Edward Conard

Top Ten New York Times Bestselling Author

  • “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
  • “…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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…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
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Thursday, February 26, 2026

AI Summary. Real GDP data show the US economy growing substantially faster than the European Union's, yet on a purchasing-power basis adjusting for price levels, the EU economy remains only slightly smaller than the US, as it was earlier. The author argues US dominance in information technology, where productivity growth is rapid and passed on as lower prices, reconciles the two measures.

Paul Krugman Krugman Wonks Out
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Since the US leads in the high-growth tech sectors, real GDP comparisons show Europe falling far behind. Yet PPP-adjusted gaps have barely moved. Europe’s GDP shortfall does not mean lower living standards because US gains show up in lower world prices.

Does faster US real GDP growth mean higher living standards than Europe's?

Core argument: Real GDP data show the U.S. growing substantially faster than the EU, while GDP measured at purchasing power parity shows the EU economy only slightly smaller than the U.S. economy in both 2007 and 2024.

Real GDP growth [2nd chart in gallery] shows the U.S. growing substantially more than the EU. So US economic growth is outpacing growth in Europe, and Europe needs to address its lag. Not so fast. The third comparison (featured image) shows GDP at PPP - i.e. using the same prices for goods in the EU and the US, [thus accounting] for differences in the overall price level. By this measure, in 2007 the EU economy was slightly, but only slightly, smaller than the U.S. economy. By 2024 the EU economy was still slightly smaller than the U.S. economy. The second and third charts look contradictory. One says that in real terms the US economy has grown much faster than the EU economy. The other says that in real terms the two economies have stayed roughly equal in size. Those statements can’t both be true, can they? Actually, they can. The EU and US economies produce different mixes of goods, with the US dominating information technology industries, which have also seen much faster productivity growth than other industries. And this difference in industrial mix causes differences in real GDP growth that aren’t reflected in different trends in living standards. A situation in which the US dominates the sector with rapid technological progress, but this progress is passed on to everyone in the form of lower prices, will look just like what we see for the US/EU comparison in practice.

Takeaways by Macro Roundup® AI

  1. Real GDP data show the U.S. growing substantially faster than the EU, while GDP measured at purchasing power parity shows the EU economy only slightly smaller than the U.S. economy in both 2007 and 2024.
  2. The apparent contradiction between the two measures reflects different industrial mixes, with the U.S. dominating information technology industries that have seen much faster productivity growth than other sectors.
  3. Differences in industrial mix generate differences in measured real GDP growth that are not reflected in diverging trends in living standards, a pattern consistent with technological progress being passed on to everyone through lower prices.

Related Articles:

  • Europe’s Tech Lag: Does It Matter? — If technology producers face competition, faster measured productivity growth in a tech-specialized country is passed to consumers in both countries through lower prices rather than higher relative living standards. Real GDP per worker over 1998-2024 diverged more between California and the rest of the US than between the US and Europe, largely reflecting industry composition.
  • Ed Conard Debates Furman On “The Expected Value of Risk Taking” — A debate on U.S. fiscal policy argues that spending increases, rather than the tax increases needed to fund them, slow growth, and that higher taxes would reduce the expected value of America's innovative risk-taking. The argument holds that cutting debt below 100% of GDP is critical.
  • 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.

AI Summary. Firms with high price-to-earnings ratios show higher subsequent growth in earnings and in earnings relative to sales, even after controlling for firm-specific risk. Among manufacturing firms, high price-to-earnings firms also have higher research and development intensity, while larger firms have lower sales growth and lower research and development intensity.

Timo Boppart, Peter Klenow, Reiko Laski and Huiyu Li Stanford University
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P/E ratios capture innovation-driven markups (“idea rents”), Boppart et al suggest. High P/E manufacturing firms have higher growth in earnings and profitability, as well as higher R&D/Sales. As firms scale up, growth slows, and R&D intensity falls.

Do high price-to-earnings ratios predict faster earnings growth and research intensity?

Core argument: Firms with high price-to-earnings ratios show higher subsequent earnings growth at all horizons, a relationship that holds after controlling for firm-specific risk.

High P/E firms have higher subsequent growth of earnings and earnings/sales. Figure 1 [] plots the 5-year ahead earnings growth against current year P/E as a binned scatterplot. A high P/E ratio today predicts high subsequent earnings growth [even after] controlling for firm-specific risk. About half of the relationship (41% over a 5-year horizon) between earnings growth and P/(E + R&D) is accounted for by higher P/E ratios predicting higher growth in earnings relative to sales as opposed to predicting just higher sales growth. Figure 2 [] shows the underlying binned scatterplot. We use P/(E + R&D) instead of P/E to remove movements in E from the deduction of R&D expenditures. The analysis focuses on manufacturing firms where R&D data is better measured. At all horizons, higher price to earning ratios today predict higher subsequent earnings growth. The predictability of earnings and profitability growth by P/E ratios may be related to firms’ innovation. Among manufacturing firms for whom R&D is reliably reported, high P/E firms have higher R&D intensity (Figure 3). Firms with higher sales have lower sales growth and lower R&D intensity. High sales firms tend to have lower R&D intensity, as shown in Figure 4 []. Larger firms also have lower sales growth, as shown in Figure 5 for all firms and Figure 6 for manufacturing firms [].

Takeaways by Macro Roundup® AI

  1. Firms with high price-to-earnings ratios show higher subsequent earnings growth at all horizons, a relationship that holds after controlling for firm-specific risk.
  2. About 41% of the 5-year-horizon relationship between earnings growth and P/(E + R&D) is accounted for by high ratios predicting growth in earnings relative to sales rather than sales growth alone.
  3. Among manufacturing firms with reliably reported R&D, high P/E firms have higher R&D intensity, while firms with higher sales have both lower R&D intensity and lower sales growth.

Related Articles:

  • A Macroeconomic Perspective on Stock Market Valuation Ratios — The authors argue that a decline in labor's share of US corporate value added, combined with weak corporate investment, mechanically raises valuation-to-earnings ratios even without changes in expected returns or growth. They find corporate enterprise value rose alongside an equal-sized increase in free cash flow's share of value added.
  • 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.
  • Reconciling Macroeconomics and Finance for the U.S. Corporate Sector: 1929 to Present — Using integrated U.S. macroeconomic and financial accounts, the authors find that fluctuations in expected cash flows to corporate owners, rather than expected rates of return, have been the dominant driver of swings in U.S. corporate market valuations. They attribute most valuation fluctuations to changes in the share of corporate output flowing to owners as pure rent.

AI Summary. Low switching costs among artificial intelligence services have pushed companies to pass innovation gains to users, with a $20-per-month subscription price unchanged even as features and performance improved substantially. One analysis found GPT-4-equivalent performance now costs $0.40 per million tokens versus $20, equivalent to a 70% annual deflation rate.

Jason Furman New York Times
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Furman argues that the ease of switching between frontier LLMs implies that the leading firms likely won’t be able to build “moats”. He notes GPT-4-equivalent performance has seen a 70% annual deflation rate since 2022.

Do low switching costs force AI companies to pass gains to users?

Core argument: One analysis found that GPT-4-equivalent performance now costs $0.40 per million tokens versus $20 in late 2022, the equivalent of a 70% annual deflation rate.

This ease of switching has forced companies to pass the gains from innovation on to users. Free tiers now offer capabilities that recently would have seemed almost unimaginable. OpenAI pioneered a $20-per-month subscription three years ago, a price point many competitors matched. That price has not changed, even as features and performance have improved substantially. One recent analysis found that “GPT-4-equivalent performance now costs $0.40/million tokens versus $20 in late 2022.” That is the equivalent of a 70% annual deflation rate — remarkable by any standard, especially in a time when affordability has become a dominant public concern.

Takeaways by Macro Roundup® AI

  1. One analysis found that GPT-4-equivalent performance now costs $0.40 per million tokens versus $20 in late 2022, the equivalent of a 70% annual deflation rate.
  2. OpenAI's $20-per-month subscription, pioneered three years ago and matched by many competitors, has not changed in price even as features and performance improved substantially.
  3. Ease of switching between AI providers has forced companies to pass innovation gains on to users, with free tiers now offering capabilities that recently would have seemed almost unimaginable.

Related Articles:

  • S&P 500 Margin Expansion All Coming from Tech — All of the increase in the S&P 500's operating margin over the past 20 years has come from tech-related sectors — information technology, communication services and consumer discretionary — while operating margins for non-tech companies have stayed near 9%.
  • Data Update 6 for 2026: In Search of Profitability! — Corporate profit margins have trended upward across roughly three decades of company data. The author attributes the increase largely to a shift in market composition, as technology companies with superior unit economics and economies of scale supplant manufacturing and service businesses.
  • 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.

AI Summary. The author argues that companies are collectively over-investing in artificial intelligence and that markets will correct when that belief dissipates. Because debt, particularly private credit, now finances much of this investment, the author contends a correction would spread beyond equity holders and produce a banking-style crisis driven by non-bank lenders.

Aswath Damodaran Musings on Markets
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Damodaran argues that the private credit industry’s increasing financing of the AI buildout is another sign that “a shakeout is overdue, which will separate the sloppy lenders from the good ones, and perhaps shrink private credit to healthier levels.”

Does debt financing of AI investment spread losses beyond shareholders?

Core argument: Damodaran contends that companies are collectively over-investing in AI, driven by what he calls the big market delusion, and that markets will have to correct when that delusion dissipates.

The coming together of [two storylines] on AI and private credit comes with a risk that may extend well beyond the players in these spaces. If you agree with my contention that companies are collectively over- investing in AI, driven by the big market delusion, there will be a time when that delusion dissipates and markets will have to correct. In an all or mostly-equity driven space, the pain will be borne by shareholders or owners of these companies, but while painful to them, its ripple effects will be limited. When debt enters the picture, as it has in the AI investment space, the effects of a correction will no longer be isolated to equity investors in these companies, and as private credit gets repriced (from the marking of debt down to reflect higher default risk), the pain to the rest of the economy increases. In effect, we will have a banking crisis created primarily by non-banking lenders behaving badly.

Takeaways by Macro Roundup® AI

  1. Damodaran contends that companies are collectively over-investing in AI, driven by what he calls the big market delusion, and that markets will have to correct when that delusion dissipates.
  2. In an all-equity or mostly-equity financed space, Damodaran argues the pain of an AI correction would fall on shareholders and owners, with limited ripple effects beyond them.
  3. Because debt has entered AI investment, Damodaran argues a correction that marks private credit down to reflect higher default risk would spread pain to the rest of the economy, producing a banking crisis created primarily by non-bank lenders.

Related Articles:

  • Alphabet Sells Almost $32 Billion Bonds as Tech Races to Fund AI — Alphabet raised almost $32bn of debt across dollar, sterling, and Swiss franc offerings, including an ultra-rare 100-year sterling note, reflecting the funding needs of tech firms building artificial intelligence capacity. Demand was strong, with US tranches drawing more than $100bn of orders and the century bond nearly 10x oversubscribed.
  • 2026 Credit Outlook: From Scarcity to Selection—The Return of a Buyer’s Market — Capital spending by Amazon, Meta, Oracle, Alphabet and Microsoft has tripled since 2023, and sell-side forecasts project more than $2.7tn of cumulative outlays through 2029, mostly tied to AI infrastructure. These programs, initially funded largely from internal cash flow, are shifting toward debt, with the companies pricing roughly $90bn of bond deals.
  • AI Capex – Financing The Investment Cycle — 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.

AI Summary. European defense officials argue that small, cheap drones have proven as effective as heavy armour in Ukraine, but stockpiling millions of them risks holding weapons made obsolete within months by new software, radio frequencies, and autonomous navigation. Drones that dominate one week can be jammed or outclassed the next.

Charles Clover, Sylvia Pfeifer, Laura Pitel and Christopher Miller Financial Times
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Military drones have a high rate of obsolescence, reducing the value of stockpiling drones in the manner of other munitions. Finland’s defence minister argues that Nato countries must increase productive capacity and be prepared to “scale it up fast.”

Should militaries stockpile drones that become obsolete within months?

Core argument: Finland's defence minister Antti Häkkänen said stored drones "might be out of date a month after you store them," and that older models are neither accurate nor useful as software, radio control frequencies and autonomous navigation advance.

The war in Ukraine has proved that small, cheap drones can be as effective as heavy armour. But this has also exposed a dilemma: by the time a country has bought and stored millions of drones, many may already be obsolete — overtaken by new software, radio control frequencies or advances in autonomous navigation. “You don’t need the old models, right? They are not accurate or useful,” Finland’s defence minister Antti Häkkänen said, “and they might be out of date a month after you store them.” Häkkänen said the Ukrainian war had shown that “you have to have rapid adaptation of rapidly developing technology and then scale it up fast”. First-person-view quadcopters and longer-range autonomous strike drones depend on software updates, secure communications links and supply chains that can shift in months or days. A model that dominates one week can be electronically jammed or tactically outclassed by the next.

Takeaways by Macro Roundup® AI

  1. Finland's defence minister Antti Häkkänen said stored drones "might be out of date a month after you store them," and that older models are neither accurate nor useful as software, radio control frequencies and autonomous navigation advance.
  2. The war in Ukraine has shown that small, cheap drones can be as effective as heavy armour, while exposing the dilemma that millions of drones bought and stored may already be obsolete.
  3. First-person-view quadcopters and longer-range autonomous strike drones depend on software updates, secure communications links and supply chains that can shift in months or days, and a dominant model can be jammed or tactically outclassed within a week.

Related Articles:

  • Why Every Country Needs To Master The Electric Tech Stack — Drones are the foundation of hard power in the early 21st century, so a country unable to produce them domestically is at a disadvantage. As electric motors overtake combustion engines as the core technology that makes machines move, the same supply chains and production processes used for electronics can also produce cars, drones, robots, and appliances.
  • ‘We Do Fail … a Lot’: Defense Startup Anduril Hits Setbacks With Weapons Tech — Defense startup Anduril has hit setbacks across several weapons programs, including engine damage to its unmanned Fury jet fighter in a ground test, a 22-acre fire caused by a counterdrone system test, and software that struggled to command unmanned boats. Former employees report its systems in Ukraine proved vulnerable to jamming.
  • Drones Are Key to Winning Wars Now. The U.S. Makes Hardly Any — China's DJI accounts for about 70% of commercial drones sold globally, and industry experts estimate its output far exceeds that of any other manufacturer, with capacity in the millions of drones a year. About 500 US companies manufacture drones, producing fewer than 100,000 annually, according to an industry association.

AI Summary. The US Department of Defense plans to spend an additional $12.6bn on surveillance of China's military maneuvers, submarines and satellites, part of nearly $152bn allocated separately from the $893bn fiscal 2026 defense spending measure. The plan includes $1bn for classified offensive cyber operations and $1bn for the Space Force's operation of Boeing's classified X-37B orbital vehicle.

Anthony Capaccio and Roxana Tiron Bloomberg
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The Pentagon is spending an additional $12.6B on expanding surveillance of Chinese submarines and spacecraft. $1B was also included for operations of Boeing’s classified X-37B spacecraft.

How much is the Pentagon adding to surveillance of China's military?

Core argument: The Pentagon plans to spend an additional $12.6 billion to improve surveillance of China's military maneuvers, submarines and satellites, according to an 85-page document sent to Congress and obtained by Bloomberg.

The Pentagon plans to spend an additional $12.6 billion to improve surveillance of China’s military maneuvers, submarines and satellites. The China-focused expenditures are detailed in a new 85-page document sent to Congress earlier this month that spells out how the Department of Defense plans to allocate almost $152 billion passed in last year’s massive tax-and-spending package. That’s separate from the formal $893 billion fiscal 2026 defense spending measure Congress passed in January. The spending document obtained by Bloomberg features a variety of intelligence and surveillance improvements aimed mostly at keeping a close eye on China’s increasingly sophisticated military buildup. It has $1 billion to improve classified “offensive cyber operations.” There’s another $1 billion of unspecified expenditures for the US Space Force’s operation of Boeing’s classified X-37B “Orbital Test Vehicle,” although there has been little public explanation of its mission.

Takeaways by Macro Roundup® AI

  1. The Pentagon plans to spend an additional $12.6 billion to improve surveillance of China's military maneuvers, submarines and satellites, according to an 85-page document sent to Congress and obtained by Bloomberg.
  2. The China-focused spending comes out of almost $152 billion passed in last year's tax-and-spending package, separate from the $893 billion fiscal 2026 defense spending measure Congress passed in January.
  3. The Pentagon document allocates $1 billion to classified "offensive cyber operations" and another $1 billion of unspecified expenditures for the US Space Force's operation of Boeing's classified X-37B "Orbital Test Vehicle.".

Related Articles:

  • It’s Not a Space Race, It’s the Space Olympics — The US operates 81% of commercial satellites in orbit and 86% of global effective launch capacity, with NATO allies second in satellites at 11% and China second in launch capacity at 9%. China is pursuing mega satellite constellations and reusable rockets, in many cases copying approaches already proven by US companies.
  • The New Frontier for Drone Warfare Is Deep Underwater — New underwater drones can dive thousands of feet and operate for days with little human intervention, which advocates say suits them to intelligence gathering, protecting undersea infrastructure, and countering threats in the Pacific. Boeing is delivering five 85-foot Orca vehicles to the US Navy, and Australia is developing Ghost Shark with Anduril.
  • Ukraine Claims Strike On Russian Submarine With Underwater Drones — Ukraine's Security Service says it used underwater drones alongside the Ukrainian Navy to strike a Russian Kilo-class submarine, vessels valued at about $400mn, and estimates sanctions and limited access to high-tech components could push replacement costs to $500mn.

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
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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
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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.

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