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How to get more innovation bang for the research buck

Economist Staff The Economist

Date Posted:: March 3, 2020
Is Database:: Database

The average age at which great scientists & inventors produce their most important work increased by 6 years over the 20th century, primarily due to extended early-life investment in education.

The average age at which great scientists and inventors produce their most important work increased by six years over the 20th century, primarily due to extended early-life investment in education. This shift suggests that while education is crucial for fostering innovation, it also delays the onset of productive careers, potentially shortening the working lifespan of these individuals. Despite starting later, these thinkers do not exhibit increased productivity in their later years. This trend highlights the need for policy makers and educational institutions to balance the depth of education with the timing of entry into the workforce to maximize innovation output. Understanding this dynamic is essential for optimizing research funding and ensuring a steady flow of groundbreaking work that drives economic growth and technological advancement.

, “…Benjamin Jones of Northwestern University has found that the average age at which great scientists and inventors produce their most important work rose by six years over the course of the 20th century, thanks to the need for more early-life investment in education. But although important thinkers begin their careers later than they used to,they are no more productive later in life. Education, while critical to discovery, shortens the working lives of great scientists and inventors….” Economist Staff, “How to get more innovation bang for the research buck,” The Economist, February 27, 2020, https://www.economist.com/finance-and-economics/2020/02/27/how-to-get-more-innovation-bang-for-the-research-buck

Moonshot Capitalism: AI Rewrites The Venture Capital Playbook

Tim Bradshaw Financial Times

Date Posted:: September 10, 2026
Is Database:: Database

Since the start of 2024, more than $150B of venture capital has been invested into non-AI “deep tech” firms whose products are rooted in significant engineering advances, exceeding the $133B invested in such firms btw 2010 and 2019.

The AI boom is fuelling a resurgence in ambitious “moonshot” bets, as early SpaceX backers’ huge returns and falling valuations for traditional software companies force tech investors to embrace riskier and more capital-intensive dealmaking. Excluding the giant sums ploughed into AI start-ups, global investment in “deep tech” — companies whose products are rooted in big scientific or engineering advances — has exceeded $150bn since the start of 2024, more than the $133bn in the entire decade to the end of 2019, according to Dealroom. This year’s deep-tech investments have not yet surpassed 2021’s peak, which was propelled by battery and electric vehicle deals for the likes of Rivian and Northvolt — many of which turned sour, highlighting the risks involved in moonshot dealmaking.

Takeaways by Macro Roundup^® AI

Deep-tech investment excluding AI exceeded $150bn since early 2024, surpassing the entire $133bn deployed across the prior decade (through end-2019), as falling valuations for traditional software push venture capital toward capital-intensive scientific bets.
The 2021 deep-tech peak — driven by battery and electric vehicle deals including Rivian and Northvolt — has not yet been surpassed, and the subsequent losses from those deals underscore the capital destruction risk inherent in moonshot dealmaking.

The College Wage Premium in the Generative AI Era

José Azar, Mireia Gine and Javier Sanz-Espín Social Science Research Network

Date Posted:: September 4, 2026
Is Database:: Database

The college wage premium flattened in the mid-2010s and has fallen ~8% since 2022. The authors argue that this compression reflects a broad decline in the returns to formal schooling, rather than a decline in the upper tail.

After expanding for four decades, the U.S. college wage premium [dropped] sharply from 0.626 in 2022 to 0.575 in 2026. Current Population Survey data through 2026 implies an unprecedented drop in relative demand for college labor—the first sustained negative relative demand growth. Post-2022 wage growth slowed disproportionately in high-exposure occupations, which employ a disproportionate share of college graduates. By 2026, going from zero occupational AI exposure to full exposure had a negative effect on wages of−0.086. Combined with the college–non-college exposure gap, this mechanism accounts for roughly 28% of the total drop in the college wage premium from 2022 to 2026. While non-causal, these patterns indicate that task displacement in AI-exposed white-collar occupations plays a quantitatively meaningful role in the recent compression of the aggregate skill premium.

Takeaways by Macro Roundup^® AI

The U.S. college wage premium fell from 0.626 in 2022 to 0.575 in 2026—the first sustained negative relative demand growth for college labor in four decades, per Current Population Survey data.
Moving from zero to full occupational AI exposure reduced wages by 8.6 percentage points by 2026; because college graduates concentrate in high-exposure white-collar roles, this mechanism accounts for roughly 28% of the premium’s compression.

Gross and Net US Investment

Timothy Taylor Conversable Economist

Date Posted:: September 4, 2026
Is Database:: Database

U.S. real net private domestic investment—which adds to the American capital stock—is now only ~25% as large as gross investment, down from ~40% in the 1970s. Taylor suggests the widening gap between gross and net investment reflects the relatively rapid depreciation of IT-related capital.

The figure divides net investment by gross investment. Back in the 1970s, net investment was often around 40% of gross investment, but the share has been slumping over time. For the last decade or so, net investment has been about 25% of the gross–that is, about three-quarters of gross investment is just making up for depreciation of the pre-existing capital stock. The likely reason for the growing gap between gross and net investment is that modern investment is more likely to be related to information technology [which] depreciates more rapidly and thus needs to be replaced and updated more often. If we want the average US worker to be using a greater amount of capital on the job–which was one of the key drivers of rising labor productivity in the past–it now takes a bigger rise in gross investment to lead to a given rise in net investment.

Takeaways by Macro Roundup^® AI

Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment now merely replaces depreciating capital rather than expanding the productive stock.
The shift toward information technology — which depreciates faster than physical machinery — is the primary driver of the widening gap between gross and net investment.
Raising capital per worker, a historic engine of labor productivity growth, now requires a substantially larger increase in gross investment than it did several decades ago.

The AI Re-Acceleration That Wasn’t

Paul Kedrosky Applied Complexity

Date Posted:: September 3, 2026
Is Database:: Database

Kedrosky argues AI capabilities continue to improve, but “the full composite data shows flattening relative gains, not acceleration…rolling relative model gains have fallen from their 2024 peak, while model dispersion has narrowed sharply.”

Using all Epoch’s Capabilities Index observations, and controlling for developer and model family, there is no statistically significant breakpoint. A piecewise model—which splits the series into intervals and applies a sub-function to each segment—does not improve on a purely linear trend: p = 0.615, The estimated change in slope has a confidence interval of -8.4 to +23.4 points per year. In short, the maths shows there is no model acceleration, contrary to claims, and as expected. The result comes from selecting frontier observations only, choosing a breakpoint, ignoring variance collapse, and fitting separate lines on either side.

Takeaways by Macro Roundup^® AI

Epoch’s Capabilities Index shows no statistically significant AI performance acceleration when controlling for developer and model family, with a breakpoint test returning p = 0.615 and a slope-change confidence interval of -8.4 to +23.4 pts per year.
Claims of AI re-acceleration rest on a methodological artifact: selecting only frontier model observations, pre-choosing a breakpoint, ignoring variance collapse, and fitting separate trend lines on each side of that breakpoint.

Understanding AI and Productivity

Chad Syverson Economic Innovation Group

Date Posted:: August 28, 2026
Is Database:: Database

Syverson is skeptical that AI initiated the rise in productivity growth that began in 2023. The acceleration began while AI investment was small, and pandemic-era labor market churn and business dynamism match the acceleration’s start.

Productivity from mid-2022 on has maintained a faster-than-2010s trajectory involving annual growth of about 2.2%. Could this acceleration be due to AI? Perhaps. The timing leans against AI being the sole initial cause. Additionally, there were well-documented increases in economic dynamism (labor market churn and business formation) during the pandemic emergence whose timing matches the acceleration’s start. Regardless of AI’s current effect, the longer the aggregate productivity acceleration continues, the more plausible it is that AI is an important driver. As for the magnitude, a sustained increase from 1.5 to 2.2% annual productivity growth would be substantial (after a decade, GDP per capita would be 7% higher than otherwise), but hardly unprecedented. The 1995–2004 productivity boom saw annual productivity growth of nearly 3% per year, and other past general-purpose-technology-related productivity boosts saw labor productivity growth in excess of 2.5% for a decade or longer.

Takeaways by Macro Roundup^® AI

U.S. labor productivity has grown at roughly 2.2% annually since mid-2022, a pace exceeding the 2010s trend and, if sustained, implying GDP per capita roughly 7% higher within a decade than the prior trajectory.
The 1995–2004 productivity boom averaged nearly 3.0% annual growth, establishing that a durable AI-driven acceleration to 2.2% would be meaningful but well within historical precedent for general-purpose-technology cycles.
Pandemic-era surges in labor market churn and business formation align more precisely with the productivity acceleration’s start date than AI adoption does, complicating AI-as-sole-cause narratives.

US Widens AI-Driven Investment Gap With Europe

Sam Fleming, Amy Borrett and Olaf Storbeck Financial Times

Date Posted:: August 24, 2026
Is Database:: Database

Oxford Economics projects US real business investment will rise 40% over 2021–2027, ~3x the euro area’s 12%. US investment growth since 2024 has been largely information processing and software, but high US growth in GDP/hour is not “merely digital.”

Corporate spending on new equipment and facilities in the US is projected to increase 40% in real terms between 2021 and the end of next year, according to forecasts from Oxford Economics. The US surge compared with a real-terms increase of just 12% in the euro area, while German business investment is expected to have all but stagnated over the same period. Europe also faces a large and growing productivity gap with the US. “The United States has recently pulled further ahead of Europe,” Bart van Ark, a professor at the University of Manchester, told policymakers at the ECB Forum in Sintra. GDP per hour worked increased $14 in the US between 2018 and 2025, compared with just $2 in Europe. “The gap is not only a digital sector story,” added van Ark, stressing that the US outperformance extended to other sectors, including wholesale and retail as well as professional services.

Takeaways by Macro Roundup^® AI

U.S. corporate investment in equipment and facilities is projected to rise 40% in real terms between 2021 and end-2026, versus 12% in the euro area and near-zero growth in Germany, sharply widening the transatlantic capital-spending gap.
U.S. labor productivity rose $14 per hour worked between 2018 and 2025, versus $2 in Europe, with outperformance spanning wholesale, retail, and professional services—not solely the digital sector.

The average age at which great scientists & inventors produce their most important work increased by 6 years over the 20th century, primarily due to extended early-life investment in education.

Since the start of 2024, more than $150B of venture capital has been invested into non-AI “deep tech” firms whose products are rooted in significant engineering advances, exceeding the $133B invested in such firms btw 2010 and 2019.

Are investors abandoning software for capital-intensive science bets?

Takeaways by Macro Roundup® AI

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The college wage premium flattened in the mid-2010s and has fallen ~8% since 2022. The authors argue that this compression reflects a broad decline in the returns to formal schooling, rather than a decline in the upper tail.

Is the college degree losing its economic value to artificial intelligence?

Takeaways by Macro Roundup® AI

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U.S. real net private domestic investment—which adds to the American capital stock—is now only ~25% as large as gross investment, down from ~40% in the 1970s. Taylor suggests the widening gap between gross and net investment reflects the relatively rapid depreciation of IT-related capital.

Does faster asset depreciation explain slowing productivity growth?

Takeaways by Macro Roundup® AI

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Kedrosky argues AI capabilities continue to improve, but “the full composite data shows flattening relative gains, not acceleration…rolling relative model gains have fallen from their 2024 peak, while model dispersion has narrowed sharply.”

Does AI capability growth actually accelerate or just appear to?

Takeaways by Macro Roundup® AI

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Syverson is skeptical that AI initiated the rise in productivity growth that began in 2023. The acceleration began while AI investment was small, and pandemic-era labor market churn and business dynamism match the acceleration’s start.

Is AI-driven productivity growth sustainable at historical technology boom levels?

Takeaways by Macro Roundup® AI

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Oxford Economics projects US real business investment will rise 40% over 2021–2027, ~3x the euro area’s 12%. US investment growth since 2024 has been largely information processing and software, but high US growth in GDP/hour is not “merely digital.”

Is artificial intelligence investment widening the transatlantic productivity divide?

Takeaways by Macro Roundup® AI

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