“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
“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
“…a 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 very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
“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 full-throated defense of economic dynamism.” - The Wall Street Journal
“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
AI Summary.Inflation-protected U.S. Treasury yields rose from about 3.5% in early 1997 to about 4.5% by 2000, compared with roughly 2.4% on the 10-year and 3% on the 30-year today. The author argues that this 1990s experience helps calibrate expectations if new software technologies produce a comparable acceleration in productivity growth.
Matt KleinThe Overshoot
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Klein compares measures of real rates from the 1990s productivity boom to today’s real rates, using TIPS, as well as “synthetic TIPS” derived by subtracting inflation expectations from nominal rates. Current real rates are very low by comparison.
Would faster productivity growth from new software technologies push real yields higher?
Core argument: Real yields on TIPS were roughly 3.5% when the securities were introduced at the start of 1997 and rose gradually to about 4.5% by the peak of the bubble in 2000.
Real yields on actual TIPS were ~3.5% when they first arrived at the beginning of 1997, and then rose gradually to ~4.5% by the peak of the bubble in 2000. Yields on “synthetic” TIPS derived by removing estimates of inflation expectations from nominal yields were also around 3.5% in early 1997 and 4.5% in the first half of 2000, though they were more volatile in between. The yield on the benchmark 10y TIPS is currently 2.4% while the yield on the 30y TIPS is around 3%. Knowing what actually happened in the 1990s is helpful for calibrating expectations about what could happen in the next decade, if new software technologies lead to a comparable acceleration in productivity growth.
Takeaways by Macro Roundup® AI
Real yields on TIPS were roughly 3.5% when the securities were introduced at the start of 1997 and rose gradually to about 4.5% by the peak of the bubble in 2000.
"Synthetic" TIPS yields, derived by stripping estimates of inflation expectations out of nominal yields, also stood near 3.5% in early 1997 and 4.5% in the first half of 2000, with more volatility in between.
The benchmark 10-year TIPS yields 2.4% and the 30-year TIPS around 3%, while the 1990s experience offers a guide for calibrating expectations if new software technologies deliver a comparable acceleration in productivity growth.
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AI, Productivity, and Rates: Part I— A San Francisco Federal Reserve model estimates that the growth contribution from rising resource utilization in recent quarters has been larger than in almost any comparable five-quarter stretch since 1947 outside recoveries from downturns. That measure is based on a modified version of the average worker's weekly hours rather than unemployment or capacity utilization.
AI and Productivity— The recent pickup in US labor productivity appears driven by higher utilization of existing capital—running factories, server racks, and hotel rooms harder—rather than by firm-level efficiency gains from AI. Adoption remains too thin and the cross-sectional evidence too weak to conclude that AI-driven productivity gains are already widespread.
Have We Entered an Era of High Productivity Growth?— Labor productivity has grown solidly while the San Francisco Federal Reserve's total factor productivity index, which adjusts for the equipment and technology workers use, has grown modestly, suggesting gains so far reflect better tools rather than broader advances. A regime-switching model puts the probability of a high-productivity regime at 57% using labor productivity and 21% using total factor productivity.
AI Summary.Measured total factor productivity growth is estimated to come almost entirely from higher input utilisation rather than underlying efficiency gains, based on a method that infers unobserved capital and labour utilisation from movements in hours per worker. On this evidence, recent productivity gains reflect "working harder" rather than "working smarter.
Shane Boyle, John Fernald and Huiyu LiCenter For Economic and Policy Research
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US labor productivity has accelerated, with output per hour growing at a mean annual rate of 2.5% btw 2023–2026Q1, ~1pp above its 2005–2019 pace. The gains have largely been driven by higher input utilisation, which is ‘inherently temporary.”
Does higher input utilisation explain recent measured productivity growth?
Core argument: Since the beginning of 2024, utilisation growth accounts for essentially all measured total factor productivity growth, suggesting the measured productivity gains derive from "working harder" rather than "smarter".
Input utilisation is not observed directly for the entire economy; it must be inferred. Consider a firm that wants to meet strong demand but has a given capital stock, workforce, and technology. It can ask its existing workers to work longer (which we observe). It can also run its capital longer. Each margin is costly, for example, overtime pay, so firms typically use all of them at once. The observed margin serves as a proxy for the unobserved ones. The method infers changes in industry utilisation from observed movements in hours per worker, scaled by an estimated pass-through of those movements into labour productivity. Industry estimates are aggregated using Domar weights, which reflect each industry’s importance. The stacked bars in Figure 2 show measured TFP growth split into [Fernald's] measure of utilisation growth in light grey and utilisation-adjusted TFP growth in dark grey. In 2023, utilisation growth was a drag on measured TFP growth, and utilisation-adjusted TFP growth soared. Since the beginning of 2024, however, utilisation accounts for essentially all TFP growth. For now, the measured productivity gains appear to derive from “working harder” rather than “smarter.”
Takeaways by Macro Roundup® AI
Since the beginning of 2024, utilisation growth accounts for essentially all measured total factor productivity growth, suggesting the measured productivity gains derive from "working harder" rather than "smarter".
In 2023, utilisation growth was a drag on measured TFP growth while utilisation-adjusted TFP growth soared, according to Fernald's decomposition of measured TFP.
Economy-wide input utilisation is not observed directly and is inferred from movements in hours per worker, scaled by an estimated pass-through into labour productivity, with industry estimates aggregated using Domar weights.
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Productivity During and Since the Pandemic— Total factor productivity growth since early 2021 has run only slightly above its 2010–19 average, suggesting the 2020 productivity surge reflected cyclical dynamics layered on a continuation of the slow pre-pandemic trend. Productivity has since grown somewhat faster than the authors' analysis predicted, but remains well below the 1995–2004 pace.
The Impact of AI on the U.S. Labor Market— Using observed AI usage data across 321 U.S. occupations, the authors estimate that highly exposed occupations saw a 6.7% decline in real wage growth with no detectable employment effects. The estimated declines are concentrated among the lowest earners, with service workers down 24.3% and the bottom wage quartile down 10.7%, while top earners show no significant effect.
Why Wages And Productivity Look Set To Diverge Further— In the US, Europe and Japan, pay growth has decoupled from productivity growth, with productivity pulling ahead. US labor productivity, measured as real GDP per hour worked, is more than 5x its 1947 level while real hourly compensation is only about 3x, and median wage growth lags even further behind.
AI Summary.In the US, Europe and Japan, pay growth has decoupled from productivity growth, with productivity pulling ahead. US labor productivity, measured as real GDP per hour worked, is more than 5x its 1947 level while real hourly compensation is only about 3x, and median wage growth lags even further behind.
Joel SussFinancial Times
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In advanced economies, increases in labor productivity growth have decoupled from real wage growth, especially post-1980.
Are wages falling further behind productivity growth in advanced economies?
Core argument: US labour productivity, measured as real GDP per hour worked, is more than five times its 1947 level, while real hourly compensation is only about three times greater.
In the US, Europe and Japan, pay growth has decoupled from productivity growth, with the latter having pulled ahead. US Labour productivity — measured as real GDP per hour worked — is now more than five times greater than in 1947, whereas real hourly compensation is only about three times greater. Median wage growth has lagged even further behind productivity growth, with inequality pushing the average wage higher than the median. (The figures above show average rather than median wages; plotting median wages would show an even greater divergence.)
Takeaways by Macro Roundup® AI
US labour productivity, measured as real GDP per hour worked, is more than five times its 1947 level, while real hourly compensation is only about three times greater.
Pay growth has decoupled from productivity growth in the US, Europe and Japan, with productivity pulling ahead in all three.
Median wage growth has lagged productivity growth by even more than average wage growth, as inequality pushes the average wage above the median.
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The Record Divide Between Corporate Profits and Worker Pay— Labor's share of gross domestic income fell to 51%, the lowest since records began in 1947, while profits' share rose to 12.1%, the highest since 1950. Inflation-adjusted hourly wages are up 3% since the end of 2019, compared with a 50% rise in profits.
AI and Productivity— The recent pickup in US labor productivity appears driven by higher utilization of existing capital—running factories, server racks, and hotel rooms harder—rather than by firm-level efficiency gains from AI. Adoption remains too thin and the cross-sectional evidence too weak to conclude that AI-driven productivity gains are already widespread.
Understanding Trends in Worker Pay over the Past 50 Years— Productivity growth has been unequal across industries, across firms within industries, and across workers within firms, slowing growth in both the productivity and the pay of the median worker. The authors argue that working- and middle-class men earlier received "breadwinner rents"—pay above their marginal value to employers—and then endured slow wage growth as women's workforce participation rose.
AI Summary.About 73m US households hold retirement accounts, mostly defined-contribution plans whose balances have risen $6.7tn, and 45m households account for nearly $15tn in annual outlays, close to 3x Germany's economy and 70% of China's GDP. This group's spending has sustained faster growth than comparably wealthy economies.
Jason ThomasCarlyle
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Citing the spending of the top 45mm US households, Jason Thomas argues that US economic growth could be characterized less as ‘k-shaped’ than “travelling at two speeds, one roughly the same rate as Europe’s and another that’s racing far ahead.”
Does retirement wealth explain why US spending outpaces peer economies?
Core argument: Balances in US defined-contribution retirement plans have risen by $6.7tn since the start of 2019, a 12.7% annually compounded gain, with roughly 73 million US households holding retirement accounts.
Roughly 73 million US households have retirement accounts (primarily defined-contribution plans like 401ks) that consist primarily of claims on businesses whose revenue growth and market values provide another hedge against inflation. Balances in defined contribution plans have increased by $6.7 trillion (+12.7%, annually compounded) since the start of 2019. US personal savings rates have fallen sharply over the past year (from 5.5% in April 2025 to 3% in May 2026) but that seems entirely rational. If your retirement balance is far above where you expected it to be, why not spend a bit more of your current income than previously intended? If we net across these overlapping cohorts and exclude recent first-time home purchases, we’re left with 45 million households that combine to account for nearly $15 trillion in annual outlays. That’s an extraordinary sum, equal to nearly 3x the size of the entire German economy and 70% of the GDP of China. And this third of the population has not only been insulated from the inflation shock but also exhibits the propensity to spend out of wealth and income to an extent that’s sustained a far higher rate of GDP growth than observed in economies with comparable living standards.
Takeaways by Macro Roundup® AI
Balances in US defined-contribution retirement plans have risen by $6.7tn since the start of 2019, a 12.7% annually compounded gain, with roughly 73 million US households holding retirement accounts.
Netting overlapping cohorts and excluding recent first-time home purchases leaves 45 million US households accounting for nearly $15tn in annual outlays, equal to nearly 3x the German economy and 70% of China's GDP.
The US personal savings rate fell from 5.5% in April 2025 to 3% in May 2026, a decline the article argues is rational when retirement balances sit far above expectations.
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K-Shaped Economy?— Available spending data does not support the narrative of a bifurcated "K-shaped" consumer economy: surveys show households earning under $50,000 reported spending growth of 5%, versus 4.6% for those earning over $100,000. Government data show the top income decile's share of aggregate spending at 22.8%, down from 23.4% a year earlier.
The K-Shaped Economy’s Defining Statistic Has Some Problems— The widely cited estimate that the top 10% of US earners account for 45% of consumer spending comes from a method combining Federal Reserve survey and financial-accounts data. Its author says he is more confident in the trajectory—a significant, consistent rise in the top 10% and 20% shares over 30–35 years—than the level.
The Two Europes— The International Monetary Fund projects Eastern European economies will close much of the gap with US per capita GDP — Poland from 34% to 67%, Romania 27% to 60%, Lithuania 29% to 69% — while Western Europe slips, with France falling from 86% to 71% and Italy from 93% to 68%.
AI Summary.Using 5.1m product listings from Sears catalogs, the authors construct a quality-adjusted price index implying much lower goods inflation for 1900–1990 than standard deflators, with real goods consumption growing 39x rather than 10.3x. They estimate faster growth before World War II (5.4% a year, 1900–1939) than after (4.2%, 1946–1980).
Verónica Bäcker-Peral and Benjamin WittenbrinkMassachusetts Institute of Technology
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Using 5.1mm Sears catalog listings and LLM-based hedonic estimation, this study finds real goods consumption grew 39-fold from 1900 to 1990, not 10.3-fold as official data imply, with the largest mismeasurement concentrated before WWII.
Does quality-adjusted pricing show faster goods consumption growth before the war?
Core argument: Using a quality-adjusted price index built from 5.1 million Sears catalog listings, the authors estimate real goods consumption grew by a factor of 39 between 1900 and 1990, compared with a factor of 10.3 using standard goods deflators.
Measuring real GDP growth requires distinguishing changes in prices from changes in product quality... systematic quality adjustment. price indexes are unavailable for much of the twentieth century. We construct a new quality-adjusted price index using 5.1 million product listings from Sears catalogs, 1900–1990. The resulting cost-of-living index implies substantially lower goods inflation than conventional deflators between 1900 and 1990, real goods consumption grew by a factor of 39 using our index,compared with a factor of 10.3 using standard goods deflators. Figure 5 shows our estimates of the cost-of-living index for consumer goods in the solid red line. The dashed black line shows average cumulated price changes for the same sample of consumer goods. The gap.is largest before World War II, reversing the conventional view that goods consumption growth was slower before 1945 than in the post-war decades.As Gordon puts it, 'the history of price changes from 1914 to 1947 [is] the black hole where little is known.' This paper sheds light on that black hole. We estimate average annual real goods consumption growth of 5.4% for 1900-1939 and 4.2% for 1946-1980... the era of fastest growth was in the prewar, not postwar, contrary to conventional estimates.
Takeaways by Macro Roundup® AI
Using a quality-adjusted price index built from 5.1 million Sears catalog listings, the authors estimate real goods consumption grew by a factor of 39 between 1900 and 1990, compared with a factor of 10.3 using standard goods deflators.
The authors estimate average annual real goods consumption growth of 5.4% for 1900–1939 and 4.2% for 1946–1980, implying the fastest growth came in the prewar rather than postwar era, contrary to conventional estimates.
The new cost-of-living index implies substantially lower goods inflation than conventional deflators, with the gap largest before World War II, a period Gordon describes as "the black hole where little is known.".
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European vs. U.S. Economic Performance: An Update— Productivity growth from 2000-2019 was higher in the US than in western Europe, but almost half the gap disappears when information and communications technology is excluded, even though tech was 9.2% of US output versus 5.4% in the EU. The author estimates this difference in industrial mix accounts for roughly 40% of the overall productivity growth gap.
Is The Great Stagnation Actually Just a ‘So-So’ Stagnation?— Long-running U.S. tests show population average reading scores moved from 255 to 256 out of 500 and math from 266 to 271, despite educational attainment rising more than three years. The author argues that if added schooling has not raised productivity, measured total factor productivity growth has been understated, shrinking the apparent "Great Stagnation" by about a third.
AI Summary.As labor force participation falls, a shrinking group of workers generates the income, taxes, and innovation supporting a growing number of non-workers, leaving the economy more fragile because labor shocks are concentrated among fewer participants. Labor scarcity raises the return on automation, robotics, and software, making growth depend on productivity rather than participation.
Paul KedroskyApplied Complexity
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Overall LFP is at a 50-year low. Kedrosky warns, “As fewer adults work or seek work, a larger fraction of voters experience the economy mostly as consumers, retirees, or rentiers, not as workers…[which] changes incentives around….taxation and redistribution.”
How does falling labor force participation reshape growth and fragility?
Core argument: Falling labor force participation leaves a shrinking core of workers generating the income, taxes, and innovation that support a growing number of non-workers, and makes the economy more fragile because labor shocks are concentrated among fewer participants.
As fewer adults work or seek work, a larger fraction of voters experience the economy mostly as consumers, retirees, or rentiers, not as workers. That changes political incentives around wages, immigration, AI, taxation, and redistribution. The economy becomes increasingly dependent on a shrinking core. A shrinking group of workers generates the income, taxes, and innovation that support a growing number of non-workers. The economy becomes more fragile because labor shocks are concentrated among fewer participants. Capital must increasingly substitute for labor. Labor scarcity raises the return on automation, AI, robotics, and software. The AI bet becomes as much about compensating for workers' absence as simple replacement. Growth increasingly depends on productivity, on not participation. Any [productivity] miss will be much more consequential than in the past, given that labor no longer picks up the slack.
Takeaways by Macro Roundup® AI
Falling labor force participation leaves a shrinking core of workers generating the income, taxes, and innovation that support a growing number of non-workers, and makes the economy more fragile because labor shocks are concentrated among fewer participants.
As more voters experience the economy as consumers, retirees, or rentiers rather than workers, political incentives shift around wages, immigration, AI, taxation, and redistribution.
Labor scarcity raises the return on automation, AI, robotics, and software, making the AI bet as much about compensating for workers' absence as replacing them, with growth depending on productivity rather than participation and any productivity miss more consequential than in the past.
Related Articles:
Baby Busts and Growth Booms: Demographic Change and the Macroeconomy— A 1pp lower birth rate 20 years earlier is associated with 22 log points higher output per worker 20 years later and 29 log points higher after 40 years, about 0.73pp faster annual growth. The authors find lower birth rates are also associated with more labor-saving patents, larger high-tech shares, and higher productivity growth.
Have We Entered an Era of High Productivity Growth?— Labor productivity has grown solidly while the San Francisco Federal Reserve's total factor productivity index, which adjusts for the equipment and technology workers use, has grown modestly, suggesting gains so far reflect better tools rather than broader advances. A regime-switching model puts the probability of a high-productivity regime at 57% using labor productivity and 21% using total factor productivity.
The Budget and Economic Outlook: 2026 to 2036— The Congressional Budget Office projects the federal deficit will grow from $1.9tn (5.8% of GDP) to $3.1tn (6.7%) over a decade, above the 3.8% averaged over the past 50 years, with rising net interest costs driving much of the increase. Federal debt held by the public is projected to rise from 101% to 120% of GDP.
AI Summary.Europe trains more engineering graduates per capita than China and more STEM PhDs than any region outside the United States, yet the only EU-born companies to reach $100bn market value in the past fifty years, Spotify and BioNTech, listed on US exchanges. Europe captures 6% of global AI startup funding versus 61% for the United States.
Mario KeputaSocial Science Research Network
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Despite top STEM talent and high savings, Europe captures just 6% of AI funding and lacks trillion-dollar firms. Between 2008 and 2021, ~30% of EU-founded unicorns relocated abroad, largely to the US, seeking deeper liquidity, higher valuations, and pro-growth regulation.
Why does Europe's world-class STEM talent fail to produce giant companies?
Core argument: Europe captures just 6% of global AI startup funding, versus 61% for the United States and 17% for China, despite training more engineering graduates per capita than China and more STEM PhDs than any region outside the U.S.
Europe produces more engineering graduates per capita than China. It trains more PhDs in STEM fields than any region outside the United States. Europe's universities rank among the world's best in dozens of disciplines. Europe's household savings rate exceeds that of America. Europe's research output, measured by publications and citations, is world-class. And yet the only EU-born companies to reach a market capitalisation of $100 billion in the past fifty years, Spotify and BioNTech, did so on the NYSE and Nasdaq respectively. Both chose American exchanges over European ones. None of the world's trillion-dollar companies is European. Europe captures just 6% of global AI startup funding, compared with 61% for the United States and 17% for China. Between 2008 and 2021, nearly 30% of European-founded unicorns relocated their headquarters abroad, overwhelmingly to the United States. They did not leave for the weather. They left because U.S. capital markets offered deeper liquidity, broader analyst coverage, higher valuations, and a regulatory environment designed for growth.
Takeaways by Macro Roundup® AI
Europe captures just 6% of global AI startup funding, versus 61% for the United States and 17% for China, despite training more engineering graduates per capita than China and more STEM PhDs than any region outside the U.S.
The only EU-born companies to reach $100bn market capitalisation in the past fifty years, Spotify and BioNTech, listed on the NYSE and Nasdaq respectively, and none of the world's trillion-dollar companies is European.
Nearly 30% of European-founded unicorns relocated their headquarters abroad between 2008 and 2021, overwhelmingly to the United States, where capital markets offered deeper liquidity, broader analyst coverage, higher valuations, and a regulatory environment designed for growth.
Related Articles:
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.
Do Adults Have the Skills They Need to Thrive in a Changing World?— An international assessment of adult skills describes numeracy proficiency levels ranging from counting objects and adding small whole numbers at the lowest level, to extracting information from tables and graphs and performing basic arithmetic with money and percentages at Level 1, up to analysing complex mathematical information and critically evaluating whether data support a claim at Level 5.
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.
