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Outdated straitjacket’: German debt brake dilemma to haunt next government

New chancellor will face stiff challenges to any attempt to loosen borrowing rules despite public support

Germany’s strict debt brake not only helped to bring down its last government, but will also haunt its next one. 

Lacklustre growth, looming spending increases and the need to boost defence and infrastructure investment will test Berlin’s commitment to abide by the constitutional requirement to keep the structural deficit at 0.35 per cent of GDP, economists predict.

“Finding the fiscal space for all the required policies exclusively in austerity looks like a mission impossible,” said Carsten Brzeski, global head of macro at ING. Any new government “will have to agree on looser fiscal policies”, he added. 

Friedrich Merz, head of the fiscally conservative Christian Democratic Union and clear frontrunner to become chancellor after federal elections next month, has promised to “uphold” the debt brake. “Today’s debts are tomorrow’s tax increases,” the CDU manifesto claims.

The rule, enacted in 2009 when public borrowing ballooned after the state bailed out the financial services industry, has since been decried by analysts and politicians as too rigid. 

Merz has also hinted several times that he may be open to tweaking the rule that Holger Schmieding, chief economist of Berenberg, called an “outdated fiscal straitjacket” for Europe’s largest economy. 

Public support for reform has also sharply increased: 55 per cent of Germans now support an overhaul of the strict borrowing limits, according to a January poll by Forsa on behalf of the German Council on Foreign Relations, compared with just 32 per cent last July.

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Not everyone is convinced that a Merz-led government would fundamentally change tack.

“I share the markets’ hope that Germany’s fiscal policy will change, but I still struggle to make this my economic base case,” Bank of America’s Europe economist Evelyn Herrmann told the Financial Times. 

Most observers expect only a limited relaxing rather than a complete axing of the borrowing cap. Fiscally conservative institutions such as the Bundesbank and the Council of Economic Experts have long called for nuanced changes that would open the door to a limited increase in public borrowing.

The council last year suggested allowing a structural deficit of up to 1 per cent if the government’s debt-to-GDP ratio falls below 60 per cent, and 0.5 per cent as long as it is below 90 per cent. With the ratio hovering just above 60 per cent, that would only create room for 0.15 per cent of GDP of additional government debt per year — a change that would not provide much more fiscal space.

A more powerful option would be the creation of further off-balance sheet funds for areas earmarked for additional spending such as infrastructure and the armed forces. Nato members face increasing pressure from US President Donald Trump to spend more on defence.

“Politically, such [changes in the structural deficit level and off-balance sheet funds] could be put to voters as upholding and reforming the debt brake rather than abolishing it”, said Michael Hüther, president of German Economic Institute (IW), a Cologne-based think-tank. 

The blueprint for such off-balance sheet operations is the €100bn in additional borrowing to buy tanks, fighter jets and other weapons and munition that Chancellor Olaf Scholz pushed through parliament shortly after Russia’s full-scale invasion of Ukraine in early 2022.   

Hüther is calling for a special purpose fund that borrows to spend €60bn each year on public infrastructure over a decade. Since 2019, the investment needs have surged from €460bn to €600bn, according to a joint study by IW and IMK, another economic think-tank.

Another special purpose fund to cover increases in military spending is seen as an additional option by Hüther and many other economists.

But even if a Merz-led coalition agreed on such steps, it may still struggle to win enough support in parliament for such moves. All reform options require a two-thirds supermajority among MPs, and there is little legal leeway to fudge things. The constitutional court in 2023 shot down the Scholz government’s attempt to use pandemic-era emergency funds for the green transition instead. This ruling eventually led to the demise of the three-way coalition last autumn.

Quirks in the German electoral system mean that the far-right Alternative for Germany (AfD) and the “leftwing-conservative” Sahra Wagenknecht Alliance (BSW) might control one-third of the seats in the next Bundestag even if they only receive a lower share of the popular vote.

Such a scenario would make winning support for the necessary constitutional changes even tougher. The AfD campaigns for a balanced budget and mainstream parties are adamant not to co-operate with the far-right party under any circumstances. Moreover, Wagenknecht herself said that her party would veto any constitutional change to buy “more and more weapons”.

Even if Germany’s next chancellor can overcome all political obstacles, a series of spending decisions taken by Scholz’s ill-fated three-way coalition will further limit the room to increase debt. 

Germany’s structural deficit is already on track to rise to 2 per cent in 2027 even without any additional defence and infrastructure investment, according to December’s Bundesbank forecast.

“The idea that the next government has the option to significantly increase public borrowing is hard to reconcile even with a highly generous reading of European fiscal rules,” said one person familiar with those calculations, referring to the EU’s 3 per cent deficit target.

“They are likely to limit the room for additional deficits significantly,” this person added. 

Calculations by the Jacques Delors Centre suggest that Germany could borrow an additional €48bn a year, or about 1.2 per cent of GDP, without getting in conflict with the EU rules. 

With no party forecast to win a straightforward majority in February’s election, coalition talks are likely to drag on for months. Then the new government’s first priority will be to agree budgets for this year and 2026.  

BofA’s Hermann warns that markets may instantly price in any move to increase public borrowing through higher yields on bonds. As private sector borrowing costs would rise as a consequence, this could dampen corporate investment and damage an already weakened economy.

“If we get a market reaction long before real fiscal change, this would tighten finance conditions and potentially damage real GDP growth,” she said.

Shell dominates carbon credit market as clean energy spending scaled back

Oil and gas groups rely more heavily on offsets to reach climate targets than any other sector

Shell dominated the $1.4bn global market for carbon credits last year as oil and gas companies scaled back their spending on clean energy and relied more heavily on offsets to reach their climate targets than any other sector.

Credits represent a tonne of CO₂ or other greenhouse gases reduced, removed or saved, and are used as a cheap way to progress towards climate promises made to investors.

UK-listed oil majors Shell and BP rolled back their clean energy spending last year. Shell also weakened its climate targets.

The voluntary carbon market runs alongside larger and more expensive trading systems run by governments, including the EU’s Emissions Trading System under which polluters trade permits giving them the right to emit.

Shell uses credits to help keep some of its climate promises, including a target to cut emissions per unit of energy sold by 15 to 20 per cent by the end of the decade compared with 2016.

To be used as offsets, credits must first be “retired”, meaning they cannot be traded further so the saving can only be counted once.

MSCI Carbon Markets, whose preliminary data for last year covers major platforms that issue carbon credits, said Shell removed 14.9mn credits from global trading in 2024, more than twice as many as Italian energy producer Eni, the next biggest user.

Separate data shows Shell retired nearly three times more credits than the next most prominent user, Microsoft, last year, Allied Offsets told the Financial Times. Its database covers 99 per cent of the market.

“We retire credits to compensate emissions, including those associated with the energy our customers use in transport, homes, producing goods and providing services,” Shell said.

It added that “decarbonisation must start with avoiding and reducing emissions”, but that carbon credits could “compensate” for emissions where it was not possible to swap technologies for zero-emission alternatives fast enough. 

Voluntary carbon markets outside the jurisdiction of governments have been rocked by accusations of fraud, double-counting, abuse of indigenous communities and flawed methodologies.

Since then energy groups have paused some of their purchases of new credits backed by green projects, such as planting trees or storing CO₂ underground, said Dirk Forrister, chief executive of the International Emissions Trading Association, a Switzerland-based lobby group.

But they have been using up their old stock of credits and counting them towards climate goals.

By contrast tech groups such as Microsoft have continued to strike new deals to offset their AI-fuelled emissions in years to come. “Tech may have risen a little bit, oil and gas pulled back some,” Forrister said. 

European oil groups — Shell, BP, TotalEnergies, Eni and Equinor — are still committed to net zero emissions by 2050, suggesting they must invest in credits if they want to avoid overhauling their entire business model. 

The fossil fuel sector overall was responsible for more than four in 10 credits used last year, three times more than any other sector, and a slightly higher proportion than 2023, MSCI’s data also show. 

Shell has retired more credits cumulatively than any other company, Allied Offsets said, with the vast majority of these linked to projects that avoid hypothetical emissions, such as when a forest is protected from being cut down. 

A person close to Shell said its portfolio of credits was linked to “a wide range of diverse projects across the world”.

How price elastic is demand for AI?

DeepSeek and semiconductors

We argued yesterday that if DeepSeek shows competitive AI models can be built at a much lower cost than believed, we need to revise our view of the likely economic structure of what the artificial intelligence industry will be. Returns might be less concentrated, and more of the value created might be captured by consumers (“legit invigorating” OpenAI boss Sam Altman said of this week’s developments, coining a fine euphemism for a massive loss in personal net worth).

That’s a point about the distribution of value. It leaves open the question of how much value is created. That, in turn, depends a lot on how the appearance of a radically lower-cost competitor will affect AI demand. If demand for that technology is very price elastic (shouldn’t it be?), that means the world will use way more of it than we thought it would before DeepSeek’s breakthrough.

Consider yesterday’s vicious sell-off in electricity companies near data centre hotspots. You might read that as the market saying demand for AI will not be very price elastic: data centres won’t need as much power because demand for AI services won’t surge as it gets cheaper. But that’s not necessarily the message. Maybe the market is saying the electricity demand won’t be where we thought, that is, near a few huge proprietary data centres run by giant US tech companies. Instead, AI will be run on smaller data centres all over the place. It is interesting, in this context, that while Nvidia recovered sharply yesterday, the hardest hit utilities (Constellation, Vistra and NRG) did not.

So what about semiconductors? There is an argument to be had about whether the DeepSeek breakthrough shows Nvidia is about to lose pricing power (the market has concluded, for now, it won’t). But there is another question about other semiconductor companies that make non-GPU chips that are nonetheless required in data centres: networking chips (Broadcom), memory chips (Micron), and power management chips (Monolithic). If demand for AI services is price elastic, these companies — which got hit hard this week — might continue to grow fast.

Stacy Rasgon, semiconductor analyst at Bernstein, sums it up nicely:

Semiconductor stocks are very volatile and highly cyclical, and some of them may be overvalued even after this week’s correction. But we don’t think the sector’s tremendous outperformance over the past 10 years is a fluke. The world is becoming more silicon intensive. And nothing about the DeepSeek news changes that.

Monday’s AI news didn’t just hit chipmakers, utilities and data centre infrastructure providers. Energy commodities and conductive metals fell too. Oil and nickel (a key ingredient in batteries) fell. Copper, which carries electricity into data centres, had a particularly steep decline:

Copper prices are volatile. Recently, they have mostly vacillated on economic news out of China, the biggest copper consumer. September’s peak coincides with market excitement and later disappointment about Beijing’s stimulus, and December’s rise, which this week’s news has partially undone, was partly about the country hitting its 5 per cent growth target. Because of various issues in the copper market, investors tend to get the best return by owning the groups that mine it. Those companies’ shares had tracked China’s outlook, and took a spill this week, too:

There has been a bull case for owning copper in recent years: copper wiring is crucial to the green transition and the AI push, yet bringing on new supply is cost and time-intensive. That should translate to high prices and strong returns in the short-term, and sustained long-term demand.

In response, all but one of the big miners have spent more on copper mining over the past two years, but are expected to slow down in the next few years — potentially an attempt hit a balance that keeps prices high, but not so high as to destroy demand or bring more supply online:

Has DeepSeek’s success diminished the bull? If AI is now more efficient, will there be less demand for data centres and therefore copper? Combined with the new US administration’s pushback against the green transition, the outlook for copper appears to be getting worse.

But this all hinges on AI demand. As we wrote above, if AI is further commoditised, there is the chance then that there will be more data centres, just owned by different people and in different places. That would only help the case for copper: new data centres may not run on Nvidia and Broadcom chips any more or be concentrated in Washington state or Virginia, but they will need just as much copper wire.

There is a lot we do not know about future supply and demand. Most of the copper miners do not disclose their spending on copper exploration. But Freeport-McMoRan does, and — while it is just pennies compared to their capex — it has risen fast, and may signal that other miners are looking to bring new supply online in the longer term, too:

In the long run, the world is going to need more copper. But there is going to be a lot of price volatility along the way — even more than with semiconductors.

Activists hold US Steel CEO’s feet to the smelter

David Burritt will have to provide a vision of how the company can thrive on its own if a Nippon Steel deal does not materialise

Donald Trump’s re-election shows America is big on comebacks. And his 2020 electoral defeat suggests bitter losses can still lead to future success. US Steel CEO David Burritt is seeking a similar redemption arc.

Burritt engineered the $15bn sale of his company to Nippon Steel in 2023, only to see it blocked in the last weeks of Joe Biden’s presidency. Trump, for his part, never favoured selling the company to a foreign buyer. Nor did the United Steelworkers of America. But the buyout agreement has yet to be terminated and US Steel and Nippon are holding out hope that the newly inaugurated Trump can be persuaded to reverse Biden’s verdict.

While the US Steel boss fights the last battle, some investors have moved on to a new one. Earlier this week, hedge fund Ancora Holdings declared it wants fellow shareholders to replace the board and sack Burritt, whom it thinks can no longer effectively govern. It is not uncommon for a CEO to leave when a big transaction falls apart, but Burritt insists that his final chapter is not written.

Ancora may be harsh to fault Burritt for pursuing the deal with Nippon, as if an unprecedented brawl over a buyer from an allied nation was predictable. The Nippon share price offer, more than double where US Steel was previously trading, came amid a process kicked off by a hostile bid for US Steel from another rival, Cleveland Cliffs. 

Moreover, it’s not like buyer and seller didn’t try to get the deal through. Nippon made generous, if uneconomic, concessions to allow local control of its prey. With Burritt at the helm, US Steel is pursuing two lawsuits, one over the Washington rejection and another over the union and Cleveland Cliffs’ attempts to scotch the deal. Besides, failure isn’t so bad. A Nippon abandonment would secure a $565mn termination fee for US Steel.

If the merger proves truly dead, the question of who should run the steelmaker is worth asking. Ancora says Burritt has failed as an operator and describes its candidate to replace him, industry executive Alan Kestenbaum, as a steel-sector “legend”. Such a person would come in handy: US Steel’s current share price is just $36, far below the $55 on offer from Nippon.

The biggest challenge for Burritt is that, unless he can revive the Nippon deal before its June drop-dead date, he must provide a persuasive vision of how US Steel can thrive on its own. Yet his brokering of the Nippon deal suggests he doesn’t think it can. It wouldn’t be surprising if shareholders are ready to give Ancora, which may have its own M&A angle, a hearing.

What to Know About China’s DeepSeek AI

The Chinese upstart says it has trained high-performing AI models cheaply, without using the most advanced chips

DeepSeek has Silicon Valley in awe and investors in a frenzy.

The Chinese artificial-intelligence upstart has shot to prominence after saying it had trained high-performing AI models cheaply, without the most advanced chips.

Tech stocks sank Monday as investors fretted about the implications, wiping some $1 trillion from the stock market’s value. Nvidia, which makes the chips at the heart of the AI boom, closed down 17%. Nvidia and other stocks that swooned recovered some ground Tuesday.

Here’s what you need to know about DeepSeek:

DeepSeek is a Chinese AI company, which just over a week ago launched its latest AI model, which it calls R1. The company said the model was particularly good at problem solving, performing on par with OpenAI’s o1 reasoning model—but at a fraction of the cost per use. A DeepSeek app is currently top in iPhone download rankings for the U.S.

The conventional thinking was that AI companies needed expensive, leading-edge computer chips—such as those made by Nvidia—to train the best systems. That has justified huge spending by the biggest U.S. tech companies, such as Alphabet and Meta Platforms.

Just last week, companies including SoftBank, Oracle and OpenAI pledged to spend $500 billion to build new AI infrastructure in a venture they call Stargate.

DeepSeek’s use of less advanced chips—combined with innovative model-training techniques—is now raising questions about the investment case for stocks seen as big winners from AI.

In addition, DeepSeek released its R1 model as open source. That means other companies can pick up and adapt the model for their own use, potentially opening the door for other cheap AI alternatives.

It is hard for DeepSeek to buy cutting-edge chips because of U.S. export controls, intended to hinder Chinese organizations from developing innovative AI for military purposes.

That DeepSeek appears to have been able to achieve state-of-the-art performance suggests that those export controls may be ineffective—either because U.S.-designed chips aren’t necessary to make the best AI models, or because those chips are somehow making it to China in sufficient quantities anyway.

DeepSeek grew out of a hedge fund co-founded by Liang Wenfeng that uses AI to find profitable trades in financial markets. Liang, a math geek who caught the investing bug, started writing AI algorithms to pick stock as a student. He founded his hedge fund, called High-Flyer, with two college friends in 2015. It now manages some $8 billion, making it one of China’s largest quantitative funds.

No. DeepSeek is a closely held Chinese company led by Liang, which isn’t traded on the stock market.

The researchers behind DeepSeek say that they tested R1 against some of the top AI models from OpenAI—and found that it was very competitive. Those evaluations include one developed by OpenAI itself that includes computer-programming tasks that an AI model must complete on its own, such as patching a bug in a given piece of software. R1 performed on par with a version of OpenAI’s reasoning-focused model, called o1, and outperformed an earlier one called o1-mini.

DeepSeek published costs for using R1 that were an order of magnitude below those charged by U.S.-based companies for their most sophisticated models.

Users have said R1’s writing and problem-solving skills are impressive but some note that the model performed worse than rivals on specific types of problem solving. In coming weeks, more third-party testing should give a better understanding of how well R1 really performs. And users can test it out themselves, too.

In a paper published last week, the Chinese researchers behind DeepSeek said their new model would sometimes suddenly stop and realize it should re-evaluate its initial approach to a problem, and allocate more thinking time to do so. They described the behavior as the model having an “Aha!” moment.

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“Rather than explicitly teaching the model on how to solve a problem, we simply provide it with the right incentives, and it autonomously develops advanced problem-solving strategies,” the researchers wrote.

What have U.S. AI companies said about DeepSeek?

OpenAI CEO Sam Altman on Monday called R1 “an impressive model, particularly around what they’re able to deliver for the price,” in a post on X. He also said that it was invigorating to have a new competitor and that his company would move up some of its product releases.

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President Trump said the launch of a low-cost Chinese AI model should be seen as a wake up call for U.S. industries. Trump also announced plans to impose new tariffs on semiconductor imports. Photo: elizabeth frantz/Reuters

Why is Nvidia taking such a big hit?

Nvidia has been one of the biggest winners in the AI boom because its chips have almost exclusively powered the training and in many cases the day-to-day running of the most powerful existing AI models. Nvidia—and its investors—have bet heavily that new generations of those cutting-edge chips will be necessary to develop the most powerful AI models. DeepSeek’s success suggests that Nvidia’s lead on AI chip development may not be as big as thought, or as crucial to developing new AI models.

In a statement, Nvidia called DeepSeek “an excellent AI advancement” and said the work required for it to come up with answers, called inference, “requires significant numbers of Nvidia [chips] and high-performance networking.”

Is DeepSeek a disaster for stocks linked to the AI boom?

Not everyone thinks DeepSeek has upended the AI-infrastructure industry. While DeepSeek might have found a way to cut AI training costs, AI demand keeps surging, and tech companies still need more computing power, wrote Stacy Rasgon, a Bernstein semiconductor analyst.

“Is DeepSeek doomsday for AI buildouts?” Rasgon and his colleagues wrote in a report on Monday. “We don’t think so.”

What does DeepSeek mean for the global AI race?

DeepSeek’s success building an AI model could rebalance the global playing field when it comes to AI development—and that has cheered some countries outside the U.S.

Government officials in France, for instance, said Monday that DeepSeek shows that agile companies with clever techniques still compete in the AI race, even if they have less money or limited access to the best AI chips. In other words, opportunities remain for those outside of the U.S. to catch up to Silicon Valley.

“The message is that we can compete,” said an official at France’s Élysée Palace, noting that raw computing power may no longer be the determinant of who wins in AI.

To be sure, DeepSeek also is a warning to other parts of the world. French startup Mistral AI has made its name on being a smaller, more efficient competitor to U.S. companies like OpenAI. Now it will have to keep up with DeepSeek and others that use its models, too.