To site new generation we must develop inclusive processes that don’t just reward the most influential.
When you fly into Maui, at some point on the approach to Kahului airport you usually get to see the Kaheawa wind farm running up the side of Pu’u Kukui, on the west side of the island. Some people call it a visual desecration of natural beauty. Others see it as a realistic step towards mankind learning to live in harmony with nature. I’m in the latter camp, but have heard a lot from those in the former.
For me, views are not like food. One sour ingredient doesn’t ruin the whole composition. I would rather there weren’t transmission lines spanning the canyon in one of my favorite hiking spots near my home, but these days I don’t really focus on them. And complaining about them has always felt a bit first world problemish. Then again, aesthetics are a very personal thing and I recognize that preferences different from my own can be equally valid (even if I secretly think they are WRONG ;-).
As the world moves away from burning fossil fuels, it’s clear that no energy source is without externalities. For solar and wind, visual and noise pollution are raised most often. With increasing pressure for local renewables, we will be hearing those concerns more often.
That’s what makes the Energy Institute working paper that Stephen Jarvis released in January so timely and important. He examines how much people dislike living near electricity infrastructure by looking at the impact on property values. His paper is not the first to do this — Lucas has a nice 2011 paper on the impact of nearby fossil fuel power plants — but Stephen’s clever empirical approach to the issue gives us the most credible answers yet for wind and solar plants. What makes the research so compelling is that he then asks how the local economic impact plays into the approval or rejection of proposed renewables projects, and the implications of that for the cost of cutting carbon emissions.
The setting is the UK, Stephen’s native land (and where he will be returning in the fall to start as an assistant professor at the London School of Economics). What’s unusual about the dataset he studies is that it not only includes every wind and solar project ever built in the country, but also every project that applied for a siting permit and was rejected. Of the nearly 3500 projects, he can even tell which ones almost made it, but got rejected at the last stage. That sets up a nearly perfect counterfactual (yes, there’s always some reason they aren’t perfectly comparable, but this is pretty darn close), allowing him to measure how property values changed near new renewables generation compared with locations that just missed out.
In short, Stephen finds that the impact of wind turbines on property values can be substantial. For houses within 2 km, a 10 MW wind farm knocks around 6% off home values on average, compared to the homes equally near the projects that didn’t get built. That average effect turns out to be mostly driven by homes in wealthier areas and with a direct line of sight to the turbines (some fancy geospatial modeling here to figure out which homes got that sour ingredient). For those properties, the reduction is nearly 15%, while in areas that are less well off or can’t see the wind farm the effect seems to be small and not statistically distinguishable from zero.
Solar farms, on the other hand, don’t move the needle at any distance, though that might be because UK solar farms have been pretty small so far. (It’s not the first country you think of for great solar resource.)
Still, the results show wind farms can have a real impact on property values around wealthy communities. Do policymakers take that impact seriously enough? Or maybe too seriously?
The paper looks at how much these effects matter in the siting approval process, which is predominantly local in the UK. Does lost value to neighboring properties get as much weight as the value created from the electricity output, from reducing pollution or from lowering development costs? Or do effects on nearby property get more weight, which is almost the definition of NIMBYism.
Stephen examines which of these, and some other, factors are associated with getting a project approved. By far the most important factor is the impact on property values. A 10 million pound projected impact on local property values is estimated to lower the probability of approval by 3%. Similar size financial effects from changes in costs, output value or environmental benefits have a tiny impact on approval probability.
That raises an interesting question: if the effect on nearby, mostly wealthy, property owners gets overweighted in the local decision-making process, would regional planning that is more balanced lower the overall cost of developing low-carbon energy sources? Probably. We only have estimates of what it would have cost to build elsewhere, but using his best estimates, Stephen finds that without the NIMBY bias, the same amount of capacity could have been built in better locations at 10%-29% lower total economic cost (which includes effect on property values). There are some caveats on the exact number, but it is clear that local resistance and a lack of regional planning can have big impacts on where renewables get built and how much net economic value they produce.
There are some other questions that Stephen hasn’t answered, yet. One is whether this effect is unique to renewable electricity generation, or is this a more general phenomenon about industrial development?
Another question, if wealthy neighborhoods take a bigger financial hit from nearby siting of wind turbines, what is the right policy response? Should the turbines just be redirected to less wealthy areas? Or does shared responsibility for reducing GHGs mean that no one gets a pass? Maybe a community that accepts a wind farm should also receive compensation? With growing recognition of past injustices — and lack of representation — in locating industrial facilities and environmental hazards, it is clear that now is the time to confront these issues for siting renewable generation.
President Biden’s pledge last week on greenhouse gas reductions amounts to reducing emissions by about 40% between now and 2030. That’s going to require a lot of new solar and wind farms, as well as transmission lines, battery factories, lithium mining, and other activities many people won’t want to live near or look at. To fulfill that pledge, we are going to have to figure out where all those new industrial facilities can go, and how to equitably make it happen.
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Suggested citation: Borenstein, Severin. “Finding Homes for Wind and Solar” Energy Institute Blog, UC Berkeley, April 26, 2021, https://energyathaas.wordpress.com/2021/04/26/finding-homes-for-wind-and-solar/
Severin Borenstein is Professor of the Graduate School in the Economic Analysis and Policy Group at the Haas School of Business and Faculty Director of the Energy Institute at Haas. He received his A.B. from U.C. Berkeley and Ph.D. in Economics from M.I.T. His research focuses on the economics of renewable energy, economic policies for reducing greenhouse gases, and alternative models of retail electricity pricing. Borenstein is also a research associate of the National Bureau of Economic Research in Cambridge, MA. He served on the Board of Governors of the California Power Exchange from 1997 to 2003. During 1999-2000, he was a member of the California Attorney General's Gasoline Price Task Force. In 2012-13, he served on the Emissions Market Assessment Committee, which advised the California Air Resources Board on the operation of California’s Cap and Trade market for greenhouse gases. In 2014, he was appointed to the California Energy Commission’s Petroleum Market Advisory Committee, which he chaired from 2015 until the Committee was dissolved in 2017. From 2015-2020, he served on the Advisory Council of the Bay Area Air Quality Management District. Since 2019, he has been a member of the Governing Board of the California Independent System Operator.