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Rob and Jesse get into the nitty gritty on China’s energy policy with Joanna Lewis and John Paul Helveston.

China’s industrial policy for clean energy has turned the country into a powerhouse of solar, wind, battery, and electric vehicle manufacturing.
But long before the country’s factories moved global markets — and invited Trump’s self-destructive tariffs — the country implemented energy and technology policy to level up its domestic industry. How did those policies work? Which tools worked best? And if the United States needs to rebuild in the wake of Trump’s tariffs, what should this country learn?
On this week’s episode of Shift Key, Rob and Jesse talk with two scholars who have been studying Chinese industrial policy since the Great Recession. Joanna Lewis is the Provost’s Distinguished Associate Professor of Energy and Environment and Director of the Science, Technology and International Affairs Program at Georgetown University's School of Foreign Service. She’s also the author of Green Innovation in China. John Paul Helveston is an assistant professor in engineering management and systems engineering at George Washington University. He studies consumer preferences and market demand for new technologies, as well as China’s longstanding gasoline car and EV industrial policy. Shift Key is hosted by Robinson Meyer, the founding executive editor of Heatmap, and Jesse Jenkins, a professor of energy systems engineering at Princeton University.
Subscribe to “Shift Key” and find this episode on Apple Podcasts, Spotify, Amazon, or wherever you get your podcasts.
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Here is an excerpt from our conversation:
Robinson Meyer: One kind of classical hard problem about industrial policy is selecting the technology that is going to eventually be a winner. And there’s a few ways to get around this problem. One is to just make lots of bets.
One thing that’s been a little unclear to me about the set of technology bets that China has made is that it has seemed to pick a set of technologies that are now extremely competitive globally, and it did seem to pick up on those technologies before Western governments or firms really got to them. Is that entirely because China just made a bunch of technology bets and it happened that these are the ones that worked out? Is it because China could look ahead to the environmental needs of the world and the clean development needs of the world and say, well, there’s probably going to be a need for solar? There’s probably going to be a need for wind? There’s probably going to be a need for EVs? Or is it a third thing, which is that China’s domestic needs, its domestic energy security needs, just happen to align really well with the direction of development that the world is kind of interested in moving in anyway.
John Paul Helveston: All of the above. I don’t know — like, that’s the answer here. I’ll add one thing that’s a little bit nuanced: There’s been tremendous waste. I’ll just put that out there. There’s been all kinds of investments that did not pan out at all, like semiconductors for a long, long time. Just things that didn’t work.
I think where China has had a lot of success is in areas where … It’s like the inverse of what the United States innovation ecosystem does well. China’s ecosystem is really driven around production, and a lot of that is part of the way the government’s set up, that local provinces have a ton of power over how money gets spent, and often repurpose funds for export-oriented production. So that’s been a piece of the engine of China’s economic miracle, is mass producing everything.
But there’s a lot of knowledge that goes along with that. When you look at things like solar, that technology goes back many, many decades for, you know, satellites. But making it a mass produced product for energy applications requires production innovations. You need to get costs down. You need to figure out how to make the machine that makes the machine. And that is something that the Chinese ecosystem does very well.
So that’s one throughline across all of these things, is that the technology got to a certain level of maturity where production improvements and cost decreases were the bigger things that made them globally competitive. I don’t think anyone would be considering an EV if we were still looking at $1,000 a kilowatt hour — and we were there just 15 years ago. And so that’s the big thing. It’s just production. I don’t know if they’ve been exceptionally good at just picking winners, but they’re good at picking things that can be mass produced.
Music for Shift Key is by Adam Kromelow.
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France’s deadliest heat wave since 2003 killed more than 2,700 people — and possibly as many as 5,700.
More than 5,700 excess deaths were recorded in France during this summer’s record-breaking heat wave, the country’s health agency announced today. That makes the event — which ran, by the official reckoning, from June 17 to July 2 — the country’s deadliest heat wave in more than 20 years.
That’s in line with other estimates we’ve heard. EuroMOMO, a network of European public health agencies that track excess mortality, found that the continent saw more than 10,000 excess deaths during the same period. Roughly 90% of those victims were older than 65, it said. (France’s cohort seems similar: Adults older than 75 made up about two-thirds of the victims, the government said.)
These numbers are staggering — and much larger than some astute Heatmap readers might anticipate. If you read my colleague Jeva Lange’s piece on why it’s so hard to estimate heat deaths last week, she cited a much smaller estimate: Roughly 2,700 died in France during the most recent heat wave. That tally came from Christopher Callahan, an Indiana University scientist who studies climate change’s economic and social costs.
Why is there such a gap between the figures? I emailed Callahan to find out. He shared a few thoughts. First, he uses a different (and theoretically more rigorous) method than the French government: “Our approach uses a statistical relationship between temperature and mortality to explicitly quantify how many additional deaths are associated with a given day’s temperature,” he wrote. “France’s report of excess deaths is just based on how many more people died in late June compared to previous Junes - but we don’t know if those people died because of the heat or some other factor.” (Carbon Brief recently published a Q&A on these varying approaches.)
That might mean his estimate is right, in which case France has misidentified roughly nearly 3,000 deaths. But it could also mean his model, which is trained on data from 2004 to 2019, is “missing something,” he said, like a post-Covid change to public health risk. Last year, Callahan and his colleagues used a similar model to estimate deaths from France’s worst-ever heatwave, a 2003 episode that overwhelmed morgues and killed about 16,000 people. Even 23 years ago, global warming helped make that disaster larger than it needed to be: Some 6,000 of those deaths were due to climate change, their paper found.
Either estimate of the 2026 heat wave, of course, is shattering. As Jeva wrote, even the lower figure would mean the 2026 heat wave killed as many people as died in three years of French homicides. But the divergence in estimates tells us something else too: Even as climate change breaks records and alters our world, we’re never going to quite agree on where it ends and normal randomness begins.
The AI data center boom does not seem close to ending. Google’s parent company, Alphabet, announced its second quarter results this evening, and it beat Wall Street’s expectations, nearly quadrupling its profit on a year-over-year basis. Among the drivers: Its cloud business grew 82% compared to the same quarter last year. (As I’ve written, that rapid growth is helping to turn Alphabet and other hyperscalers into light industrial firms.)
The company’s AI bets seem to be paying off so far — so Google is now planning on spending even more on data centers, energy infrastructure and AI development this year than it once anticipated. It raised its estimates of 2026 capital expenditure to $195 billion to $205 billion, which is above earlier projections and twice as much as it spent in the same category last year. 2027 could be even bigger, it signaled. The company’s shares fell slightly on the news in after-hours trading, but from an energy and climate wonk perspective, the message is clear: For now, the AI demand surge transforming the power sector — and the real economy — continues to chug along.