Economic development in an age of great-power competition
Now that the United States has introduced a new set of import tariffs on Chinese goods, the world’s two largest economies appear to be on the brink of open economic warfare – and developing countries are in danger of getting caught in the crossfire. Beyond the risk that they could face sanctions or other trade restrictions if one superpower perceives them to be helping the other, Sino-American trade tensions are eroding the value of many of these economies’ comparative advantages, such as cheap labour and land. Coping with these challenges will require skillful economic statecraft.
Comparative and competitive advantages are dynamic by nature; they can be acquired or lost over time. As Harvard’s Michael Porter put it in 1990, “National prosperity is created, not inherited. It does not grow out of a country’s natural endowments, its labour pool, its interest rates, or its currency’s value, as classical economics insists.” Rather, an economy’s competitiveness “depends on the capacity of its industry to innovate and upgrade.”
As a growing number of governments pursue industrial policies – from short-term protective measures, like tariffs, to more forward-looking initiatives, such as targeted subsidies and deep structural reforms – the capacity to innovate and upgrade depends significantly on the state’s ability to work with the market to boost competitiveness. This poses a challenge for advanced economies no less than it does for developing countries.
Consider Europe, which was forced to rethink its prevailing business model – selling high-quality engineering products – after Russia’s full-scale invasion of Ukraine in 2022. As supply chains were disrupted, and energy costs and inflation soared, Europe’s reliance on others for critical goods, including inputs for its own manufacturing, became an enormous economic liability. Add to that China’s growing dominance in electric vehicles, and Europe finds itself increasingly anxious about its future competitiveness.
To be sure, many European economies remain highly competitive: Europe dominates the top 20 of the International Institute for Management Development’s 2023 World Competitiveness Rankings, with Denmark, Ireland, and Switzerland leading the pack. But Europe’s larger economies have been sliding in the rankings. Germany dropped seven spots between 2022 and 2023, to 22nd place, and France fell five spots, to 33rd.
One problem, pointed out in a report from the McKinsey Global Institute, is that while Europe leads in sustainability and inclusivity, per capita GDP (at purchasing power parity) is lagging. In 2022, it was 27% lower than in the United States, with about half that difference attributable to cultural norms – Europeans work fewer hours per capita over their lifetimes – and the other half resulting from differences in productivity levels. Boosting productivity is now a central concern of European policymakers and will have to be addressed partly through the development of high-tech industries.
This approach has certainly worked for the US, which spends 3.5% of its GDP on research and development – a smaller share than South Korea (4.9%) and Israel (5.6%), but significantly larger than China (2.4%) and the European Union (2.2%). All of these economies are devoting considerable attention to dual-use R&D in strategic areas like artificial intelligence, green tech, and quantum computing. What stands out about the US is that, while the government is providing funding and incentives, not least through the 2022 Inflation Reduction Act, it is the private sector that is driving plans to invest $400-500 billion in R&D over the next decade.
As a report by the Boston Consulting Group notes, R&D is part of a “virtuous cycle of innovation” that sustains America’s technological leadership. For example, the US claims 46% of the global market for semiconductor design. Thanks to its advanced technologies, the US semiconductor industry has a gross profit margin of 59%, which is 11 percentage points higher than competitors. In 2020, US semiconductor revenues reached $208 billion – twice the revenues of the second-leading country.
But not just anyone can emulate America’s high-tech success, which is partly a function of its large and dynamic capital market. In 2022, the total market capitalization of the US stock market was 2.5 times higher than that of Europe. As a share of GDP, total market value in the US exceeded 158% in 2022, lower than Taiwan (195% of GDP), but higher than every other economy, including China (65.4%), Japan (126%), Germany (45.5%), and India (103.7%).
With its deep capital markets, the US is well-positioned to generate funding for high-risk R&D and, more importantly, reward and retain talent. Other economies – including China, the EU, Japan, and most developing countries – cannot compete on this front, not least because their banking systems remain far more risk-averse.
Recognizing America’s comparative advantages in high-tech sectors, China focused on building prowess in mid-tech areas of engineering and operational production and distribution, which opened the way to comprehensive competition at scale. Since 2014, China has led the world in exports of high-technology goods, accounting for more than 30% of the global market share. Since 2000, it has tripled its share of gross value added.
For developing countries, this means that it will be very difficult to compete in mid-tech industries, not just the high-tech sectors that the advanced economies (and, increasingly, China) dominate. Add to that their limited capacity to finance investment and their dependence on access to global or regional markets to achieve economies of scale, and economic statecraft becomes all the more challenging.
Some priorities are clear. To achieve technological upgrading, countries must invest as much as possible in digital infrastructure and education, as well as projects related to the United Nations Sustainable Development Goals. To cope with rising protectionism among major economies, they will most likely also increase support for domestic “champions,” even if it means perpetuating market fragmentation.
Overall, however, we will probably see a lot more experimentation in development strategies in the coming years. Developing countries will just have to hope that the US and China come to some sort of grand bargain before their competition escalates into conflict.
Andrew Sheng is a distinguished fellow at the Asia Global Institute at the University of Hong Kong.
Xiao Geng, Chairman of the Hong Kong Institution for International Finance, is a professor and Director of the Institute of Policy and Practice at the Shenzhen Finance Institute at The Chinese University of Hong Kong, Shenzhen.
CAMBRIDGE – The recent passing of psychologist and Nobel laureate Daniel Kahneman is an apt moment to reflect on his invaluable contribution to the field of behavioral economics. While Alexander Pope’s famous assertion that “to err is human” dates back to 1711, it was the pioneering work of Kahneman and his late co-author and friend Amos Tversky in the 1970s and early 1980s that finally persuaded economists to recognize that people often make mistakes.
When I received a fellowship at Stanford University’s Center for Advanced Study in the Behavioral Sciences (CASBS) four years ago, it was this fundamental breakthrough that motivated me to choose the office – or “study” (to use CASBS terminology) – that Kahneman occupied during his year at the Center in 1977-78. It seemed like the ideal setting to explore Kahneman’s three major economic contributions, which challenged economic theory’s apocryphal “rational actor” by introducing an element of psychological realism into the discipline.
Kahneman’s first major contribution was his and Tversky’s groundbreaking 1974 study on judgment and uncertainty, which introduced the idea that “biases” and “heuristics,” or rules of thumb, influence our decision-making. Instead of thoroughly analyzing each decision, they found, people tend to rely on mental shortcuts. For example, we may rely on stereotypes (known as the “representativeness heuristic”), be overly influenced by recent experiences (the “availability heuristic”), or use the first piece of information we receive as a reference point (the “anchor effect”).
Second, Kahneman and Tversky’s work on “prospect theory,” which they published in 1979, critiqued expected utility theory as a model of decision-making under risk. Drawing on the “certainty effect,” Kahneman and Tversky argued that humans are psychologically more affected by losses than gains. The perceived loss from misplacing a $20 note, for example, would outweigh the perceived gain from finding a $20 note on the sidewalk, leading to “loss aversion.”
This insight is also at the core of the “framing effect.” The theory, developed while Kahneman was a fellow at CASBS and Tversky was a visiting professor at Stanford, posits that the way information is presented – whether as a loss or a gain – significantly influences the decision-making process, even when what is framed as a loss or gain has the same value.
Lastly, there is Kahneman’s popular masterpiece, the bestselling Thinking, Fast and Slow. Published in 2011 and offering a lifetime’s worth of insights, the book introduced the general public to two stylized modes of human decision-making: the “quick,” instinctive, emotional mode that Kahneman called System 1, and the “slower,” deliberative, or logical mode, which he called System 2. Humans, he showed, are prone to abandoning logic in favor of emotional impulses.
Kahneman received the Nobel Prize in Economics in 2002, despite, as he jokingly remarked, having never taken a single economics course. Nevertheless, his scholarship laid the groundwork for an entirely new field of economic research – and it had all begun in Study 6.
In particular, Kahneman’s work had a profound impact on University of Chicago economist Richard Thaler, who went on to become a Nobel laureate himself. As an assistant professor, Thaler managed to “finagle” a visiting appointment at the National Bureau of Economic Research, whose offices were located down the hill from CASBS, enabling him to connect with Kahneman and Tversky.
In 1998, Thaler co-authored a seminal paper with Cass Sunstein and Christine Jolls, introducing the concept of “bounds” on reason, willpower, and self-interest, and highlighting human limitations that rational-actor models had overlooked. By the time he received the Nobel Prize in 2017, Thaler had systematically documented “anomalies” in human behavior that conventional economics struggled to explain and conducted highly influential research (with Sunstein) on “choice architectures,” popularizing the idea that subtle design changes (“nudges”) can influence human behavior.
But as I gazed at the sweeping views of Palo Alto and the San Francisco Peninsula from the office window at CASBS, the birthplace of behavioral economics, I could not help but wonder whether Kahneman, despite his famously gentle nature, had perhaps been too critical of human decision-making. Are all deviations from “pure” economic logic necessarily “irrational”? Is our inability to align with the idealized model of economic analysis, coupled with our inevitable – albeit predictable – irrationality, really an inherent weakness? And is our tendency to rely on emotions rather than reason a fatal flaw, and if so, could our susceptibility to instinct ultimately lead to our downfall?
I wish I could ask Kahneman these questions. During my time there in 2020-21, Kahneman, affectionately known as “Danny” to all, was not just what CASBS called a “ghost” of the “study” – a former occupant who had been a major influence on my work – but also, happily, a vibrant, living legend who had enthusiastically invited me to discuss these very issues in person. Looking back, I regret my “planning fallacy” in not taking him up on his offer to deepen our conversation sooner – a sentiment shared by both my System 1 and System 2 modes. If “to err is human,” Danny taught me a poignant final lesson in human error.