Edward Conard

Top Ten New York Times Bestselling Author

  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “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
  • “…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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…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
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “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 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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Wednesday, February 25, 2026

AI Summary. Using an econometric model extracting the common trend in real interest rates across advanced economies, the authors estimate that the global neutral real interest rate fell about 3.5 percentage points from 1990 to 2019, then rose about 1 percentage point after COVID, leaving global and U.S. estimates near 0.5%.

Marco Del Negro, Elena Elbarmi, and Michael Pham Federal Reserve Bank of New York
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Using a model that extracts common trends in multiple series, FRBNY estimates that both global and US r* rose by about 1pp post-COVID to ~0.5%. The neutral rate had fallen from 3% in the early 1990s to < 0% after the GFC, and even further in the 2010s.

How much has the global neutral real interest rate shifted?

Core argument: Global r* fell from about 3% in the early 1990s to below 0% after the financial crisis, continued declining through the 2010s, and then rose by about 1 percentage point after COVID, per an econometric model extracting the common real-rate trend across countries.

After the late 1980s, we can talk of a global r*, since the trends in real rates are one and the same across advanced countries [see charts in gallery]. We provide a measure of “global” r* using data on short- and long-term yields and inflation for several countries, based on an econometric model that extracts the common trend in real rates across all the countries in the sample. Global r* fell from about 3% in the early 1990s to below 0% after the financial crisis. It continued declining in the 2010s and then rose by about 1 percentage point after COVID. By and large, the U.S. r* has tracked global r* since the late 1980s, except that it declined comparatively more in the aftermath of the financial crisis. The dashed black line in the chart shows the posterior median of global r* with the shaded areas showing the 68 and 95% coverage intervals. The dotted black line shows the posterior median of U.S. r*.By 2024, the end of the sample, the Bayesian “median posterior” estimates of both global and U.S. r* are around 0.5% (more precisely, 0.31 and 0.46). The large posterior coverage intervals shown in the chart are there to remind us that extracting trend from cycle is a difficult task. [But although] the level of r* is very uncertain, the model is able to detect changes in r* over time with greater statistical confidence. The first row of the table [] reports the decline in global and U.S. r* from 1990 to 2019, by our calculations. The median estimate of the decline is about 3.5pp for both the world and the U.S. Although the exact magnitude of the decline is uncertain, there is no question statistically that such a decline in r* had taken place from the 1990s to before COVID.

Takeaways by Macro Roundup® AI

  1. Global r* fell from about 3% in the early 1990s to below 0% after the financial crisis, continued declining through the 2010s, and then rose by about 1 percentage point after COVID, per an econometric model extracting the common real-rate trend across countries.
  2. Median posterior estimates put both global and U.S. r* near 0.5% by 2024 — 0.31% and 0.46% respectively — with wide posterior coverage intervals underscoring the difficulty of separating trend from cycle.
  3. The median estimated decline in r* from 1990 to 2019 is about 3.5 percentage points for both the world and the U.S., and the authors judge the occurrence of such a decline statistically beyond question despite uncertainty about its exact magnitude.

Related Articles:

  • What Next for r*? A Capital Market Equilibrium Perspective On The Natural Rate of Interest — A capital-market equilibrium model estimates that the steady-state safe natural rate of interest across advanced economies has fallen from about 5% to about 0%, driven by slower growth, demographics, higher mark-ups, and rising risk premia. The author estimates that artificial-intelligence-driven growth and heightened inflation risk could each raise it by about 1 percentage point.
  • The Race Between Asset Supply and Asset Demand — The authors estimate that demand for assets has outpaced supply by roughly 400% of GDP versus 100%, making rising asset demand the leading contributor to falling interest rates. They project that debt sustainability requires fiscal consolidation exceeding 10% of GDP, though debt could reach 250% of GDP without raising interest rates.
  • Demographics, Wealth, and Global Imbalances in the Twenty-First Century — Because the elderly hold much more wealth than the young and on average do not draw it down much as they age, the authors' model projects no "great demographic reversal": population aging is estimated to push global rates of return down by about 1.07pp and raise global wealth from 456% to 498% of world GDP.

AI Summary. The share of S&P 500 stocks moving more than 10% in a single day has increased, and high dispersion alongside low implied correlation suggests stocks are trading more on their own fundamentals. Combined with extremely elevated options activity, these larger idiosyncratic moves leave market structure more vulnerable to an abrupt, outsized move.

Torsten Sløk Apollo
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An uptick in the share of S&P 500 firms moving >10% in a single day, with a lower correlation of returns across firms and bigger gaps between winners and losers, suggests that individual stocks “are increasingly trading on their own fundamentals.”

Do bigger single-stock swings leave market structure vulnerable to an abrupt move?

Core argument: The share of S&P 500 constituents moving more than 10% in a single day has risen, with high dispersion and low implied correlation suggesting stocks are increasingly trading on their own fundamentals.

The share of S&P 500 names moving more than 10% in a single day has increased, and high dispersion and low implied correlation suggest stocks are increasingly trading on their own fundamentals. At the same time, options activity remains extremely elevated, consistent with heavy retail speculation and leverage-like exposure. Larger idiosyncratic moves and outsized options participation leave the market structure more fragile and more vulnerable to an abrupt, outsized move.

Takeaways by Macro Roundup® AI

  1. The share of S&P 500 constituents moving more than 10% in a single day has risen, with high dispersion and low implied correlation suggesting stocks are increasingly trading on their own fundamentals.
  2. Options activity remains extremely elevated, consistent with heavy retail speculation and leverage-like exposure.
  3. Larger idiosyncratic single-stock moves combined with outsized options participation leave market structure more fragile and more vulnerable to an abrupt, outsized move.

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.
  • 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.
  • The Old Economy Begins To Take Its Revenge — The author argues that capital rotates between the financial economy's asset-light booms and the physical economy, with commodity capacity constraints and the use of critical materials as geopolitical leverage now making returns on physical investment more attractive. In this view, higher interest rates reflect the better returns and capital spending needed to expand production capacity.

AI Summary. Global stocks in the US-heavy MSCI World Index are up 2%, versus 9% excluding the US — shaping up as the worst year for US stocks relative to the rest of the world since at least 1995. Bank of America surveys show record investor allocation to euro assets.

Katie Martin Financial Times
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The MSCI World Index net US stocks is up 9% year to date, while the S&P 500 is slightly down, the biggest shortfall in US returns relative to the rest of the world since 1995. BofA investor surveys show the largest positive allocation to euro assets on record.

Are US stocks lagging the rest of the world by record margins?

Core argument: The MSCI World Index, heavily skewed toward the US, is up 2% so far in 2026, versus 9% excluding the US, shaping up to be the worst year for US stocks relative to the rest of the world since at least 1995.

Global stocks, measured in the widely tracked MSCI World Index and skewed heavily towards the US, are up by 2% so far in 2026. That’s decent. But if you strip out the US, you’re up a much rosier 9%. This is shaping up to be the worst year for US stocks compared with the rest of the world since at least 1995. Regular surveys of investors by Bank of America show the biggest positive allocation to euro assets on record in an impressive global rebalancing. The bank’s European survey shows over a third now hold a higher allocation to EU stocks than benchmarks would usually suggest, up from just 9% three months ago. A net 22% now say they hold a lower-than-benchmark allocation to the US, from just 6% at the end of 2025.

Takeaways by Macro Roundup® AI

  1. The MSCI World Index, heavily skewed toward the US, is up 2% so far in 2026, versus 9% excluding the US, shaping up to be the worst year for US stocks relative to the rest of the world since at least 1995.
  2. Bank of America investor surveys show the biggest positive allocation to euro assets on record, with over a third of European respondents holding above-benchmark allocations to EU stocks, up from 9% three months earlier.
  3. A net 22% of investors in Bank of America's survey report a lower-than-benchmark allocation to the US, up from 6% at the end of 2025.

Related Articles:

  • Foreigners Rebuff ‘Sell America’ and Buy a Net $1.6 Trillion in Assets — Treasury Department data show overseas investors bought a net $1.55tn of long-term US financial assets, up from $1.18tn the prior year, including $720bn in equities and just under $409bn in Treasury notes and bonds. China was a net seller of $208.6bn, with its Treasury holdings ending at $683.5bn.
  • 2026 Outlook: Tech Tonic — A Broadening Bull Market — Most major equity markets have outperformed the US, with Europe, China and Asia generating almost double US total returns in dollar terms and gains of 54% in Italy, 73% in Spain and 71% in Korea. US returns have been driven by strong earnings, particularly in technology, while Europe's have come largely from rising valuations.
  • American Unexceptionalism — The S&P 500 has outperformed other developed-market equities by a cumulative 150% over the past fifteen years, but the authors attribute about 80% of that gap to a strengthening dollar and expanding relative valuations rather than fundamentals such as dividends, buybacks, and organic growth. U.S. valuations sit around the 90th percentile on price-to-earnings measures.

AI Summary. Homeownership among married 30-year-olds has changed little (63% to 60%), and rose from 25% to 29% among single 30-year-olds living alone, while 30-year-olds living with parents are mostly male, never-married, and without a college degree. Among men without a college degree, the marriage rate fell from 58% to 36%.

Aziz Sunderji Home Economics
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The share of American 30-year-olds living with their parents or roommates nearly doubled btw 1990 and 2025, from 17% to 32%. Aziz Sunderji finds that this group is largely responsible for the age cohort’s 15pp decline in homeownership over that period.

Do falling marriage rates explain more 30-year-olds living with parents?

Core argument: Among men without a college degree, the group most likely to live with their parents, the marriage rate has fallen from 58% to 36%.

Among married 30-year-olds, the homeownership rate has barely budged—63% in 1990, 60% today. Among single 30-year-olds living alone, the homeownership rate actually rose, from 25% to 29%. The typical 30-year-old living at home is male (61%), has never been married (89%), and doesn’t have a college degree (73%). Only 27% have a bachelor’s, compared to 42% of all 30-year-olds. In the early 1990s the profile of those living at home at 30 looked nearly identical: 64% male, 77% never married, and less educated than average. [However], in the ’90s, a greater proportion of young, less educated men would have gotten married and moved out. Among men without a college degree—the group most likely to be living with their parents—the marriage rate has plunged from 58% to 36%.

Takeaways by Macro Roundup® AI

  1. Among men without a college degree, the group most likely to live with their parents, the marriage rate has fallen from 58% to 36%.
  2. Homeownership among married 30-year-olds has barely moved, from 63% in 1990 to 60% today, while among single 30-year-olds living alone it rose from 25% to 29%.
  3. The typical 30-year-old living at home is male (61%), never married (89%), and without a college degree (73%), with only 27% holding a bachelor's versus 42% of all 30-year-olds.

Related Articles:

  • Changes in Milestones of Adulthood — Among US young adults aged 25–34, the share completing a high school or college degree rose 9 percentage points to 83%, while the share ever married fell 18 points to 44% and the share living with a child fell 16 points to 39%. Economic milestones became more common as family formation milestones became less common.
  • What Explains Low Millennial Home Ownership? — At age 30, 31% of Millennials still live with parents or roommates versus 19% of Boomers, and only 61% of Millennial household heads are married versus 77% of Boomers; the analysis attributes most of the 18-percentage-point home ownership gap (25% versus 43%) to these two differences. Among married household heads, the ownership gap narrows to 8 points.
  • Young Adults Are Growing Increasingly Economically Dislocated — The share of young adults who are neither in education, employed, seeking work, nor caring for children is rising in many countries, among both young men and young women. Including stay-at-home parents in the standard "not in education, employment or training" measure obscures this increase.

AI Summary. South Korea's total fertility rate rose to 0.8, up from 0.75 and an all-time low of 0.72, which the national statistics agency attributes to a post-pandemic rebound in marriages and more favorable attitudes toward childbearing. The government's mid-range projection still implies a population decline of 10mn by 2067.

Daniel Tudor Financial Times
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South Korea’s fertility rate rose for the second consecutive year to .8, from its trough of .72 in 2023. The current level implies that 100 young Koreans today will have ~16 grandchildren.

Does a rising fertility rate reverse an expected population decline?

Core argument: South Korea's total fertility rate rose to 0.8 last year from 0.75 in 2024 and an all-time low of 0.72 in 2023, according to official data released Wednesday.

Korea’s total fertility rate — the average number of children a woman is expected to have over her lifetime — climbed to 0.8 last year, up from 0.75 in 2024 and an all-time low of 0.72 in 2023, official data released on Wednesday showed. Park Hyun-jung, director of population trends at Statistics Korea, attributed the rise to a rebound in marriages after the pandemic and improved perceptions around childbearing. Attitudes towards childbirth outside marriage — long a taboo — had also relaxed slightly, she said. In 2024, 5.8% of Korean children were born out of wedlock, up from 4.7% the year earlier. Jeong Jae-hoon, a professor at Seoul Women’s University, said the rise in births came from a relatively larger cohort of women born in the mid-1990s who were now at peak childbearing age. But women born in the 2000s made up a smaller group, he added, meaning that even if TFR rises to 1.27 — the Korean government’s mid-range projection — the overall population will decline by 10mn by 2067.

Takeaways by Macro Roundup® AI

  1. South Korea's total fertility rate rose to 0.8 last year from 0.75 in 2024 and an all-time low of 0.72 in 2023, according to official data released Wednesday.
  2. Park Hyun-jung, director of population trends at Statistics Korea, attributed the increase to a post-pandemic rebound in marriages and improved perceptions of childbearing; births outside wedlock reached 5.8% of Korean children in 2024, up from 4.7% a year earlier.
  3. Jeong Jae-hoon of Seoul Women's University said the rise in births came from a relatively larger cohort of women born in the mid-1990s, and that even if the fertility rate reaches the government's mid-range projection of 1.27, South Korea's population will decline by 10mn by 2067.

Related Articles:

  • Two Is Already Too Many — South Korea's low fertility rate reflects in part decades of government antinatalist policy: family planning centered on contraceptive distribution is estimated to have averted 1.8m–2.1m births by 1976 at about $103 per prevented birth in today's money. Fertility fell from six children per woman in 1960 to three by 1978.
  • The Case for Gradual Population Decline — South Korea's fertility rate fell below 1.7 in 1985 and its share of population aged 20-40 has fallen 20% since 2000, yet it ranked first in Bloomberg's Innovation Index and twelfth in a global soft power ranking. The author argues low fertility does not inevitably cause technological and cultural stagnation.
  • Depopulation Globally and in the Asia-Pacific: The Shape of Things to Come — Population aging and fertility below replacement levels are connected to a revolution in family structure in which families grow smaller, fewer people marry, and voluntary childlessness becomes common across countries. As a result, families become less able to bear the demands that may be placed on them.

AI Summary. A model estimates Russian casualties in the full-scale Ukraine war at 1.1m–1.4m, including 230,000–430,000 dead, equivalent to roughly one in 25 Russian men aged 18–49 killed or severely wounded. One estimate puts Ukrainian casualties at 600,000 with 100,000–140,000 dead—lower in absolute terms but a higher share of its population.

Economist Staff The Economist
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The Economist estimates one in 25 Russian men btw the ages of 18 and 49 have been killed or wounded in Ukraine since 2022. CSIS estimates Ukrainian casualties at one in 16. Russian losses are escalating; today it is “losing more men than it can recruit.”

How do Russian and Ukrainian war casualties compare?

Core argument: The Economist's model puts Russian casualties at 1.1m–1.4m, including 230,000–430,000 dead, implying that one in 25 Russian men aged 18–49 may have been killed or severely wounded since the full-scale war began.

Our model suggests that Russian casualties are now between 1.1m and 1.4m, of whom 230,000-430,000 are dead. That would mean one in 25 Russian men between the ages of 18 and 49 may have been killed or severely wounded since the start of the full-scale war. There are too few reliable estimates of Ukrainian deaths to construct a similar meta-estimate. One single estimate, published on January 27th by CSIS, a think-tank, put total Ukrainian casualties at 600,000 as of December, including 100,000-140,000 dead. Though much lower than Russia’s casualties in absolute terms, as a share of its population it is higher—equivalent to about one in 16 Ukrainian men aged 18-49 before the war. These figures exclude civilian deaths, for which reliable data are scarcer still. Ukrainian losses appeared heaviest early in the war: American officials estimated that 70,000 soldiers had already been killed by August 2023. Russia’s campaign, by contrast, has only grown bloodier. Some estimates suggest that it is now losing roughly 1,000 soldiers a day. Our modelling shows that as many may have died in the past year as in the first three combined. It is losing more men than it can recruit.

Takeaways by Macro Roundup® AI

  1. The Economist's model puts Russian casualties at 1.1m–1.4m, including 230,000–430,000 dead, implying that one in 25 Russian men aged 18–49 may have been killed or severely wounded since the full-scale war began.
  2. CSIS estimated total Ukrainian casualties at 600,000 as of December, including 100,000–140,000 dead, a lower absolute figure than Russia's but a higher share of population, equivalent to about one in 16 prewar Ukrainian men aged 18–49.
  3. Some estimates put Russia's losses at roughly 1,000 soldiers a day, and The Economist's modelling suggests as many may have died in the past year as in the first three combined, more men than Russia can recruit.

Related Articles:

  • Russian War Spending May Be Maxed Out — Despite large increases in value-added, excise, income, and social insurance taxes, deficits financed roughly two-thirds of the rise in Russia's consolidated budget spending, including more than 80% of the federal spending increase. Russian government debt remains very low relative to national income, yet officials plan slower nominal spending growth and no additional military and national security spending in ruble terms.
  • Russians Shun Putin’s Plea for More Babies as Population Shrinks — Russia's population decline has accelerated, with births falling 3.4% to 1.22m — the lowest level in roughly 25 years — while deaths rose 3.3% to 1.82m, according to Russia's Federal Statistics Service. The decline is attributed in part to Russia's war on Ukraine, though detailed mortality data has been classified and war deaths enter the statistics with long delays.
  • The Russian Paradox: So Much Education, So Little Human Capital — Russia is an exception to the global correspondence between educational attainment and human capital, combining an advanced educational profile with strikingly poor health outcomes and only weak contributions to knowledge production and skills-intensive service exports. World Health Organization estimates put male life expectancy at age 15 near that of the world's least developed countries.

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
Date Posted:

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
Date Posted:

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
Date Posted:

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.