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Thea Riofrancos, a professor of political science at Providence College, discusses her new book, Extraction, and the global consequences of our growing need for lithium.

We cannot hope to halt or even slow dangerous climate change without remaking our energy systems, and we cannot remake our energy systems without environmentally damaging projects like lithium mines.
This is the perplexing paradox at the heart of Extraction: The Frontiers of Green Capitalism, a new book by political scientist and climate activist Thea Riofrancos, coming out September 23, from Norton.
Riofrancos, a professor at Providence College, has spent much of her academic career studying mining and oil production in Latin America. In Extraction, she traces the lithium boom of the past five or so years, as the aims of the Global North and Global South began to resemble an inverted mirror. Countries in the latter group that have long been sites of mineral extraction — with little economic benefit — are now seeking to manufacture the more lucrative high tech products further down the supply chain. Meanwhile, after decades of offshoring, Europe and the U.S. suddenly want to bring mining back home in pursuit of “green dominance,” she writes. All of this is happening against the backdrop of China’s geopolitical rise, the war in Ukraine, the COVID-19 pandemic, and worsening effects of climate change.
The book also spends time with the indigenous communities and environmental defenders fighting the lithium industry in Chile, Portugal, and the American West. Riofrancos doesn’t shy away from difficult questions, such as whether there is such a thing as a “right place” for a lithium mine. But she’s optimistic that there’s a better path than the one we’re on now. “The energy transition has presented a fork in the road for the entire economic and social order,” she writes. Down one road, we entrench existing power structures. Down the other, we capitalize on the energy transition to create a more just society.
Green capitalism, Riofrancos argues, is an oxymoron. While we can’t avoid extraction, we can reduce the need for it, for example through better public transit, smaller EV batteries, and minerals recycling, she concludes.
This interview has been edited and condensed for length and clarity.
Are there notable differences between lithium and the extraction of other natural resources?
Yes and no. Whether it’s copper or lithium or gold or cobalt — and even I would include hydrocarbons in this, to a degree — whether we look at the economics, the way that they have boom and bust cycles, the fact that governments, even neoliberal governments, tend to take a pretty concerted interest in extractive sectors within their jurisdiction, environmental concerns and direct forms of violence that are meted out at environmental defenders — no, it’s not different. Which should raise alarm bells because a lot of those dynamics are not positive.
What’s different, though, is that precisely because mining companies and host governments claim that the extraction of lithium is urgent and essential for the energy transition, what ends up happening is that these big claims are made — like, “We are now a sustainable mining company because we’re extracting lithium,” or, “This is part of our green industrial policy.” This toxic and dirty extractive sector is now greenified because of its role in the energy transition. On the one hand, that’s greenwashing. On the other, it’s an opening. When companies make those claims, it’s something to hold them accountable to.
I was somewhat surprised by the issues you describe with the way lithium mining is regulated in Chile — the companies do their own environmental monitoring, there’s a lack of transparent data, the brine they mine in the Atacama is not considered water under Chilean law, etc. It seems like the state could change a lot of this. Why hasn’t it?
States in the Global South, although not exclusively there, lack geological and hydrological data about their own territory. In ways that we can trace to colonialism and neocolonialism in terms of who controls the territory and who has knowledge about it, the actors that have the basic data about deposits, how they interact with water sources, all of that, are the companies. And so to even regulate these companies better, you first need to set up independent and objective sources of data collection — and that’s something that any state might struggle with, but especially in the Global South, given the kind of legacy under which these companies operated, with little oversight of the state.
The [U.S. Geological Survey] doesn’t exist everywhere in the world. Not every state has a surveying agency with that level of expertise. And even in the U.S., the USGS actually has quite partial knowledge of what’s here. And there are many examples of companies in the U.S. hiding proprietary knowledge from the government.
What about after Gabriel Boric became president in Chile, in 2022, and created this new public-private partnership between the mining giant SQM and the government. Wouldn’t that have given the Chilean government more visibility and more control?
I think in some ways he’s made strides. He has set aside many salt flats for conservation. A right wing government wouldn’t have done that. He also is inserting the state, via the state-owned copper company Codelco, entering into public-private partnerships with companies, including SQM. If all goes according to plan, that will help the state learn more about lithium extraction, or maybe even set up their own lithium company, which was the initial goal of this government.
I’ll just point out two things to show how this is difficult. According to indigenous communities and environmental activists that have been organizing around this, they were excluded from the initial moment where that memorandum of understanding between SQM and Codelco was signed, and so they felt like it was a reenactment of historic injuries by a government that they had cautiously supported or thought would be different. Now they’re back at the negotiating table and indigenous communities are being consulted again. But there was a critical moment where the MOU was signed and indigenous communities were not present, and actually learned about it from the media. These historic patterns are really hard to change because companies hold a lot of power.
Even a progressive government is balancing indigenous rights and ecological protection with a desire to not lose market share. Argentina is starting to catch up with Chile — is Chile still going to remain the number two producer globally? Does it need to change its regulations to attract more companies? This is the kind of double bind that Global South societies find themselves in.
You write about this tension between expanding extraction and minimizing environmental and community impacts. Do you believe there are actually ways to minimize these impacts?
Absolutely. You can do anything better. I believe in human ingenuity and science and figuring out how to improve processes. There are ways to extract using less water, using a smaller land footprint, using fewer polluting energy sources. One of the reasons emissions from mining are not insignificant is a lot of it happens off-grid, and for now, that means diesel generators or gasoline-powered mining vehicles, let alone the cargo ships that are shipping the stuff around the world. So we could think about localizing or regionalizing supply chains.
The question is, how do we get companies to change their practices? They might do it if a regulator tells them they have to, if civil society puts so much pressure on them that it just becomes reputational harm if they don’t do it, if perhaps activist shareholders ask or tell the company to change its practices.
But the company, if it’s a shareholder-owned company, has one main obligation, which is to maximize the value of their shares. Changing your technological setup and your physical plant arrangement is costly, and it may not immediately produce more profits. And so you have to think about, what are the crude economic dynamics that keep companies on a particular technological path in terms of how they do their physical operations? And then think, using the power of policy, of economics, of consumer pressure, whatever it is, how to get them to make a decision that may not be in their immediate shareholder interest.
One theme in the book is that countries in the West are making a case for domestic mining by arguing that it will be greener than mining in the Global South. Is there any evidence for that? What’s the logic?
This was honestly one of the most surprising things in my research as someone that primarily has worked in Latin America. I heard some rumblings — and this was in 2019, before the pandemic — of EU officials wanting to onshore. It confused me because mining is toxic, it’s low value-added. And what I learned is that it had come to a point where Western policymakers saw the whole supply chain as a domain of geostrategic power.
And then, probably some people really feel this way, and other people are using it as nice rhetoric, but Western policymakers also started to come to the idea that it would be more “responsible” to mine in the West. This is in no small part due to the fact that the mining industry has deservedly gotten a lot of negative coverage for, in some cases, outright killing people. In other cases, you have an avalanche that destroys a village. You have water contamination. There are issues around forced labor, how the Uyghurs are treated in China. So there was a lot of bad press on the industry. I think they thought, We can solve a few problems at once. We can increase our geopolitical power by having domestic supply chains for the most important 21st century technologies, and we can also make the claim to consumers, regulators, and the media that this is better if you care about responsible, ethical, green mining.
The reality is, of course, more complex than that. Our mining law in the U.S. that governs hard rock mining on public lands is from 1872, which tells you everything you need to know. It’s extremely out of date with the modern mining industry and the scale of harm that mining poses, and it also literally was implemented during the westward expansion and dispossession of indigenous peoples to serve that end.
In fact, countries in Latin America tend to have better — on paper — governance of mining than the U.S., though they may not have the state capacity to always implement it. In Europe, there’s even more dependence on imports. A lot of the European countries have almost no regulations on the books for basic things like, how do you deal with mining waste? And so in the Global North, what we have to fight for is a mining governance regime and a set of legal codes and regulations that is up to date.
This book is pretty critical of the way communities have been treated in the lithium boom so far. What are some of the ways community engagement can be done better?
We see better outcomes when communities are organized, when they actually identify as a community, have some meetings, maybe set up a group to coordinate themselves. Like, who’s going to go to the public hearing? Who’s going to contact a lawyer? Who’s going to contact the water expert? Because communities need a lot of outside help. The companies have lawyers, they have experts, they probably have friends in government. A lot of lawyers and experts that companies hire used to work for the government, and they know these processes inside out, and so the community needs to be as or more organized. They’re already on the losing end of a power imbalance.
In a way, none of this is about what companies can do, because I presume that companies are responsive to pressure. Multinationals, insofar as they’re shareholder-owned, their main goal is to maximize value, and that’s it. It’s that simple. And so in order to get them to behave differently towards communities, outside forces need to take a role. The first outside force is the community itself. A second is, how involved is the government? And how objective and public-serving is the government? Where governments take a more objective role and help protect the baseline rights of communities, make sure that those rights are not being violated by companies, help distribute more culturally sensitive and appropriate information about the mine, we could get better outcomes that way.
You had activists tell you, “I support lithium mining, but this is the wrong place for it.” Do you think there is such a thing as a right or wrong place, or even a better or worse place for a lithium mine?
This was honestly the most vexing question that I had to contemplate in my own research. I often think about how these communities are called NIMBYs, and there’s two reasons that’s a really inappropriate term. First of all, the “my backyard” — not every person has private property, or that’s not their stake in the matter. It’s not about, this is going to decrease the value of my property, or this is going to disrupt my ocean view. It’s about the land that they have a deep relationship with.
The second thing is, I don’t think most of the people that call these communities NIMBYs would really want to live next to a large-scale mine, either. They are just enormous scars on the landscape. I understand that they are necessary, to some degree, to provide for the technologies that we enjoy, including life-saving and planet-saving technology. Even in my perfect world, where everyone is riding an electric bus or bike or walking around, some lithium is still needed in the near term. In the future, we could conceivably enter into a circular economy, but we don’t have the level of feedstock for that yet.
So the question remains, where are we going to mine? I don’t have an easy answer to that, but I will say that in the entire process of land use planning, the corporation is the protagonist. In the U.S., a place that I think most political scientists would say has more state capacity than a country in Africa or Latin America, we do not use that capacity to proactively plan land use. I think it would make sense to really rearrange the process such that governments plan with substantial community input, and then corporations, if we want to have private corporations doing this, get the ability to compete for contracts. I know that would be a big lift to change that policy dynamic, but I think we need to have the conversation.
You write a lot about this difficult dance between supply and demand in mining. What are you seeing right now in how the lithium industry is reacting to Trump’s dismantling of EV policy?
With Trump, it’s particularly interesting and bizarre because on the list of fast-tracked mines, you have several lithium mines and some lithium processing along with other “critical minerals.” He really wants to expand mining, to the point that the Pentagon is now the No. 1 investor in our only rare earth mine in the U.S. They bought 15% of MP Materials’ shares, the company that manages the Mountain Pass mine. And so Trump is fast-tracking mines, he’s sending huge amounts of public money to financially underwrite these mining companies. But yet, he’s destroying demand for rare earths. He loves to talk about AI and military tech — that’s a small slice of demand. It’s really about wind turbines and electric vehicle motors. That’s really where the demand is. With lithium, it’s even clearer.
That all seems like a recipe for prices to crash.
The thing is, they already had crashed because of a supply glut. But at the same time, the market will likely pick back up because we’re seeing so much action elsewhere in the world. It’s very easy to focus on the U.S., especially because the U.S. government is such a basket case right now. But if we zoom out, there’s been a bunch of recent reporting, including in Heatmap, on how rapidly the energy transition is going in other parts of the world, with China playing an enormous role not only on the trade side, but also in foreign direct investment, in setting up solar and EV manufacturing hubs in the Global South.
And so I think that Trump can dismantle EVs as much as he wants in the U.S., and that’s a shame given that transportation is our most polluting sector. I mean, that pains me as a climate activist. But the world is bigger than the U.S.
The last thing I’ll say — and this is another interesting contradiction — in the Big, Beautiful Bill, it’s not across the board against all green technologies. There’s this distinction that conservatives increasingly like to make called “clean, firm power.” So they put nuclear, geothermal, and battery storage in that. Now, battery storage, what is that made of? Lithium. So in a weird way, they like lithium mining, they like batteries for storage, they just don’t like electric vehicles. We’re still going to have lithium demand in the U.S., and lots of individual people will still buy electric cars, and blue states will still procure them for their public fleets. He’s not going to kill the market. He’s just going to slow its growth, primarily by making it less affordable for working and middle class people.
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Current conditions: After forming into Tropical Storm Bertha late Monday, the system is barreling toward the Florida Panhandle as it makes landfall as far west as Texas • In the Pacific, Hurricane Fausto has strength as it heads toward Hawaii but remains a Category 1 storm • Temperatures in Ouargla, Algeria’s southern city in the Sahara desert, are soaring to nearly 120 degrees Fahrenheit this week.
Emissions from the United States’ electrical sector spiked 4% last year as demand for power drove up generation from coal. That’s according to the latest annual assessment published Tuesday morning by the U.S. Energy Information Administration. The report, which has tracked annual emissions data from all power sources since 2010, found that U.S. energy-related carbon dioxide emissions increased by 2%, or about 115 million metric tons, in 2025. But the power sector specifically saw a surge of 4%, or 58 million metric tons, due to a spike in fossil fuel use. Coal-fired generation rose by 13%, even as natural gas-fired power fell 4%. Renewables helped avoid more coal use. While wind generation increased 3%, solar skyrocketed by 34%. Generation from all other sources — including nuclear and the category of “other renewables” that includes hydropower and geothermal — were essentially flat last year.
The coal surge isn’t unique to the U.S., as my colleague Matthew Zeitlin wrote last year. Worldwide, rising demand for electricity and shrinking supply of natural gas coming through the Strait of Hormuz made for a good year for coal.
Watershed, the software platform focused on corporate sustainability, just published what it called its first comprehensive open framework for estimating the greenhouse gas emissions from companies’ use of AI programs. The framework has three elements: A comprehensive system that includes all phases of a data center’s use, from model training to inference to hardware production; a function unit of kilograms of carbon dioxide equivalent per million tokens; and a three-tier calculation approach “that aligns with companies’ data quality.”
In a statement to my colleague Emily Pontecorvo, Watershed’s science chief John Bistline said he had “heard from companies that they’re already being asked about AI emissions from investors, from auditors, from regulators, and right now most of them are guessing. We wanted to give them something that was more defensible.”
Oil prices spiked again Tuesday after President Donald Trump publicly weighed taking “a nice big fat shot” at Iran’s Pickaxe Mountain, where Israeli intelligence suggests the Islamic Republic moved its uranium-enriching centrifuges last fall. Brent crude, the main European benchmark for the price per barrel of oil, rose nearly 3% to over $91. West Texas Intermediate, the U.S. price signal, saw a 3% hike to just nearly $85. Murban crude — out of the United Arab Emirates, therefore the most sensitive to Persian Gulf disruptions — soared nearly 5% to just under $86 per barrel.
Shakeups among smaller producers, meanwhile, appeared to cancel out each other’s effects on the market. The shot: Kazakhstan, which falls just outside the top 10 oil-producing nations, is halting crude shipments to the Russia ports it relied on to get its hydrocarbons to market now that Ukraine is consistently attacking the Kremlin’s energy infrastructure, according to the Financial Times. The chaser: Norway’s oil output just beat forecasts, per Oil Price.
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Unlike the last man Trump put in charge of the Environmental Protection Agency during his first term in office, Lee Zeldin hadn’t formally worked for the coal industry before serving in government. But the EPA administrator sure made it sound like the industry’s executives are high-priority constituents. At a National Coal Council event in Washington, D.C.’s Willard Hotel that E&E News covered, Zeldin said “many of the items that were on your wish list are now done.” In the coming months, he added, the agency would get to “the remainder of those items,” but said he wouldn’t “prejudge” any rulemaking outcomes. “Between now and your next meeting, I’m excited to be able to share with great optimism, hope, and enthusiasm that you all, again, not prejudging the outcome of any rulemaking, we’ll have a lot to celebrate the next time you all get together again in January,” Zeldin said. One thing the EPA can’t do: Keep the coal plants the Trump administration wants open actually running. As Matthew wrote last year, the big problem with aging coal stations is that they keep breaking down.
Mergers and acquisitions within the global nuclear industry totaled more than $7 billion in value in the first half of 2026, doubling that same figure from a year earlier. That’s according to new data the law firm White & Case LLP shared Tuesday with World Nuclear News. The number of individual deals increased 10%, from 40 to 44. “At the current pace of dealmaking activity, 2026 is set to surpass all years aside from 2024 when a record $29 billion of M&A activity was registered,” the law firm said. More proof that the nuclear dealmaking boom, as Heatmap’s Katie Brigham wrote last year, “is real.”
It’s not just automobiles going hybrid-electric. The startup Electra, which has promised to build a nine-passenger hybrid-electric plane that can take off in as little as 150 feet, is now pumping $850 million into its first aircraft factory in Ohio. The plant, announced Tuesday, will build up to 800 aircraft per year at full capacity. But as Electrek put it, “that’s a big commitment for a plane that hasn’t flown yet.”
Frontier model developers still keep their energy use largely a secret, but Watershed is proposing a new formula that will at least get you close.
With companies now rapidly adding artificial intelligence into their products and using it across their workstreams, it stands to reason that all that extra energy use might show up in their climate accounting. But to any business that wants to get a sense of how big its AI-related emissions footprint is becoming — and, god forbid, maybe even try to reduce it — I say well, good luck. AI providers mostly keep the data required to make such calculations a secret.
Now Watershed, a startup that helps companies track and estimate their carbon emissions, is proposing a workaround. The firm published a white paper on Wednesday laying out a method for companies to produce rough estimates of their carbon impact from AI, while also encouraging them to demand better data from AI developers.
“We’ve heard from companies that they’re already being asked about AI emissions from investors, from auditors, from regulators, and right now most of them are guessing,” John Bistline, Watershed’s head of science, told me. “We wanted to give them something that was more defensible.”
For most frontier AI models, including those developed by OpenAI and Anthropic, there’s very little information to work with. Google is the only proprietary AI developer that has published a transparent estimate of its model’s operational energy use and related emissions. In a paper last August, researchers at the company found that “the median Gemini apps text prompt consumes 0.24 watts,” which is “less energy than watching nine seconds of television,” and released 0.03 grams of CO2-equivalent. These numbers may be out of date by now, however. In the paper, the authors note that this already represented a 33-fold reduction in energy consumption compared to the previous year.
That’s one challenge with estimating AI-related emissions — tech companies are both growing and innovating rapidly, expanding their energy footprints while also finding greater efficiencies, which may be one reason they don’t disclose this information yet.
Another obstacle is that the exercise involves making a number of carbon accounting decisions, and there’s no consensus yet on best practices. For instance, where do you draw the line on which emissions to include? You could just look at the energy required to operate the model, or you could include the energy used to train the model, or even the emissions related to fabricating and manufacturing the hardware it’s running on. Training a model tends to be more energy-intensive than running it to respond to queries, but it only happens once. If you’re going to include training emissions, the next question is, how should responsibility for those be allotted across the lifetime of the model and its use by hundreds of thousands of customers?
Another decision is how to account for differences in user behavior. A model’s energy intensity can vary widely depending on whether the user is asking a simple question, requesting complex research, generating images, or dispatching agents to conduct multiple tasks simultaneously. Models capable of “reasoning” use an estimated 30 times more electricity than those without that ability, according to research by HuggingFace, a company that creates tools for AI developers. A per-prompt emissions average would not capture these differences, and therefore would not give companies actionable information to help them reduce their emissions.
A “per token” average might be more useful in that sense. When AI models process queries, they break the sentence or code down into smaller components called tokens. One token might be just the first few letters of a word. When the model generates a response, it also processes it in terms of tokens. Estimating emissions per token is not a perfect system either, however, since a token’s value can vary across AI providers. Input tokens, i.e. user questions, also tend to be less energy-intensive than output tokens, or user responses, and a single per-token average will conceal that difference.
Then there’s the question of how to get from a model’s energy intensity to an emissions estimate. Should you use the real-world average carbon intensity of the electric grid? What about any clean energy agreements the AI company may have signed? And how should you factor in companies that decide to bypass the grid entirely and build their own on-site generation, which tends to use natural gas?
The Watershed paper proposes some answers to these questions, and also offers guidance for how companies can develop emissions estimates based on the data available to them.
While most of the published research on AI emissions to date has calculated energy intensity on a per-query basis, Watershed advocates for a per-token approach. — i.e. “kilowatt-hours per thousand tokens.” The authors reason that electricity use scales more directly with the number of tokens used than the number of queries submitted. AI application customers are also often billed based on their token usage, so there’s a business case for tracking tokens and trying to use them more efficiently.
For those companies working with essentially zero data — not even the number of tokens they’re using per year — Watershed recommends they approximate their AI emissions using a “spend-based” method. This means simply multiplying the amount they spend per year on AI services by an emissions factor of 0.134 kilograms of carbon dioxide equivalent per U.S. dollar, which is based on U.S. Bureau of Economic Analysis numbers for the data processing sector of the economy.
The Watershed paper concedes that whatever number this method spits out will be wrong, noting that it “can misestimate true AI emissions by several times in either direction,” and advising companies to treat this as a “provisional placeholder.” But publishing these numbers, even though they are wrong, could help push AI companies toward more transparency if they want to correct the record.
For companies that do track their token volumes, Watershed has a more rigorous solution. The paper proposes a formula companies can use to calculate their AI emissions, accounting not just for inference energy use, but also training emissions, embodied emissions of the data processing equipment, and a figure known as “power usage effectiveness.” This captures the energy consumed by cooling systems, power conversion, and other data center infrastructure that’s not directly serving AI processing. Since model-specific values for the various inputs to the formula are mostly not available today, Watershed has provided default values gathered from previous studies, including papers by Microsoft and Google. Companies can substitute the actual numbers disclosed by AI providers into the formula as that information becomes available.
I reached out to Google, Microsoft, Anthropic, and OpenAI to ask why they didn’t share token carbon intensity, and whether they planned to in the future. Only Microsoft responded to my inquiry, pointing me to its blog post and peer-reviewed paper estimating general AI energy use across frontier models.
To get the most accurate estimate, companies would also need to know where, geographically, their AI queries are being serviced, since emissions from the electric grid varies by region. In some cases, companies may be able to actually choose where their queries are being processed, offering another lever by which they could potentially reduce their emissions.
The right data, disclosed in sufficient detail, will unlock companies’ ability to reduce their AI-related emissions, Watershed argues. Employees would have more reason to choose the most appropriate model for a given task, for example, like avoiding using energy-intensive reasoning models for basic questions.
“I think about a John von Neumann test here,” Bistline said, referring to the mathematician and proto-computer scientist. “You wouldn’t ask an advanced model like Fable anything that you would be embarrassed to ask John von Neumann, or Marie Curie, right? You wouldn’t want to ask ‘how many R’s are there in Strawberry?’ or ‘which restaurants would you recommend I go to in Miami?’”
Of course, companies can already implement this recommendation today, but there will be no way to account for and prove that they are reducing their emissions as a result until AI providers disclose distinct model-based energy estimates.
As Bistline mentioned, this information isn’t just nice-to know — companies are already being asked for it. Upcoming regulations in California and the European Union will require large companies to disclose their total direct emissions, and will eventually require them to disclose indirect emissions like AI energy use. The EU’s AI Act will also require AI companies to disclose a breakdown of the energy consumption of its general purpose AI models.
“There are customer-side disclosure rules and provider-side ones developing in parallel,” Bistline said, “and right now there’s no agreed methodology connecting the two, which is the gap we’re trying to address with our AI emissions framework.”
Average U.S. gasoline prices have slipped back above $4 a gallon.
A decade ago, the Princeton economists Alan Blinder and Mark Watson published a paper about a fact that they called “not nearly as widely known as it should be”: The U.S. economy has done better under Democratic presidents than Republican presidents.
Blinder was not a completely impartial observer — he served on President Bill Clinton’s Council of Economic Advisers, and Clinton later appointed him vice chair of the Federal Reserve — but he and Watson compiled a lengthy list of statistics to back up their claim. The U.S. economy has grown faster, produced more jobs, had a lower unemployment rate, seen higher corporate profits and investment, and experienced better stock market performance under Democrats than Republicans. While the original paper described this divergence from 1947 to 2013, recent research has shown that it held through the subsequent Obama, Trump, and Biden administrations.
The only metric where the two parties come close is inflation, but Democrats still seem to have a tiny edge there, even after the Biden-era inflation.
Why? Blinder and Watson found that it didn’t entirely come down to timing. (Other observers have disputed this, arguing that Republicans tend to get elected at the peak of economic booms, while Democrats win during or just after recessions.) Instead, Blinder and Watson found that a few factors — oil shocks, productivity growth, a more favorable international growth environment, and perhaps better consumer confidence — could explain much of the divergence.
Of course, these factors can’t be entirely separated from a president’s record in office. Oil shocks, for example, tend to drag down global growth, which in turn slows the U.S. economy. And as Watson and Blinder write, some of those oil shocks “may have been induced by [American] foreign policy.” By that mechanism, presidential bellicosity in the Middle East can translate into poorer economic outcomes. This belligerence may even be, as the writer Matt Yglesias contended earlier this year, Republican presidents’ “worst economic policy.”
Why am I recounting all this? Because average U.S. gasoline prices have slipped back above $4 a gallon, according to AAA. (As I write, they stand at $4.01.) The collapse of the ceasefire with Iran — and President Trump’s inability to figure out how to end a war he started — are once again driving up fossil fuel prices.
The numbers add up. Defense Secretary Pete Hegseth told Congress today that the Iran War has cost $37.5 billion so far, but according to a tracker from Brown University researchers, Americans have already paid nearly double that — $71 billion! — on more expensive gasoline and diesel fuel. A billion here, a billion there, and pretty soon you’re talking about real economic underperformance. That estimate suggests the burden of higher energy prices from the Iran War has wiped out the expected $65 billion consumer boost from the One Big Beautiful Bill Act’s expanded tax refunds.
Of course, from a decarbonization perspective, higher gas prices are good, in theory. They encourage people to drive less and to switch to more fuel-efficient — or even fully electrified — vehicles, reducing carbon emissions. (This is part of why I joke about Degrowth Donald, raising fuel prices as he goes.) But short-term oil shocks are the second worst kind of emissions reductions after recessions: They are unlikely to last; they will probably not lead to real decarbonization; and they produce a lot of human misery along the way.
Perhaps this oil spike won’t persist. Perhaps Trump will find a way out of the quagmiring conflict in the Persian Gulf. Perhaps Republican presidential underperformance really does all come down to luck, too. (Or maybe, as a 2020 paper argued, Democratic presidents benefit from a “pre-election growth surge” just before a Republican wins.) But I think it’s worth noting that the recent trickle of news — and the recent and less noticed surge in gas prices — is how an oil interruption results in slower growth overall. If oil shocks really are responsible for GOP presidential underperformance, this is what it would look like.
The irony is that technology finally exists to make the American transportation sector — and the overall economy — less dependent on oil. This technology was developed at the American public’s expense to help manage a scenario much like this one. And the administration has undermined it at almost every opportunity.