If models become more efficient still, there are yet more uses to which they can be put. In recent months, several AI labs have launched “Deep Research” tools, combining reasoning models with the ability to search the web for information and set themselves follow-up tasks. The tools are one of the first mainstream examples of what the AI industry calls “agents”, quasi-autonomous AI systems that can carry out many tasks sequentially. And because it takes them between five and 30 minutes to give a response, running such an agent uses more energy than asking a simple query.
Such efficiency gains leave some wary of the Jevons paradox popping up in other industries. Lynn Kaack, who leads the AI and Climate Technology Policy Group at the Hertie School in Berlin, worries that, by increasing efficiency and reducing costs in areas like shipping, AI will incentivise companies to increase their activity.
Those concerned about the trajectory of AI’s environmental costs are looking for ways to alter it. Mr Gamazaychikov, for instance, hopes that his effort to rank various AI models will allow users and businesses to find the most efficient one for any given task, rather than always using the “best”.
But the closed nature of the biggest labs complicate things. OpenAI, for instance, gives away access to its top-tier models below cost, according to Sam Altman, its boss; Google and Amazon charge less for access to their own AI systems than the cost of the electricity alone, insiders claim. That means users have less motivation to hunt for the most efficient model than they would if they had to pay the true cost of their use. And greater transparency around efficiency and emissions may not result in meaningful behavioural change: after all, there is little evidence to show that growing awareness of the carbon cost of flying has stopped people taking flights.
Coming clean
Many observers think that the best way forward is through tighter regulation, both of AI itself and of the energy it consumes. The first has had limited success in Europe—from the summer of 2026, developers of “high risk” AI will need to tell regulators about the energy it consumes—and is struggling to get off the ground almost everywhere else. In America the Trump administration’s bonfire of red tape means voluntary efficiency drives are more likely than new regulations.
That said, trying to regulate the development of AI specifically is not the only option: broader policies meant to motivate emissions cuts, such as carbon pricing, can help too. Arguably the most important change will come from speeding up the transition to clean energy, and boosting the amount available so that demand for greener AI does not gobble up the low-carbon electricity also needed to decarbonise other sectors, from transportation to construction. Figuring out how to do that shouldn’t require Deep Research. ■
Such efficiency gains leave some wary of the Jevons paradox popping up in other industries. Lynn Kaack, who leads the AI and Climate Technology Policy Group at the Hertie School in Berlin, worries that, by increasing efficiency and reducing costs in areas like shipping, AI will incentivise companies to increase their activity.
Those concerned about the trajectory of AI’s environmental costs are looking for ways to alter it. Mr Gamazaychikov, for instance, hopes that his effort to rank various AI models will allow users and businesses to find the most efficient one for any given task, rather than always using the “best”.
But the closed nature of the biggest labs complicate things. OpenAI, for instance, gives away access to its top-tier models below cost, according to Sam Altman, its boss; Google and Amazon charge less for access to their own AI systems than the cost of the electricity alone, insiders claim. That means users have less motivation to hunt for the most efficient model than they would if they had to pay the true cost of their use. And greater transparency around efficiency and emissions may not result in meaningful behavioural change: after all, there is little evidence to show that growing awareness of the carbon cost of flying has stopped people taking flights.
Coming clean
Many observers think that the best way forward is through tighter regulation, both of AI itself and of the energy it consumes. The first has had limited success in Europe—from the summer of 2026, developers of “high risk” AI will need to tell regulators about the energy it consumes—and is struggling to get off the ground almost everywhere else. In America the Trump administration’s bonfire of red tape means voluntary efficiency drives are more likely than new regulations.
That said, trying to regulate the development of AI specifically is not the only option: broader policies meant to motivate emissions cuts, such as carbon pricing, can help too. Arguably the most important change will come from speeding up the transition to clean energy, and boosting the amount available so that demand for greener AI does not gobble up the low-carbon electricity also needed to decarbonise other sectors, from transportation to construction. Figuring out how to do that shouldn’t require Deep Research. ■
Put to good use
Focusing on the energy impact of training models, however, may be a distraction. Boris Gamazaychikov, who is in charge of AI sustainability at Salesforce, a software company, compares it to trying to estimate the carbon footprint of a flight by including the impact of building the plane itself. Not only is that construction cost tiny compared with the fuel used over a typical lifetime in service, it’s also impossible to calculate the per-passenger impact until the aircraft is finally retired.
Instead, he says, it is best to focus on the energy impact of using AI, a process called inference. Brent Thill of Jefferies, an analyst, estimates that this stage accounts for 96% of the overall energy consumed in data centres used by the AI industry. Mr Gamazaychikov is trying to put hard numbers on that side of the industry, working with HuggingFace, an AI cloud provider, to systematically test the efficiency of hundreds of AI models. The results show the difficulty of generalising: the difference between the most and least power-hungry models is more than 60,000-fold.
Some of that difference arises from the AI models’ varying purposes. The most efficient model tested, called BERT-tiny, draws just 0.06 watt-hours (Wh) per task—about a second’s worth on an exercise bike—but is useful only for simple text-manipulation tasks. Even the least power-hungry image-generation model tested, by contrast, requires 3,000 times as much electricity to produce a single image.
All the same, says Sasha Luccioni of HuggingFace, concrete figures are not always available. Her company could test only the models it could download and run on its own hardware. “OpenAI has not released a single metric about ChatGPT,” Ms Luccioni says, even though such data exist.
Another difficulty in calculating energy use is the fact that AI models are rapidly evolving. The release of DeepSeek V3 in December, a top-tier AI model made by a lab spun off from a Chinese hedge fund, initially looked like good news for those concerned about the industry’s energy use. A raft of improvements meant that the final training run was more than ten times faster than that of Meta’s Llama 3.3 model just a few weeks earlier, with a roughly proportionate reduction in power used. Inference also became less power-hungry.
In January, as the implications of that improvement became clear, the stock prices of chipmakers crashed. But Satya Nadella, the boss of Microsoft, predicted the upset would be brief, citing the Jevons paradox, a 19th-century observation that the rising efficiency of steam engines opened up new economic uses for the technology and thereby raised demand for coal.
For AI, the rebound effect arrived in the form of “reasoning” models, including DeepSeek’s follow-up model, R1. If normal chatbots exhibit what Daniel Kahneman, a psychologist and Nobel economics laureate, called “type one” thinking—prioritising speedy responses—reasoning models display “type two”: structured replies that attempt to break a problem into its constituent parts, solve it with a variety of approaches, and check their answer is correct before settling on it as the final response.
Training a reasoning model is not much harder than training a normal AI system, especially if you have pre-existing models to learn from. But running it requires significantly more power, since the “reasoning” step, in which the problem is thought through before a final answer is reached, takes longer. The efficiency improvements DeepSeek pioneered in V3 were more than eaten up by the extra thinking time used by R1 a couple of months later.
Focusing on the energy impact of training models, however, may be a distraction. Boris Gamazaychikov, who is in charge of AI sustainability at Salesforce, a software company, compares it to trying to estimate the carbon footprint of a flight by including the impact of building the plane itself. Not only is that construction cost tiny compared with the fuel used over a typical lifetime in service, it’s also impossible to calculate the per-passenger impact until the aircraft is finally retired.
Instead, he says, it is best to focus on the energy impact of using AI, a process called inference. Brent Thill of Jefferies, an analyst, estimates that this stage accounts for 96% of the overall energy consumed in data centres used by the AI industry. Mr Gamazaychikov is trying to put hard numbers on that side of the industry, working with HuggingFace, an AI cloud provider, to systematically test the efficiency of hundreds of AI models. The results show the difficulty of generalising: the difference between the most and least power-hungry models is more than 60,000-fold.
Some of that difference arises from the AI models’ varying purposes. The most efficient model tested, called BERT-tiny, draws just 0.06 watt-hours (Wh) per task—about a second’s worth on an exercise bike—but is useful only for simple text-manipulation tasks. Even the least power-hungry image-generation model tested, by contrast, requires 3,000 times as much electricity to produce a single image.
All the same, says Sasha Luccioni of HuggingFace, concrete figures are not always available. Her company could test only the models it could download and run on its own hardware. “OpenAI has not released a single metric about ChatGPT,” Ms Luccioni says, even though such data exist.
Another difficulty in calculating energy use is the fact that AI models are rapidly evolving. The release of DeepSeek V3 in December, a top-tier AI model made by a lab spun off from a Chinese hedge fund, initially looked like good news for those concerned about the industry’s energy use. A raft of improvements meant that the final training run was more than ten times faster than that of Meta’s Llama 3.3 model just a few weeks earlier, with a roughly proportionate reduction in power used. Inference also became less power-hungry.
In January, as the implications of that improvement became clear, the stock prices of chipmakers crashed. But Satya Nadella, the boss of Microsoft, predicted the upset would be brief, citing the Jevons paradox, a 19th-century observation that the rising efficiency of steam engines opened up new economic uses for the technology and thereby raised demand for coal.
For AI, the rebound effect arrived in the form of “reasoning” models, including DeepSeek’s follow-up model, R1. If normal chatbots exhibit what Daniel Kahneman, a psychologist and Nobel economics laureate, called “type one” thinking—prioritising speedy responses—reasoning models display “type two”: structured replies that attempt to break a problem into its constituent parts, solve it with a variety of approaches, and check their answer is correct before settling on it as the final response.
Training a reasoning model is not much harder than training a normal AI system, especially if you have pre-existing models to learn from. But running it requires significantly more power, since the “reasoning” step, in which the problem is thought through before a final answer is reached, takes longer. The efficiency improvements DeepSeek pioneered in V3 were more than eaten up by the extra thinking time used by R1 a couple of months later.
The tricky task of calculating AI’s energy use
Making models less thirsty may not lessen their environmental impact
April 9th 2025
A fifth of all electricity used in Ireland is spent powering the country’s data centres, more than is used by its urban homes. With one data centre for every 42,000-odd people, Ireland has one of the highest per-person concentrations of computing power in the world. Loudoun County, just outside Washington, DC, beats it: its 443,000 residents rub shoulders with scores of data centres—more than the next six biggest clusters in America combined. In 2022 their peak energy usage was almost 3 gigawatts (GW), a power draw that, if maintained year round, would approach Ireland’s total annual consumption.
Around 1.5% of global electricity is spent on powering data centres. Most of that is for storing and processing data for everything from streaming video to financial transactions. But artificial intelligence (AI) will make up much of future data-centre demand. By 2038 Dominion, a power company, expects the data centres in Loudoun County alone to need more than 13GW. The International Energy Agency, a forecaster, estimates that global data-centre power demand could increase by between 128% and 203% by 2030, mostly because of AI-related energy consumption.
Big tech is confident that the environmental benefits justify the costs. “AI is going to be one of the main drivers of solutions to the climate situation,” says Demis Hassabis, the boss of Google DeepMind. Others disagree. This week’s special section explores the arguments in detail. It examines the ways in which AI can help clean up some of the most polluting industries, including energy production and heavy industry, and discusses the possibility of moving data centres off Earth altogether. It will also examine why AI’s energy footprint is so hard to quantify, and what its true environmental impact might be.
Tech firms are generally unwilling to share information about their AI models. One indirect way to estimate the environmental impact of building and deploying AI models, therefore, is to look at the firms’ self-reported carbon emissions. Google’s greenhouse-gas emissions rose by almost half between 2019 and 2023, according to the search giant, primarily because of increases in the energy consumption of data centres and supply-chain emissions. Microsoft’s emissions jumped by roughly a third in 2023, compared with three years earlier, partly due to its own focus on AI.
None
Another approach to estimating AI’s environmental footprint is to add up the energy use of the infrastructure used to build the models themselves. Meta’s Llama 3.1, a large language model (LLM), for example, was trained using chips from Nvidia which can draw 700 watts of power each, around half that of a fancy kettle, and it ran those chips for a cumulative 39.3m hours. The resulting energy used, 27.5 gigawatt-hours (GWh), is enough to supply 7,500 homes with a year’s worth of power.
Tech companies, perhaps unsurprisingly, are keen to argue that this energy bill is not nearly as outlandish as it might appear. The immediate climate impact of the final Llama 3.3 training run, Meta estimates, is emissions worth 11,390 tonnes of CO2—about the same as 60 fully loaded return flights between London and New York. Those are the emissions, at least, of the power grid that supplied the company’s data centre. But Meta argues that, since electrons are fungible, if enough renewable energy is bought on the opposite side of the country—or even at another time altogether—the true emissions fall to zero.
Making models less thirsty may not lessen their environmental impact
April 9th 2025
A fifth of all electricity used in Ireland is spent powering the country’s data centres, more than is used by its urban homes. With one data centre for every 42,000-odd people, Ireland has one of the highest per-person concentrations of computing power in the world. Loudoun County, just outside Washington, DC, beats it: its 443,000 residents rub shoulders with scores of data centres—more than the next six biggest clusters in America combined. In 2022 their peak energy usage was almost 3 gigawatts (GW), a power draw that, if maintained year round, would approach Ireland’s total annual consumption.
Around 1.5% of global electricity is spent on powering data centres. Most of that is for storing and processing data for everything from streaming video to financial transactions. But artificial intelligence (AI) will make up much of future data-centre demand. By 2038 Dominion, a power company, expects the data centres in Loudoun County alone to need more than 13GW. The International Energy Agency, a forecaster, estimates that global data-centre power demand could increase by between 128% and 203% by 2030, mostly because of AI-related energy consumption.
Big tech is confident that the environmental benefits justify the costs. “AI is going to be one of the main drivers of solutions to the climate situation,” says Demis Hassabis, the boss of Google DeepMind. Others disagree. This week’s special section explores the arguments in detail. It examines the ways in which AI can help clean up some of the most polluting industries, including energy production and heavy industry, and discusses the possibility of moving data centres off Earth altogether. It will also examine why AI’s energy footprint is so hard to quantify, and what its true environmental impact might be.
Tech firms are generally unwilling to share information about their AI models. One indirect way to estimate the environmental impact of building and deploying AI models, therefore, is to look at the firms’ self-reported carbon emissions. Google’s greenhouse-gas emissions rose by almost half between 2019 and 2023, according to the search giant, primarily because of increases in the energy consumption of data centres and supply-chain emissions. Microsoft’s emissions jumped by roughly a third in 2023, compared with three years earlier, partly due to its own focus on AI.
None
Another approach to estimating AI’s environmental footprint is to add up the energy use of the infrastructure used to build the models themselves. Meta’s Llama 3.1, a large language model (LLM), for example, was trained using chips from Nvidia which can draw 700 watts of power each, around half that of a fancy kettle, and it ran those chips for a cumulative 39.3m hours. The resulting energy used, 27.5 gigawatt-hours (GWh), is enough to supply 7,500 homes with a year’s worth of power.
Tech companies, perhaps unsurprisingly, are keen to argue that this energy bill is not nearly as outlandish as it might appear. The immediate climate impact of the final Llama 3.3 training run, Meta estimates, is emissions worth 11,390 tonnes of CO2—about the same as 60 fully loaded return flights between London and New York. Those are the emissions, at least, of the power grid that supplied the company’s data centre. But Meta argues that, since electrons are fungible, if enough renewable energy is bought on the opposite side of the country—or even at another time altogether—the true emissions fall to zero.
China’s economic policymaking has its own weaknesses, of course; some are mirror images of America’s. Its economy is threatened by deflation, not inflation. The country’s consumer prices declined by 0.1% in February, compared with a year earlier. And its policymakers are, if anything, too rigid in their goals and too slow to change course. Only in September last year did they turn decisively to the goal of boosting consumption to help the economy weather a long-running property slump and the forthcoming trade war.
That war has arrived with a speed and ferocity China did not anticipate. According to Goldman, a 50% hike in American tariffs (roughly the scenario China faced before it retaliated) would have cut the country’s GDP by about 1.5%. A hike of 125% will reduce it by 2.2% this year. The first 50 points, in other words, hurt more than the second or third. Exorbitant tariffs kill trade and you cannot kill the same trade twice.
These calculations cannot, however, take full account of the damage to confidence and financial-risk appetite. China’s stockmarket plummeted on April 7th, after the government chose to retaliate against Mr Trump. The country’s “national team” of state-directed banks and investment funds was obliged to step in to stabilise prices. China’s leaders have also announced that they are ready to do more to stimulate the economy if required, by cutting interest rates and bank-reserve requirements, as well as by selling more government bonds.
They will have to issue a lot of them to offset the tariff shock. Barclays, yet another bank, calculates that China would need up to 7.5trn yuan (over $1trn, or 5% of this year’s GDP) of extra stimulus on top of the easing of 2.4trn yuan it announced in March. Even that would only get growth to about 4%. To hit the government’s target of “around” 5%, the 7.5trn yuan would have to be closer to 12trn (or 9% of GDP).
Offshore bonanza
Another survival strategy for Chinese exporters is to recede upstream, out of the direct reach of American tariffs. They can sell parts and components to trading partners in neighbouring countries, where they can be incorporated into finished products for export to America. On the face of it, the incentive to pursue this strategy will be overwhelmingly strong if China remains stuck with American tariffs of over 100% while countries including Thailand and Vietnam face levies of only 10%.
One problem is that this strategy is no secret to the trade warriors in the White House. Peter Navarro, Mr Trump’s trade adviser, recently accused Vietnam of acting as a “colony” for Chinese manufacturers. “They slap a made-in-Vietnam label” on a Chinese good “and send it here to evade the tariffs”, he complained to Fox News. Vietnam could jeopardise its own access to the American market if it does not distance itself from China.
Chinese manufacturers may have doubts of their own. Even if their Asian neighbours can now seal a “bespoke” deal with Mr Trump, it could easily come unstuck in the months and years ahead. The United States-Mexico-Canada (USMCA) trade agreement has not held fast, even though Mr Trump himself signed it. What if a country’s trade surpluses with America fail to narrow in a year or two, due to larger macroeconomic forces outside the country’s direct control? Could the reciprocal tariffs return? The post-war trading rules that America helped enshrine once offered convincing answers to these doubts. They gave exporters the certainty they required to serve the world’s biggest market. That certainty has now gone for good.
No bell sounded in the world’s busiest ports when America’s tariffs came into effect. Cargo kept moving. But make no mistake, the death knell of the post-war trading order has been rung. ■
That war has arrived with a speed and ferocity China did not anticipate. According to Goldman, a 50% hike in American tariffs (roughly the scenario China faced before it retaliated) would have cut the country’s GDP by about 1.5%. A hike of 125% will reduce it by 2.2% this year. The first 50 points, in other words, hurt more than the second or third. Exorbitant tariffs kill trade and you cannot kill the same trade twice.
These calculations cannot, however, take full account of the damage to confidence and financial-risk appetite. China’s stockmarket plummeted on April 7th, after the government chose to retaliate against Mr Trump. The country’s “national team” of state-directed banks and investment funds was obliged to step in to stabilise prices. China’s leaders have also announced that they are ready to do more to stimulate the economy if required, by cutting interest rates and bank-reserve requirements, as well as by selling more government bonds.
They will have to issue a lot of them to offset the tariff shock. Barclays, yet another bank, calculates that China would need up to 7.5trn yuan (over $1trn, or 5% of this year’s GDP) of extra stimulus on top of the easing of 2.4trn yuan it announced in March. Even that would only get growth to about 4%. To hit the government’s target of “around” 5%, the 7.5trn yuan would have to be closer to 12trn (or 9% of GDP).
Offshore bonanza
Another survival strategy for Chinese exporters is to recede upstream, out of the direct reach of American tariffs. They can sell parts and components to trading partners in neighbouring countries, where they can be incorporated into finished products for export to America. On the face of it, the incentive to pursue this strategy will be overwhelmingly strong if China remains stuck with American tariffs of over 100% while countries including Thailand and Vietnam face levies of only 10%.
One problem is that this strategy is no secret to the trade warriors in the White House. Peter Navarro, Mr Trump’s trade adviser, recently accused Vietnam of acting as a “colony” for Chinese manufacturers. “They slap a made-in-Vietnam label” on a Chinese good “and send it here to evade the tariffs”, he complained to Fox News. Vietnam could jeopardise its own access to the American market if it does not distance itself from China.
Chinese manufacturers may have doubts of their own. Even if their Asian neighbours can now seal a “bespoke” deal with Mr Trump, it could easily come unstuck in the months and years ahead. The United States-Mexico-Canada (USMCA) trade agreement has not held fast, even though Mr Trump himself signed it. What if a country’s trade surpluses with America fail to narrow in a year or two, due to larger macroeconomic forces outside the country’s direct control? Could the reciprocal tariffs return? The post-war trading rules that America helped enshrine once offered convincing answers to these doubts. They gave exporters the certainty they required to serve the world’s biggest market. That certainty has now gone for good.
No bell sounded in the world’s busiest ports when America’s tariffs came into effect. Cargo kept moving. But make no mistake, the death knell of the post-war trading order has been rung. ■
Between consumers and their Calvins
China may throw some more punches of its own. It has already placed several firms, including PVH, the owner of Calvin Klein, on its list of “unreliable entities” that warrant government scrutiny and restrictions. It could now follow through and hamstring their business. It has also severed some American dronemakers from their Chinese suppliers, and curtailed exports to America of a variety of critical metals. On April 8th a list of other possible responses was posted online by several well-connected commentators. China could suspend all co-operation with America on fentanyl, for example. It could also ban imports of American poultry and other agricultural products, such as soyabeans and sorghum, which mainly come from Republican states.
China may impose restrictions on American services, too. A paper published this week by the Ministry of Commerce was at pains to point out that Uncle Sam runs a surplus with China in services trade (although it is far smaller than America’s deficit in goods trade). If China were to follow the same crude formula that America used to calculate its original reciprocal tariffs, China would be entitled to impose a levy of 28% on American services. China could also probe the intellectual property held by American firms, which may constitute monopolies earning excess profits, according to one influential blogger.
Such retaliation would make a deal with Mr Trump less likely. He seems keen to isolate China by talking to everyone else first. But from China’s point of view, talks with America’s president offer plenty of risk for little reward. America wants to “decouple” from China and contain its economic rise, whatever happens to the balance of trade. Commercial relations between the two superpowers may be at a “cyclical” low—but they are also in secular decline.
Any gains China won through talks might then be whittled away over time. The country’s leaders also have a lot to lose if discussions go awry. No adviser to Xi Jinping, China’s ruler, would risk exposing him to the kind of public humiliation meted out to Volodymyr Zelensky, Ukraine’s president, in February. A trade war is bearable. An Oval Office circus is not.
If the two superpowers do continue to fight, who will back down first? Mr Trump inherited a stretched stockmarket, but a strong economy. America’s latest job figures beat forecasts; household balance-sheets are robust. The president has done his best to squander that legacy. Before the tariff delay, JPMorgan Chase, a bank, suggested America had a 60% chance of falling into a recession and a 40% chance of taking the world economy down with it.
Those odds have presumably dropped a bit. But the tariffs that remain will still raise prices, eroding household purchasing power and, possibly, delaying any interest-rate cuts from the Federal Reserve. For over a third of products that America buys abroad, China is the dominant supplier, meeting 70% or more of America’s foreign demand, according to Goldman Sachs, another bank. The trade war will more than double the price of these goods.
Even before inflation rises, uncertainty has spiked. And that can be equally damaging to investment and spending. A daily index of trade-policy uncertainty, calculated by Dario Caldara of the Federal Reserve and others, has been over twice as high as its previous record, reached during Mr Trump’s first trade war. The president’s supporters point out that tariffs have been a consistent preoccupation of his since the 1980s. But he seems to pursue uncertainty with equal conviction. He is a mercantilist, yes, but a mercurialist above all.
China may throw some more punches of its own. It has already placed several firms, including PVH, the owner of Calvin Klein, on its list of “unreliable entities” that warrant government scrutiny and restrictions. It could now follow through and hamstring their business. It has also severed some American dronemakers from their Chinese suppliers, and curtailed exports to America of a variety of critical metals. On April 8th a list of other possible responses was posted online by several well-connected commentators. China could suspend all co-operation with America on fentanyl, for example. It could also ban imports of American poultry and other agricultural products, such as soyabeans and sorghum, which mainly come from Republican states.
China may impose restrictions on American services, too. A paper published this week by the Ministry of Commerce was at pains to point out that Uncle Sam runs a surplus with China in services trade (although it is far smaller than America’s deficit in goods trade). If China were to follow the same crude formula that America used to calculate its original reciprocal tariffs, China would be entitled to impose a levy of 28% on American services. China could also probe the intellectual property held by American firms, which may constitute monopolies earning excess profits, according to one influential blogger.
Such retaliation would make a deal with Mr Trump less likely. He seems keen to isolate China by talking to everyone else first. But from China’s point of view, talks with America’s president offer plenty of risk for little reward. America wants to “decouple” from China and contain its economic rise, whatever happens to the balance of trade. Commercial relations between the two superpowers may be at a “cyclical” low—but they are also in secular decline.
Any gains China won through talks might then be whittled away over time. The country’s leaders also have a lot to lose if discussions go awry. No adviser to Xi Jinping, China’s ruler, would risk exposing him to the kind of public humiliation meted out to Volodymyr Zelensky, Ukraine’s president, in February. A trade war is bearable. An Oval Office circus is not.
If the two superpowers do continue to fight, who will back down first? Mr Trump inherited a stretched stockmarket, but a strong economy. America’s latest job figures beat forecasts; household balance-sheets are robust. The president has done his best to squander that legacy. Before the tariff delay, JPMorgan Chase, a bank, suggested America had a 60% chance of falling into a recession and a 40% chance of taking the world economy down with it.
Those odds have presumably dropped a bit. But the tariffs that remain will still raise prices, eroding household purchasing power and, possibly, delaying any interest-rate cuts from the Federal Reserve. For over a third of products that America buys abroad, China is the dominant supplier, meeting 70% or more of America’s foreign demand, according to Goldman Sachs, another bank. The trade war will more than double the price of these goods.
Even before inflation rises, uncertainty has spiked. And that can be equally damaging to investment and spending. A daily index of trade-policy uncertainty, calculated by Dario Caldara of the Federal Reserve and others, has been over twice as high as its previous record, reached during Mr Trump’s first trade war. The president’s supporters point out that tariffs have been a consistent preoccupation of his since the 1980s. But he seems to pursue uncertainty with equal conviction. He is a mercantilist, yes, but a mercurialist above all.
Can China fight America alone?
The world’s two biggest economies begin an almighty trade clash
April 10th 2025
Victoria Harbour is Hong Kong’s most glamorous body of water. But Rambler Channel is where the free port’s work is done. The quays along its banks extend over more than 7km. Gantry cranes, rail-mounted or rubber-tyred, serve as many as 24 vessels at a time. Last year, the surrounding port handled over 10m of the standardised containers that carry goods across the world, parcelling globalisation up into metal boxes, in green, blue and red.
No bell or siren interrupted the port’s work at a minute past noon on April 9th—nothing to mark the moment when America’s devastating “reciprocal” tariffs came into effect. Containers kept circulating. Globalisation kept moving. A balding lorry driver reversed into position under a “reach stacker”, which hoisted his cargo into the air, like a weight-lifter jerking a barbell. The scene was deceptively anti-climactic, for a threshold had been crossed. Most goods leaving the port—and others like it across China—will now incur outlandish tariffs if they enter America, the world’s biggest market and, until now, its staunchest champion of global trade.
Read more of our coverage of Donald Trump’s tariffs
Trump’s incoherent trade policy will do lasting damage
The tariff madness of King Donald, explained
With tariffs paused, Republicans dodge a fight with Trump
The tariffs on China are so extravagantly high because it chose to retaliate, punch for punch, against what it calls America’s “economic bullying”. When President Donald Trump unveiled a 34% tariff on China on April 2nd, China matched it. When Mr Trump then raised it to 84%, China answered in kind. Then, hours after America’s tariff came into effect, Mr Trump took a third swing. He hiked the levy from 104% at noon (including an earlier penalty of 20% related to China’s role in fentanyl production) to 125% after dusk.
Even as he hit China, he retreated elsewhere. Reciprocal tariffs on other countries, linked to the size of their trade surpluses with America, will now not come into force for another 90 days. Countries will instead face a 10% tariff as they seek “bespoke” agreements with the president.
Mr Trump’s retreat earned a hearty “thank you” from America’s financial markets. The bond market, in particular, had been making people a little “queasy”, Mr Trump conceded. After his reprieve, stocks surged. The S&P 500 index ended the day up by 10%, leaving it 3% below its level at the end of April 1st, before the whole charade began (see chart).
Despite Mr Trump’s retreat, the tariffs that remain are still historic. They average over 25% across all trading partners, when weighted by America’s imports last year. The last-minute rise on China, which remains a huge trading partner, was more than enough to offset the last-minute reprieve offered to India, Japan, South Korea and Taiwan, all combined. As a consequence, America’s weighted overall tariff is still above the level it reached after the infamous Smoot-Hawley act of 1930. At the time that legislation passed, this newspaper described it as “the tragi-comic finale to one of the most amazing chapters in world tariff history”.
Today’s chapter, still more amazing and tragicomic, has not yet reached its finale. The 90 days earmarked for country-by-country negotiations is a blink of an eye in the geological timescale of trade talks. When the serious bargaining begins, some countries may not pucker up enough for Mr Trump’s liking. The president still seems intent on imposing tariffs on copper, lumber, pharmaceuticals and semiconductors. And on May 2nd parcels from China that are worth less than $800 will face onerous duties and documentation requirements, which they previously escaped because the revenue was often not worth the hassle of collecting it.
The world’s two biggest economies begin an almighty trade clash
April 10th 2025
Victoria Harbour is Hong Kong’s most glamorous body of water. But Rambler Channel is where the free port’s work is done. The quays along its banks extend over more than 7km. Gantry cranes, rail-mounted or rubber-tyred, serve as many as 24 vessels at a time. Last year, the surrounding port handled over 10m of the standardised containers that carry goods across the world, parcelling globalisation up into metal boxes, in green, blue and red.
No bell or siren interrupted the port’s work at a minute past noon on April 9th—nothing to mark the moment when America’s devastating “reciprocal” tariffs came into effect. Containers kept circulating. Globalisation kept moving. A balding lorry driver reversed into position under a “reach stacker”, which hoisted his cargo into the air, like a weight-lifter jerking a barbell. The scene was deceptively anti-climactic, for a threshold had been crossed. Most goods leaving the port—and others like it across China—will now incur outlandish tariffs if they enter America, the world’s biggest market and, until now, its staunchest champion of global trade.
Read more of our coverage of Donald Trump’s tariffs
Trump’s incoherent trade policy will do lasting damage
The tariff madness of King Donald, explained
With tariffs paused, Republicans dodge a fight with Trump
The tariffs on China are so extravagantly high because it chose to retaliate, punch for punch, against what it calls America’s “economic bullying”. When President Donald Trump unveiled a 34% tariff on China on April 2nd, China matched it. When Mr Trump then raised it to 84%, China answered in kind. Then, hours after America’s tariff came into effect, Mr Trump took a third swing. He hiked the levy from 104% at noon (including an earlier penalty of 20% related to China’s role in fentanyl production) to 125% after dusk.
Even as he hit China, he retreated elsewhere. Reciprocal tariffs on other countries, linked to the size of their trade surpluses with America, will now not come into force for another 90 days. Countries will instead face a 10% tariff as they seek “bespoke” agreements with the president.
Mr Trump’s retreat earned a hearty “thank you” from America’s financial markets. The bond market, in particular, had been making people a little “queasy”, Mr Trump conceded. After his reprieve, stocks surged. The S&P 500 index ended the day up by 10%, leaving it 3% below its level at the end of April 1st, before the whole charade began (see chart).
Despite Mr Trump’s retreat, the tariffs that remain are still historic. They average over 25% across all trading partners, when weighted by America’s imports last year. The last-minute rise on China, which remains a huge trading partner, was more than enough to offset the last-minute reprieve offered to India, Japan, South Korea and Taiwan, all combined. As a consequence, America’s weighted overall tariff is still above the level it reached after the infamous Smoot-Hawley act of 1930. At the time that legislation passed, this newspaper described it as “the tragi-comic finale to one of the most amazing chapters in world tariff history”.
Today’s chapter, still more amazing and tragicomic, has not yet reached its finale. The 90 days earmarked for country-by-country negotiations is a blink of an eye in the geological timescale of trade talks. When the serious bargaining begins, some countries may not pucker up enough for Mr Trump’s liking. The president still seems intent on imposing tariffs on copper, lumber, pharmaceuticals and semiconductors. And on May 2nd parcels from China that are worth less than $800 will face onerous duties and documentation requirements, which they previously escaped because the revenue was often not worth the hassle of collecting it.
The surging gold price is boosting Central Asia’s economies
But foreign investors might want to tread carefully
March 27th 2025
Tian Shan—the name for the mountains that cross Kazakhstan, Uzbekistan and Kyrgyzstan—roughly translates as “Mountains of Heaven”. It is fitting for a range that is dotted with gold mines, including Kumtor, one of Central Asia’s largest and a symbol of Kyrgyz national pride. Moreover, it is not just the mountains of Central Asia that hold big reserves. Hundreds of kilometres to the west, in Uzbekistan’s Kyzylkum Desert, sits Muruntau, the world’s largest open-pit gold mine.
Now the good times are rolling. The price of gold has more than doubled since 2019. In March it breached $3,000 per troy ounce for the first time. That is good news for both governments and miners in the poor but mineral-rich Central Asian states. The yellow metal is the biggest export for Kyrgyzstan, Tajikistan and Uzbekistan, and one of the biggest in Kazakhstan, the region’s largest and richest economy.
Indeed, the Uzbek Navoi Mining and Metallurgical Company (NMMC), which operates the Muruntau mine, is the world’s fourth-largest gold producer. It accounted for almost one-sixth of the Uzbek state’s revenue in 2023, when prices were significantly lower than they are today. The European Bank for Reconstruction and Development forecasts average economic growth of 5.7% for Central Asia this year—well above its forecast of 3.2% for emerging markets in general.
The gold boom has made life easier for the region’s central bankers. After the Kazakh tenge struck a record low against the dollar in January, the country’s policymakers sold some of their gold reserves—the value of which had soared to a record $25.9bn in October—to prop up the currency. Russia has become reliant on imports from Central Asia to dodge Western sanctions. In both Kazakhstan and Uzbekistan central bankers have used gold to settle transactions with their trading partner without the need for SWIFT, a Western financial-messaging network from which many Russian banks have been barred.
Little surprise, then, that the region’s leaders are eager to mine still more gold. Under his “Uzbekistan 2030” strategy, Shavkat Mirziyoyev, the country’s president, seeks 50% more production by the end of the decade. Mr Mirziyoyev wants to reduce the government’s role in the economy and entice foreign capital. To that end, the state-owned NMMC is reportedly planning an initial public offering (in London, with a rumoured valuation of more than £4bn, or $5.2bn). China has also invested in Central Asian gold-mining as part of its Belt and Road Initiative, focusing on Tajikistan, the region’s poorest country. In 2018 it agreed to build a power station in return for the right to develop the Upper Kumarg gold mine.
Foreign investors have not always had an easy time in the region. Kyrgyzstan’s Kumtor mine had for decades been run by Centerra Gold, a Canadian company. In 2021, amid tax disputes and allegations of environmental damage, it was taken over by the government of Sadyr Japarov, Kyrgyzstan’s nationalist president. In ordinary times, that might give overseas investors pause. But gold is alluring, especially when prices are this high. ■
But foreign investors might want to tread carefully
March 27th 2025
Tian Shan—the name for the mountains that cross Kazakhstan, Uzbekistan and Kyrgyzstan—roughly translates as “Mountains of Heaven”. It is fitting for a range that is dotted with gold mines, including Kumtor, one of Central Asia’s largest and a symbol of Kyrgyz national pride. Moreover, it is not just the mountains of Central Asia that hold big reserves. Hundreds of kilometres to the west, in Uzbekistan’s Kyzylkum Desert, sits Muruntau, the world’s largest open-pit gold mine.
Now the good times are rolling. The price of gold has more than doubled since 2019. In March it breached $3,000 per troy ounce for the first time. That is good news for both governments and miners in the poor but mineral-rich Central Asian states. The yellow metal is the biggest export for Kyrgyzstan, Tajikistan and Uzbekistan, and one of the biggest in Kazakhstan, the region’s largest and richest economy.
Indeed, the Uzbek Navoi Mining and Metallurgical Company (NMMC), which operates the Muruntau mine, is the world’s fourth-largest gold producer. It accounted for almost one-sixth of the Uzbek state’s revenue in 2023, when prices were significantly lower than they are today. The European Bank for Reconstruction and Development forecasts average economic growth of 5.7% for Central Asia this year—well above its forecast of 3.2% for emerging markets in general.
The gold boom has made life easier for the region’s central bankers. After the Kazakh tenge struck a record low against the dollar in January, the country’s policymakers sold some of their gold reserves—the value of which had soared to a record $25.9bn in October—to prop up the currency. Russia has become reliant on imports from Central Asia to dodge Western sanctions. In both Kazakhstan and Uzbekistan central bankers have used gold to settle transactions with their trading partner without the need for SWIFT, a Western financial-messaging network from which many Russian banks have been barred.
Little surprise, then, that the region’s leaders are eager to mine still more gold. Under his “Uzbekistan 2030” strategy, Shavkat Mirziyoyev, the country’s president, seeks 50% more production by the end of the decade. Mr Mirziyoyev wants to reduce the government’s role in the economy and entice foreign capital. To that end, the state-owned NMMC is reportedly planning an initial public offering (in London, with a rumoured valuation of more than £4bn, or $5.2bn). China has also invested in Central Asian gold-mining as part of its Belt and Road Initiative, focusing on Tajikistan, the region’s poorest country. In 2018 it agreed to build a power station in return for the right to develop the Upper Kumarg gold mine.
Foreign investors have not always had an easy time in the region. Kyrgyzstan’s Kumtor mine had for decades been run by Centerra Gold, a Canadian company. In 2021, amid tax disputes and allegations of environmental damage, it was taken over by the government of Sadyr Japarov, Kyrgyzstan’s nationalist president. In ordinary times, that might give overseas investors pause. But gold is alluring, especially when prices are this high. ■
For Wall Street itself, that means the hurdle to investing in China has been raised. But there are plenty of investors in other countries who have trillions of dollars of their own to deploy. Capital allocators in New York may feel as if they cannot appear too bullish on China for political reasons. Their peers in Dubai, Geneva and Singapore will not feel the same compunctions. Indeed, American politics may push foreigners towards China even as it keeps Americans out. The Trump administration’s chaotic spending cuts and on-again, off-again tariff promises are a big part of why American markets are in the doldrums.
All this presents an opportunity for Chinese policymakers. A recovering economy, a truce between the government and business, and a swell of interest in China’s technological innovation have begun to revive overseas interest. It is early days, and more is to be done. But the opportunity to seal the deal is there—if they wish to take it. ■
All this presents an opportunity for Chinese policymakers. A recovering economy, a truce between the government and business, and a swell of interest in China’s technological innovation have begun to revive overseas interest. It is early days, and more is to be done. But the opportunity to seal the deal is there—if they wish to take it. ■
Can foreign investors learn to love China again?
Wall Street still needs more to coax it back. But non-American firms may be ready to return
March 27th 2025
FOR CHINESE stocks to outperform American ones is rare enough. But this year the MSCI China index has beaten its American equivalent by an impressive 20 percentage points, on the back of excitement about cutting-edge tech firms such as DeepSeek and Manus AI. American shares, meanwhile, have been weighed down by worries about a bellicose Trump administration and the danger of a slowing economy.
Could this revival be enough to entice international investors back to China? It has been a rocky romance so far. When outsiders looked at China’s vast economy and rapid growth in the early 2010s, many saw a land of endless opportunity. More recently, however, slowing growth and a government crackdown on private firms, ranging from video-game makers to tutoring companies, has led to a reduction in the share of domestically listed stocks that are held by foreign institutions. From 6.4% at the start of 2021, it fell to just 4% at the end of 2024.
The main beneficiary of the market upswing has been Hong Kong-listed high-tech stocks, reflecting Western investors’ newfound enthusiasm for Chinese artificial intelligence. Even after the recent rally, many of the companies in question still look cheap. Hong Kong’s Hang Seng tech index has a price-to-earnings ratio (based on expectations of earnings next year) of around 19, compared with almost 70 at its peak in 2021. China’s tech firms are not just markedly cheaper than American tech stocks by the same measure; they are cheaper than American stocks overall.
When it comes to mainland stocks, though, investors are more reluctant. Cheapness may be necessary for a resumption of foreign interest, but it is not sufficient. Three issues make investors cautious. All would have to be resolved for them to return in good number.
Some progress has been made on the first issue, which was what initially sent foreign investors running for the hills. China’s tech crackdown began in 2020, when officials cancelled the initial public offering of Ant Group, the fintech arm of Alibaba, a tech giant, after the firm’s founder, Jack Ma, criticised the country’s regulators. The move sparked discussion of whether China had become “uninvestable”. Now a thaw seems to be in progress. Last month Xi Jinping, China’s president, got together with a group of private-sector leaders that included Mr Ma and Liang Wenfeng, the founder of DeepSeek. Mr Xi stressed the importance of entrepreneurship and the scale of the Chinese market.
A revival in the Chinese economy would help too. The slump of the past few years, driven by the country’s troubled property industry, has knocked consumer spending, the main engine of growth for most large Chinese companies. Here, the necessary work is half-done at best. On March 16th the state laid out a new economic-rescue plan, apparently demonstrating its commitment to boosting consumption. The plan included schemes to subsidise interest on consumer loans and a modest increase in China’s stingy government pension. Yet it was worth only 2% of GDP—not quite the bazooka required to really get consumption going.
The last challenge, and the one that looks least likely to be resolved in the foreseeable future, is politics. Miserable relations between China and America have made Uncle Sam’s investors wary. In 2023 Joe Biden, then America’s president, signed rules that required American private-equity investors to receive approval if they wished to invest in some high-tech Chinese sectors. Mr Trump is likely to expand their reach.
Wall Street still needs more to coax it back. But non-American firms may be ready to return
March 27th 2025
FOR CHINESE stocks to outperform American ones is rare enough. But this year the MSCI China index has beaten its American equivalent by an impressive 20 percentage points, on the back of excitement about cutting-edge tech firms such as DeepSeek and Manus AI. American shares, meanwhile, have been weighed down by worries about a bellicose Trump administration and the danger of a slowing economy.
Could this revival be enough to entice international investors back to China? It has been a rocky romance so far. When outsiders looked at China’s vast economy and rapid growth in the early 2010s, many saw a land of endless opportunity. More recently, however, slowing growth and a government crackdown on private firms, ranging from video-game makers to tutoring companies, has led to a reduction in the share of domestically listed stocks that are held by foreign institutions. From 6.4% at the start of 2021, it fell to just 4% at the end of 2024.
The main beneficiary of the market upswing has been Hong Kong-listed high-tech stocks, reflecting Western investors’ newfound enthusiasm for Chinese artificial intelligence. Even after the recent rally, many of the companies in question still look cheap. Hong Kong’s Hang Seng tech index has a price-to-earnings ratio (based on expectations of earnings next year) of around 19, compared with almost 70 at its peak in 2021. China’s tech firms are not just markedly cheaper than American tech stocks by the same measure; they are cheaper than American stocks overall.
When it comes to mainland stocks, though, investors are more reluctant. Cheapness may be necessary for a resumption of foreign interest, but it is not sufficient. Three issues make investors cautious. All would have to be resolved for them to return in good number.
Some progress has been made on the first issue, which was what initially sent foreign investors running for the hills. China’s tech crackdown began in 2020, when officials cancelled the initial public offering of Ant Group, the fintech arm of Alibaba, a tech giant, after the firm’s founder, Jack Ma, criticised the country’s regulators. The move sparked discussion of whether China had become “uninvestable”. Now a thaw seems to be in progress. Last month Xi Jinping, China’s president, got together with a group of private-sector leaders that included Mr Ma and Liang Wenfeng, the founder of DeepSeek. Mr Xi stressed the importance of entrepreneurship and the scale of the Chinese market.
A revival in the Chinese economy would help too. The slump of the past few years, driven by the country’s troubled property industry, has knocked consumer spending, the main engine of growth for most large Chinese companies. Here, the necessary work is half-done at best. On March 16th the state laid out a new economic-rescue plan, apparently demonstrating its commitment to boosting consumption. The plan included schemes to subsidise interest on consumer loans and a modest increase in China’s stingy government pension. Yet it was worth only 2% of GDP—not quite the bazooka required to really get consumption going.
The last challenge, and the one that looks least likely to be resolved in the foreseeable future, is politics. Miserable relations between China and America have made Uncle Sam’s investors wary. In 2023 Joe Biden, then America’s president, signed rules that required American private-equity investors to receive approval if they wished to invest in some high-tech Chinese sectors. Mr Trump is likely to expand their reach.
Estate agents in China are trying everything to sell flats
You can place your deposit in bushels of wheat or strings of garlic
March 27th 2025
On the list of professions that are currently flourishing in China, estate agents do not come high up. Houses were once easy to sell, the surest investment available. But as a result of a four-year slump in the market, millions of homes now sit unsold. Some already paid-for properties are not even getting built. New home starts fell by almost 30% in the first two months of this year, compared with a year earlier. As of February, average new home prices had fallen for 21 months in a row.
Around a tenth of estate agents in the biggest Chinese cities have closed since 2021, according to industry estimates. The decline has been even sharper in small towns. Yanjiao, just outside Beijing, has seen hundreds shut, says one survivor. Another says his income has fallen by half in three years. So perhaps some of the wilder antics of those still trying to shift flats are understandable.
In recent months 31 men in the southern city of Huizhou bought flats at the request of their girlfriends, perhaps thinking that they had found “the one”. They then discovered that their girlfriends were estate agents trying to sell those apartments and were not interested in marriage. Authorities launched an investigation, telling local media that 15 women, all at the same firm, were behind the scheme and had used a dating app to find their targets. The incident is probably “just the tip of the iceberg”, warned a newspaper run by China’s housing ministry on March 24th.
Some estate agents are offering valuable inducements. Last year a firm in Zhejiang province said it would give out a 10-gram gold bar (worth around $1,000) for each house it sold. A Beijing-based company promised to throw in a holiday home in the seaside city of Yantai for anyone who paid for an apartment in the capital with cash. Other firms have offered everything from iPhones to stakes in a private-jet company.
Another tactic is to slash downpayments. A developer in the southern city of Zhongshan allowed a deposit of just 9.90 yuan ($1.30) for some flats. Developers in the agricultural province of Henan permitted farmers to put down wheat or other crops as a deposit. In 2022 Central China Group, one such developer, ended up with 430 tonnes of garlic after selling 30 apartments, according to local media reports.
Brokers are changing their pitch. Livestreaming is now a popular way to sell houses, with 500,000 agents on Douyin, the Chinese version of TikTok. Some sing, dance and do comedy sketches from unsold homes. In March, “U-bro”, a robot with a camera that shows houses and answers questions, began livestreaming in the city of Wuhan.
Government officials are trying to help by easing developers’ financing woes and encouraging people to trade in their old homes for new ones. But JPMorgan Chase, a bank, expects that in 2025 Chinese property developers will account for two-thirds of Asia’s defaults. Many analysts do not expect a recovery in the Chinese market until 2026.
If there is one group that can see a silver lining, it may be young men. The social pressure for them to own a home before women will consider them husband material is huge. But with prices in Beijing in late 2019 at 44 times average salaries, such a purchase has long proved out of reach for many. That ratio is now down to a mere 32 times. Some young men, if they can work out which of the women are not just estate agents in disguise, may be looking to snap up a bargain and pop the question. ■
You can place your deposit in bushels of wheat or strings of garlic
March 27th 2025
On the list of professions that are currently flourishing in China, estate agents do not come high up. Houses were once easy to sell, the surest investment available. But as a result of a four-year slump in the market, millions of homes now sit unsold. Some already paid-for properties are not even getting built. New home starts fell by almost 30% in the first two months of this year, compared with a year earlier. As of February, average new home prices had fallen for 21 months in a row.
Around a tenth of estate agents in the biggest Chinese cities have closed since 2021, according to industry estimates. The decline has been even sharper in small towns. Yanjiao, just outside Beijing, has seen hundreds shut, says one survivor. Another says his income has fallen by half in three years. So perhaps some of the wilder antics of those still trying to shift flats are understandable.
In recent months 31 men in the southern city of Huizhou bought flats at the request of their girlfriends, perhaps thinking that they had found “the one”. They then discovered that their girlfriends were estate agents trying to sell those apartments and were not interested in marriage. Authorities launched an investigation, telling local media that 15 women, all at the same firm, were behind the scheme and had used a dating app to find their targets. The incident is probably “just the tip of the iceberg”, warned a newspaper run by China’s housing ministry on March 24th.
Some estate agents are offering valuable inducements. Last year a firm in Zhejiang province said it would give out a 10-gram gold bar (worth around $1,000) for each house it sold. A Beijing-based company promised to throw in a holiday home in the seaside city of Yantai for anyone who paid for an apartment in the capital with cash. Other firms have offered everything from iPhones to stakes in a private-jet company.
Another tactic is to slash downpayments. A developer in the southern city of Zhongshan allowed a deposit of just 9.90 yuan ($1.30) for some flats. Developers in the agricultural province of Henan permitted farmers to put down wheat or other crops as a deposit. In 2022 Central China Group, one such developer, ended up with 430 tonnes of garlic after selling 30 apartments, according to local media reports.
Brokers are changing their pitch. Livestreaming is now a popular way to sell houses, with 500,000 agents on Douyin, the Chinese version of TikTok. Some sing, dance and do comedy sketches from unsold homes. In March, “U-bro”, a robot with a camera that shows houses and answers questions, began livestreaming in the city of Wuhan.
Government officials are trying to help by easing developers’ financing woes and encouraging people to trade in their old homes for new ones. But JPMorgan Chase, a bank, expects that in 2025 Chinese property developers will account for two-thirds of Asia’s defaults. Many analysts do not expect a recovery in the Chinese market until 2026.
If there is one group that can see a silver lining, it may be young men. The social pressure for them to own a home before women will consider them husband material is huge. But with prices in Beijing in late 2019 at 44 times average salaries, such a purchase has long proved out of reach for many. That ratio is now down to a mere 32 times. Some young men, if they can work out which of the women are not just estate agents in disguise, may be looking to snap up a bargain and pop the question. ■
In the long term, China needs to reform the unbalanced fiscal relations between the central government, which collects 45% of China’s revenues, and local governments, which have to carry out 85% of the public spending. If local governments were less strapped for cash, they might be less feral about collecting it. Until then, profit-driven law enforcement will remain the bane of profit-seeking enterprise. ■
The Chinese government is cracking down on predatory law enforcement
Extortion by local officials causes a lot of anger
March 27th 2025
To rescue china’s lacklustre economy, the ruling Communist Party is trying to revive the animal spirits of entrepreneurs and rehabilitate the profit motive. Xi Jinping, China’s leader, has welcomed Jack Ma, a leading tech boss, back in from the cold, and basked in the reflected glory of DeepSeek, a private AI firm. The government has also recently released five employees of Mintz, an American due-diligence firm, detained in 2023. To get rich is, if not glorious, at least less dangerous than it seemed a few years ago.
But there is one kind of buck-chasing the party is determined to quash: profit-driven law enforcement. This is the over-zealous collection of fees, fines and back-taxes by cash-strapped local governments eager to refill their coffers. In his report to China’s legislature this month, Li Qiang, the prime minister, vowed “resolute steps to prevent unauthorised cross-jurisdictional and profit-driven law enforcement”. On March 24th the Ministry of Finance said it will “resolutely prevent and correct” random charges, fines and levies.
Such money-grubbing has mushroomed since the pandemic, as conventional sources of revenue have fallen. Last year China’s tax collection fell by 3.4%, and revenues from land sales by 16%. The money raised from fines and confiscations, by contrast, increased by 14.8%.
Desperate local governments have resorted to new and crude tactics to raise money. Last year a mining company in western China was hit with a demand for 668m yuan ($92m) for alleged tax obligations going back 20 years. In dozens of reported cases executives have been detained on frivolous charges and obliged to bribe their way out of custody.
Distance is no barrier. Officials have crossed jurisdictional lines to hit up companies or individuals in other provinces, a practice known as “fishing in distant seas”. Foreigners are not exempt. Last year a foreign investment manager based in Beijing discovered that his local business partner had been arrested. Even though the charges came from a lowly sub-provincial jurisdiction, his lawyers advised him to leave the country immediately with his family, which he duly did.
Scholars have warned of grave damage to China’s private sector. Zhao Hong of Beijing University wrote in December that fishing in distant seas and other abuses “are tantamount to draining the pond to catch the fish”. Zhou Tianyong, a senior official at the Central Party School, a training institute for cadres, wrote of the profiteering last September in existential terms. In an online post that was quickly scrubbed from social-media sites he wrote that if local officials keep using the detention of entrepreneurs to boost revenue, it would lead to a “national economic disaster”. Enterprises across the country would collapse, he warned, together with hopes of reviving the economy.
Leaders have woken up to the damage the shakedowns are doing to private business. China’s highest prosecutorial body, the Supreme People’s Procuratorate, has started to crack down. It reviewed 1,500 cases last year and has blocked improper attempts to grab 570m yuan in assets.
As well as legal remedies, some experts propose preventive measures. One idea is that all seized assets should be handed over to the central authorities. That would reduce the incentive for local officials to overreach. The central government is also trying to find less painful ways to fill local coffers. In November it said it would let provinces issue extra bonds worth 6trn yuan over the next three years to replace more expensive, “hidden” debts. This should give local governments more financial breathing room and a less compelling need to gouge their constituents.
Extortion by local officials causes a lot of anger
March 27th 2025
To rescue china’s lacklustre economy, the ruling Communist Party is trying to revive the animal spirits of entrepreneurs and rehabilitate the profit motive. Xi Jinping, China’s leader, has welcomed Jack Ma, a leading tech boss, back in from the cold, and basked in the reflected glory of DeepSeek, a private AI firm. The government has also recently released five employees of Mintz, an American due-diligence firm, detained in 2023. To get rich is, if not glorious, at least less dangerous than it seemed a few years ago.
But there is one kind of buck-chasing the party is determined to quash: profit-driven law enforcement. This is the over-zealous collection of fees, fines and back-taxes by cash-strapped local governments eager to refill their coffers. In his report to China’s legislature this month, Li Qiang, the prime minister, vowed “resolute steps to prevent unauthorised cross-jurisdictional and profit-driven law enforcement”. On March 24th the Ministry of Finance said it will “resolutely prevent and correct” random charges, fines and levies.
Such money-grubbing has mushroomed since the pandemic, as conventional sources of revenue have fallen. Last year China’s tax collection fell by 3.4%, and revenues from land sales by 16%. The money raised from fines and confiscations, by contrast, increased by 14.8%.
Desperate local governments have resorted to new and crude tactics to raise money. Last year a mining company in western China was hit with a demand for 668m yuan ($92m) for alleged tax obligations going back 20 years. In dozens of reported cases executives have been detained on frivolous charges and obliged to bribe their way out of custody.
Distance is no barrier. Officials have crossed jurisdictional lines to hit up companies or individuals in other provinces, a practice known as “fishing in distant seas”. Foreigners are not exempt. Last year a foreign investment manager based in Beijing discovered that his local business partner had been arrested. Even though the charges came from a lowly sub-provincial jurisdiction, his lawyers advised him to leave the country immediately with his family, which he duly did.
Scholars have warned of grave damage to China’s private sector. Zhao Hong of Beijing University wrote in December that fishing in distant seas and other abuses “are tantamount to draining the pond to catch the fish”. Zhou Tianyong, a senior official at the Central Party School, a training institute for cadres, wrote of the profiteering last September in existential terms. In an online post that was quickly scrubbed from social-media sites he wrote that if local officials keep using the detention of entrepreneurs to boost revenue, it would lead to a “national economic disaster”. Enterprises across the country would collapse, he warned, together with hopes of reviving the economy.
Leaders have woken up to the damage the shakedowns are doing to private business. China’s highest prosecutorial body, the Supreme People’s Procuratorate, has started to crack down. It reviewed 1,500 cases last year and has blocked improper attempts to grab 570m yuan in assets.
As well as legal remedies, some experts propose preventive measures. One idea is that all seized assets should be handed over to the central authorities. That would reduce the incentive for local officials to overreach. The central government is also trying to find less painful ways to fill local coffers. In November it said it would let provinces issue extra bonds worth 6trn yuan over the next three years to replace more expensive, “hidden” debts. This should give local governments more financial breathing room and a less compelling need to gouge their constituents.
