Edward Conard

Top Ten New York Times Bestselling Author

  • “…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 fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “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
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Friday, February 27, 2026

AI Summary. An International Monetary Fund index of capital-account restrictions shows controls receded from 1999 to the early 2010s and fell again between 2016 and 2019, before a modest comeback in which 41 countries broadened their restrictions. Russia tightened controls after invading Ukraine, and Argentina reimposed curbs to stem a currency crisis.

Economist Staff The Economist
Date Posted:

IMF data shows that despite trade tensions, capital controls have not increased globally, and indeed fell btw 2016 and 2019, though populism surged globally.

Are capital controls making a comeback after decades of liberalization?

Core argument: The IMF's Financial Account Restrictiveness Index shows 41 countries have widened the breadth of their capital controls since 2019; Russia tightened controls after invading Ukraine, and Argentina reimposed el cepo to stem a currency crisis.

[The IMF] Financial Account Restrictiveness Index divides transactions into dozens of subcategories, asking if foreigners can freely buy the country’s bonds, if residents can open foreign-currency bank accounts, if exporters must surrender dollar earnings to the government, and so on, and reports the fraction of subcategories that face some restriction. It shows that capital controls receded between 1999 and the early 2010s, when the European sovereign-debt crisis rocked some previously open economies. Worldwide curbs fell again from 2016 to 2019, even as populist nationalism was on the march. Lately controls have staged a modest comeback: 41 countries have increased the breadth of their restrictions since 2019. Russia tightened controls after it invaded Ukraine. Argentina reimposed el cepo (the clamp) to stem a currency crisis. A second index, developed by Wenjie Li, another IMF economist, uses a dash of judgment to rate the intensity of controls on a five-point scale. Going by this FinOpen index, Bhutan had the most closed capital account in the world in 2022 (the latest year available). Entirely open economies ranged from rich financial havens (Andorra and Panama) to Liberia, a desperately poor country that lives up to its name in its treatment of foreign capital.

Takeaways by Macro Roundup® AI

  1. The IMF's Financial Account Restrictiveness Index shows 41 countries have widened the breadth of their capital controls since 2019; Russia tightened controls after invading Ukraine, and Argentina reimposed el cepo to stem a currency crisis.
  2. The IMF index, which reports the fraction of dozens of transaction subcategories facing restrictions, shows capital controls receding between 1999 and the early 2010s and falling again from 2016 to 2019, even as populist nationalism advanced.
  3. On the FinOpen index developed by IMF economist Wenjie Li, which rates control intensity on a five-point scale, Bhutan had the world's most closed capital account in 2022, while Andorra, Panama and Liberia were entirely open.

Related Articles:

  • Can Trade Intervention Lead to Freer Trade? — China accounts for over 31% of global manufacturing but under 13% of global consumption, while the United States accounts for under 17% of manufacturing and nearly 27% of consumption. The author argues persistent surpluses reflect household subsidies to producers, and that the US could counter them with tariffs or taxes on capital inflows.
  • Can Trump Reduce the Trade Deficit? — A world of widespread tariffs would also shrink international capital flows, and because the US trade deficit is the counterpart of large capital inflows, reduced capital mobility would narrow that deficit. The author argues this would occur largely by reducing overall investment in the US economy.
  • The Dangerous Triumph Of Neo-Mercantilism — Neo-mercantilism is thriving in both China, which pairs infant-industry promotion with large trade surpluses, and in a United States focused on external deficits and protecting domestic markets. The author argues this will likely fracture the world economy, and that a new multilateral treaty could include a mechanism to combat large structural trade surpluses.

AI Summary. Taxes or restrictions on short-term capital inflows were argued to be a more direct and potentially superior tool than tariffs for shrinking the trade deficit, since tariffs risk retaliation and supply-chain distortions. Proponents said such measures could reduce reliance on household and government borrowing to sustain employment, if paired with efforts to strengthen domestic demand and tradables capacity.

Joyce Chang, Zahin Ov, Amy Ho and Mohammed Hossain J.P. Morgan
Date Posted:

JPM reports on a Princeton conference on the prospects for reducing global imbalances by means of policies directly impacting the capital account, such as taxes or other breakers on capital flows, rather than via trade policies such as tariffs or quotas.

Are capital inflow taxes better than tariffs for shrinking trade deficits?

Core argument: Speakers argued that taxes or restrictions on short-term capital inflows are a more direct, macro-consistent tool for reducing the trade deficit than tariffs, which risk retaliation and supply chain distortions.

Taxes or levies on short-term capital inflows were discussed as a more direct, macro consistent tool to reduce the trade deficit than tariffs, which risk retaliation and supply chain distortions. Speakers argued that well designed restrictions or taxes on inflows could be a legitimate—and potentially superior—tool to rebalance trade than tariffs, provided they are part of a broader strategy to strengthen domestic demand and tradables capacity. Restrictions/taxes on capital inflows could align the country’s external position with domestic needs instead of passively absorbing foreign savings and compensating with rising debt. The expected benefits are smaller structural trade deficits with less reliance on household/fiscal leverage to maintain employment and a healthier composition of growth and debt, with less vulnerability to inflow reversals. Speakers specifically endorsed measures that target capital inflows (i.e., capital-flow management), not a classic Tobin tax (i.e., tax on FX transactions) or blanket tax on all currency trading. An inflow tax can be designed to penalize short-term/volatile financing without unduly harming productive investment or needed hedging [Editor’s Note: Such a tax on “hot money” might prevent inflow reversals or “sudden stops” under stressful circumstances, but would not address prolonged global imbalances.]

Takeaways by Macro Roundup® AI

  1. Speakers argued that taxes or restrictions on short-term capital inflows are a more direct, macro-consistent tool for reducing the trade deficit than tariffs, which risk retaliation and supply chain distortions.
  2. Speakers endorsed capital-flow management targeting inflows rather than a classic Tobin tax on foreign exchange transactions, contending an inflow tax can penalize short-term, volatile financing without unduly harming productive investment or needed hedging.
  3. Speakers expected such measures to yield smaller structural trade deficits, less reliance on household and fiscal leverage to sustain employment, and reduced vulnerability to inflow reversals, provided they accompany a broader strategy to strengthen domestic demand and tradables capacity.

Related Articles:

  • The Dangerous Triumph Of Neo-Mercantilism — Neo-mercantilism is thriving in both China, which pairs infant-industry promotion with large trade surpluses, and in a United States focused on external deficits and protecting domestic markets. The author argues this will likely fracture the world economy, and that a new multilateral treaty could include a mechanism to combat large structural trade surpluses.
  • 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.
  • Europe Has No Choice But To Intervene On Trade — Manufacturing competitiveness is argued to stem largely from lower labor costs relative to productivity, so policies that raise the household share of income weaken competitiveness while countries that suppress wages gain at trade partners' expense. The author argues Europe must therefore intervene in its external accounts to offset foreign trade intervention rather than cut wages and welfare.

AI Summary. Labor Department data analyzed by researchers show the number of software developers up 5% year over year, a pace largely consistent with the past 23 years, while computer programmers declined slightly in line with a decades-long trend. The median young computer science graduate earned 63% more than the typical young graduate in 2024, up from 47% in 2009.

Greg Ip Wall Street Journal
Date Posted:

The number of employed software developers in the US in January was up 5% from January 2025, consistent with a return to its mean pace since 2002. The median wage premium for a new computer science grad relative to other new grads rose 15pp from 2009 through 2024.

Is AI reducing software developer employment and pay?

Core argument: The ranks of software developers rose 5% in January from a year earlier, a pace largely consistent with the past 23 years, according to Labor Department data analyzed by James Bessen of Boston University's Technology and Policy Research Initiative.

The ranks of software developers, widely assumed to be acutely vulnerable to AI, are up 5% in January from a year earlier, a pace largely consistent with the past 23 years. That’s according to Labor Department data analyzed by James Bessen, executive director of the Technology and Policy Research Initiative at Boston University. The number of computer programmers, who assist developers in ensuring code runs properly, was down slightly in the last year, in line with a secular decline in place for decades. Competition from AI isn’t forcing computer scientists to take pay cuts, either. In 2024, the median young computer science graduate earned 63% more than the typical young graduate, up from 47% in 2009, data from Connor O’Brien at the Institute for Progress shows

Takeaways by Macro Roundup® AI

  1. The ranks of software developers rose 5% in January from a year earlier, a pace largely consistent with the past 23 years, according to Labor Department data analyzed by James Bessen of Boston University's Technology and Policy Research Initiative.
  2. The number of computer programmers, who assist developers in ensuring code runs properly, declined slightly over the past year, in line with a secular decline in place for decades.
  3. The median young computer science graduate earned 63% more than the typical young graduate in 2024, up from 47% in 2009, according to data from Connor O'Brien at the Institute for Progress.

Related Articles:

  • Looking for the Ladder — The article argues that the hiring downturn in occupations most exposed to generative AI reflects interest-rate sensitivity rather than AI itself, since roughly 38% of workers in the most AI-exposed quintile work in information, finance and insurance, and professional and technical services, versus under 2% in the least-exposed quintile.
  • AI Is Simultaneously Aiding and Replacing Workers, Wage Data Suggest — Wage data suggest greater artificial intelligence exposure is associated with lower wage growth in occupations where experienced workers earn little premium over entry-level workers, and with higher wage growth where that premium is large. The authors interpret this as AI substituting for workers in jobs requiring little tacit knowledge while complementing experienced workers elsewhere.
  • AI Tracker – The GDP Dividend; A Jobs Dilemma — Unemployment in occupations exposed to artificial intelligence rose to 3.8% from 3%, a larger increase than the 0.3 percentage point rise in the national rate, while unemployment in non-exposed occupations edged lower. The rise is concentrated among workers aged 34 and under, whose jobless rate jumped to 5.3% from 3%.

AI Summary. OpenAI closed a funding round that could raise up to $110bn at a $730bn valuation, with Nvidia and SoftBank each committing $30bn and Amazon $15bn initially plus $35bn tied to an initial public offering or the development of artificial general intelligence. Its revenues are forecast to reach more than $60bn by 2027, contingent on securing computing power.

George Hammond Financial Times
Date Posted:

OpenAI closed a fundraising round that raised $75-110B, valuing the firm at $730B. Nvidia, Amazon and SoftBank anchored the raise.

How much can an AI developer raise in a single funding round?

Core argument: OpenAI closed a funding round that could raise up to $110bn at a $730bn valuation, as the ChatGPT maker seeks to regain its lead over rivals Anthropic and Google.

OpenAI has closed a blockbuster funding round that could raise as much as $110bn and values the ChatGPT maker at $730bn, as the AI start-up tries to wrestle back its lead from rivals Anthropic and Google. Nvidia and SoftBank have each committed $30bn, to be paid in three installments. Amazon will invest $15bn initially and another $35bn either when OpenAI goes public or manages to build the much more powerful AI dubbed “artificial general intelligence.” OpenAI’s revenues were roughly $13bn last year and are forecast to hit $30bn this year before rising to more than $60bn in 2027, according to a person with knowledge of the group’s finances. That forecast relies on securing computing power to train and run its models. In a flurry of deals last year, OpenAI committed to purchase roughly $1.4tn of computing power over eight years.

Takeaways by Macro Roundup® AI

  1. OpenAI closed a funding round that could raise up to $110bn at a $730bn valuation, as the ChatGPT maker seeks to regain its lead over rivals Anthropic and Google.
  2. Nvidia and SoftBank each committed $30bn payable in three installments, while Amazon will invest $15bn initially and a further $35bn either when OpenAI goes public or builds artificial general intelligence.
  3. OpenAI's revenues of roughly $13bn last year are forecast to reach $30bn this year and more than $60bn in 2027, a projection that depends on securing computing power, against commitments to purchase roughly $1.4tn of computing power over eight years.

Related Articles:

  • Everyone’s Looking For A Bubble. No One Sees The Stampede — A proprietary model estimates monthly artificial intelligence revenue grew roughly 18-fold in two years, from $772m to $13.8bn, with AI accounting for an estimated 23% of Google Cloud, 10% of Azure and 5% of Amazon Web Services. The model's ratio of investment to revenue fell from 6.1x to 4.7x, still historically high.
  • The Macro Implications of the AI Capex Boom — Artificial intelligence capital spending is estimated to add roughly 1.4 percentage points to US growth in one year and about 1.5 points the next, comparable to business investment's contribution during the tech bubble. A material part of that estimate reflects profits at Nvidia and a few other chipmakers that are unlikely to be recycled back into the economy.
  • Rough Notes, Feb 20, 2026: AI Capex in Q4 GDP, Anthropic Revenues, Agentic Domains, etc — An early estimate puts the floor contribution of artificial intelligence capital spending to fourth-quarter US GDP growth at about 64%, and likely closer to 80% including externalities and multipliers, though the calculation is not adjusted for imports. The author also notes that token price deflation persists and that US-China token price differences are immense and growing.

Monday, March 2, 2026

AI Summary. Tanker traffic through the Strait of Hormuz, which normally carries a fifth of global oil and liquefied natural gas supply, appears significantly disrupted as shippers, producers, and insurers turn cautious. Analysts estimate an $18/bbl risk premium in crude, and project European gas and spot liquefied natural gas could reach about $25/mmBtu if flows halt for a month.

Daan Struyven, Samantha Dart, Yulia Zhestkova Grigsby, Alexandra Paulus, et al. Goldman Sachs
Date Posted:

GS forecasts a muted response to the Iran conflict, with a full one-month supply disruption from the Strait of Hormuz causing a $10–15/bbl increase in crude prices. They do see potential for a 130% spike in LNG prices for Europe, much less for the US.

How much do oil and gas prices rise if shipping halts?

Core argument: The authors estimate an $18/bbl real-time risk premium in crude prices based on a 15% weekend gain in retail prices, approximately matching their fair-value estimate of a six-week full halt in Strait of Hormuz flows.

Tanker traffic through the Strait of Hormuz--through which normally 1/5 of global supply for both oil and LNG flows--appears significantly disrupted as many shippers, oil producers, and insurers have shifted to a cautious wait-and-see mode amidst reports about damaged ships. Based on the 15% weekend gain in retail prices, we estimate an $18/bbl real-time risk premium in crude oil prices, which corresponds approximately to our estimate of the fair value effect of a six-week full halt in Strait of Hormuz flows (allowing for spare pipeline capacity use as a partial offset). This estimated impact moderates to +$4 if only 50% of the flows are halted for one month. However, oil prices can rise substantially more if the market demands a premium for the risk of more persistent supply disruptions. We see significant upside risk to prices from a potential sustained disruption of LNG supply through the Strait of Hormuz. In a scenario where flows halt for one month, we think it is likely that [European gas] and [Spot LNG] could approach 74 EUR/MWh ($25/mmBtu)--130% above current levels--a threshold that triggered large natural gas demand responses during the 2022 European energy crisis. We see limited upside risk to US natural gas prices.

Takeaways by Macro Roundup® AI

  1. The authors estimate an $18/bbl real-time risk premium in crude prices based on a 15% weekend gain in retail prices, approximately matching their fair-value estimate of a six-week full halt in Strait of Hormuz flows.
  2. A halt of 50% of Strait of Hormuz flows for one month moderates the estimated crude price impact to +$4/bbl, though prices could rise substantially more if the market demands a premium for more persistent supply disruptions.
  3. European gas and spot LNG prices could approach 74 EUR/MWh ($25/mmBtu), 130% above current levels, if LNG flows through the Strait of Hormuz halt for one month, a threshold that triggered large demand responses during the 2022 European energy crisis.

Related Articles:

  • 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.
  • How China Curbed Its Oil Addiction—and Blunted a U.S. Pressure Point — Nearly half of passenger vehicles sold in China last year were all-electric or plug-in hybrids, up from 6% in 2020, while domestic oil output rose 13% from 2018 to 2024 to about 4.3m barrels a day. China still imports roughly 11m barrels a day, about 70% of what it consumes.
  • Power Politics: Energy Self-Sufficiency in a Modern Mercantilist World — China leads in adding power to the grid, with more than 30,000 miles of ultra-high-voltage transmission lines versus zero in the US and lead times for large transformers of 48 weeks against a US average of 143 weeks. This positions China to accommodate new demand sources such as artificial intelligence.

AI Summary. US industry booms averaging 300% gains over two years were on average followed by flat prices rather than crashes, according to an analysis of long-run stock market data. Booming and crashing industries are associated with subsequent high volatility, but post-boom performance is not significantly different from unconditional returns once market trends are controlled for.

William Goetzmann, Otto Manninen, and James Tyler National Bureau of Economic Research
Date Posted:
Is Database:
Database

Industry data back to 1871 show that in periods identified as “booms,” a sector’s stocks had an average growth of 300% over two years; yet conditional on such a gain, the mean subsequent price path was flat. On average, booms are not followed by crashes.

Do industry booms typically end in crashes?

Core argument: Industry booms in the sample averaged 300% growth over two years, yet their average subsequent price path was flat, supporting the finding that booms on average are not followed by crashes.

What happens when one industry suddenly booms? Is it likely that the boom in that sub-sector continues, reverses, or reverts to average industry behavior? We use the Cowles (1938) data for the early years beginning in 1871 and Fama-French industry portfolio data up to the current time. A boom is identified when an industry earns both a raw and market-adjusted return of 100% or more over the past two years, and a raw return of at least 50% over the past five years. To avoid double-counting, once a month is tagged as a boom, the following 12 months cannot initiate a new boom episode. Figure 5 reports event studies [on each of the industry datasets] using this definition. The booms in the sample had an average growth of 300% over two years. However, conditional on this huge gain, their average subsequent price path was flat. The figures look nearly identical. They support the basic finding that booms on average are not followed by crashes. Further industry-level analysis shows that booming (and crashing) industries are associated with subsequent high volatility, making both crashes and repeat booms more likely. But once one controls for market trends, post-boom performance is not significantly different from unconditional returns. For crashing industries, rebounds are slightly more likely than further declines. This is potentially useful information for investors considering tactical industry allocations in real time.

Takeaways by Macro Roundup® AI

  1. Industry booms in the sample averaged 300% growth over two years, yet their average subsequent price path was flat, supporting the finding that booms on average are not followed by crashes.
  2. A boom is identified when an industry earns both a raw and market-adjusted return of at least 100% over two years plus a raw return of at least 50% over five years, using Cowles (1938) data from 1871 and Fama-French industry portfolios.
  3. Booming and crashing industries are associated with subsequent high volatility, making both crashes and repeat booms more likely, but once market trends are controlled for, post-boom performance is not significantly different from unconditional returns.

Related Articles:

  • Is It a Bubble? — Transformational technologies have historically generated excessive enthusiasm and investment, producing more infrastructure than needed, asset prices that prove too high, and losses for those funding them, while also accelerating adoption. AI enthusiasm is argued to fit this pattern, with debt financing having the potential to magnify the effects.
  • Who Is On the Other Side? — Research defining an industry "run-up" as a cumulative return of 100% or more over two years finds that such run-ups do not predict unusually low average future returns, though they do raise the probability of a crash, defined as a 40% drawdown. Volatility, turnover, and equity issuance help predict those crashes.
  • Predictable Financial Crises — Historical data indicate that when credit and asset prices grow rapidly over three years, the probability of a financial crisis within the next three years is 40%, versus 7% in stable periods. The authors find 63% of crises were preceded by such credit-market overheating, which also forecasts weaker medium-term economic growth.

AI Summary. The average tenure of a company in the S&P 500 stock index has fallen to about 15 years and continues to decline. Contributing factors include faster creative destruction, technological innovation that lets new business models scale quickly and displace incumbents, and mergers and private equity buyouts that remove large firms from public markets.

Torsten Sløk Apollo
Date Posted:
Is Database:
Database

The mean tenure of firms in the S&P 500 at the start of 2026 is 15 years, down from 18 years in 2012 and 25 years in 1980. Sløk attributes the increase in churn to a faster pace of technological change and an increase in M&A and buyout activity.

Why are companies staying in the leading stock index for fewer years?

Core argument: The average tenure of a company in the S&P 500 index is 15 years and continues to decline.

The average number of years a company remains in the S&P 500 index keeps declining. Several factors are driving the faster churn in the index: 1. Creative destruction operates more rapidly, shortening the typical time a company remains large and competitive enough to stay in the S&P 500. 2. Technological innovation (IT, internet, AI, cloud, mobile) creates new business models that scale quickly and displace incumbents before they can adapt. 3. M&A and private equity activity more regularly remove large firms from public markets via buyouts or mergers.

Takeaways by Macro Roundup® AI

  1. The average tenure of a company in the S&P 500 index is 15 years and continues to decline.
  2. Faster creative destruction shortens the period a company stays large and competitive enough to remain in the S&P 500.
  3. Technological innovation across IT, internet, AI, cloud, and mobile creates business models that scale quickly and displace incumbents, while M&A and private equity activity remove large firms from public markets through buyouts and mergers.

Related Articles:

  • The Long Goodbye? Incumbent Competitiveness in the 21st Century — Value creation among large American companies has become concentrated in a newer cohort of firms: businesses founded after World War II accounted for 8% of the top 50 companies' total market value in 1990 but 77% by 2024. The leading 20th-century incumbents are fading as this newer group takes over.
  • Which U.S. Stocks Generated the Highest Long-Term Returns? — Of the 29,078 U.S. common stocks in a database spanning nearly a century, 51.6% had negative cumulative returns, while 17 stocks returned more than 5m% — led by Altria at 265m%. Those top performers averaged annualized returns of just 13.47%, underscoring the value of time invested.
  • Long-Term Shareholder Returns: Evidence From 64,000 Global Stocks — A study of about 64,000 global stocks estimates net global stock market wealth creation of $75.7tn, with returns highly concentrated: the top 159 firms (0.25%) account for half of net wealth creation and the top 1,526 (2.39%) account for all of it. Fewer than half of stocks beat one-month US Treasury bills, 42.6% of non-US and 44.8% of US stocks.

AI Summary. U.S. weapons manufacturers delivered stronger stock returns after the Cold War than during it, even as U.S. military spending fell from around 7% of the economy to about 3.7%, with the "guns" sector posting the third-best total return among 49 U.S. sectors, behind software and microchips.

James Mackintosh Wall Street Journal
Date Posted:

Btw 1988 and 2025, US defense spending fell from ~7% of GDP to 3.7%, while defense sector profit margins doubled to ~7.7% up from ~3.7% in 1988. Mackintosh argues that an increase in foreign customers, not monopsony, was the key driver.

Do defense stocks perform better when military spending falls?

Core argument: The U.S. "guns" sector delivered the third-best total return of 49 U.S. sectors defined by Dartmouth finance professor Kenneth French from just before the Berlin Wall fell to now, trailing only software and microchips.

U.S. weapons manufacturers actually performed better in the years since the end of the Cold War than during it. That’s despite U.S. military spending plummeting from around 7% of the economy in 1988 to about 3.7% today. From just before the Wall fell to now, the “guns” sector had the third-best total return out of 49 U.S. sectors defined by Kenneth French, a Dartmouth finance professor. It came in behind software and microchips. Aerospace, where major defense stocks including Boeing sit, also did well, coming in sixth. Some of the post-1989 margin improvement is because companies were allowed to merge, although that has been true of other sectors. Some of it is because corporate taxes came down. But I would argue a lot is because companies increasingly sell to foreign customers that have less ability to extract lower prices by pointing to fat profits. Smaller domestic military budgets also reduce the need for companies to kowtow to politicians by maintaining unprofitable operations in their districts or supporting civilian projects.

Takeaways by Macro Roundup® AI

  1. The U.S. "guns" sector delivered the third-best total return of 49 U.S. sectors defined by Dartmouth finance professor Kenneth French from just before the Berlin Wall fell to now, trailing only software and microchips.
  2. U.S. weapons manufacturers performed better after the Cold War than during it, even as U.S. military spending fell from around 7% of the economy in 1988 to about 3.7% today.
  3. Post-1989 margin improvement stems partly from permitted mergers and lower corporate taxes, and, the author argues, largely from rising sales to foreign customers less able to extract lower prices by pointing to fat profits.

Related Articles:

  • Trump Demands More Defense Spending But Threatens Biggest Contractors — An executive order requires major defense contractors to end stock buybacks and dividends and cap executive pay at $5m a year until they invest more in factories and research, alongside a demand that Congress raise annual defense spending by over 50% to $1.5tn. Whether a president can mandate private capital allocation is unclear.
  • Investors Pour Billions Into Europe’s AI And Defence Start-ups — European venture capital investment rose 5% to €66bn, a post-pandemic high, with artificial intelligence deals accounting for more than 35% of all transactions at €23.5bn, up from €17.7bn the prior year. Investment in European defence and related technology start-ups rose 55% to a record $8.7bn.
  • Waking the Sleeping European Giant — Europe, at roughly 500m people and a $26tn economy with world-class aerospace, shipbuilding, pharmaceutical, vehicle and weapons manufacturers, has the material basis to be a military superpower. National militaries' preference for home-country suppliers has left subscale defense firms, and common procurement could raise output and lower unit costs.

AI Summary. Designating an AI company a supply-chain risk would be devastating because it depends on cloud hosting from Amazon, Microsoft, and Google, all of which hold US defense contracts, though such authority appears limited to work covered by US government contracts. The author argues governments have incentive to destroy any private firm that dictates terms to their military.

Ben Thompson Stratechery
Date Posted:

Ben Thompson argues the Pentagon’s position vis-à-vis Anthropic is reasonable given that the potential capabilities of AI “are sufficiently powerful to fundamentally affect the US’s freedom of action.”

How vulnerable are AI firms to being labeled supply-chain risks?

Core argument: Designating Anthropic a supply chain risk would decimate the company, which relies on cloud hosting from AWS, Microsoft, and Google — all holders of Department of War contracts — and, the author expects, on Nvidia as well.

[Designating Anthropic a supply chain risk] would decimate Anthropic: at a bare minimum, the company relies on cloud hosting from AWS, Microsoft, and Google, all of which have contracts with the Department of War; I imagine the same applies to Nvidia. Fortunately for the company, Hegseth’s declaration does seem out of step with the law, which limits Hegseth’s authority to work covered by U.S. government contracts; in other words, AWS could still serve Anthropic models, as long as it doesn’t use Anthropic models for any of its services offered to the U.S. government. Why would the U.S. government want to kneecap one of its AI champions? In fact, Amodei already answered the question: if nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company. The reason goes back to the question of international law. International law is ultimately a function of power; might makes right. There are some categories of capabilities — like nuclear weapons — that are sufficiently powerful to fundamentally affect the U.S.’s freedom of action; we can bomb Iran, but we can’t North Korea.

Takeaways by Macro Roundup® AI

  1. Designating Anthropic a supply chain risk would decimate the company, which relies on cloud hosting from AWS, Microsoft, and Google — all holders of Department of War contracts — and, the author expects, on Nvidia as well.
  2. Hegseth's declaration appears out of step with law limiting his authority to work covered by U.S. government contracts, so AWS could still serve Anthropic models provided it excludes them from services offered to the U.S. government.
  3. Amodei's own argument supplies the rationale: if a private company developed nuclear weapons and sought to dictate terms to the U.S. military, the U.S. would be incentivized to destroy that company, because international law is a function of power.

Related Articles:

  • Anthropic Says DeepSeek, MiniMax Distilled AI Models for Gains — Anthropic says three Chinese artificial intelligence developers — DeepSeek, MiniMax Group, and Moonshot — violated its terms of service by using thousands of fraudulent accounts to generate more than 16m exchanges with its Claude models. The company says this practice, known as distillation, lets rival labs improve their own models by training on outputs from more powerful systems.
  • The Geopolitics of AI: Decoding the New Global Operating System — The performance gap between the top American and Chinese AI models narrowed from 9.3% to 1.7%, with Chinese firms relying on cheaper open-source models—DeepSeek prices usage 20-40x below OpenAI's ChatGPT. This price advantage could win adoption in developing countries and build dependency on Chinese AI ecosystems.

AI Summary. The Pentagon is working to maintain sufficient stocks of Thaad, Patriot, and Standard Missile interceptors being used to defend against Iranian missiles and drones, with Thaad systems deployed to Israel, Jordan, South Korea, and Guam. Patriots intercept lower-flying threats, while SM-3s can hit ballistic missiles above the atmosphere.

Michael Gordon and Shelby Holliday Wall Street Journal
Date Posted:

The US is running down its interceptor stock, given the pace of use since 2024. The WSJ notes, “If the war drags on and more interceptors are needed, the Pentagon would need to decide whether to access stockpiles in the Pacific.”

Are missile interceptor stocks limiting U.S. air defense operations?

Core argument: A major Pentagon concern is maintaining sufficient Thaad interceptor stocks, as U.S. forces also operate the system in South Korea and Guam to deter North Korea and China.

The Thaad antimissile system was deployed to Israel in 2024, along with the U.S. Army troops to operate it, as the Biden administration sought to protect the country against Iran. A Thaad has also been deployed to Jordan, where many U.S. combat aircraft are now deployed. A major concern for the Pentagon is to maintain a sufficient stock of interceptors for the Thaad, which U.S. forces also operate in South Korea and Guam, to deter North Korea and China. The Pentagon is also racing to replenish stocks of Patriot and Standard Missile interceptors, which also take out aerial threats and are being used to defend against Iranian missiles and drones. Patriots take out lower-flying threats, while SM-3s can intercept ballistic missiles above the Earth’s atmosphere.

Takeaways by Macro Roundup® AI

  1. A major Pentagon concern is maintaining sufficient Thaad interceptor stocks, as U.S. forces also operate the system in South Korea and Guam to deter North Korea and China.
  2. The Biden administration deployed a Thaad antimissile system and U.S. Army troops to operate it to Israel in 2024, with another Thaad sent to Jordan, where many U.S. combat aircraft are now based.
  3. The Pentagon is racing to replenish Patriot and Standard Missile interceptors used against Iranian missiles and drones, with Patriots taking out lower-flying threats and SM-3s intercepting ballistic missiles above the Earth's atmosphere.

Related Articles:

  • Israel’s 12-Day War Revealed Alarming Gap in America’s Missile Stockpile — US THAAD missile-defense operators fired more than 150 interceptors against Iranian ballistic missiles, nearly a quarter of the roughly 650 the Pentagon has purchased at about $13m each. Replenishing that stock would likely take over a year and cost $1.5bn–$2bn, according to a defense-procurement researcher's estimate, while the manufacturer says it can make about 100 interceptors this year.
  • The West’s Insatiable Demand for Missiles Is Boosting U.S. Weapons Makers — U.S. weapons makers are reporting rising missile sales, with Lockheed Martin's missiles and fire control division up 11% and RTX's Raytheon unit up 8%, and Raytheon's order backlog reaching $63.5bn. The U.S. Army asked Lockheed to quadruple PAC-3 missile output, while Northrop Grumman expects to produce 25,000 solid rocket motors annually by 2029, up from 13,000.
  • Defence Groups Bet Big On Drone-Destroying Laser Weapons — Major defense contractors including RTX, MBDA, and QinetiQ are investing heavily in high-energy laser weapons to destroy drones, a technology long regarded as science fiction. Britain's Ministry of Defence says its DragonFire laser will be deployed on Royal Navy ships five years ahead of schedule, firing at roughly £10 a shot.