By: Josh Gabbatiss
Wind turbines have increased local incomes by around 5% and house values by 2.6% in parts of the US, according to a new study.
The research, published in the journal Energy Policy, found benefits in terms of jobs, taxes and land payments associated with renewable energy.
In the study, the authors used the variation in wind-power growth in counties across the US to assess economic outcomes for comparable areas. They say that their approach allowed them to isolate and prove the causal effect of windfarm construction on economic outcomes.
Last year, wind power generated 9% of electricity in the US, with much of it coming from onshore turbines in rural regions. The researchers note that, according to their findings, wind power has brought the greatest benefits to such areas.
Upon his election in 2020, US president Joe Biden committed to an inclusive clean energy transition, achieving 100% zero-carbon electricity by 2035 while ensuring jobs and support for communities around the nation.
The authors of the new research say their results provide evidence for the benefits of wind turbines and could help to generate local support for them in rural areas.
The study notes that US wind power has grown “tremendously” in a relatively short space of time.
As the maps below show, in 1995, when wind power made up 0.1% of US electricity, it was concentrated in California. It has now spread across much of the nation, particularly in Texas and some of the Great Plains states where wind speeds are particularly high.
Much of US wind power capacity is located in counties classified as rural areas. For wind-power advocates, besides their climate benefits, these installations are a potential source of income for communities that are often struggling economically.
Windfarms can provide jobs to those building and maintaining the turbines, as well as income to local landowners and greater demand for local goods and services.
However, in some quarters of the US there have been concerns that wind turbines could harm communities, chiefly by lowering property prices. This echoes backlashes seen in the UK and France, although in both nations onshore wind power is, in fact, broadly very popular.
Researchers Prof Eric Brunner of the University of Connecticut and Dr David Schwegman of the American University assessed 2,971 counties over the period 1995-2018, of which 465 installed wind turbines.
The study concluded that, on average, US counties where wind energy was built saw increases in per-capita income of 5% and per-capita gross domestic product (GDP) of 6.5%, relative to the average trends seen in counties that did not have new wind turbines. Furthermore, they concluded that the economic impacts were directly caused by the installation and operation of the windfarms.
Unlike some previous studies, they also found a positive impact on home values in counties where wind power was built – a boost of 2.6% compared to the average outcomes in counties with no turbines built.
These are average annual increases for the eight years after turbine construction, relative to the year prior to construction starting.
As an example, Schwegman tells Carbon Brief that, according to his findings, building a 100 megawatt (MW) wind farm – close to the average once the smallest installations of less than 2MW are excluded – would increase county-wide incomes in an average-sized county by more than $300 per capita and median home values by more than $400.
However, the study also showed that the size of these effects depended heavily on the size of the windfarms being built, with the positive results skewed towards those with larger capacity installations.
Extra space for large installations could also explain why rural areas that built windfarms saw a GDP boost around three times larger than urban areas adding wind capacity, according to the study. Schwegman adds:
“It’s unclear if the economic benefits are inherently greater for rural counties, versus the fact that there is just more ability to put wind turbines into rural counties.”
The researchers employed a model that allowed them to use the variation in wind-power installation across the US as a natural experiment to compare those counties with and without the technology.
It used a “difference-in-differences” method which allowed them to compare economic outcomes in counties before and after they built wind turbines, against counties that did not build wind turbines but were otherwise similar.