Macro Moments Weekly: United States at 250—Exceptional Returns, Exceptional Economy

Key takeaways:

• US exceptionalism is long-term, not recent: America's superior equity returns are rooted in more than a century of innovation, capital formation, and economic adaptability—not just the technology boom of the last two decades.
• AI is reinforcing US competitive advantages: The leading AI platforms are being developed and commercialised by highly profitable US technology firms, whose scale, cash generation, and data advantages position them at the centre of the next wave of productivity growth.
• The strength of the US extends beyond Big Tech: While technology companies dominate headlines, broader earnings growth, entrepreneurial culture, risk-taking capital, and economic dynamism continue to support the case for sustained US market leadership.

4th July 1776 marks the founding of the United States of America.

By the time you read this, the 250th anniversary of the nation will probably be over. This seems to be a good moment to re-examine US exceptionalism, the extraordinary returns the country has delivered for investors over time. At present, US equities represent is 63% of the MSCI World Index¹ and have dominated returns since the global financial crisis nearly two decades ago. But that is missing the point, this is a much older story: Since 1900, the US equity market has returned 6.6% in real terms every year. Contrast that with Europe, at 4.3%. And had it not been for the UK compounding at 5.5%, the European figure would have been significantly lower.² Notwithstanding the destruction of capital in 1907, 1929, 1973 and 2008, the United States has managed to return after each of these crises and perform well. (Gold star for anyone who knows the only two markets that outperformed the United States since 1900.)  

The ability of the US to “do it better” is perhaps its greatest advantage. The development of the railroad post-1860 is well documented, although the bankruptcies were equally common. The railroad needed steel, and the steel mill wasn’t new; the Bessemer process was not new either, it was just inefficient. The improvements made by Alexander Holley allied to Andrew Carnegie’s investment literally created the rails for the railroad, and at a reasonable price. The movie, the motor car, the airplane, the internet—all originated elsewhere but were perfected and made profitable in the United States. Most recently, the genius of the iPhone was to take available technology, re-imagine it and deliver it better.

Then we come to artificial intelligence (AI), and here the story changes. The drive to make machines ‘intelligent’ has been the goal of every programmer since the computer was conceived. But it is in the US where the large language models (LLM) were developed and are now on every desktop and smartphone. We are still only in the infancy of discovering the start of the tasks that AI can relieve us of, such as software coding.

The rollout of AI is dominated by the 4 hyperscalers: Microsoft, Alphabet, Amazon and Meta. Their extraordinary cashflows have meant unlike the railroads, these investments are being made mostly with cash. Those cashflows have come from Microsoft reinventing the way we work, Alphabet how we search for information, Meta how we live our social lives and Amazon how we shop. Each were able to commercialise and develop by recognising the power of data. There has been competition in some areas; for instance, TikTok and Shein, but others have been complementary even supplementary. There is no monopoly, but first-mover advantage allied to restless re-invention (particularly at Amazon) has created these tech-driven financial powerhouses.

In keeping with its libertarian principles, the US has not regulated this industry it is up to the market to make the best of it.

In the world of LLMs, there are differences between each, in both cost and performance. Businesses and consumers now use the hyperscalers to direct us to the one that will give us, the consumer, the access to the right model, at the price we can afford, including their own. In a system this open, the risk is that competitors can use bots to do this, without having to build the systems and investing in the models. Development of models such as Mythos is designed to stop this, in essence stopping parasitical, piratical bots. Creating a moat behind which the developer can be rewarded.

The US economy is feeding off this success. The last three quarters have shown a significant shift the pace of productivity growth, alongside gross domestic product that has moved back close to its old average of 2.75%. The counterfactual that all the growth is AI growth, is clearly not the case. The new Federal Reserve Chair Kevin Warsh seems to be more committed to the fight against inflation than the markets expected, which should prove helpful as growth accelerates.

The debate in the market is how should one price this new technology, as it is a true revolution. Have we committed too much capital, and the returns cannot match it? (As did our railroad forebears.) If so, when is the bubble going to burst? Those addicted to Tobins-Q ratios and Shiller CAPE P/E ratio wince at valuations, even more than they did three years ago.

But this also misses the point. Whilst the extraordinary earnings growth of the tech sector cannot be missed, the breadth of US earnings growth is also clear. The S&P 500 Equal Weight Index has substantially outperformed the Magnificent Seven³ year to date, reflecting this. The expectations for the second quarter are very high, but if Micron’s earnings are anything to go by, there is plenty of room for upside surprise in both tech and across a wide range of other sectors.

There is a breadth about the US economy, without which the exceptional returns of the equity market over the last 125 years would not have been possible. It has been suggested that the ability to fail fast is critical, in allowing capital to flow to where it is truly productive. But to fail fast you need two other elements: firstly, you can’t fail unless you exist. You need someone to back you in the first place. You need risk-takers with deep pockets. They do that because they have more success than failure. Secondly, you need a reliable method that exposes failure and a culture that both recognises and accepts it, not as a disaster but as normal.

But you will not find risk-takers unless you have a culture that is insatiably curious, remarkably focused and always fascinated by learning and improvement.

Happy Birthday USA!