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The Nobel Prize in Economics goes to prosperity researchers

Darren Acemoglu, Simon Johnson and James A. Robinson received this year’s Nobel Prize in Economic Sciences for their contributions to proving the importance of public institutions to a country’s prosperity.

KEY FACTS

  • The prestigious prize, officially known as the Sveriges Riksbank Prize for Economic Sciences in Memory of Alfred Nobel, is the last prize awarded this year and is worth SEK 11 million ($1.1 million).
  • This year’s laureates showed that one of the explanations for differences in countries’ prosperity is the social institutions introduced during European colonization. Inclusive institutions were often introduced in countries that were poor at the time of colonization, which over time led to general prosperity for the population. This is an important reason why former colonies that were once rich are now poor and vice versa.
  • Introducing inclusive institutions would create long-term benefits for everyone, but extractive institutions provide short-term gains for those in power. As long as the political system ensures they retain their control, no one will trust their promises of future economic reforms. According to the laureates, this is the reason why there is no improvement.
  • “Reducing the huge income gaps between countries is one of the greatest challenges of our time. The laureates have demonstrated the importance of public institutions in achieving this,” said Jakob Svensson, Chairman of the Economic Sciences Prize Committee.
  • “Societies with poor rule of law and institutions that exploit the population do not generate growth or change for the better,” the prize’s organizers add on their website.

TANGENT

Darren Acemoglu and Simon Johnson work at MIT, while James Robinson is at the University of Chicago.

Acemoglu and Johnson recently collaborated on a book researching technology through the ages that demonstrates how some technological advances are better at creating jobs and spreading wealth than others.

KEY STORY

The Economics Prize is not one of the original science, literature and peace prizes created by the will of dynamite inventor and businessman Alfred Nobel and first awarded in 1901, but is a later additional prize established and funded by the Central Bank of Sweden in 1968.

Past recipients of the award include a number of influential thinkers such as Milton Friedman, and John Nash – played by actor Russell Crowe in the 2001 film A Beautiful Mind, and former US Federal Reserve Chairman Ben Bernanke.

Last year, Harvard economic historian Claudia Goldin won a prize for her work highlighting the causes of pay and labor market inequality between men and women.

AI Spending Is Complicating The Fed’s Fight Against Inflation

Silicon Valley leaders have long argued that artificial intelligence will make technology and services dramatically cheaper. OpenAI CEO Sam Altman has described a future where intelligence becomes extremely inexpensive, while Tesla and SpaceX CEO Elon Musk has predicted that AI and robotics will create greater abundance and drive down costs.

So far, those benefits have yet to materialise at scale. AI adoption remains relatively slow, while the enormous investment needed for data centres and AI infrastructure is putting pressure on electricity prices, supply chains and other costs. For the Federal Reserve, this creates a difficult balancing act: AI could eventually boost productivity and reduce inflation, but its current buildout is contributing to higher prices.

OpenAI chief economist Ronnie Chatterji said AI needs to be adopted by organisations and generate measurable value before its broader economic impact becomes visible in productivity statistics.

AI Adoption Remains Uneven

Capital spending on AI infrastructure in the U.S. is expected to reach $581 billion this year, according to Goldman Sachs Research, with global investment potentially reaching $1 trillion.

Despite the scale of spending, adoption remains far from universal. A May survey by the U.S. Census Bureau found that 17% to 20% of U.S. businesses reported using AI, with adoption significantly higher among large companies.

Companies that have implemented AI at scale also highlight the challenges. Julie Averill, former CIO of Lululemon, said successful deployment requires changes in employee behaviour and trust in the technology. OpenAI has observed a similar divide: its most advanced business users deploy AI at around eight times the rate of average companies.

Why Productivity Gains May Take Time

Economists point to the limits of automation. AI can perform individual tasks effectively, but many jobs combine tasks that are difficult to automate.

Stanford professor Charles Jones refers to these as “weak links”. Radiology, for example, involves interpreting scans but also communicating with patients and working with colleagues. AI can automate part of the job without eliminating the profession itself.

As a result, the full economic impact of AI may not become clear until businesses adopt the technology more broadly and reorganise their operations around it.

AI Adds To The Fed’s Policy Challenge

AI’s economic impact has become part of the Federal Reserve’s policy debate. Fed Chairman Kevin Warsh has argued that AI could eventually become a significant disinflationary force by increasing productivity and strengthening U.S. competitiveness.

Other officials are more cautious. In July, the Fed kept interest rates at 3.5% to 3.75%, while some officials expressed concern that AI infrastructure spending could add to inflationary pressures.

Minneapolis Fed President Neel Kashkari pointed to massive data-centre investment as a new source of demand. Household electricity prices rose 10% in the two years through July, compared with a 6.2% increase in overall consumer prices. Meanwhile, shortages of chips and other AI components are pushing up costs. JPMorgan Chase estimates that DRAM prices could rise 400% by the end of 2026 compared with 2024.

Warsh has consequently adopted a more cautious tone, saying that while AI investment is laying the groundwork for future growth, the timing and scale of its economic effects remain difficult to predict.

For the Fed, the challenge is clear: AI could eventually deliver major productivity gains, but the cost of building that future is already showing up in the economy.

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