Edward Conard

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  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “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
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…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
  • “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
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  • “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
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
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When Investment Gets Real (and Netted)

Cardiff Garcia FT Alphaville
Date Posted:
August 11, 2014
Is Database:
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Real investment is 18% cheaper relative to GDP and 20% cheaper relative to consumption goods than in 1970.

Real investment is 18% cheaper relative to GDP and 20% cheaper relative to consumption goods than in 1970.
The cost of real investment has decreased significantly, with a unit of real investment now 18% cheaper relative to GDP and 20% cheaper relative to consumption goods compared to 1970. This trend is driven by a dramatic fall in prices for non-construction investment goods compared to construction investment goods. From 1970-2013, the investment deflator grew at an average of 3.3% per year, slower than the GDP and PCE deflators, which grew at 3.7% and 3.8%, respectively. Despite these price trends, real net non-construction investment as a share of GDP has not shown a rising long-term trend, indicating that while gross investment data appears optimistic, net figures reveal a more nuanced picture. This suggests that while investment goods have become cheaper, the impact on real net investment growth is less pronounced due to high depreciation rates in non-construction sectors.

"...These differences imply that a unit of real investment is now 18 percent cheaper relative to a unit of GDP than in 1970 and 20 percent cheaper relative to a unit of consumption goods. Within the category of investment, prices for non-construction investment goods have fallen quite dramatically relative to those for construction investment goods (Figure 10)....These differences imply that a unit of real investment is now 18 percent cheaper relative to a unit of GDP than in 1970 and 20 percent cheaper relative to a unit of consumption goods. Within the category of investment, prices for non-construction investment goods have fallen quite dramatically relative to those for construction investment goods (Figure 10)...."When investment gets real (and netted)Cardiff GarciaLearn moreFollow @cardiffgarcia

This entry was posted byCardiff Garciaon Monday August 11th, 2014 18:40. Tagged withUS Economy. Garcia, Cardiff, "When Investment Gets Real (and Netted)," FT Alphaville, August 11, 2014. Available at:http://ftalphaville.ft.com/2014/08/11/1918572/when-investment-gets-real-and-netted/

Expect plenty of debate on these matters for a long time to come. More inthe usual place.

Again, these are merely conjectures, and I didn’t even delve into the likely mismeasurements in the data or the role of policy throughout this period. Truthfully I’m not sure what’s going on and need to think about it more. Comments with alternative explanations would be appreciated.

Yet this doesn’t rule out the possibility that supply-side problems also have played a role. The IT improvements of the 1990s spread to other sectors as general-purpose technologies and contributed to widespread productivity acceleration. But once that process ran its course, productivity in these other sectors once again grew softly, as it has since the 1970s, even as these sectors’ relative share of the economy climbed:

Income inequality climbed and the labour share of income fell. The distributional outcomes were part of the problematic debt dynamics chronicled byAtif Mian and Amir Sufi, wherein broad-based growth instead was driven largely by middle- and lower-income households taking out debt against increasingly overvalued housing collateral. Then came the housing bust and the nightmarish cyclical collapse.

Hard to say. The impressive advancements in IT and heavily IT-using sectors were uniquely labour-saving, and they also were unpaired with the absorption of the displaced workers into good jobs in other sectors. (Globalisation alsoplayed a role.)

Given the continued deflation of IT goods, why didn’t the deepening resume? Why didn’t investment remain a larger share of the economyin real termsgiven that the goods were cheapening?

These are only guesses, but to start with the former, look again at Figure 13. There was a significant increase in the share of real, depreciation-adjusted, non-construction investment throughout the 1990s — representing significant capital deepening. But the progress reversed after the dot-com bubble burst:

Yet these investment trends could be consistent with elements ofboththe Secular Stagnation, which emphasizes a persistent demand shortfall, andthe supply-side productivity Great Stagnation idea.

The decline of the construction investment share, the inability of the economy to grow more strongly despite the technology-driven deflation of investment goods, and rising income inequality are all part of the Secular Stagnation thesis.

Ideally, companies would spend more of their cash either on new investment opportunities or on hiring people; expectations of strongernominaldemand growth in the future would help the chances of both. Such a development would also incentivise the riskier money managers to use less leverage, as unlevered return expectations would be higher.

Policymakers have spent the last six years seeking ways to disintermediate this relationship, both using regulatory tools and in some cases providing safer collateral directly. But a more fundamental macroeconomic fix is needed.

To explain the mechanism crudely, this pool contributed to the emergence of a financial system in which the repo desks at dealer banks acted as intermediaries between these cash pools seeking a safe money-like haven on one side; and aggressive, levered fixed-income investors (hedge funds, separate accounts, prop traders, absolute return bond funds, certain pension schemes, etc) on the other side. Among other uses, these investors channeled that leverage into securities financing.

In addition, the nominal trends do matter. The deflation in IT leaves big amounts of cash on the books of corporates. That cash is invested mainly for preservation. The steadily rising amount of this “leftover” money is one of the four new cash pools of the past two decades described in theexcellent paperby Zoltan Poszar thatwe coveredrecently. (The other three are the liquidity tranches of FX reserves managed by sovereigns, the cash managed by big institutional investors and asset managers, and the cash collateral reinvestment accounts of securities lenders.)

Is the secular decline in real construction investment as a share of GDP worrying? Is it just the natural consequence of an economy in which services increasingly are a bigger part? Maybe, though it also seems likely that part of this trend is being driven by changing demographics. As for the cyclical trend, the construction sector stillaccountsfor a large share of the remaining labour market slack.

All very interesting, though the right interpretation and policy conclusions remain unclear to me.

Cardiff here. The economists add that these trends are similar across the developed world.

All of this means that the data on real investment in the US look much healthier.In real terms, investment as a share of (real) GDP shows no sign of secular decline (Figure 11); and in particular, due to the price trends depicted in Figure 10, real non-construction investment shares appear to have secularly risen, doubling from roughly 6 percent in the early 1970s to above 12 percent in 2013 (Figure 12).

This is, in our view, an optimistic finding, considering that construction investment (especially residential) should, in theory, have less of an impact on potential growth than non-construction investment - due to the stronger technological propagation/spillover effects that typically come with investment in equipment and intellectual property.

Yet we should highlight that the real data shown in Figure 11 & Figure 12 measure investment in gross terms. Once depreciation is netted out, real investment trends look less optimistic, particularly for non-construction investment, where depreciation rates are the highest.

Indeed,real net non-construction investment as a share of (real) GDP doesn’t exhibit the rising long-term trend shown in Figure 12; but it also doesn’t appear to have secularly declined either (Figure 13).

These differences imply that a unit of real investment is now 18 percent cheaper relative to a unit of GDP than in 1970 and 20 percent cheaper relative to a unit of consumption goods. Within the category of investment, prices for non-construction investment goods have fallen quite dramatically relative to those for construction investment goods (Figure 10).

Figure 9 shows that the price deflator for investment goods has grown at a persistently slower rate than has the GDP deflator or the consumption deflator. From 1970-2013, the investment deflator grew by 3.3 percent per year on average, versus average yearly growth of 3.7 percent and 3.8 percent, respectively, for the GDP and PCE deflators.

From the note, emphasis ours, and click to enlarge the images:

So far, so unsurprising. More interesting is the outcome when the category-specific price deflators are applied.

They did find that the nominal decline of investment as a share of GDP was due to both construction and non-construction investment. But while the latter has been falling since the late 1990s, much of the recent decline in the share of nominal investment has been due to the former: in other words, to the housing bust.

In June, economists at Citi broke down the investment figures in the US and across advanced economies in three ways: real vs nominal, construction vs non-construction, and gross vs net of depreciation.

Most goods and services, of course, inflate rather than deflate over time, while deflation in IT allows companies to spend less of their money on this category without actually buying less of the IT goods. (A similar and related story can be told aboutdurable goods, whose component in the Personal Consumption Expenditure price index started deflating in the mid-1990s.)

A version of that question wasaskeda little while back by Matt Yglesias, who later built this chart (viaTyler Cowen) showing the decline in nominal IT investment in the United States as a share of nominal GDP:

Does the secular deflation of computers and related equipment skew the macroeconomic data on investment in the direction of irrelevance?

Cardiff writes mostly about US macroeconomic issues, with daily excursions into other topics about which he claim no expertise. Before Alphaville, Cardiff spent a little more than two years as a reporter at Dow Jones Financial News covering investment banking, asset management, and private equity. Along the way he has written freelance pieces on a variety of other topics from behavioural psychology to Muay Thai, the latter also being a personal interest that involves frequently getting kicked in the shins (and torso, and head).

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Previous articleJuly 24, 2014Household Balance Sheet Rebuilding after the Housing Bust and Great Recession: Evidence from Panel DataUS households showed limited balance sheet adjustments after the Great Recession, with debt reduction due to less new borrowing rather than increased repayment.Next articleAugust 16, 2014Secular stagnation: Facts, causes, and cures - a new Vox eBookNew Vox eBook by @CoenTeulings and @RichardBaldwin explores secular stagnation, a prolonged period of low economic growth, highlighting its causes and potential solutions.
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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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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  • 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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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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  • 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.
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