

These results are subject to endogeneity bias because of the previously mentioned selection effects. It was found that homeowners in these areas prefer larger homes, to be closer to major roads, to be outside of established ‘villages’. Lot size was not found to be a significant factor. Agricultural land is priced lower and property with open water or wetlands are priced higher. Multiple apartments, families, or mobile homes on a parcel reduce the value as well as age of the home.

The existence of turbines within 1 to 3 miles had negative impacts on property values between 15.6% and 31%. Having at least one turbine on the parcel reduced prices by 65%. Effects for turbines at other distances are negative but insignificant.

Some results are subject to the endogeneity biases discussed previously. If this is the case, these estimates would overstate the negative effect of turbine proximity. There was a positive impact of having turbines within .1 miles and some weakly positive impacts for turbines between .5 miles and 1 mile, but negative impacts for turbines between 1 and 1.5 miles away. This may be because homes closer to turbines expect future wind development, which would necessitate easement payments. Throughout all of these regressions the inverse distance measure is strongly significant and negative. This indicates that wind turbines are negatively impacting property values in a way that is declining over the distance from the turbines.

For Lewis County, the proximity effects are still negative, but not significant. For Clinton and Franklin Counties proximity effects are negative and strongly significant.

Heintzelman, M., Tuttle, C. (2011). Values in the Wind: A Hedonic Analysis of Wind Power Facilities. Retrieved from: http://www.wind-watch.org/documents/values-in-the-wind-a-hedonic-analysis-of-wind-power-facilities/