The Great Productivity Divide

Why Institutions Matter More Than AI

💬 Price discovery, not technological discovery, drives sustained productivity growth.

Productivity is the key to the wealth of nations: it rests on a foundation of labor, capital, markets, technology, and institutions that work together to promote efficiency. A single strong component is not sufficient. All of these elements must interact effectively to produce the gains that lead to economic growth.

Today, there is a fierce debate about the geoeconomic significance of artificial intelligence. Enormous sums are being invested in chips, data centers, and machine learning. The two primary players, China and the United States, are in direct competition over AI and their economic futures.

However, technological achievement may not be the decisive factor in this race. Price discovery, not just technological discovery, is the mechanism that drives sustained productivity growth. Innovation generates lasting gains only when markets and economic systems deploy new technologies efficiently across large numbers of firms and workers.

The intensifying competition between the United States and China may therefore hinge not just on AI, but on how this technology and others are integrated into their respective economies. In other words, on symbiosis between public and private technology and economic institutions. Surprisingly, despite China’s vaunted gains in AI and robotics, it is falling far behind the US in terms of productivity.

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The Widening Global Productivity Gyre

For the past three decades, beginning with the technology boom of the late 1990s, the United States has led the world in productivity growth. Several factors help explain this divergence from other major economies. The US hosts many of the largest technology firms, and its deep capital markets combined with flexible labor conditions have allowed rapid deployment of key resources to the most productive firms— including new entrants.

The US regulatory environment has also been more conducive to rapid innovation than in Europe, where productivity growth has been stifled by overregulation and limited access to venture capital, which has often slowed the scaling and diffusion of new technologies.

According to OECD productivity data,,output per hour worked in the US is roughly 25 percent higher than in the Eurozone, a gap that has widened since the global financial crisis in 2008. In the last last 50 years, the US has created 241 companies worth $10 billion or more, while Europe has created only 14, according analysis by Andrew McAfee of MIT Sloan reported in the Wall Street Journal.

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The Growing US-China Productivity Divide

China’s economic rise over the past four decades has been remarkable. Yet the productivity gains that once drove that expansion have slowed markedly in recent years, especially when measured by total factor productivity (TFP).

Despite the image of China as a manufacturing powerhouse, output per hour worked remains only about one-third of the level in the US. Although TFP grew by 3–4 percent annually during the boom years of reform and opening, productivity growth has slowed to around 1 percent or less in recent years.

While some industries, such as electronics, are more productive than others, the overall average is dragged down by lower-productivity sectors elsewhere in the economy. Beyond manufacturing competence, the issue is the inefficient economy-wide allocation of resources. The momentum of earlier market reforms has continued to weaken as many of those reforms have been unwound.

The productivity gap between the US and China today is roughly comparable to the gap between the US and Japan in the early 1950s, when Japan was still at a very early stage of its postwar industrial recovery.

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Two Systems, One Technology

Artificial intelligence influences productivity not only through software and data, but through automation in the physical economy.

China today installs roughly half of the world’s industrial robots each year, according to the International Federation of Robotics. Yet technology adoption alone does not guarantee productivity leadership.

Deploying robotics effectively requires capital investment, management flexibility, and constant experimentation on factory floors. Productivity gains typically emerge not from a single technological breakthrough but from thousands of incremental improvements as firms discover more efficient ways to integrate new technologies into production.

China excels at industrial scale, but in an environment where central planning often picks winners and users, the latest and best technologies may not flow to the firms that could use them most productively.

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The Deng Reforms and Price Discovery

Ironically, China’s economic rise itself demonstrates the power of price discovery. When Deng Xiaoping launched China’s reform era in the late 1970s, he did more than open the country to global trade. Deng gradually introduced mechanisms that allowed prices and incentives to guide large parts of the economy. Township and village enterprises, private manufacturing clusters, export-oriented industrialization, and Special Economic Zones all allowed market signals to shape investment decisions.

Deng acknowledged the central role of markets in this process, observing that “planning and market forces are not the essential difference between socialism and capitalism,” meaning that markets could function as instruments within a socialist system.

China’s reform era allowed price discovery to operate across large swaths of the economy, unleashing decades of rapid productivity growth.

One issue worth watching in the United States is growing use of government support for industries viewed as critical to national defense. If prices are supported to give domestic companies time to catch up, such measures should be used sparingly and remain clearly temporary.

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Energy and the Discovery of Efficiency

The American shale revolution provides another example of how productivity gains often emerge through decentralized rather than centrally planned experimentation.

The underlying technologies of shale technology, hydraulic fracturing and horizontal drilling, had existed for decades. What transformed global energy markets was the ability of multiple firms to experiment with different drilling techniques in response to price signals: rising oil and natural gas prices in the early 2000s.

Over time those experiments dramatically reduced the cost of extracting oil and gas from shale formations. As Brian Potter argues in The Origins of Efficiency, technological breakthroughs become economically transformative only when firms learn how to utilize them efficiently and at scale.

In both cases, China’s reform era and the American shale revolution, the technologies that were used already existed. What mattered was the economic system’s ability to discover how these technologies could be used most productively.

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The Theory of Price Signals

Economists have long emphasized the importance of price signals in coordinating economic activity. A century ago Ludwig von Mises argued that the central challenge of economic organization was economic calculation, or the ability of an economy to determine how scarce resources should be allocated.

Later, Friedrich Hayek explained that market prices transmit dispersed information that no central planner can fully possess. Similarly, János Kornai showed that economies with distorted price signals struggle to identify productive investments.

When price discovery weakens, capital may remain trapped in inefficient sectors even as new technologies emerge.

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A Battle of Systems, Not Technology

Much of the geopolitical discussion about artificial intelligence frames the issue as a technological race. But history suggests that technological invention alone rarely determines economic outcomes.

As the historian Joseph Needham observed in his classic study of the history of Chinese science, imperial China produced many remarkable technological breakthroughs centuries before Europe, yet those inventions did not translate into sustained industrial growth. The successful deployment of technology in an economy depends not only on invention but on the institutional systems that allocate resources and reward innovation.

The AI “race” may therefore be less a battle of technologies than a competition between economic systems. The decisive issue may not be technological discovery, but price discovery.

During the early years of the Cold War, George F. Kennan warned that the Soviet system was inherently doomed to failure not because of a technological arms race, but because of inherent institutional weaknesses that would ultimately undermine its economy. In “The Sources of Soviet Conduct,” he wrote that the Soviet Union “bears within it the seeds of its own decay.”

Kennan believed the ultimate test between the two systems would be their capacity to adapt and allocate resources efficiently. In the age of artificial intelligence, that insight may once again prove relevant.

The future of the global economy may depend not only on who invents the most powerful technologies, but on which economic systems are best able to discover how to use them most productively.

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^📍Chicago

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Sources

• OECD productivity data (annual)

• Conference Board Total Economy Database (TFP)

• International Federation of Robotics World Robotics Report (2024)

• Brian Potter — The Origins of Efficiency (2025)

• Joseph Needham — Science and Civilisation in China (1954)

• George Kennan — “The Sources of Soviet Conduct” Foreign Affairs (1947)

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