Edward Conard

Top Ten New York Times Bestselling Author

  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
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The Macroeconomic Effects of Corporate Tax Reforms

Francesco Furno New York University
Date Posted:
December 8, 2021
Is Database:
Database

The Kennedy tax cuts had a corporate tax multiplier of 2.5 for GDP and 1.85 for investment, significantly higher than the TCJA-17’s multiplier of 0.6 for both variables.

The macroeconomic effects of corporate tax reforms reveal significant differences between the Kennedy tax cuts and the Trump Tax Cuts and Jobs Act (TCJA-17). The Kennedy tax cuts resulted in a corporate tax multiplier of 2.5 for GDP and 1.85 for investment, significantly higher than the TCJA-17's multiplier of 0.6 for both variables. This disparity is largely due to differences in tax depreciation policies and corporate structures. In the 1960s, the corporate tax wedge increased from 0.72 to 0.84, stimulating investment as 75% of economic activity occurred in c-corporations. In contrast, the TCJA-17's accelerated tax depreciation policy meant that tax savings were often distributed to shareholders rather than reinvested, limiting its macroeconomic impact. The Kennedy cuts provided a stronger stimulus by addressing the scarcity of savings, whereas the TCJA-17 occurred in an era of abundant savings and weak demand, leading to different economic outcomes.

“…the time-series of investment and payouts to shareholders reported inFigure 10reveal an interesting pattern. increase in payouts to shareholders outweighs the increase in investment a.er the recent TCJA-17, but not a.er the Kennedy’s tax cuts..is can be observed both at the aggregate and at the c-corporations level. In fact, payouts does not appear to deviate much from the pre-reform trend, unlike investment which exhibits a clear acceleration. The increase in capital formation is gigantic: aggregate business investment is 50% higher in 1966 than in 1963, and c-corporations’ investment is 80% higher….”

The Macroeconomic Effects of Corporate Tax Reforms: Extended Excerpt Image 1


"... the results are reported in Figure 11. In response to the Kennedy’s tax cuts, the model predicts a large increase in GDP and investment, and a small effect on payouts to shareholders: the opposite of Trump’s Tax Cuts and Jobs Act. Similarly, the corporate tax multiplier for Kennedy’s tax cuts is around 2:5 for GDP, 1:85 for investment, and close to zero for payouts to shareholders. For the TCJA-17, the multiplier is around 0:6 for each variable. For every dollar of lost corporate tax revenues, the Kennedy’s corporate tax cuts stimulated GDP four times more than the TCJA-17. The intuition behind these results is the following. In the early 1960s, the corporate tax rate was high and tax depreciation policy was not accelerated as it was mimicking economic depreciation. As a result, the corporate tax wedge was well below one (around 0:72) before the reform. The Kennedy’s tax cuts increased the wedge significantly (to around 0:84), thus providing strong stimulus to the investment of c-corporations. Moreover, since around 75% of economic activity was taking place in the c-corporate sector, the aggregate effect was less diluted than in 2017….”

The Macroeconomic Effects of Corporate Tax Reforms: Extended Excerpt Image 2


“..To better understand how each factor (i.e. tax rate, tax depreciation, pass-through share, policy intervention) contributed to the outcomes reported in Figure 11, I perform another counterfactual experiment. First, I control for differences in the policy intervention by simulating the exact same reform in both 1961 and 2017: an unanticipated permanent reduction in the corporate tax rate by 10%. Then, I start from the calibration for 2017 and simulate the reform after changing one of the tax rate, tax depreciation rate and pass-through share at a time. So, for example, I take the calibration for 2017, set the tax depreciation rate equal to that in 1961, and simulate the reform. I repeat the same for the tax rate and the pass-through share. the results are reported in Figure 12. the exercise shows that differences in tax depreciation policy between the early 1960s and 2017 account for most of the difference in the macroeconomic response to the reform. Looking at long-run changes, differences in pre-reform corporate tax rates and in the pre-reform share of pass-through businesses contribute similarly to the difference between the two reforms. the interaction between these three factors, instead, can be assessed by looking at the difference between the first and the second vertical bar for each variable. For example, under the 1961 calibration, the long-run investment response is +14:24%, while the response under the 2017 calibration with each factor introduced at a time is only +8:39%, which implies an interaction effect of +5:85%. For the corporate tax multiplier, interaction effects appear to be smaller. Moreover, the multiplier is unaffected by the size of the pass-through sector. ‘is happens because a smaller pass-through sector implies larger aggregate stimulus after a corporate tax cut, but also a larger loss of corporate tax revenues - since a larger share of the economy receives the tax cut. the multiplier takes into account both effects, which almost perfectly offset each other in this specific experiment…”

The Macroeconomic Effects of Corporate Tax Reforms: Extended Excerpt Image 3


Francesco Furno, "The Macroeconomic Effects of Corporate Tax Reforms," New York University, November 12, 2021, https://ffurno.github.io/JMP_Corporate_Tax_Reforms.pdf

Core finding, "... the results are reported in Figure 11. In response to the Kennedy’s tax cuts, the model predicts a large increase in GDP and investment, and a small effect on payouts to shareholders: the opposite of Trump’s Tax Cuts and Jobs Act. Similarly, the corporate tax multiplier for Kennedy’s tax cuts is around 2:5 for GDP, 1:85 for investment, and close to zero for payouts to shareholders. For the TCJA-17, the multiplier is around 0:6 for each variable. For every dollar of lost corporate tax revenues, the Kennedy’s corporate tax cuts stimulated GDP four times more than the TCJA-17. The intuition behind these results is the following. In the early 1960s, the corporate tax rate was high and tax depreciation policy was not accelerated as it was mimicking economic depreciation. As a result, the corporate tax wedge was well below one (around 0:72) before the reform. The Kennedy’s tax cuts increased the wedge significantly (to around 0:84), thus providing strong stimulus to the investment of c-corporations. Moreover, since around 75% of economic activity was taking place in the c-corporate sector, the aggregate effect was less diluted than in 2017….”

The Macroeconomic Effects of Corporate Tax Reforms: Extended Excerpt Image 4

Evidence from the Trump vs Kennedy Tax Cuts

Mike Pettis Comment, "In this very interesting paper @Furno_Francesco compares the Kennedy corporate tax cuts in the early 1960s with the recent Trump corporate tax cuts, and finds that the former stimulated output roughly four times more than the latter. Put differently, the Kennedy tax cuts seem to have increased business investment while the Trump tax cuts were mostly passed on to shareholders which, as Atif Mian, Ludwig Straub and Amir Sufi have explained elsewhere, was likely in turn to lead to higher household debt. Furno explains that “A large part of this difference can be attributed to differences in pre-reform tax depreciation policy.” As I argued in my book and elsewhere, I think the reasons the Kennedy tax cuts flowed into investment and Trump tax cuts into savings had to do with the very different relationship between savings and investment at the time of the tax cuts. From a macro point of view corporate tax cuts increase business profits, which raise corporate savings. Whether these are used to fund investment or are passed on to shareholders depends on whether the main constraint on business investment is scarce savings or weak demand. In the former case, higher business profits can lead fairly automatically to higher business investment. If savings are abundant and the cost of capital low, however, the constraint is likely to be weak demand. In that case businesses will have little incentive to increase investment, and a cut in their taxes simply increases the after-tax profits they pass on to shareholders or use to acquire other companies. In the early 1960s, much of the world was still in the process of rebuilding itself after the ravages of two world wars. With high global investment needs and low global savings (the war caused income to plummet and, with it, savings), the main economic constraint was a scarcity of savings needed to fund investment. This was a time when the US was exporting so much of its domestic savings to the rest of the world that capital controls were imposed to restrict the outflow of dollars. Under these conditions it is not surprising that any policy that generated an increase in savings was likely - in classic supply-side fashion - to lead to an increase in business investment. In recent decades, however, conditions were dramatically different. The world has become awash in ex ante savings, and the US has become the dumping ground for nearly half of the world’s excess savings. What is more, US businesses are sitting on huge piles of cash and can only use them to buy back shares or purchase other companies. It is weak demand, in other words, and not scarce savings, that has limited business investment. In that case policies that increase in savings have little to no impact on business investment, and in fact could actually reduce business investment if the increase in business savings were balanced by a reduction in household income (and, with it, consumption). To me this is the key difference between the Kennedy and Trump tax cuts. The former provided more savings at a time when American businesses wanted to invest more, but were unable to do so in part because of the fierce global competition for US savings. The latter provided more savings at a time when the world was awash in excess savings and American businesses wouldn’t invest until they saw a rise in demand. As an aside, I am re-reading Charles Arthur Conant’s 1900 book, and it is amazing how similar the problem of excess savings the global economy faced in the 1880s-90s. At one point he proposes establishing a state pension system to help generate the demand needed to absorb excess global savings. This is because “experience has shown that when saved capital accumulates rapidly, the groping after new uses for it causes waste and disaster”.

Core of paper“…In the model, corporate tax changes affect the economy primarily through the investment decision of c-corporations, which is affected not only by the tax rate but also by tax depreciation policy. Specifically, the possibility to deduct investment from the tax base (partially) counteracts the distortion introduced by the tax rate: the faster investment is deducted from the tax base, the smaller the distortion to the rate of return on investment. As a result, when tax depreciation policy is very accelerated - like it was in 2017 - the rate of return on investment is almost unaffected by corporate tax policy, and a reduction in the corporate tax rate is not particularly expansionary……However, irrespective of how much stimulus is provided to investment, a corporate tax cut always entails a transfer of resources from the government to c-corporations. When pre-reform tax depreciation policy is very accelerated, the tax-savings from a rate cut are not used for investment and are distributed to the shareholders. When pre-reform tax depreciation policy is not very accelerated, instead, the extra cash is used for investment. Moreover, since a change to the corporate tax rate affects only c-corporations, the aggregate effect is diluted by the presence of pass-through businesses. After a rate reduction, pass-through entities are not only excluded from the tax cut, but they are also put at a competitive disadvantage. ‘is happens because they compete with c-corporations in the production of (imperfectly) substitutable goods, which further amplifies the shift of economic activity from pass-through businesses to c-corporations and reduces the aggregate effect even more….”

Ed Comment:I think petit only gets it part correct. He admits that the US was exporting savings in the 1960s. That suggests a surplus of savings (which he twists into a shortage). I suspect the big change is that today you have to grow by innovating/taking risk and that takes longer to take effect. In the 60’s we were building manufacturing capacity in the face of faster growth. That allows you to temporarily overbuild without much risk. That’s not true in today’s slow growth environment.

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Showing 484 database articles primarily about either Productivity, Cronyism, Incentives/Risk-Taking, Innovation/Research, Institutional Capabilities, Intangibles, Investment, Startups, or Workforce Reorganization

The College Wage Premium in the Generative AI Era

AI Summary. S. 575 between 2022 and 2026, the first sustained decline in relative demand for college-educated labor in four decades. AI exposure in white-collar occupations accounts for roughly 28% of that drop, as wage growth slowed disproportionately in high-AI-exposure jobs where college graduates are concentrated.

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.

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

Core argument: The U.S. college wage premium fell from 0.626 to 0.575 between 2022 and 2026—the first sustained decline in relative demand for college labor after four decades of uninterrupted expansion.

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

  1. The U.S. college wage premium fell from 0.626 to 0.575 between 2022 and 2026—the first sustained decline in relative demand for college labor after four decades of uninterrupted expansion.
  2. Moving from zero to full occupational AI exposure reduced wages by 0.086 log points by 2026.
  3. the college–non-college AI-exposure gap accounts for roughly 28% of the total premium compression over that period.

Related Articles:

  • Looking for the Ladder — The downtick in hiring in AI-exposed occupations started 6 months prior to the release of ChatGPT, and is “perfectly” aligned with the start of Fed rate hikes…
  • How Students and Recent Grads are Responding to the Rise of AI — Far from shying away from AI, American undergraduates “are flocking towards the most-AI-exposed degrees,” with enrollment in these majors up 8% last year…
  • AI and Young-adult Jobs: The Real Mystery — Since the summer of 2023, the employment rate for Americans 22–25 has declined for both college grads and non-college workers, a phenomenon beyond both…
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Gross and Net US Investment

AI Summary. Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment merely replaces depreciating assets. The shift toward faster-depreciating information technology assets requires larger gross investment increases to achieve any given gain in productive capital per worker.

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.

Does faster asset depreciation explain slowing productivity growth?

Core argument: 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 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

  1. 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.
  2. The shift toward information technology — which depreciates faster than physical machinery — is the primary driver of the widening gap between gross and net investment.
  3. 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.

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  • Capital Is Making a Comeback — Btw 1985-2021 the capital intensity of the American economy was relatively flat as a rise in intangible investment was offset by a decline in tangible…
  • The Transition to a Higher Cost of Capital — Bridgewater Associates co-CIO Karen Karniol-Tambour expects 10-year Treasury yields to rise from the current ~4.5% to compensate for structurally higher fiscal…
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The AI Re-Acceleration That Wasn’t

AI Summary. 615). Claims of re-acceleration result from cherry-picking frontier observations, selecting a breakpoint, ignoring variance collapse, and fitting separate lines on either side.

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.”

Are AI performance gains accelerating or just appearing to through selective measurement?

Core argument: 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.

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

  1. 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.
  2. 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.

Related Articles:

  • Why .400 Hitters Disappeared — and What It Means for AI — As AI model performance converges toward a ceiling, relative gains per improvement cycle shrink, transforming frontier capability from a pricing moat into a commodity where price becomes the primary differentiator and margin pressure intensifies across leading providers.
  • Chart of the Day: Small Models are Closing the Gap to Frontier AI — Small AI models are closing the gap with large ones, achieving the same reasoning benchmarks with 142x fewer parameters than required two years ago. This makes on-device AI viable without data centers, compressing the economic case for cloud-based, per-query AI services.
  • Anthropic’s Best AI Model Struggles To Attract Users As Cheaper Tools Thrive — Spending on the most expensive AI model from a leading provider has plateaued at 11% of total outlay, as cheaper, older models prove capable of handling most business tasks.
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Understanding AI and Productivity

AI Summary. U.S. productivity growth has accelerated to ~2.2% annually since mid-2022, above the 2010s baseline, though pandemic-era labor market and business formation dynamics likely contributed alongside AI. Historical general-purpose technology booms sustained labor productivity growth above 2.5% for a decade or more, making the current acceleration substantial but not unprecedented.

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.

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

Core argument: 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.

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

  1. 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.
  2. 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.
  3. 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.

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  • AI and Productivity — Rising US labor productivity is driven by higher capital utilization—factories, servers, and hotel rooms running harder—rather than new investment or efficiency gains at the individual task level.
  • Google’s AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy — Google’s new AI & Economy ATLAS maps 15M AI interactions to occupations, tasks, and activities, showing AI use is pervasive but not intensive…
  • Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools — Event studies indicate that adoption of AI coding tools raised “commits” (saved code updates) ~180%, but releases by only ~30%. Large upstream…
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US Widens AI-Driven Investment Gap With Europe

AI Summary. US corporate investment in equipment and facilities is projected to grow 40% in real terms by the end of next year, versus 12% in the euro area, widening a productivity gap where output per hour worked rose $14 in the US compared with $2 in Europe since 2018.

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.”

Is artificial intelligence investment widening the transatlantic productivity divide?

Core argument: 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.

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

  1. 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.
  2. 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.

Related Articles:

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    • Europe USA Relative Performance
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Why Big Tech’s AI Spending Is $3 Trillion Higher Than It Seems

AI Summary. Nine major technology companies carry ~$3tn in off-balance-sheet AI commitments — 5x their ~$600bn in reported capital spending — obligations that are growing faster than traditional investment and triple their combined lease and debt liabilities.

Peter Rudegeair and Peter Santilli Wall Street Journal
Date Posted:
August 17, 2026
Is Database:
Database

A WSJ analysis finds 9 firms involved in the data center buildout have ~$3T in off-balance-sheet commitments largely tied to AI infrastructure. The growth in such obligations has outpaced the firms’ capex growth over the last year.

Are technology companies hiding the true cost of artificial intelligence?

Nine top tech companies had some $3 trillion of off-balance-sheet commitments mostly related to AI, according to a Wall Street Journal analysis of footnotes in their most recent securities filings. Those obligations are growing faster than traditional “capex,” which totaled about $600 billion over the past year they reported, and were about triple what the companies owe under their outstanding leases and long-term borrowings.

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  • The Market Is Asking Questions — AI infrastructure debt spreads are widening as markets question whether returns on massive, front-loaded capital spending will outpace financing costs before assets depreciate. If compute demand plateaus from efficiency gains or slow adoption, the industry faces a glut of expensive, rapidly depreciating capacity.
  • Big Tech Credit Risks Rise Sharply As AI Spending Soars — The cost of insuring major technology companies' debt against default has reached record highs, driven by surging AI infrastructure spending that is straining balance sheets and pushing credit ratings toward junk status.
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