Edward Conard

Top Ten New York Times Bestselling Author

  • “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
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Wednesday, November 12, 2025

AI Summary. Global electricity demand is projected to rise roughly 40–50% by 2035, even though electricity currently accounts for only 21% of total final energy consumption worldwide. Electricity use by servers optimized for artificial intelligence is projected to rise fivefold by 2030, yet data centres are projected to account for less than 10% of global electricity demand growth through 2030.

Stéphanie Bouckaert, Christophe McGlade, Brent Wanner et al. International Energy Agency
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Global electricity demand is forecast to rise by 40–50% by 2035. Only 10% of this growth is due to AI. Coal demand, driven by power generation in India and China, is 2x its 2000 level, but will likely peak before 2035 as cleaner energy comes online.

How much will global electricity demand rise by 2035?

Core argument: The World Energy Outlook 2025 projects electricity demand rising around 40–50% by 2035, though electricity accounts for only 21% of total final consumption while serving sectors making up over 40% of the global economy.

Electricity rises by around 40% to 50% by 2035. End-use electrification already accounts for half of today’s global energy investment. For the moment, electricity accounts for only 21% of total final consumption globally, but it is the key source of energy for sectors accounting for over 40% of the global economy and the main source of energy for most households. Driven by surging data centre expansion, electricity consumption by AI-optimised servers increases fivefold by 2030, due to a doubling of total electricity consumption by data centres by 2030. [Yet] data centres account for less than 10% of global electricity demand growth between 2024 and 2030. Cooling is a rising source of electricity demand, led by developing economies. In [one scenario] income-driven air conditioning use adds around 330 GW to global peak demand by 2035, and higher temperatures add another 170 GW. Since 2000, coal has been the fastest growing fossil fuel in the global energy mix. Global coal demand has nearly doubled since then, and reached the record level of 6,090 million tonnes of coal equivalent (Mtce) in 2024, driven mainly by the use of coal to generate power in emerging market and developing economies, in particular China and India. Global coal demand peaks before 2030 and by 2035, demand is around 8% lower than 2024 levels.

Takeaways by Macro Roundup® AI

  1. The World Energy Outlook 2025 projects electricity demand rising around 40–50% by 2035, though electricity accounts for only 21% of total final consumption while serving sectors making up over 40% of the global economy.
  2. Electricity consumption by AI-optimised servers increases fivefold by 2030 as total data centre electricity use doubles, yet data centres account for less than 10% of global electricity demand growth between 2024 and 2030.
  3. Global coal demand nearly doubled since 2000 to a record 6,090 million tonnes of coal equivalent in 2024, driven mainly by power generation in emerging market and developing economies, particularly China and India, and peaks before 2030, sitting about 8% below 2024 levels by 2035.

Related Articles:

  • Economic Growth Now Depends on Electricity, Not Oil — Average annual electricity load growth reached 3% and is projected to continue at that rate for five years, with utilities raising expected peak demand for 2029 by 12%, or 101 gigawatts, driven by data centers, new factories, electric vehicles, heat pumps, and hydrogen production.
  • Heliocentrism — An energy use must be electrified before green grid electricity can decarbonize it, and while US grid decarbonization continues at a steady pace, the electricity share of final US energy consumption has grown little. Transmission line growth runs well below Department of Energy targets for 2030 and 2035, and transformer delivery times have stretched from 4–6 weeks to 2–3 years.
  • What’s Happening to Wholesale Electricity Prices? — Average US retail electricity prices have risen about 35% since 2020, while average wholesale electricity costs have nearly doubled, with wholesale prices far more volatile. Wholesale location marginal prices consist of energy generation costs (typically 80–90% of the total), transmission congestion, and transmission losses, with a price spike partly driven by a large rise in natural gas prices.

AI Summary. Global data center, AI infrastructure and related power buildout could cost over $5tn, requiring funding from every public capital market plus private credit, alternative capital providers and possibly governments. The largest cloud providers generate over $700bn of annual operating cash flow and reinvest roughly $500bn in capital spending, with about $300bn a year estimated to fund AI and data centers.

Tarek Hamid, C. Stephen Tusa, Jr., Harlan Sur, et al. J.P. Morgan
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JPM estimates that to meet an IRR hurdle of 10% on their forecast AI investment through 2030 would require ~$650B in annual revenue in perpetuity. That would be 58bps of global GDP, or $34.72/month from every current iPhone user.

How will a five-trillion-dollar AI infrastructure buildout be financed?

Core argument: Global data center, AI infrastructure and related power buildout could cost over $5 trillion in the authors' view, requiring funding from every public capital market plus private credit, alternative capital providers and government involvement.

Building out global data center and AI infrastructure and related power supplies could cost over $5 trillion in our view. Funding that extraordinary growth will likely require participation from every public capital market as well as private credit, alternative capital providers and even government involvement. Hyperscaler cash flow will have to do an enormous amount of the heavy lifting. Hyperscalers are generating over $700 billion of operating cash flow per annum, and reinvesting ~$500 billion of that back into capex. Note that ~$500 billion of reinvestment back into the collective businesses does not include ~$250 billion of research and development spending per year. We are assuming approximately $300 billion per year of hyperscaler capex reflects cash flow funded AI and data center capex (while AI is crowding out a lot of spending, it's not crowding out all spending). To drive a 10% return on our modeled AI investments through 2030 would require ~$650 billion of annual revenue into perpetuity, which is an astonishingly large number. But for context, that equates to 58bp of global GDP, or $34.72/month from every current iPhone user, or $180/month from every Netflix subscriber.

Takeaways by Macro Roundup® AI

  1. Global data center, AI infrastructure and related power buildout could cost over $5 trillion in the authors' view, requiring funding from every public capital market plus private credit, alternative capital providers and government involvement.
  2. Hyperscalers generate over $700 billion of operating cash flow per year and reinvest roughly $500 billion into capex, separate from about $250 billion of annual research and development spending, with roughly $300 billion of that capex assumed to fund AI and data centers.
  3. Earning a 10% return on the modeled AI investments through 2030 would require about $650 billion of annual revenue into perpetuity, equal to 58bp of global GDP, $34.72 per month from every current iPhone user, or $180 per month from every Netflix subscriber.

Related Articles:

  • Investor Angst Over Big Tech’s AI Spending Spills Into Bond Market — Investors have sold off bonds issued by large US technology companies building data centres, including Alphabet, Meta, Microsoft and Oracle, as concerns over artificial intelligence spending reached the bond market. Bank of America data show the extra yield investors demand to hold this debt over Treasuries rose to 0.78 percentage points from 0.5.
  • Meta, xAI Starting Trend for Billions in Off-Balance Sheet Debt — Off-balance-sheet structures such as special purpose vehicles and asset-tied joint ventures are becoming the standard financing route for AI data center deals. Morgan Stanley estimates tech firms will need as much as $800bn from private credit by 2028, with roughly $1.5tn of external financing required across the AI ecosystem.
  • Minsky Moments and AI CapEx — Capital-spending forecasts for the four largest cloud providers rose nearly 50% over the year, and AI data centers are increasingly funded through leveraged and off-balance-sheet structures, including $3.2bn in senior secured notes and a roughly $30bn asset-backed financing. The author argues this marks a speculative-finance phase where borrowers must roll over principal.

AI Summary. Technology valuations are not extreme by historical standards, with the Nasdaq Composite's average forward price-to-earnings ratio near 29 versus above 32 before the artificial intelligence boom. Concern instead centers on leverage: AI-related companies issued $139bn of corporate bonds this year, about 9% of investment-grade issuance and 23% above last year.

Asa Fitch and Dan Gallagher Wall Street Journal
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The share prices of AI-related firms as a multiple of forward earnings have seen a downtick as some investors worry about rising leverage. AI-related companies issued $139B of debt so far this year, or 9% of all investor-grade issuance.

Is rising debt, not valuations, the main risk in the AI boom?

Core argument: AI-related companies had issued $139 billion of corporate bonds this year as of last month, about 9% of all investment-grade issuance and a 23% jump over last year, according to a Goldman Sachs report.

Overall, tech valuations don’t look outrageous, especially with companies like Nvidia minting profits. The average forward price-to-earnings ratio for the tech-heavy Nasdaq Composite Index is about 29—a high number, to be sure, but nothing astronomical for a basket of growing companies. That figure reached above 32 in 2021, the year before the AI boom. [A] source of concern lies in the huge amount of leverage needed to finance the outsize ambitions of AI’s biggest players. Oracle reached a $300 billion deal with OpenAI in September to supply it with AI computing power, and it raised $18 billion through a bond sale the same month. That is a foretaste of what analysts say will be a growing pool of debt tied to data centers. AI-related companies had issued $139 billion of corporate bonds this year as of last month, according to a Goldman Sachs report—about 9% of all investor-grade issuance and a 23% jump over last year. Meta Platforms organized a $27.3 billion financing for a Louisiana data-center complex last month alone in what was the largest-ever private-debt deal.

Takeaways by Macro Roundup® AI

  1. AI-related companies had issued $139 billion of corporate bonds this year as of last month, about 9% of all investment-grade issuance and a 23% jump over last year, according to a Goldman Sachs report.
  2. The Nasdaq Composite's average forward price-to-earnings ratio is about 29, below the above-32 level reached in 2021, the year before the AI boom.
  3. Oracle reached a $300 billion deal with OpenAI in September to supply AI computing power and raised $18 billion through a bond sale that month, while Meta Platforms organized a $27.3 billion financing for a Louisiana data-center complex, the largest-ever private-debt deal.

Related Articles:

  • Why We Are Not In A Bubble….Yet — The 5 largest US technology companies are worth about 16% of the global public equity market, and the top 10 US stocks nearly 25%, almost $25tn. The author argues valuations are high but not bubble-level, with the "Magnificent 7" median forward price-to-earnings ratio at 27x, roughly half that of the late-1990s leaders.
  • Four Things: OpenAI’s Backstop, CoreWeave CDS, Oregon, and Humanity’s TAM — A suggestion that the U.S. government could guarantee data-center financing, later disavowed by OpenAI's leadership, signaled that AI build-out costs have reached utility proportions. The author argues lenders may now price OpenAI more like a sovereign-backed utility than a growth company, exposing the fragility of the capital structure behind compute-intensive AI.
  • Investor Angst Over Big Tech’s AI Spending Spills Into Bond Market — Investors have sold off bonds issued by large US technology companies building data centres, including Alphabet, Meta, Microsoft and Oracle, as concerns over artificial intelligence spending reached the bond market. Bank of America data show the extra yield investors demand to hold this debt over Treasuries rose to 0.78 percentage points from 0.5.

AI Summary. Average net debt relative to earnings for about 2,500 companies in the MSCI ACWI global stock index improved to 1.74x in the first half of this year from 2.53x a decade earlier, indicating stronger corporate balance sheets. Meanwhile, the International Monetary Fund projects government debt across major economies will rise annually through 2030 to about 137% of GDP.

Finbarr Flynn, Tasos Vossos, and Greg Ritchie Bloomberg
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The debt of several blue-chip firms, including Microsoft in the US, Siemens in Germany and LVHM in France, trades at lower yields than the underlying government benchmark, as “tough fiscal compromises” look unlikely.

Are corporate balance sheets now stronger than government finances?

Core argument: Net debt to EBITDA for roughly 2,500 companies in the MSCI ACWI Index improved to an average of 1.74 times in the first half of this year from 2.53 a decade ago, according to data compiled by Bloomberg.

A key measure of corporate creditworthiness — net debt relative to earnings before interest, taxes depreciation and amortization — has hovered near its lowest post-financial-crisis level in recent years, despite higher borrowing costs. For about 2,500 companies in the MSCI ACWI Index, that metric improved to 1.74 times on average in the first half of this year from an average of 2.53 a decade ago, data compiled by Bloomberg show. A lower reading signals stronger balance sheets. By contrast, the debt-to-gross domestic product ratio across major economies has been going up, and the International Monetary Fund estimates it’ll rise every year through 2030 to about 137%. Microsoft has such strong earnings that its net debt is just a 10th of the last 12 months’ earnings. And in France, Orange — formerly known as France Telecom and a classic case of corporate deleveraging — is being rewarded by traders with a lower risk premium. Around 5% of French investment-grade notes trade at yields less than government debt, data compiled by Bloomberg show.

Takeaways by Macro Roundup® AI

  1. Net debt to EBITDA for roughly 2,500 companies in the MSCI ACWI Index improved to an average of 1.74 times in the first half of this year from 2.53 a decade ago, according to data compiled by Bloomberg.
  2. The International Monetary Fund estimates the debt-to-GDP ratio across major economies will rise every year through 2030 to about 137%, while corporate leverage has hovered near its lowest post-financial-crisis level.
  3. About 5% of French investment-grade notes trade at yields below government debt, according to data compiled by Bloomberg, and traders reward Orange, a case of corporate deleveraging, with a lower risk premium.

Related Articles:

  • Why Microsoft Has Lower Borrowing Costs Than the U.S. — Two AAA-rated Microsoft bonds trade at yields slightly below equivalent U.S. Treasurys, an unusual negative spread given that companies are more likely to default than a government able to tax and that corporate bonds are harder to sell. Demand for high-quality corporate debt has compressed the AAA corporate spread to 0.3 percentage point over Treasurys.
  • French Companies’ Borrowing Costs Fall Below Government’s As Debt Fears Intensify — Bond yields for French companies including L'Oréal, Airbus and Axa have fallen below those on French government debt of similar maturity, with 10 French firms trading at a negative spread to the sovereign — the most in data going back to 2006, according to Goldman Sachs. Sovereign yields typically set a baseline for corporate bonds.
  • Our Thoughts on Large US Deficits and Their Impact on Bond Yields — Total borrowing in the US is about average despite high government deficits, as high public borrowing has contributed to the need for higher interest rates that have depressed private sector borrowing. Risk premiums on long-dated debt look about average, with no market signs that economic or debt limits are currently being hit.

AI Summary. German industrial production stands at its 2005 level, with analysts arguing that core strengths—a hard-to-decarbonise industrial base, export dependence, and combustion-engine expertise—have become vulnerabilities. Chinese capital goods average 30% cheaper than European equivalents and have closed the quality gap, leaving Germany with its first capital-goods trade deficit with China since records began in 2008.

Olaf Storbeck, Sebastien Ash and Florian Müller Financial Times
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German industrial production is only at its 2005 level, even after a partial rebound in September. Since the start of the year, Germany has run a deficit in capital goods with China, the first since 2008.

Have German industry's core strengths turned into vulnerabilities?

Core argument: German industrial production sits at its 2005 level even after a partial rebound in September, with Marcus Berret of Roland Berger arguing that many of Germany's economic core strengths have turned into vulnerabilities.

Industrial production sits at the 2005 level even after a partial rebound in September. “Many of Germany’s economic core strengths have turned into vulnerabilities,” says Marcus Berret, global managing director at Roland Berger, a Munich-based consultant. Those include a large industrial base that is hard to decarbonise, a high dependence on exports at a time when globalisation is under threat, and a mighty auto industry having to write off 140 years of internal combustion engine expertise. All this is exacerbated by two distinct political decisions in the US and China, taken 10 years apart: Donald Trump’s trade war, and Beijing’s decision a decade ago to turn itself into a global high-tech engineering powerhouse. On average, Chinese capital goods are 30% cheaper than those of Europeans. Crucially, manufacturers in the Asian superpower have also closed the quality gap. Since the start of 2025, Germany is now running a trade deficit in capital goods with China over a rolling 12-month period. That is a first since records began in 2008. Chinese machinery exports to Europe roughly doubled to around €40bn in over six years and may reach €50bn this year, according to industry association VDMA.

Takeaways by Macro Roundup® AI

  1. German industrial production sits at its 2005 level even after a partial rebound in September, with Marcus Berret of Roland Berger arguing that many of Germany's economic core strengths have turned into vulnerabilities.
  2. Chinese capital goods are on average 30% cheaper than European equivalents and Chinese manufacturers have closed the quality gap, leaving Germany with a rolling 12-month trade deficit in capital goods with China since the start of 2025, a first since records began in 2008.
  3. Chinese machinery exports to Europe roughly doubled to about €40bn over six years and may reach €50bn this year, according to industry association VDMA.

Related Articles:

  • Europe is Pricing Itself Out of Existence — Europe paid 166.3% more for its primary energy mix than it would have using conventional sources, equal to 5.6% of GDP rather than 3.37%, which the author argues largely explains minimal European growth. European Union primary energy consumption has fallen 17.47% from its peak, with renewables at 16.6% of the mix and renewable electricity priced at 5x conventional.
  • The Future of European Competitiveness – A Competitiveness Strategy for Europe — A European Union competitiveness report attributes the EU's labour productivity growth gap with the US largely to weaker activity in information and communications technology and large-scale digital services; excluding main ICT sectors, EU productivity was broadly at par with the US from 2000-2019. It estimates Europe's investment share must rise about 5 percentage points of GDP.
  • Europe Is Losing — Europe's share of global stock market valuations has fallen from 18% to 10% for the EU and from 8.3% to 2.6% for the UK, while America's has held at 48%. Tax revenue equals 38–44% of output in Germany, Italy and France versus 25% in the US, and industrial electricity costs 3–4x US levels.

AI Summary. Shortages of advanced semiconductors in China are acute enough that authorities have begun intervening in how output from Semiconductor Manufacturing International, the country's largest contract chip maker, is distributed, prioritizing Huawei's artificial-intelligence chip production. Chinese firms also smuggle Nvidia chips or access them remotely through cloud computing abroad.

Lingling Wei, Amrith Ramkumar and Robbie Whelan Wall Street Journal
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The Chinese government has started managing SMIC’s chip output, prioritizing Huawei’s demand as American export controls have created an “acute” shortage of advanced semiconductors in China.

Are chip export controls creating real semiconductor shortages in China?

Core argument: Shortages of advanced semiconductors in China are acute enough that the government has begun intervening in how output from Semiconductor Manufacturing International, the country's largest contract chip maker, is distributed, according to people familiar with the matter.

Shortages of advanced semiconductors are so acute that the government has begun intervening in how the output of China’s largest contract chip maker, Semiconductor Manufacturing International, is distributed, according to people familiar with the matter. Chinese authorities are trying to give priority to the needs of tech conglomerate and national champion Huawei Technologies, which uses SMIC technology to make artificial-intelligence chips, the people said. Companies in China also continue to smuggle Nvidia chips or access them remotely in other countries using cloud computing. According to contracts reviewed by The Wall Street Journal, at least 16 refrigerator-sized Blackwell racks—shipped in smaller parts and reassembled in China—were set to be delivered by November. That amount of chips isn’t sufficient to train advanced, large-scale AI models, but it can still be useful for conducting research and developing powerful applications.

Takeaways by Macro Roundup® AI

  1. Shortages of advanced semiconductors in China are acute enough that the government has begun intervening in how output from Semiconductor Manufacturing International, the country's largest contract chip maker, is distributed, according to people familiar with the matter.
  2. Chinese authorities are trying to give priority to Huawei Technologies, which uses SMIC technology to make artificial-intelligence chips, according to people familiar with the matter.
  3. At least 16 refrigerator-sized Blackwell racks, shipped in smaller parts and reassembled in China, were set to be delivered by November, according to contracts reviewed by The Wall Street Journal, an amount insufficient to train advanced large-scale AI models but useful for research and developing powerful applications.

Related Articles:

  • China Seeks To Triple Output Of AI Chips In Race With The US — China is preparing three new fabrication plants dedicated to producing Huawei's artificial intelligence processors, and people familiar with the effort say their combined capacity, once fully ramped up, could exceed current output from comparable lines at SMIC, China's leading chipmaker. Huawei denies having plans to launch its own fabrication plants.
  • China Has Its Own Concerns About Nvidia H20 Chips — China's leaders cite security concerns, including suspicion of hidden back doors in US-designed chips, as a rationale for their drive toward chip self-sufficiency. The dilemma extends beyond chips: US intelligence reportedly found extra modems on Chinese-made port cranes, and the US has banned Chinese components from connected auto systems.
  • Industrial Policy and Economic Security — Industrial policy justified on national security grounds requires weighing how much economic inefficiency is worth tolerating, since costs incurred today make a country poorer and therefore less able to project power later. The calculation is difficult because security gains are probabilistic and long-term economic costs are speculative.

Thursday, November 13, 2025

AI Summary. Analysts forecast an average annual total return of 6.5% for the S&P 500 stock index over the next 10 years, within a range of 3% to 10%, which would rank in the 27th percentile of 10-year returns since 1900. The base case combines 6% annual earnings-per-share growth, a 1% annual decline in valuations, and a 1.4% average dividend yield.

Peter Oppenheimer, Timothy Moe, Ben Snider, Sharon Bell, et al. Goldman Sachs
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Goldman forecasts an annualised total return of 6.5% for the S&P 500 over the next decade, underperforming STOXX Europe 600’s 7.1% (7.5% in $ terms) and Japan’s 8.2% (10.2–11.7% in $ terms).

How much will US stocks return over the next decade?

Core argument: The forecast calls for an average annual S&P 500 total return of 6.5% over the next 10 years, with upside and downside scenarios spanning 3% to 10%, a base case that would rank in the 27th percentile of 10-year returns since 1900.

We forecast an average annual S&P 500 total return of 6.5% during the next 10 years, with upside and downside scenarios indicating a range of 3% to 10%. Relative to the distribution of S&P 500 10-year returns since 1900, this base case 6.5% return would rank in the 27th percentile. Adjusting for our economists' estimated average inflation rate of 2.2%, our forecast would indicate a real return of 4%. The building blocks of our base case 6.5% return forecast consist of 6% annualised earnings per share growth, a 1% annualised decline in valuations, and a 1.4% average dividend yield. The S&P 500 net profit margin and ROE currently stand near record highs, and many of the tailwinds to corporate profitability in recent decades are unlikely to boost profits to a similar extent going forward.

Takeaways by Macro Roundup® AI

  1. The forecast calls for an average annual S&P 500 total return of 6.5% over the next 10 years, with upside and downside scenarios spanning 3% to 10%, a base case that would rank in the 27th percentile of 10-year returns since 1900.
  2. The 6.5% base case comprises 6% annualised earnings-per-share growth, a 1% annualised decline in valuations, and a 1.4% average dividend yield, and implies a 4% real return against an estimated 2.2% average inflation rate.
  3. The S&P 500 net profit margin and return on equity stand near record highs, and many of the tailwinds to corporate profitability in recent decades are unlikely to boost profits to a similar extent going forward.

Related Articles:

  • Why We Are Not In A Bubble….Yet — The 5 largest US technology companies are worth about 16% of the global public equity market, and the top 10 US stocks nearly 25%, almost $25tn. The author argues valuations are high but not bubble-level, with the "Magnificent 7" median forward price-to-earnings ratio at 27x, roughly half that of the late-1990s leaders.
  • How Much Wealth Would Be Destroyed By An AI Stockmarket Crash? — Americans hold about $42T, or 20% of total household wealth, in US stocks, up four percentage points since the dotcom era, while foreign investors hold $18T. A dotcom-scale drop would erase $16T of household wealth and, using an estimated $3.20 spending decline per $100 of lost stock wealth, cut consumption by roughly $890bn, or 2.9% of GDP.
  • Minsky Moments and AI CapEx — Capital-spending forecasts for the four largest cloud providers rose nearly 50% over the year, and AI data centers are increasingly funded through leveraged and off-balance-sheet structures, including $3.2bn in senior secured notes and a roughly $30bn asset-backed financing. The author argues this marks a speculative-finance phase where borrowers must roll over principal.

AI Summary. U.S. Treasury market liquidity briefly deteriorated around new tariff announcements, with wider bid-ask spreads, lower order book depth, higher price impact, and sharply higher price volatility, before quickly reverting to levels typical of recent years. The authors find the association between liquidity and volatility remained consistent with its historical relationship.

Michael Fleming Federal Reserve Bank of New York
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Treasury market liquidity, whether measured by bid-ask spreads, order book depth, or Treasury price volatility, sharply declined in response to the April 2 tariff announcement, but quickly recovered after April 9, when the tariffs were mostly postponed.

Did Treasury market liquidity deteriorate lastingly after new tariff announcements?

Core argument: Treasury market bid-ask spreads widened notably after the April 2, 2025 tariff announcement, but by much less than in March 2020 and somewhat less than during the March 2023 regional banking turmoil, narrowing after tariffs were mostly postponed on April 9.

In 2025, the Federal Reserve has cut interest rates, trade policy has shifted abruptly, and economic policy uncertainty has increased. How have these developments affected the functioning of the key U.S. Treasury securities market?. We find that liquidity briefly worsened around the April 2025 tariff announcements. Bid-ask spreads widened notably after the April 2 tariff announcement, albeit to a much lesser extent than in March 2020 and even somewhat less than during the March 2023 regional banking turmoil.They narrowed after the April 9 announcement that the new tariffs were mostly being postponed and have since been commensurate with levels typically observed in recent years. Order book depth also points to relatively poor liquidity in April 2025, when available depth declined to the lowest levels since March 2023, [but] then quickly recovered. Price impact rose abruptly on April 2, but then quickly reverted. Treasury price volatility rose sharply following the April 2 tariff announcement, peaking between April 7 and April 9, but quickly declined after the April 9 announcement.The [featured] chart shows that the 2025 observations (in dark blue) fall in line with the historical relationship; i.e. the association between liquidity and volatility in 2025 has been consistent with the past association between these two variables.

Takeaways by Macro Roundup® AI

  1. Treasury market bid-ask spreads widened notably after the April 2, 2025 tariff announcement, but by much less than in March 2020 and somewhat less than during the March 2023 regional banking turmoil, narrowing after tariffs were mostly postponed on April 9.
  2. Treasury order book depth fell in April 2025 to its lowest levels since March 2023 and price impact rose abruptly on April 2, with both measures quickly recovering.
  3. Treasury price volatility rose sharply after the April 2 tariff announcement, peaked between April 7 and April 9, and declined quickly after the April 9 postponement, with the 2025 association between liquidity and volatility consistent with the historical relationship.

Related Articles:

  • Signs of Stress in Money Markets — Federal Reserve balance sheet reduction and heavy Treasury bill issuance are pushing money market funding spreads higher, with key overnight repo rates rising above the rate the Federal Reserve pays on bank reserves. The financial system is nearing the point where bank reserves are no longer ample, and persistent funding-rate volatility could affect credit markets.
  • Data Update 4 for 2025: Interest Rates, Inflation and Central Banks! — Interest rates are ultimately driven by macroeconomic fundamentals, with an "intrinsic risk-free rate" defined as the sum of the inflation rate and real GDP growth tracking the observed 10-year Treasury bond yield closely. On this view, central banks' influence comes from preferential access to data on those fundamentals, their capacity to alter them, and their credibility.
  • Treasuries Rally Is Proving Trump’s ‘Sell America’ Critics Wrong — Investors have continued buying US government debt despite concerns over tariffs, tax cuts, budget deficits, and pressure on the Federal Reserve, with benchmark 10-year yields down about half a percentage point to roughly 4%. The $30tn Treasuries market has returned about 6%, and US 10-year yields have fallen the most among G-7 nations.

AI Summary. China's manufactured goods surplus exceeds $2tn in its own customs data, about 10.5% of Chinese GDP and over 2% of world GDP, far exceeding the combined peak surpluses of Germany and Japan. The author argues the International Monetary Fund understates this by relying solely on reported current account balances, which have not similarly jumped.

Brad Setser Council On Foreign Relations
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China’s surplus in manufactured goods is now over 2% of global GDP; greater than the combined surpluses of Germany and Japan at their peaks. China’s overall goods surplus is $1.2T, $800B higher than it was in 2020.

Does relying on current account data understate China's manufacturing surplus?

Core argument: China's surplus in manufactured goods exceeds $2 trillion in China's customs data, around 10.5% of China's GDP and over 2% of world GDP, far exceeding the combined surpluses of Germany and Japan at their peaks.

In the IMF’s data on global goods trade volume, China’s exports are up a cumulative 40% in volume terms since the end of 2019, while imports in volume terms are up only 1%. China’s surplus in manufactured goods, in China’s customs data, now easily exceeds $2 trillion. That is around 10.5% of China’s GDP, and over 2% of world GDP, a surplus that far exceeds the combined surpluses of Germany and Japan at their peaks. China’s surplus in all goods is now $1.2 trillion in China’s customs data, after a roughly $800 billion increase over the last 5 years. The customs surplus is around 6% of China’s GDP and well over 1 percentage point of the GDP of China’s trading partners. Yet the IMF relies exclusively on countries' reported current account surpluses and deficits in its assessment of the size of external payments imbalances. And China’s current account surplus, scaled to its GDP, hasn’t really popped. The IMF’s preferred solution to deflationary pressures in Asia, is monetary easing—which tends to weaken the currency and raise the external surplus. The right response to a shortfall in demand that is leading to deflation and a rising trade surplus, though, is a sustained fiscal expansion.

Takeaways by Macro Roundup® AI

  1. China's surplus in manufactured goods exceeds $2 trillion in China's customs data, around 10.5% of China's GDP and over 2% of world GDP, far exceeding the combined surpluses of Germany and Japan at their peaks.
  2. China's export volumes are up a cumulative 40% since the end of 2019 in the IMF's global goods trade data, while its import volumes are up only 1%.
  3. The IMF relies exclusively on countries' reported current account balances to assess external payments imbalances, and China's current account surplus scaled to GDP has not popped even as its customs goods surplus rose roughly $800 billion over five years to $1.2 trillion.

Related Articles:

  • China’s “Anti-Involution” Campaign: Global Implications — China's economy has slowed as domestic investment stagnates and consumer spending stays weak, with the shortfall partly offset by rising net exports. The author argues these internal problems are being passed to the rest of the world, since export values are rising about 6% a year while import values are down 2.2%.
  • Chinese Exports Unexpectedly Slump for First Time Since February — China's exports contracted 1.1% from a year earlier, as a more than 25% drop in shipments to the US outweighed a 3.1% rise in exports to all other countries. Weak imports alongside export strength earlier in the year pushed China's trade surplus to a record $965bn.
  • Trade With China Is Becoming a One-Way Street — China's import volumes have shown no growth since the end of 2022 while its export volumes rose 33%, according to data from the Netherlands Bureau of Economic Policy Analysis. In dollar terms, Chinese imports fell 11% from the US, 17% from Japan, and 18% from Germany, as Chinese companies replace overseas suppliers with domestic ones.

AI Summary. Global trade openness — world exports plus imports as a share of world GDP — rose steadily until the global financial crisis and has since fluctuated without further advance or retreat, leaving trade at a plateau of peak globalization. US tariffs have diverted Chinese goods to other markets and prompted transshipment to the US via third countries.

Robin Brooks Robin Brooks Substack
Date Posted:
Is Database:
Database

The sum of global exports and global imports relative to global GDP has been stable over the past decade. Robin Brooks argues that despite the ongoing trade wars, “we’re essentially in a holding pattern at peak globalization.”

Has globalization retreated, or is global trade openness holding at a plateau?

Core argument: Global trade openness, measured as global exports plus imports divided by world GDP, rose steadily until the global financial crisis and has since moved sideways amid various shocks, leaving globalization neither advancing nor retreating.

The chart shows a widely-used measure of global trade openness, which is the sum of global exports plus global imports divided by world GDP. This ratio increased steadily until the global financial crisis, whereafter it went into a holding pattern with lots of ups and downs due to various shocks. While it’s true that globalization hasn’t advanced any further over the past decade, it hasn’t retreated either. We’re essentially in a holding pattern at peak globalization. The fact that there’s been no retreat in globalization is consistent with all the work I’ve done on Chinese exports in recent posts. US tariffs have resulted in massive trade diversion of Chinese goods to the rest of the world as well as transshipment of goods to the US via third countries. In the end, however, China remains the biggest producer of goods and the US is the biggest consumer. Those two forces inevitably have to meet in global trade, just - these days - on a more circuitous route.

Takeaways by Macro Roundup® AI

  1. Global trade openness, measured as global exports plus imports divided by world GDP, rose steadily until the global financial crisis and has since moved sideways amid various shocks, leaving globalization neither advancing nor retreating.
  2. US tariffs have resulted in trade diversion of Chinese goods to the rest of the world and transshipment to the US via third countries, according to the author's analysis of Chinese exports.
  3. China remains the biggest producer of goods and the US the biggest consumer, forces the author argues inevitably meet in global trade, now by a more circuitous route.

Related Articles:

  • Why Global Imbalances Do Matter — From 2008 to 2023 the US household and corporate sectors ran average savings surpluses of 3.5% and 1.6% of GDP respectively, leaving the federal government as the dominant net borrower in the US economy. This suggests the benefit of persistent net capital inflows is the ability to run larger fiscal deficits and grow public debt.
  • How NOT To Negotiate With China — Trade diversion signals deep distress in China's export sector, and the author argues a sustained 10% tariff hike would be more credible than larger ones and could counter China's rare earths leverage. Easing up on Chinese exporters instead signals weakness and discourages Europe from coordinating with the US.
  • The True Cost of China’s Falling Prices — Prices fell for 51 of 67 consumer items tracked over a two-year period in China, while the broader GDP deflator, which includes upstream sectors, declined for 10 straight quarters, indicating deflation is more entrenched in industry. The share of "zombie" firms whose profits cannot cover debt interest rose from 19% to 34% over five years.

AI Summary. China is designing a "validated end-user" system that would fast-track rare-earth and other restricted material export approvals for U.S. firms while excluding companies tied to the U.S. military. The arrangement would let China ease export flows while keeping the materials away from U.S. military suppliers.

Jon Emont and Raffaele Huang Wall Street Journal
Date Posted:

While China is planning on easing exports of rare earths, a “validated end-user” system will keep them out of the American defense supply chain going forward, meaning the US defense industrial base will have to build an alternative supply chain.

Is China easing rare-earth exports while blocking military-linked buyers?

Core argument: China plans a "validated end-user" (VEU) system that would fast-track export approvals of rare earths and other restricted materials to U.S. firms while excluding companies with ties to the U.S. military, according to people familiar with the plan.

China plans to ease the flow of rare earths and other restricted materials to the U.S. by designing a system that will exclude companies with ties to the U.S. military while fast-tracking export approvals for other firms, according to people familiar with the plan. The “validated end-user” system, or VEU, would enable Chinese leader Xi Jinping to follow through on a pledge to President Trump to facilitate the export of such materials while ensuring that they don’t end up with U.S. military suppliers, a core concern for China.

Takeaways by Macro Roundup® AI

  1. China plans a "validated end-user" (VEU) system that would fast-track export approvals of rare earths and other restricted materials to U.S. firms while excluding companies with ties to the U.S. military, according to people familiar with the plan.
  2. The VEU system would let Chinese leader Xi Jinping honor his pledge to President Trump to facilitate exports of such materials while ensuring they do not reach U.S. military suppliers, a core concern for China.

Related Articles:

  • Mad Libs: Just Fill In The Blanks — China expanded its rare earth export controls to require licenses for any product containing more than 0.1% by value of Chinese rare earths or made with equipment containing them, with a presumption of denial for military uses and scrutiny of advanced semiconductor uses. Aggressive enforcement would affect industries from chips and autos to aerospace, defense and medical equipment.
  • China Cracks Down On Foreign Companies Stockpiling Rare Earths — China is warning foreign buyers of rare earths and derived products such as magnets that building large inventories will bring supply restrictions, and is limiting approved export volumes to prevent stockpiling, according to people familiar with the matter.
  • China’s Weaponisation of Rare Earths is a New Kind of Trade War — China's export controls on rare earth materials and magnets threatened to halt production across the auto industry, the largest manufacturing sector in most advanced economies, and forced Washington to negotiate on tariffs. Despite China's well-known dominance of rare earth production, Western governments and companies have not developed alternative suppliers.