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AI Summary. The gap between growth-oriented and value-oriented new business applications is widening, a divergence likely driven by a proliferation of startups built around artificial intelligence. Large language models are lowering the barriers to starting a business.
Core argument: U.S. business applications continue to rise, and breaking them into value and growth companies reveals a widening divergence between the two categories.
Breaking down business applications into value and growth companies reveals a widening divergence, likely driven by the proliferation of AI-enabled startups, as large language models dramatically lower the barriers to entrepreneurship.AI Summary. The authors forecast that the drag on US growth from higher oil prices will roughly offset the boost from recent tax cuts, and have lowered their GDP growth projection by 0.5 percentage points to 2.0%. Their baseline now runs about half a percentage point below estimated potential growth, with adverse scenarios three-quarters to a full point below.
Core argument: The authors lowered their 2026 Q4/Q4 U.S. GDP growth forecast by 0.5pp to 2.0% since the war with Iran began, reflecting higher oil prices and incoming Q1 GDP tracking data.
Coming into the year, we expected the transition from tariff drag in 2025 to a tax cut boost in 2026 to generate above-potential GDP growth this year. But as Exhibit 8 shows, we now expect the drag on growth from higher oil prices to roughly offset the boost to growth from the 2025 fiscal bill. Reflecting both the impact of higher oil prices and incoming Q1 GDP tracking data, we have lowered our 2026 Q4/Q4 GDP growth forecast by 0.5pp to 2.0% since the war began. For upcoming quarters, our baseline forecast is about ½pp below our estimate of potential growth, and in our adverse or severely adverse scenarios, GDP growth would be ¾-1pp below potential.AI Summary. U.S. core goods inflation has been running at its fastest pace outside the post-pandemic reopening, and the author argues tariffs are not the main explanation: prices rose 8% for computer software and accessories, which are tariff-exempt, while tariff-hit motor vehicles and parts were flat. Services inflation, including restaurants, dental visits and haircuts, also remains faster than before the pandemic.
Core argument: Core goods inflation ran about 1 percentage point faster than pre-pandemic rates in both 2023 and 2024, with goods price declines starting to slow from mid-2024.
Prices for physical goods were rising faster than at any point outside of the post-pandemic reopening before the Iran War. While some of that can reasonably be attributed to tariffs, tariffs are not the only, or even the main explanation. First, core goods inflation was running about 1pp faster than pre-pandemic in both 2023 and 2024, with price declines starting to slow beginning in mid-2024. Second, much of the recent pick-up in core goods inflation is attributable to items that are explicitly exempted from tariffs, such as computer parts that are used in data centers. By contrast, important categories that have been subjected to large tariffs, such as motor vehicles and parts—both directly and via punitive tariffs on steel and aluminum—have experienced relatively little inflation. The PCE price index for “computer software and accessories” rose by 8% between February 2025 and February- 2026, whereas prices for “motor vehicles and parts” have been flat. The boom in demand for goods needed for AI development has dwarfed the impact of tariffs. [Further], inflation [for restaurants] and other services, such as dental visits, haircut and dry cleaning have all either remained persistently faster than before the pandemic or have accelerated in the past year. Tariffs cannot plausibly explain any of these moves.AI Summary. Statistical models of University of Michigan consumer sentiment—trained on 1990–2019 data using inflation, unemployment, real consumer spending, and the S&P 500—fit the series well back to the 1950s but predict higher sentiment than observed after the pandemic price shock. Adding a variable measuring how far the consumer price level exceeded its pre-pandemic trend tracks the actual decline in sentiment.
Core argument: Two statistical models of University of Michigan consumer sentiment, trained on 1990–2019 data using inflation, unemployment, real consumer spending, and the S&P 500, fit the series back to the 1950s but diverge after COVID's price shock.
[The chart in gallery] shows the full UMich series, along with two predictions from two statistical models, based on inflation, unemployment, real consumer spending, and the S&P 500. We trained the model on data from 1990-2019 and then forecast and backcast. As you see, both models fit the data well, even back to the 1950s. At least, they do until COVID and the shock to prices. Then the first model says we should be a lot happier, damnit! To explain the gap, [Daniel Posthumus and I added this variable] which we think of as a trend-break to the price level. We run a smooth trend through the CPI price level through 2019, and extend the trend’s 2014-19 growth rate. Think of that shaded area at the end as a quantifying of the extent to which people were shocked/surprised/angered by the jump in the price level. We plug the log difference between trend and actual into the model, which, as you see in the pullout above, tracks the actual decline in sentiment.AI Summary. Polling by YouGov finds about 60% of Americans at every income level believe they are taxed too much, despite facing very different tax rates. Many states have cut taxes citing strong economic growth, localities are enacting property-tax exemptions for retirees, and the Tax Foundation warns states risk cuts they cannot afford.
Core argument: YouGov polling finds around 60% of Americans at every income level believe they are taxed too much, despite being taxed at very different rates, with Democrats and Republicans and rich and poor alike sharing the view.
Democrats and Republicans alike think they are overtaxed, as do both rich and poor. YouGov’s polling finds that around 60% of Americans at every income level think they are taxed too much—despite being taxed at very different rates. Statehouses are hearing this, too. Many, citing strong economic growth, have cut taxes in recent years. Enthusiasm is building to go further and faster, leaving some observers wary. “Most have done so responsibly thus far,” says Jared Walczak of the Tax Foundation, a think-tank. “But they now risk overreaching and making reductions they cannot afford.” A wave of localities is pushing through property-tax exemptions for retirees. Florida is flirting with abolishing non-school property taxes altogether. Ohio has a possible ballot initiative to scrap them in all forms.AI Summary. Research on "transformative entrepreneurs" argues that turning inventions into long-run growth depends on tycoons who control and popularize new technologies. An analysis of 11 American technological waves over 150 years, scoring leaders by company revenue, employment, market value, corporate control, and personal wealth, ranks Henry Ford as the most powerful.
Core argument: John D. Rockefeller's peak wealth equalled roughly 1.5% of American GDP, and Elon Musk may be richer still depending on how his wealth is calculated, though The Economist's ranking places Henry Ford as the most powerful mogul America has seen.
A paper by Ufuk Akcigit points to the crucial role of so-called “transformative entrepreneurs” in turning inventions into long-run economic growth. In short, prosperity requires tycoons. To understand how the AI magnates compare with business titans through history, The Economist examined 11 technological waves in America over the past 150 years, from railways to the internet. For each, we picked the top five people responsible for the control, distribution and popularisation of that technology. We quantified the power of each by looking at the revenue, employment and market value of their companies at their peak, as well as a subjective assessment of the degree of corporate control held by the tycoon, along with their personal wealth. Riches alone would not capture the full extent of a tycoon’s power. At his peak the wealth of John D. Rockefeller, founder of Standard Oil, was equivalent to around 1.5% of American GDP. Mr. Musk may be richer still, depending on how his wealth is calculated. By our ranking, however, Henry Ford is the most powerful mogul America has seen so far.AI Summary. US labor force survey data show occupational stability rather than economy-wide disruption from generative artificial intelligence, with the dissimilarity in occupational mix between older and more recent college graduates rarely deviating outside a 30–33% range. The authors note this limited early impact resembles the pace of change in previous periods of technological disruption.
Core argument: The dissimilarity in occupational mix between older and more recent college graduates has rarely moved outside the 30–33% range since January 2021, which the authors argue is inconsistent with generative AI substantially changing the labor market for recent graduates.
Overall, the March 2026 CPS releases do not indicate a meaningful shift from December in most categories. If generative AI were in fact substantially changing the labor market for recent college graduates, we would expect to see a growing dissimilarity in the occupational mix between these two groups [Figure 8]. Taking a closer look at the trend since January 2021, the dissimilarity between older and more recent college graduates rarely deviates outside of the 30-33% range [Figure 9]. The picture of AI’s impact on the labor market that emerges from our data is one that largely reflects stability, not major disruption at an economy-wide level. The lack of widespread impacts at this early stage is not unlike the pace of change with previous periods of technological disruption. [As a prospective research strategy], preregistering areas where we would expect to see the impact and continuing to monitor monthly impacts will help us distinguish rumor from fact.AI Summary. U.S. manufacturing growth is attributed to demand rather than tariffs, with McKinsey analysis finding that sectors with strong domestic production also had strong imports rather than the lower imports that reshoring would imply. Computer and electronic products output rose 7.7% while imports in the sector rose 40.5%, and aerospace and transportation equipment output rose 28%.
Core argument: U.S. domestic production of computer and electronic products rose 7.7% in the fourth quarter from a year earlier while imports in the sector rose 40.5%, part of a pattern McKinsey found in several sectors where strong production coincided with strong imports.
This stealth recovery, though, isn’t because of tariffs. Instead, credit goes to the most basic economic force of all: demand. The U.S. is good at making things that happen to be in big demand right now. McKinsey looked at production, imports and investment, reasoning that reshoring would be associated with lower imports and more investment. While no uniform pattern emerged, they did find in several sectors that where domestic production was strong, so were imports. Where production was down, so were imports. For example, domestic production of computer and electronic products last year was up 7.7%. (All its figures are from the fourth quarter compared with a year earlier.) But imports in this sector were up even more, by 40.5%. Aerospace and transportation equipment (which excludes trucks and cars) also boomed last year, with domestic output up 28%. No mystery here. Boeing’s jetliner deliveries soared 72% last year to 600 as production, curtailed over safety scrutiny, recovered. A new global arms race is lifting orders for jet fighters, missiles and helicopters. Meanwhile, aerospace imports rose 3%.AI Summary. America's three largest legacy defense contractors—Lockheed Martin, RTX and Northrop Grumman—together generated roughly 8x the combined sales of newcomers Anduril, Palantir and SpaceX, yet the three upstarts are worth more than 3x the legacy trio. Their valuations reflect investor optimism that they can shake up the arms industry.
Core argument: Lockheed Martin, RTX and Northrop Grumman together generated roughly eight times the combined sales of Anduril, Palantir and SpaceX last year, with SpaceX and Palantir earning much of their revenue from customers other than the Pentagon.
Last year America’s three biggest legacy primes—Lockheed Martin, RTX and Northrop Grumman—between them generated around eight times the combined sales of the three newcomers (and SpaceX and Palantir make much of their money from customers other than the Pentagon). Even so, investors are bullish. The upstart trio are worth more than three times the three biggest legacy contractors, reflecting among other things optimism over their ability to shake up the arms industry. The price tag on the company partly reflects the record amounts of venture-capital money pouring into defence startups in America. The buzz is helped by President Donald Trump’s quixotic quest to have Congress boost the next fiscal year’s defence budget by more than two-fifths from its current level, to $1.5trn.AI Summary. As university attendance has expanded, the average graduate has shifted from economic elite to norm, placing graduates lower in the socio-economic pecking order than graduates of the past. In both the UK and US, only 10% of graduates are in the lowest earnings quartile, but one in three ranks in the bottom bracket for earnings relative to expectations.
Core argument: In both the UK and US, only 10% of graduates fall in the lowest earnings quartile, yet one in three ranks in the bottom bracket for earnings relative to reasonable expectations.
The expansion of higher education, while well intentioned and clearly beneficial in many aspects, has upset the balance between expectations and outcomes. The dynamic I’m talking about here is a much broader phenomenon [than the erosion of the graduate wage premium]. As more and more people go to university, the average graduate shifts from being among the economic elite to being the norm, placing them much further down the socio-economic pecking order than graduates of yesteryear. The result is that even though today’s young adults, and graduates in particular, are over-represented in the top quartile of the earnings distribution, they are also far more likely to be at the bottom than the top for earnings relative to reasonable expectations. In both the UK and US, even though only 10% of graduates are in the lowest earnings quartile, one in three is in the bottom bracket for earnings relative to expectations. As a larger share of youngsters go to university, those who don’t are an ever more disadvantaged slice of their generation.AI Summary. Florida's net domestic migration has slowed to a trickle as prime-working-age residents leave citing affordability and arrivals from other states decline. An influx of wealthy newcomers has helped drive up home prices, inflation in parts of the state outpaced the national average, home-insurance rates soared, and deaths began outnumbering births.
Core argument: Florida's net domestic migration has slowed to a trickle, as residents in their prime working years leave for other states citing affordability while arrivals from other states shrink.
Florida’s migration patterns are changing dramatically. Residents in their prime working years are heading to other states, often citing affordability concerns. At the same time, the stream of people arriving from other states is shrinking. Meanwhile, an influx of wealthy people from other states—turbocharged during the pandemic—has helped drive up home prices. Inflation in parts of Florida outpaced the national average over the past decade and home-insurance rates soared. Florida lost one driver of population growth when deaths began to outnumber births in the state in 2020. Large flows of immigration fueled gains for years, but have waned under the Trump administration’s hard-line policies. Despite the influx of wealth, net domestic migration—people arriving from other states minus those leaving to other states—has overall slowed to a trickle in the past few years.