After a rough few weeks in stock markets, many were hoping that there might be respite. But Deutsche Bank has bad news: announcing that equities are set to fall another 6%. Highlighting significant declines in consumer and corporate confidence, the bank is arguing that the S&P500 index is set to fall to around 5,250.

It is difficult to understand these moves from an economic perspective. The market seems to be in a panic about President Trump’s tariffs. But there is no reason to think that tariffs would lead to a slowdown in economic activity in the United States. In fact, they should in theory have the opposite effect: by encouraging consumers to buy American products rather than foreign alternatives, they should boost the earnings of American firms.

The threat that tariffs pose is not of recession or slowdown, but rather of elevated prices. Higher prices would presumably mean that the Federal Reserve would have to raise rates. Yet we are seeing precisely the opposite prediction by markets, which are raising their bets on the central bank cutting interest rates in 2025. The assumption here appears to be that the economy might fall into recession.

Economists appear to understand that the threat from tariffs is inflationary rather than directly risking a recession. Former Kansas City Fed president Esther George told Yahoo Finance: “Even though the market is pricing in three rate cuts, I’m just looking at this landscape and saying the Fed has an inflation problem too.” RSM economist Tuan Nyugen agreed, telling the publication: “In March and April, we’re going to see a pretty big pickup in terms of inflation.”

Why this disconnect between economists and the markets? The answer lies in the fact that markets are often creatures of sentiment rather than of rational analysis. Sentiment tends to latch onto the decisions made by others, and sentiment in American markets is increasingly latching on to actions undertaken by the President.

The “Trump put” is the idea that the new administration will consider the effect of its actions on the stock market. So, for example, if Trump’s trade rhetoric starts rattling markets — whether this is a rational response or not — the Trump put would assure investors that the new administration would pull back from such scary rhetoric.

But this is not the way the new administration is behaving. Indeed, it is disregarding the markets. A cynic might say that the term “Trump put” itself is designed to focus attention on the fact that the Trump administration is not acting in a manner that is amenable to markets. Any time the new administration “misbehaves”, a slew of articles is published highlighting that it is acting irresponsibly. Stock market traders then sell stocks, and the Trump put becomes a self-fulfilling prophecy.

How will the new administration manage this? Tariffs, while pushing up prices, should not cause a recession, though a self-fulfilling stock market doom spiral might. The Trump administration needs to take active control over the market narrative and highlight these realities. The key is getting stock markets to focus their attention elsewhere and stop obsessing over trade policies. This is a PR problem, not an economic one. As things stand, the administration is suffering from bad optics.

---

Philip Pilkington is a macroeconomist and investment professional, and the author of The Reformation in Economics

philippilk

---

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

---

Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

miquelvilam

---