Edward Conard

Top Ten New York Times Bestselling Author

  • “…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 must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…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 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
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Monday, September 28, 2026

AI Summary. Foreign investors made a record $942bn in net purchases of US stocks and investment fund shares over 12 months, the highest rolling 12-month total in Treasury data going back to 1985. Foreign demand for US debt securities moved in the opposite direction, falling to a net $188bn in the second quarter from $314bn in the first.

Michael Taffe and George Steer Financial Times
Date Posted:
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Foreign investors bought a record net $426B of US equities and fund shares in Q2, up 62% y/y, part of a record $942B in the 12 months through July. Overseas investors bought a net $188B of US debt securities in Q2, down from $314B in Q1.

Are foreign investors shifting from US debt into US stocks?

Core argument: Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, the highest rolling 12-month total in Treasury data going back to 1985.

Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, accelerating a shift in overseas investment towards American stocks and away from debt. The flows represented the highest rolling 12-month total in Treasury data going back to 1985. Net purchases of US equities and investment fund shares by foreign investors jumped to $426bn in the second quarter, up 62% from the same period in 2025, and surpassing the previous quarterly record of $299bn in 2022, according to the Bureau of Economic Analysis. Foreign demand for US debt moved in the opposite direction. Overseas investors bought a net $188bn of US debt securities in the second quarter, down from $314bn in the first.

Takeaways by Macro Roundup® AI

  1. Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, the highest rolling 12-month total in Treasury data going back to 1985.
  2. Net foreign purchases of US equities and investment fund shares reached $426bn in the second quarter, up 62% from the same period in 2025 and above the prior quarterly record of $299bn in 2022, according to the Bureau of Economic Analysis.
  3. Overseas investors bought a net $188bn of US debt securities in the second quarter, down from $314bn in the first.

Related Articles:

  • World’s Unusually High Dollar Exposure Risks Fueling Selloff — Pension funds and insurers in Canada, Denmark, Australia, Taiwan, Japan and Finland hedged just 41% of their foreign-currency exposure, the lowest share since at least 2015. With some of the largest holders of US assets carrying little protection against a weaker dollar, the currency is at risk of steeper declines if sentiment turns.
  • Foreign Investors Prefer US Stocks To Treasuries As Debt Worries Grow — International flows into US stocks averaged 2.8% of US GDP over a year, overtaking flows into US Treasuries at 2% of GDP for the first time this century outside brief episodes during the Covid-19 pandemic and after the global financial crisis, according to Deutsche Bank analysis of US Treasury data.
  • A Catalyst For The AI Bubble Break — Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.

AI Summary. The author argues that a slowdown in artificial-intelligence capital spending would remove a stimulus that has been masking weakness, colliding with overcapacity, falling prices, refinancing needs and weaker labor income. On this view the main risk is deflationary, transmitting through investment, employment, consumption, credit, housing and asset prices at once.

Paul Kedrosky Applied Complexity
Date Posted:

Kedrosky argues that the “inevitable transition” from the current inflationary AI-buildout regime to a new regime in which AI-driven productivity gains exert deflationary pressure is “where the real macro risk lies.”

Would an AI spending slowdown create deflationary rather than inflationary risk?

Core argument: The author argues the dangerous phase arrives when the AI capex boom slows, removing stimulus just as overcapacity, falling prices, refinancing needs and weaker labor income hit together, with a refinancing wall waiting in 2028.

If AI investment has been masking underlying weakness, a slowdown removes the stimulus just as overcapacity, falling prices, refinancing needs and weaker labor income hit together. A refinancing wall sits waiting in 2028. Failure is over-determined. This moment sits at the intersection of the four forces that have produced the most consequential boom-bust cycles in Western economic history: loose credit, government policy, technology, and real estate. There are, as a result, myriad catalysts, each with a low probability of happening, but which collectively guarantee collapse. That is why the principal risk is deflationary rather than inflationary. An AI bust could transmit through capex, employment, consumption, credit, housing, and asset prices simultaneously.

Takeaways by Macro Roundup® AI

  1. The author argues the dangerous phase arrives when the AI capex boom slows, removing stimulus just as overcapacity, falling prices, refinancing needs and weaker labor income hit together, with a refinancing wall waiting in 2028.
  2. The principal risk from an AI bust is deflationary rather than inflationary, according to the author, because it could transmit simultaneously through capex, employment, consumption, credit, housing, and asset prices.
  3. The author places this moment at the intersection of loose credit, government policy, technology, and real estate — the four forces behind the most consequential boom-bust cycles in Western economic history — and sees a plausible decade of Japan-style balance recession with fiscal stimulus constrained by massive deficits.

Related Articles:

  • Financing the AI Buildout — The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
  • A Catalyst For The AI Bubble Break — Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.
  • AI Set to be Largest CapEx Cycle Ever … and Soon Majority Externally Financed — Hyperscaler and data-center investment is tracking toward $1.5tn annually by 2030, which in real terms would exceed the 2005-06 housing boom, the 1990s fiber peak, and the 1882 railroad peak combined. External debt and equity are projected to fund close to 90% of the buildout, making it dependent on credit markets.

AI Summary. An analysis estimates that for US data center owners to break even on AI investments, the sector would need about $3.725tn in annual compute revenue by 2032 — roughly 9.2% of projected 2032 GDP. The estimate assumes 183 GW of US capacity completed, a $9.61tn capital base, a 10% discount rate, and a 50% operating cash flow margin.

Hanno Lustig The Two Cents
Date Posted:
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The US AI-buildout is projected to average ~3.6% of GDP over 2025–32. Lustig notes data-center operators will need ~$3.725T in annual compute revenue by 2032, 9.2% of projected GDP, to earn a 10% unlevered return on the buildout.

How much annual revenue must AI data centers generate to break even?

Core argument: Stijn’s baseline estimate holds that data center owners would need $3.725 trillion of annual revenue by 2032 — roughly 9.2% of projected 2032 GDP — to break even on AI investment at a 10% discount rate.

What do you have to believe about future revenue in order for all data center owners to to break even on their AI investment? Using a 10% discount rate, Stijn’s baseline number is 3.725 trillion of annual revenue by 2032, which would amount to roughly 9.2% of projected 2032 GDP. This number is the top line earned from selling compute in aggregate by whoever operates the 182.7 GW of US capacity completed by 2032.2. The assumptions behind that number: 183 GW of U.S. data-center capacity completed between 2025 and 2032. $8.54 trillion of construction cost, grossed up to a $9.61 trillion capital base to account for the return on capital tied up during construction. A 10% discount rate. A 6-year life for IT equipment (68% of cost) and a 20-year life for everything else (32%). A 50% operating cash flow margin.

Takeaways by Macro Roundup® AI

  1. Stijn’s baseline estimate holds that data center owners would need $3.725 trillion of annual revenue by 2032 — roughly 9.2% of projected 2032 GDP — to break even on AI investment at a 10% discount rate.
  2. The break-even calculation assumes 183 GW of U.S. data-center capacity completed between 2025 and 2032 at $8.54 trillion of construction cost, grossed up to a $9.61 trillion capital base for return on capital tied up during construction.
  3. The estimate assumes a 6-year life for IT equipment, which accounts for 68% of cost, a 20-year life for the remaining 32%, and a 50% operating cash flow margin.

Related Articles:

  • Financing the AI Buildout — The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
  • A Catalyst For The AI Bubble Break — Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.
  • Rear Window — Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.

AI Summary. Because investors can buy bonds across borders, an investment boom in one country such as the United States can draw in loanable funds from abroad and push up interest rates in other nations. The linkage is not one-for-one, since investors also weigh expected exchange-rate changes and the resulting capital gains or losses.

Paul Krugman Krugman Wonks Out
Date Posted:

The nominal 10-year Treasury yield is ~ where it was during the mid-2000s housing boom, but below its level during the late-1990s and early-2000s technology boom. Krugman asks, “If we’re now looking at an even bigger investment boom, why wouldn’t we expect to see interest rates at least that high?”

Does an investment boom in one country raise interest rates abroad?

Core argument: Because investors can buy bonds across borders, an investment boom in the United States draws loanable funds from other nations and pushes their interest rates up as well.

Investors can buy bonds across borders, so an investment boom in the United States can draw in loanable funds from other nations and drive up their interest rates. The international linkage between interest rates isn’t always one-for-one. That’s mainly because investors deciding which nation’s bonds to buy don’t just look at interest rates -- they also take into account expected changes in exchange rates. For example, there was a sharp rise in U.S. interest rates in the early 1980s that was only partially matched by a rise in German rates. The reason was that this was also a period of an extremely strong dollar, which many investors believed (correctly) would prove temporary. So German investors buying U.S. bonds had to set the high interest rates they could earn against the capital losses they were likely to experience when the dollar came back to earth.

Takeaways by Macro Roundup® AI

  1. Because investors can buy bonds across borders, an investment boom in the United States draws loanable funds from other nations and pushes their interest rates up as well.
  2. The international linkage between interest rates is not always one-for-one, mainly because investors choosing among nations’ bonds weigh expected exchange rate changes alongside interest rates.
  3. The sharp rise in U.S. interest rates in the early 1980s was only partially matched by German rates, as German investors buying U.S. bonds set high yields against likely capital losses when the strong dollar fell back.

Related Articles:

  • Financing the AI Buildout — The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
  • America’s Risky Debt: What Markets See That Policymakers Don’t — Two market-based measures suggest the safety premium investors pay to hold US Treasuries has compressed toward zero and at times reversed: the spread between top-rated corporate bonds and Treasuries after stripping out default risk, and the gap between currency-hedged foreign G10 government yields and Treasury yields at the same maturity, where longer-maturity comparisons now favor foreign bonds.
  • Don’t Draw The Wrong Conclusion From Treasury Yields — Ten-year real yields equal the average expected overnight rate over the next decade plus a term premium, and fiscal credibility or debt sustainability concerns would show up as a higher term premium. With the term premium and inflation expectations contained, the increase in bond yields reflects higher expected long-term overnight rates.

AI Summary. China has extended travel restrictions on top artificial intelligence and chip talent to their spouses and children, who must now obtain government approval before going abroad even for short trips. The requirement broadens existing curbs on the movement of influential technology entrepreneurs, researchers and executives.

Bloomberg Staff Bloomberg
Date Posted:

Beijing has expanded overseas travel restrictions for top AI professionals to include their families. While not an outright ban, foreign travel will now require state approval.

Is China extending travel approval requirements to tech talent's families?

Core argument: China now requires spouses and children of certain AI and chip executives whose work is deemed paramount to state security to obtain Beijing’s approval before traveling abroad, even for short trips, according to people familiar with the matter.

Government agencies have recently begun to share the wider restrictions with affected people, which include prominent startup founders as well as the heads of strategically important companies in AI-related fields. Direct relatives such as spouses and children of certain AI and chip executives, whose work is considered paramount to state security, are now required to obtain approval from Beijing before going abroad even for short trips. That marks a broadening of existing curbs on the freedom of movement of China’s most influential tech talent. While not an outright ban on travel, the new requirement is likely to exert a further chilling effect on a tech sector already facing unprecedented curbs. China has restricted foreign travel for top AI professionals in private firms such as Alibaba and DeepSeek since earlier this year.

Takeaways by Macro Roundup® AI

  1. China now requires spouses and children of certain AI and chip executives whose work is deemed paramount to state security to obtain Beijing’s approval before traveling abroad, even for short trips, according to people familiar with the matter.
  2. The restrictions extend to prominent startup founders and heads of strategically important companies in AI-related fields, broadening existing curbs on the movement of China’s entrepreneurs, researchers and executives.
  3. China has restricted foreign travel for top AI professionals at private firms such as Alibaba and DeepSeek since earlier this year, and the new family requirement is likely to exert a further chilling effect on the tech sector.

Related Articles:

  • Who’s Ahead in the Global AI Talent Race? — An analysis of authors at a leading AI research conference finds China is the largest originating source of elite AI talent, with its share of researchers holding Chinese undergraduate degrees rising 11 percentage points to 57%, while the US share fell to 13%. The US remains a net importer of AI researchers, gaining 2,145 while China lost 1,729.
  • China Tightens Control Of Overseas Travel In Sweeping New Law — China has imposed new legal controls on overseas travel that formalise restrictions on mid-to-senior civil servants, Communist Party cadres, state-owned enterprise employees, and private citizens working in sensitive areas, as part of efforts to protect state secrets, advanced technology, and highly skilled workers. Violators face steep fines and exit bans ranging from three months to indefinite.
  • The Future, Made In China — China's economy runs on parallel tracks: a property crash, a booming high-tech manufacturing sector, and university graduates trained for traditional white-collar jobs entering a labor market geared toward advanced manufacturing. Researchers at Stanford and Harvard found a swing from optimism to pessimism, with about 28% of citizens expecting living standards to improve.

AI Summary. China faces three options as external demand weakens: shift a larger share of national income to households so consumption absorbs more output, keep relying on investment despite weak returns, or let production and growth slow. The first requires substantial changes in income distribution and saving incentives; the second risks more debt and excess capacity; the third implies higher unemployment.

Michael Pettis China Financial Markets
Date Posted:

“Beijing cannot choose whether China will adjust; one way or another, it will.” Pettis warns Zhongnanhai against postponing rebalancing with another round of debt-financed investment “despite increasingly weak returns.”

What choices does China face as external demand weakens?

Core argument: China faces three options: shift a larger share of national income to households so consumption absorbs more output, keep relying on investment despite weak returns, or allow production and growth to slow.

What it can choose is how painful that adjustment will be. If weaker external demand is met by encouraging more borrowing and domestic investment, regardless of whether that investment is economically justified, China risks postponing the inevitable. China therefore faces the same basic choice Japan confronted, but with deeper imbalances and less accommodating global conditions. It can shift a larger share of national income toward households and allow consumption to absorb more of what the economy produces; or it can continue relying on investment, despite increasingly weak returns; or it can allow production and growth to slow. The first choice requires a substantial change in the domestic distribution of income and the incentives to save. The second risks still more debt and excess capacity and, ultimately, a more painful adjustment. The third implies higher unemployment and weaker growth.

Takeaways by Macro Roundup® AI

  1. China faces three options: shift a larger share of national income to households so consumption absorbs more output, keep relying on investment despite weak returns, or allow production and growth to slow.
  2. China confronts the same basic choice Japan faced, but with deeper imbalances and less accommodating global conditions, and can choose only how painful the adjustment will be.
  3. Meeting weaker external demand with more borrowing and domestic investment, regardless of whether it is economically justified, risks further debt and excess capacity and a more painful adjustment, while slower growth implies higher unemployment.

Related Articles:

  • The Year of the Trojan Fire Horse: China’s Imbalanced Economy and Unrelenting Mercantilism — About 30% of Chinese industrial companies are unprofitable "zombies" kept alive by subsidies far larger than those elsewhere, rather than exiting amid falling industrial producer prices. Countries with large increases in manufactured imports from China also saw slowdowns in domestic manufacturing, including declining manufacturing shares of output across most of Southeast Asia.
  • Sticking with What Works: Raising GDP Forecast on China’s Manufacturing Push — Stronger Chinese growth driven by export-oriented manufacturing may not produce net positive spillovers: for every 1pp export-driven boost to China's GDP, other economies may see a 0.1–0.3pp drag, with high-tech producers such as Europe and Japan facing greater pressure. Cheaper Chinese goods continue to exert a disinflationary impulse.
  • Record Influx Of University Graduates Pushes China’s Youth Unemployment Rate To 18.9% — China's urban unemployment rate for 16- to 24-year-olds excluding students reached 18.9%, the highest since the statistics agency revised its methodology to exclude students. A record influx of university graduates is entering a job market weighed down by weak domestic demand and growing adoption of artificial intelligence.

Tuesday, September 29, 2026

AI Summary. An expanded unemployment measure for young college graduates — including those outside the labor force who report wanting a job — averaged 10.4% in the most recent summer, the highest of the five summers compared and 0.3 percentage points above the prior high. Estimated associations with occupational AI exposure are positive but not statistically significant.

Robert Fairlie and Jane Wu National Bureau of Economic Research
Date Posted:

For American college graduates aged 22 to 25 and not in school, summer unemployment was 7.3% in 2026, versus 7.1%, 6.3%, 7.8%, and 7.2% in 2022–25. These are ordinary seasonal peaks, with no evidence of an upward trend. A broader measure tells a similar story.

Is AI raising unemployment among recent college graduates?

Core argument: On the expanded unemployment measure including “sidelined” young college graduates, the June–August average was 10.4% in 2026, compared with 9.4% in 2022, 9.3% in 2023, 10.1% in 2024 and 9.4% in 2025.

Figure 2b displays the seasonal comparison for our expanded unemployment measure, which includes young college graduates who are “sidelined,” those not officially defined as being in the labor force but nonetheless report “wanting a job.” Averaging over June, July and August, the expanded measure was 10.4% in 2026, compared with 9.4% in 2022, 9.3% in 2023, 10.1% in 2024 and 9.4% in 2025. Summer 2026 is the highest of the five summers under this definition, although it exceeds the previous high by only 0.3 percentage points. The expanded measure thus indicates a larger increase relative to 2025, while also showing that high rates in the summer are not unique to 2026. The coefficient estimates of interactions between summer 2026 and both measures of occupational AI exposure are positive, but not statistically significant. The point estimate of the interaction with occupational teleworkability is positive but difficult to separate cleanly from AI exposure (Tables 4-6).

Takeaways by Macro Roundup® AI

  1. On the expanded unemployment measure including “sidelined” young college graduates, the June–August average was 10.4% in 2026, compared with 9.4% in 2022, 9.3% in 2023, 10.1% in 2024 and 9.4% in 2025.
  2. Summer 2026 is the highest of the five summers on the expanded measure but exceeds the prior high by only 0.3 percentage points, indicating high summer rates are not unique to 2026.
  3. Coefficient estimates of interactions between summer 2026 and both measures of occupational AI exposure are positive but not statistically significant, and the positive point estimate for occupational teleworkability is difficult to separate cleanly from AI exposure.

Related Articles:

  • Graduating into Disruption: Labor Market Outcomes for AI-Exposed College Majors — College graduates in the majors most exposed to artificial intelligence show statistically significant employment declines following the arrival of AI chatbots, with the most-exposed 10% of majors down about 5 percentage points and the seventh and eighth deciles down about 2 points. The authors note flat pre-2020 trends and precise timing argue against alternative explanations such as uneven post-pandemic recovery.
  • The Jobs Apocalypse Is Postponed. An AI Jobs Boom Is Here — Employment in five industries tied to the data-centre build-out, including electrical contracting and equipment manufacturing, has risen roughly 320,000 above what broader construction and manufacturing trends would suggest. Engineers, software developers, mathematicians and data scientists have added about 730,000 jobs above the trend for professional employment overall.
  • Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence — Employment for workers aged 22–25 in the occupations most exposed to artificial intelligence has declined roughly 18pp relative to less-exposed peers, with no comparable decline in other age groups. The authors find this operates mainly through reduced hiring, concentrated where AI substitutes for human tasks rather than complements them.

AI Summary. Wall Street analysts covering technology project the sector's operating cash flow will more than double to roughly $2.4tn by 2028, a gain of over $1.2tn, while analysts covering the rest of the S&P 500 — technology's customers — project those firms will add far less cash flow. These sector-by-sector forecasts are internally inconsistent.

Torsten Sløk Apollo
Date Posted:
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Tech analysts expect sector operating cash flow to more than double to ~$2.4T by 2028. Analysts covering other S&P 500 sectors (tech’s customers) see far less cash growth in their sectors. Slok “raises the question of who exactly will be writing all those checks to buy AI services.”

Are tech cash flow forecasts inconsistent with customers' projected growth?

Core argument: Analysts covering the tech sector expect its operating cash flow to more than double to roughly $2.4tn by 2028, an increase of over $1.2tn.

Wall Street equity analysts work in sector silos, and when you add up their forecasts, the numbers are internally inconsistent. The analysts covering tech expect the sector's operating cash flow to more than double to roughly $2.4 trillion by 2028, an increase of over $1.2 trillion. Meanwhile, the analysts covering the other sectors in the S&P 500, which are tech's customers, expect those companies to add much less operating cash flow. In other words, the tech silo is betting on a future in which demand for AI and tech services explodes, while the silos covering the companies that would pay for those services see a much more modest outlook. Both cannot be right at the same time. The bottom line is that either tech's customers will generate a lot more cash than their analysts expect, or tech's cash flow forecasts are too optimistic, which raises the question of who exactly will be writing all those checks to buy AI services.

Takeaways by Macro Roundup® AI

  1. Analysts covering the tech sector expect its operating cash flow to more than double to roughly $2.4tn by 2028, an increase of over $1.2tn.
  2. Analysts covering the other S&P 500 sectors, which are tech's customers, expect those companies to add much less operating cash flow, leaving the combined forecasts internally inconsistent.
  3. Either tech's customers will generate much more cash than their analysts expect, or tech's cash flow forecasts are too optimistic, which raises the question of who will pay for AI services.

Related Articles:

  • A Catalyst For The AI Bubble Break — Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.
  • Financing the AI Buildout — The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
  • Rear Window — Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.

AI Summary. The Congressional Budget Office projects that if interest rates rose to 1 percentage point above its baseline, federal debt held by the public would reach 222% of GDP by 2056, 47 percentage points above baseline, with primary deficits averaging 2.3% of GDP and annual growth 0.1 percentage point slower.

CBO Staff Congressional Budget OffIce
Date Posted:
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Database

If interest rates rise 1pp above CBO’s current extended baseline (a mean rate of 4% over 2026–2056), CBO projects federal debt held by the public will be 222% of GDP in 2056, versus 175% under the current baseline.

How much would higher interest rates raise projected federal debt?

Core argument: CBO projects that under a scenario in which interest rates rise to 1 percentage point above its extended baseline, debt held by the public would reach 222% of GDP in fiscal year 2056, 47 percentage points above the extended baseline.

Under a scenario in which interest rates increased until they were 1 percentage point higher than in CBO’s extended baseline, primary deficits—that is, deficits excluding net outlays for interest—would average 2.3% of GDP over the 2026–2056 period, 0.2 percentage points larger than in the extended baseline. Debt held by the public would grow to 222 percent of GDP in fiscal year 2056, 47 percentage points larger than in the extended baseline. Average annual GDP growth over the 2026–2056 period would be 0.1 percentage point slower than in CBO’s extended baseline, and the average interest rate on federal debt would be 0.7 percentage points higher.

Takeaways by Macro Roundup® AI

  1. CBO projects that under a scenario in which interest rates rise to 1 percentage point above its extended baseline, debt held by the public would reach 222% of GDP in fiscal year 2056, 47 percentage points above the extended baseline.
  2. Primary deficits, which exclude net outlays for interest, would average 2.3% of GDP over 2026–2056 in CBO’s higher-interest-rate scenario, 0.2 percentage points larger than in its extended baseline.
  3. Under CBO’s higher-interest-rate scenario, average annual GDP growth over 2026–2056 would be 0.1 percentage point slower and the average interest rate on federal debt 0.7 percentage points higher than in its extended baseline.

Related Articles:

  • The Budget and Economic Outlook: 2026 to 2036 — The Congressional Budget Office projects the federal deficit will grow from $1.9tn (5.8% of GDP) to $3.1tn (6.7%) over a decade, above the 3.8% averaged over the past 50 years, with rising net interest costs driving much of the increase. Federal debt held by the public is projected to rise from 101% to 120% of GDP.
  • How Might Fiscal Policy Respond to the Rise of Artificial Intelligence? — The Congressional Budget Office estimates that a permanent 0.5 percentage point increase in annual productivity growth would lower publicly held federal debt after 30 years by 39% of GDP, offsetting roughly half the projected rise from 101% of GDP to 175%. Higher revenue and slower spending growth outweigh higher interest costs.
  • Soaring Bond Yields, Gaping Deficits and Towering Debts: What Could Go Wrong? — An analysis of 22 rich countries estimates that if each refinanced its entire debt at current five-year bond yields, Britain would need the largest primary surplus to stabilize its debt-to-GDP ratio, about 1.5%, followed by Italy at 1.4%, France at 1.2% and America at 1%.

AI Summary. The US 30-year Treasury yield surpassed 5.59%, a level last seen in 2002, amid a selloff across global debt markets, while the 10-year yield at 5.24% reached its highest since 2007 and two-year yields sat near 4.9%. A Bloomberg gauge shows Treasuries have lost 2.6% this year after a 6.3% gain the prior year.

Sydney Maki Bloomberg
Date Posted:

The US 30-year Treasury yield hit 5.61%, its highest level since 2002. The US 10-year Treasury yield rose to 5.281%.

Are long-term Treasury yields reaching their highest levels in decades?

Core argument: The US 30-year Treasury yield surpassed 5.59% to reach its highest level since 2002, rising for a sixth straight day amid a deepening selloff across global debt markets.

Yields on the US Treasury’s longest-dated bond rose for a sixth straight day, crossing another key threshold amid a deepening selloff across global debt markets. The 30-year rate surpassed 5.61% to touch a level last seen in 2002, in the wake of the dot-com bust. Treasuries have lost 2.6% so far this year, a Bloomberg gauge shows, compared with a 6.3% gain last year. And the selloff has hit debt across maturities, with the 10-year yield, at 5.281%, trading at its highest since 2007. Two-year yields are at about 4.9%, the last major maturity to linger below 5%.

Takeaways by Macro Roundup® AI

  1. The US 30-year Treasury yield surpassed 5.59% to reach its highest level since 2002, rising for a sixth straight day amid a deepening selloff across global debt markets.
  2. The 10-year Treasury yield hit 5.24%, its highest since 2007, while two-year yields stood at about 4.9%, the last major maturity below 5%.
  3. Treasuries have lost 2.6% so far this year on a Bloomberg gauge, compared with a 6.3% gain last year.

Related Articles:

  • America’s Risky Debt: What Markets See That Policymakers Don’t — Two market-based measures suggest the safety premium investors pay to hold US Treasuries has compressed toward zero and at times reversed: the spread between top-rated corporate bonds and Treasuries after stripping out default risk, and the gap between currency-hedged foreign G10 government yields and Treasury yields at the same maturity, where longer-maturity comparisons now favor foreign bonds.
  • Booms, Bombs and Bonds: Interest Rates, Part I — Because investors can buy bonds across borders, an investment boom in one country such as the United States can draw in loanable funds from abroad and push up interest rates in other nations. The linkage is not one-for-one, since investors also weigh expected exchange-rate changes and the resulting capital gains or losses.
  • Don’t Draw The Wrong Conclusion From Treasury Yields — Ten-year real yields equal the average expected overnight rate over the next decade plus a term premium, and fiscal credibility or debt sustainability concerns would show up as a higher term premium. With the term premium and inflation expectations contained, the increase in bond yields reflects higher expected long-term overnight rates.

AI Summary. U.S. survey data on high school students show the share of 9th graders identifying as lesbian, gay, or bisexual fell from 17% to 11% over two years, compared with a decline from 18% to 16% among 12th graders. The drop was concentrated among girls, from 27% to 22%, versus 9% to 7% among boys.

Jean Twenge Generation Tech
Date Posted:
Is Database:
Database

Among US high-school students, the LGB share fell btw 2023 to 2025 by 5pp for girls (27% to 22%), and 2pp for boys (9% to 7%). The preceding rise was likewise larger for girls: +128% from 2015 to 2021, versus +99% for boys to 2023.

Are younger teens less likely to identify as lesbian, gay, or bisexual?

Core argument: The share of U.S. 9th graders identifying as lesbian, gay, or bisexual fell from 17% in 2023 to 11% in 2025 in the CDC’s Youth Risk Behavior Survey, while 12th graders declined from 18% to 16%.

[New data from the Youth Risk Survey of U.S. 9th to 12th graders from the CDC shows] for 12th graders, 17 and 18 years old, identifying as LGB declines only a few percentage points between 2023 and 2025 (from 18% to 16%). But the headline result is for 9th graders (14 and 15 years old): Identifying as LGB absolutely plummets between 2023 and 2025, from 17% to 11%. That really does look like a free fall. The decline appears to be driven almost entirely by girls. Identifying as LGB dropped from 27% in 2023 to 22% in 2025 among girls, and from 9% to 7% among boys. [In terms of the share of high school students reporting engaging in same-sex activity] most high school students are not sexually active, so this is only a subsample of the larger group. For boys, there’s been a fairly steady rise in same-sex partners, not too different from the pattern of identifying as LGB among boys. The story is different for girls, where having non-heterosexual sex peaked in 2021 and then fell steeply.

Takeaways by Macro Roundup® AI

  1. The share of U.S. 9th graders identifying as lesbian, gay, or bisexual fell from 17% in 2023 to 11% in 2025 in the CDC’s Youth Risk Behavior Survey, while 12th graders declined from 18% to 16%.
  2. The decline appears driven almost entirely by girls, whose LGB identification fell from 27% in 2023 to 22% in 2025, compared with a drop from 9% to 7% among boys.
  3. Among sexually active teens, the share of boys reporting at least one same-sex partner has risen fairly steadily, while for girls it peaked in 2021 and then fell steeply.

Related Articles:

  • Is There Really a Generational Difference in Identifying as Lesbian, Gay, or Bisexual? — General Social Survey data show that increases among young American adults appear in same-sex sexual behavior as well as in identification, with 20% reporting a same-sex partner versus 18.5% identifying as lesbian, gay, or bisexual. The increases are larger among 27- to 41-year-olds.
  • Teens Used To Be Happier. What Changed? — The share of US high school seniors describing themselves as "very happy" peaked at 24.8% and remained around 24.4% before falling to 11.4% at its low, recovering only to 12.7%, well below the 17.9% recorded before the pandemic. The decline coincided with smartphones and social media becoming pervasive.
  • US College Students’ Well-Being — A study of US college students finds moderate-to-severe depression reported by 26% of students at one elite institution, 22% reporting moderate-to-severe anxiety and 10% contemplating suicide. Poorer mental health is associated with being female, little exercise, low grades, and financial aid; financial stress is associated with higher suicidal thoughts.

AI Summary. US defense contractors face a coming requirement to remove certain metals sourced from China and other adversary countries from their supply chains, which many contractors say isn't feasible, while some Pentagon officials target a "closed loop" of US and allied supply for some minerals by 2030.

Heather Somerville and Andrew Mollica Wall Street Journal
Date Posted:

CRU, a UK commodities-data provider, projects China will lose market share in many of the elements and minerals it has most tightly controlled by 2030, with the exception of cobalt.

Can defense contractors remove Chinese-sourced critical minerals from supply chains?

Core argument: U.S. defense contractors will be required by next year to eliminate certain metals sourced from adversary countries including China, a requirement many contractors say isn’t feasible despite the progress being made.

By next year, U.S. defense contractors will be required to eliminate from their supply chain certain metals sourced from adversary countries including China, a requirement that many contractors say isn’t feasible despite the progress being made. Some Pentagon officials say they are aiming for a “closed loop” of U.S. and allied supply chains for some minerals by 2030. In April, Deputy U.S. Trade Representative Rick Switzer said that with help from Japan and Europe, the U.S. has the capacity to develop an end-to-end critical-minerals supply chain free of China within six to 12 months, if the country were pressed to do so. Recent projections from CRU, a London-based commodities-data provider, show China losing market share by the end of the decade in many of the elements and minerals it had most tightly controlled.

Takeaways by Macro Roundup® AI

  1. U.S. defense contractors will be required by next year to eliminate certain metals sourced from adversary countries including China, a requirement many contractors say isn’t feasible despite the progress being made.
  2. Deputy U.S. Trade Representative Rick Switzer said in April that, with help from Japan and Europe, the U.S. has the capacity to develop an end-to-end critical-minerals supply chain free of China within six to 12 months if pressed to do so.
  3. Projections from CRU, a London-based commodities-data provider, show China losing market share by the end of the decade in many of the elements and minerals it had most tightly controlled, while some Pentagon officials aim for a “closed loop” of U.S. and allied supply chains for some minerals by 2030.

Related Articles:

  • China Restricts Trading With Some US Rare Earth Companies — China has added 10 American companies to its "entities list," restricting trading with firms central to US efforts to build a rare earth supply chain rivaling Beijing's, including USA Rare Earth, MP Materials, and motor manufacturer Aveox.
  • How to Fight an Economic War — China earned about $3.4bn from exporting rare-earth elements and magnets in a year, while the U.S. Geological Survey estimates a 30% disruption to U.S. supply of the rare-earth element neodymium alone would cut U.S. GDP by 2.2%, over $600bn. This asymmetry gives Chinese export controls their leverage.
  • How Japan Built a Rare-Earth Supply Chain Without China — Japan has reduced its reliance on Chinese rare earths, with industry estimates putting China's share of Japanese rare-earth imports at roughly 60% to 70%, down from 90% or more. Japan's alternative chain runs from an Australian open-pit mine through a separation plant in Malaysia to Japanese magnet makers supplying automakers.