Edward Conard

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  • “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 is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “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
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
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Corporate Taxes and the Earnings Distribution: Effects of the Domestic Production Activities Deduction

Christine Dobridge, Paul Landefeld, and Jacob Mortenson Federal Reserve Board
Date Posted:
January 7, 2022
Is Database:
Database

The 2005 U.S. corporate tax cut, particularly the Domestic Production Activities Deduction (DPAD), significantly impacted wage distribution. A 1% cut in marginal tax rates increased average earnings by 1.1%, with small firms seeing higher gains at the top of the earnings distribution.

The 2005 U.S. corporate tax cut, specifically the Domestic Production Activities Deduction (DPAD), significantly impacted wage distribution within firms, with notable effects on smaller firms. A 1% reduction in marginal tax rates led to a 1.1% increase in average earnings, with the most substantial gains at the top of the earnings distribution. For small firms, semi-elasticities at the 95th and 99th percentiles were 4.4 and 5.7, respectively, compared to 2.2 for large firms at the 99th percentile. This suggests that smaller firms experienced larger wage gains, likely due to less monopsony power and greater employee bargaining power. While overall employment remained unchanged, small firms saw an increase in employee numbers, contrasting with declines in large firms. The DPAD also spurred capital investment in large firms, indicating a shift towards capital-labor substitution. These findings highlight the tax cut's role in widening income disparities and its varied impact across firm sizes.

"...This paper investigates how corporate tax changes affect workers’ earnings. We use a dataset of U.S. worker-level W-2 filings matched with corporate tax returns and study the implementation of the Domestic Production Activities Deduction (DPAD). We find the DPAD tax rate reduction has a substantial effect on the distribution of annual wage earnings within a firm. Earnings of workers at the top of their firm’s earnings distribution rise relative to those at the bottom of the distribution. We estimate a semi-elasticity of average earnings of 1.1 with respect to the DPAD marginal tax rate reduction, while the semi-elasticity of median earnings is notably smaller—0.5. Furthermore, we estimate a semi-elasticity of 1.3 at the 95th percentile of workers’ earnings and 2.7 at the 99th percentile. This trend of larger semi-elasticities at the top of the earnings distribution is especially pronounced for small firms. Looking at overall employment effects, we see no change overall, but the number of employees rises at small firms and declines at large firms. In contrast, we find that capital investment rises for large firms, suggesting that the DPAD also resulted in domestic capital labor substitution for large corporations. Our paper has significant implications for assessing the progressivity of the U.S. tax code and for analyzing the effect of corporate tax policy changes on the U.S. income distribution....We find the DPAD tax reduction resulted in a substantial increase in mean earnings at the firm level and that earnings gains were particularly concentrated at the top of the earnings distribution within firms. Our results suggest that a one percentage point reduction in marginal tax rates due to the DPAD led to a 1.1 percent increase in average earnings at the firm level. We find a much smaller impact, however, on median earnings within a firm, with an estimated semi-elasticity that is less than half the size of the average effect. Looking more broadly across the within-firm earnings distribution, we find semi-elasticities of earnings that are statistically indistinguishable from 0 at the very bottom of the earnings distribution—the 1st percentile through the 10th percentile. At the 25th percentile, we observe a statistically significant semi-elasticity of 0.4, which rises slightly at the median and the 75th percentiles, to 0.5 and 0.6, respectively. Earnings at the top of the distribution are notably more responsive: we find a semi-elasticity of 0.9 at the 90th percentile and of 1.3 at the 95th percentile. Earnings are the most responsive at the very top of the distribution; at the 99th percentile, we observe a semi-elasticity of 2.7—more than double that of mean earnings. As a result of rising earnings at the top of the distribution, we find the tax reduction leads to a widening of the within-firm earnings distribution overall. A one percentage point tax rate reduction due to the DPAD leads to a 1.1 percent increase in the ratio of earnings paid to the 95th percentile of workers compared to the 5th percentile. The change is even more pronounced at the higher end. A one percentage point rate reduction leads to a 2.8 percent increase in the 99th-to-1st percentile earnings ratio....We also examine the DPAD’s effect on overall firm employment and investment. We find no effect of the DPAD tax reduction on firm employment but find that the number of employees rises at small firms and declines at large firms. Our estimates of investment responses are consistent with capital-labor substitution for large firms, with investment increasing substantially in the highest two quintiles of firm size. But we find no investment effect of the tax cut for small firms...."

The core evidence"... We find the DPAD tax reduction resulted in a substantial increase in mean earnings at the firm level and that earnings gains were particularly concentrated at the top of the earnings distribution within firms. Our results suggest that a one percentage point reduction in marginal tax rates due to the DPAD led to a 1.1 percent increase in average earnings at the firm level. We find a much smaller impact, however, on median earnings within a firm, with an estimated semi-elasticity that is less than half the size of the average effect. Looking more broadly across the within-firm earnings distribution, we find semi-elasticities of earnings that are statistically indistinguishable from 0 at the very bottom of the earnings distribution—the 1st percentile through the 10th percentile. At the 25th percentile, we observe a statistically significant semi-elasticity of 0.4, which rises slightly at the median and the 75th percentiles, to 0.5 and 0.6, respectively. Earnings at the top of the distribution are notably more responsive: we find a semi-elasticity of 0.9 at the 90th percentile and of 1.3 at the 95thpercentile. Earnings are the most responsive at the very top of the distribution; at the 99thpercentile, we observe a semi-elasticity of 2.7—more than double that of mean earnings. As a result of rising earnings at the top of the distribution, we find the tax reduction leads to a widening of the within-firm earnings distribution overall. A one percentage point tax rate reduction due to the DPAD leads to a 1.1 percent increase in the ratio of earnings paid to the 95th percentile of workers compared to the 5th percentile. The change is even more pronounced at the higher end. A one percentage point rate reduction leads to a 2.8 percent increase in the 99th-to-1st percentile earnings ratio….”

Christine Dobridge, Paul Landefeld, and Jacob Mortenson, "Corporate Taxes and the Earnings Distribution: Effects of the Domestic Production Activities Deduction," Federal Reserve Board, December 2021, https://www.federalreserve.gov/econres/feds/corporate-taxes-and-the-earnings-distribution-effects-of-the-domestic-production-activities-deduction.htm

Size of firms, "... Generally, these results suggest that the DPAD had larger effects on the widening of the earnings distribution for the smallest firms by employment size than for the largest firms. Small firms exhibit positive and significant semi-elasticity estimates, and the estimates are strongest at the upper end of the earnings distribution. The semi-elasticities for small firms are statistically discernible from zero at the 25th, 50th, 75th, 90th, 95th, and 99th percentiles, with magnitudes that increase substantially at the very top of the distribution. The semi-elasticities in the upper portion of the distribution are also notably larger for small firms than for larger firms. The point estimate for the median percentile of small firms is a semi-elasticity of 1.8, for example, which rises to 4.4 and 5.7 percent, respectively, for the 95th and 99th percentiles. In contrast, for the largest firms, semi-elasticity estimates are considerably smaller overall. The point estimate for the semielasticity of the earnings for the median worker is 0.03, for example, and not statistically different from zero. Estimates increase the most at the very top of the earnings distribution for the largest firms, with a 2.2 semi-elasticity of earnings estimate for workers in the 99th percentile (though still less than half the magnitude of the 5.7 estimate at the 99th percentile for the smallest firms). Interestingly, for the largest firms, we observe statistically significant earnings increases at the very bottom of the earnings distribution—the 1st, 5th, and 10th percentiles—in addition to the top of the distribution, and the magnitude of the effect is similar to that for workers in higher earnings percentiles of these large firms. For workers in the 5th and 10th percentiles of the largest firms, for example, the semi-elasticity point estimates are 0.9, similar to the point estimates of 0.7 and 0.9 for the 90th and 95th percentile. The largest firms are the only firms for which we observe earnings increases due to the DPAD at the very bottom of the distribution. For firms in the middle of the employment distribution (the 2nd through 4th quintiles), we observe a statistically significant increase in earnings only at the 99th percentile for the third and fourth employment quintiles, and also at the 75th percentile for the third employment quintile.20 Finding larger effects for small firms is consistent with employees having more bargaining power at those firms but is also consistent with small firms having less monopsony power than large firms to set earnings. We further investigate the bargaining power and monopsony theories by studying effects of the DPAD on earnings for publicly traded firms and multinational firms in our sample. Large, public firms and multinational firms operating in global markets may also be expected to have greater local wage-setting power and workers in these firms may have less bargaining power as well. Semi-elasticities specific to publicly held firms for select earnings percentiles are presented in Table VI, column (3) and shown in Figure IV.B. Multinational firm results are in Table VI, column (4). Semi-elasticities for the full earnings distribution for public and multinational firms are given in Appendix Table A3. For publicly held firms, we find little effect of the DPAD on workers’ earnings. The largestpoint estimate is for the 99th percentile of the within-firm earnings distribution and implies a semielasticity of about 2.2. This result lends some support for Ohrn’s (2021) finding that top executives of publicly traded firms capture a substantial fraction of the DPAD and bonus depreciation tax reductions, but that there are no effects elsewhere in the earnings distribution for public firms. Widening of the within-firm earnings distribution, therefore, only occurs when comparing the very top of the distribution to the very bottom; the ratio of the 99th percentile earnings to the 1st percentile earnings rises by 2.2 percent as a result of the DPAD (Table VI)...."

Corporate Taxes and the Earnings Distribution: Effects of the Domestic Production Activities Deduction: Extended Excerpt Image 1


Who gains, "...To investigate whether earnings increases are flowing to firm owners, we examine a sample of firms (half of whom are in our main sample) who reveal their owners in Schedule G of their corporate tax return.23 These data are available starting in 2011. We match these firm owners to W-2s issued by the company and determine where in the firm earnings distribution these owners lie for firms with employee counts in the first quintile of our main sample (about 50 employees or less). The location of owners in the within-firm earnings distribution is shown in Figure V. This figure demonstrates that owners comprise more than 50 percent of the workers above the 99th percentile at these firms and around 25 percent of the workers between the 95th and 99th percentiles (i.e., more than 75 percent of workers in this sample of firms are in the top 5 percent of their withinfirm distributions). This result provides suggestive evidence that earnings gains among these small firms are accruing to firm owners and that some of the corporate tax cut benefits are accruing to capital and not labor...."

Corporate Taxes and the Earnings Distribution: Effects of the Domestic Production Activities Deduction: Extended Excerpt Image 2


Employment, Net Investment, and Total Earnings Effects

"...We report results for employment in column (1) of Table VII, Panel A, and we find an aggregate firm employment effect that is indistinguishable from zero. Column (2) presents the results for net investment as a share of installed capital and finds a point estimate of 0.008, implying that a one
percentage point reduction in the tax rate leads to 0.8 percentage point increase in net investment as a share of installed capital.26 Because the calculation of net investment requires an extra year of data and therefore the sample of firms is smaller, column (3) reproduces the estimates from column (1) with the smaller, common sample as well. We see that the employment effect remains statistically insignificant if a somewhat larger magnitude in the common sample...."
"...Figure VI.B shows the response of net investment as a share of installed capital to the DPAD rate cut. We find that the investment response is generally concentrated among the largest firms, with an increase in net investment as a share of capital of about 0.8 and 1.4 for every 1 percentage point decline in the tax rate due to the DPAD, for firms in the 4th and 5th quintiles by employment size, respectively.28 Of note, the combination of results in Figures VI.A and VI.B are consistent with evidence from Lester (2018), who uses a sample of large, publicly traded firms and finds that total employment declined among firms using the DPAD while investment increased. Lester suggests that this is consistent with capital-labor substitution among these firms...."

Corporate Taxes and the Earnings Distribution: Effects of the Domestic Production Activities Deduction: Extended Excerpt Image 3


"..Similarly to the largest firms in our sample, we also observe some decline in terms of total employment for publicly traded firms and for firms that payout to shareholders (our proxy for firms less likely to be financially constrained)—declines of 1.6 percent and 1.2 percent, respectively (Table VII). In contrast, we do not observe a statistically significant responses in terms of total employment among multinationals or firms that do not payout to shareholders. But we find that all of these subsets of companies have statistically significant and sizeable investment responses (1.6 percent, 1.1 percent, 0.7 percent, 1.0 percent for publicly traded, multinational, no payout and payout firms, respectively). Of note, the results for payout and non-payout firms taken together do not provide consistent evidence of financial constraints driving firm investment or employment responses to the tax cut; if looser financial constraints due to the DPAD were the primary mechanism driving our results, we would expect to see an investment increase in the “no payout” firms only...."

Ed Comment: "Not clear what time frame they used. My guess is a short one. Very profitable firms have sustainable competitive advantages. That’s why they are more profitable. If we lower the tax rate, they and their leaders will capture some of the value in the short run. But the prospect of excess returns is the very thing the incents innovation. Without excess returns, competitors are highly incented to wait until their competitors take the risks and suffer the failures needed to create innovation. So the correct time frame for tax analysis has to be very long, much longer than anyone’s Ceteris paribus data. And the link between tax rates and R&D, which we saw recently, and here capex and tax rates, both harbingers of the future, are not encouraging that we can enjoy a free lunch in the long run. The notion of a progressive corporate tax rate that looks at returns above the cost of capital is intriguing in theory but hard to imagine how it would work in practice. This harkens back to my debate with Jan Eeckout. We can’t look at the one lucky success and tax their excess returns, if we want innovation to pay. If we want a logical tax system, we have to look at the returns of the one lucky firm divided by the cost of the entire pool of failure, or said differently, we have to discount a successful firm’s profits by its ex-ante probability of success. Good luck with that! Otherwise we are taxing the very thing we would like to avoid taxing—excess returns to innovations that are large enough to make a difference to our growth. Moreover, those are the very firms that expose our most productive workers to the technological frontier, which is critical increase the probability of producing successful innovation. And we have to treat international competitors differently, if they can’t pass their higher tax rates on to customers when competitors have lower rates in other countries."

Steve Comment: Time Frame Is 2005-2017 (Repealed By TCJA)

  • Productivity
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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…
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  • 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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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.

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  • 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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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.

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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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