Nina Schick: The Wealth Gap Between the US and Europe is Widening
Nina Schick stated that she moved to Texas two years ago to be closer to the "smart industrialization" construction site; she believes the wealth gap between the US and Europe is widening.
In nominal dollars, from 2008 to 2023, the US GDP increased from $14.77 trillion to $27.72 trillion, a growth of 87%; the EU GDP increased from $16.37 trillion to $18.59 trillion, a growth of 13.5%.
In 2023, the EU's economic scale is about 67% of the US, down from 110% in 2008; during the same period, the EU's per capita GDP relative to the US dropped from 76.5% to 50%.
The core of the divergence is productivity. Since the mid-1990s, US productivity growth has accelerated, while Europe has lagged in information and communication technology investment, the scale of the tech industry, service efficiency, and total factor productivity.
However, "Americans are richer" cannot be directly equated with a higher standard of living for all Americans. Wealth and income distribution in the US is more concentrated: from 1980 to 2017, the pre-tax income share of the richest 1% in the US rose from 11% to 21%, while in Europe it rose from 8% to 11%.
In terms of market mechanisms, the US AI, cloud computing, chips, and capital markets concentrate profits, stock options, and venture capital returns in tech clusters; Europe's higher social security, tax redistribution, and wage compression mechanisms reduce extreme wealth concentration but also make it harder for high-risk capital returns to accumulate quickly. Beneficiaries are US tech asset holders and high-skilled talent, while European companies lack scalable capital and technology platforms.
Source: Public information
ABAB AI Insight
Schick's move to Texas corresponds to the geographical restructuring of the US AI industry. San Francisco still controls models, venture capital, and software talent, but Texas is attracting data centers, electricity, semiconductor supply chains, and industrial computing projects; AI is shifting from pure software competition to a capital-intensive industry that requires land, power grids, gas power generation, cooling, and high-voltage transmission.
In terms of capital pathways, the US has formed a continuous financing chain of "venture capital - public markets - hyperscale cloud providers - debt financing - data center construction." McKinsey estimates that by 2030, global data centers will require about $6.7 trillion in investment, with AI data centers needing about $5.2 trillion; this scale is more favorable for the US, which has a deep equity and debt market, dollar financing capability, and large tech buyers.
Historically, the gap between the US and Europe has not always widened. Around the year 2000, European productivity was closer to that of the US; since then, the US has formed centralized tech giants in internet platforms, cloud services, mobile computing, and AI, while Europe has retained more manufacturing, finance, public services, and small to medium-sized enterprise structures. Only 4 of the 50 largest tech companies in the world are located in Europe, indicating that the gap is mainly concentrated in high-profit, scalable software and platform layers.
This is a matter of capital concentration. The AI economy does not raise incomes equally across countries but prioritizes regions that own model companies, chip supplies, cloud platforms, data centers, and capital market exit channels. Europe does not lack talent or investment, but lacks the organizational capacity to rapidly convert technological experiments into global platform profits; the acceleration of the US wealth advantage is essentially the compound interest of technological and financial returns within the same system.
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