Edward Conard

Top Ten New York Times Bestselling Author

  • “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 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
  • “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 full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…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 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
  • “…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 very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
Upside of Inequality Oxford Unintended Consequences

AI Summary. Prime-age (25–54) and older (55–64) employment rates in Europe exceed those in the U.S., disproving the claim that European welfare systems suppress work. Higher-welfare northern European countries tend to have higher employment rates than lower-welfare southern ones.

Chris Giles Financial Times
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Despite Europe’s high social spending relative to the US, Chris Giles notes that prime-age adult (25–54) labor force participation in the Eurozone has overtaken that of the US, and there has been a dramatic convergence in the LFP of older workers.

Does European welfare actually discourage work?

Core argument: Prime-age adults (25–54) and older workers (55–64) both achieve higher employment rates in Europe than in the U.S., refuting the premise that generous welfare systems suppress labor force participation.

It does not matter whether you use EU or Eurozone data, prime-age adults (between 25 and 54) in Europe are more likely to be in work than those in the US. Older people (between 55 and 64) also have higher employment rates in Europe. Younger people (between 15 and 24) are more likely to have a job in the US, but that results from Europeans educating themselves for longer. The proportion of young people not in education, employment or training is higher in the US than in Europe. So welfare is not stopping work. More than that, the higher-welfare north of Europe tends to have higher employment rates than the south, although there is convergence within the Eurozone. Spain, in particular, has enjoyed rapid improvements.

Takeaways by Macro Roundup® AI

  1. Prime-age adults (25–54) and older workers (55–64) both achieve higher employment rates in Europe than in the U.S., refuting the premise that generous welfare systems suppress labor force participation.
  2. The U.S. records a higher share of young people (15–24) not in education, employment, or training than Europe, indicating that lower U.S. youth employment reflects weaker human capital investment, not stronger labor markets.
  3. Within Europe, higher-welfare northern economies consistently outperform lower-welfare southern ones on employment rates, though intra-Eurozone convergence is underway, led by rapid gains in Spain.

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AI Summary. Deep-tech investment outside AI has exceeded $150bn since early 2024, surpassing the $133bn invested across the entire prior decade. Falling valuations for traditional software companies and outsized returns from early bets on capital-intensive ventures are pushing investors toward riskier, science-driven deals.

Tim Bradshaw Financial Times
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Since the start of 2024, more than $150B of venture capital has been invested into non-AI “deep tech” firms whose products are rooted in significant engineering advances, exceeding the $133B invested in such firms btw 2010 and 2019.

Are investors abandoning software for capital-intensive science bets?

Core argument: Deep-tech investment excluding AI exceeded $150bn since early 2024, surpassing the entire $133bn deployed across the prior decade (through end-2019), as falling valuations for traditional software push venture capital toward capital-intensive scientific bets.

The AI boom is fuelling a resurgence in ambitious “moonshot” bets, as early SpaceX backers’ huge returns and falling valuations for traditional software companies force tech investors to embrace riskier and more capital-intensive dealmaking. Excluding the giant sums ploughed into AI start-ups, global investment in “deep tech” — companies whose products are rooted in big scientific or engineering advances — has exceeded $150bn since the start of 2024, more than the $133bn in the entire decade to the end of 2019, according to Dealroom. This year’s deep-tech investments have not yet surpassed 2021’s peak, which was propelled by battery and electric vehicle deals for the likes of Rivian and Northvolt — many of which turned sour, highlighting the risks involved in moonshot dealmaking.

Takeaways by Macro Roundup® AI

  1. Deep-tech investment excluding AI exceeded $150bn since early 2024, surpassing the entire $133bn deployed across the prior decade (through end-2019), as falling valuations for traditional software push venture capital toward capital-intensive scientific bets.
  2. The 2021 deep-tech peak — driven by battery and electric vehicle deals including Rivian and Northvolt — has not yet been surpassed, and the subsequent losses from those deals underscore the capital destruction risk inherent in moonshot dealmaking.

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  • Capital Is Making a Comeback — Btw 1985-2021 the capital intensity of the American economy was relatively flat as a rise in intangible investment was offset by a decline in tangible…
  • Public to Private Equity in the United States: A Long-Term Look — Global venture capital returns are highly skewed: 62% of deals lose money, more than half lose 50–100% of invested capital, but fat-tailed outliers drive overall returns. This pattern mirrors historical whaling voyages, where payoffs were similarly variable and driven by rare outsized outcomes.
  • Gross and Net US Investment — Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment merely replaces depreciating assets. The shift toward faster-depreciating information technology assets requires larger gross investment increases to achieve any given gain in productive capital per worker.

AI Summary. AI-driven data-center expansion and related professional hiring have added roughly 1.05m jobs above trend since 2022–2023, spanning electrical contracting, equipment manufacturing, software development, and data science. The job gains exceed what broader construction, manufacturing, and professional employment trends would predict.

Economist Staff The Economist
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The Economist estimates that so far the AI boom has created ~1mm new jobs in the US, exceeding their estimate of ~200,000 layoffs attributed to AI since mid-2023.

Is artificial intelligence creating a genuine employment boom or temporary hiring surge?

Core argument: AI-linked demand has generated roughly 730,000 above-trend jobs in engineering, software development, and data science since 2022, substantially outpacing near-term displacement effects.

[We] tracked five industries at the heart of the data-centre build-out, from electrical contracting to equipment manufacturing. Since 2023 employment in them has risen by roughly 320,000 more than broader construction and manufacturing trends would suggest. Not all of those jobs owe their existence to AI—grid upgrades and other factory building matters too. [We also] tracked employment in professional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists—and compared their growth since 2022 with professional employment overall. These roles have added roughly 730,000 jobs above trend in recent years. AI will not have created every single one of them. But it has almost certainly created quite a few.

Takeaways by Macro Roundup® AI

  1. AI-linked demand has generated roughly 730,000 above-trend jobs in engineering, software development, and data science since 2022, substantially outpacing near-term displacement effects.
  2. Data-centre construction has added approximately 320,000 above-trend jobs across electrical contracting and equipment manufacturing since 2023, with grid upgrades and broader factory-building contributing alongside AI demand.

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  • The College Wage Premium in the Generative AI Era — S. 575 between 2022 and 2026, the first sustained decline in relative demand for college-educated labor in four decades. AI exposure in white-collar occupations accounts for roughly 28% of that drop, as wage growth slowed disproportionately in high-AI-exposure jobs where college graduates are concentrated.
  • Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence — Young workers in the most AI-exposed occupations face an employment shortfall ~19% below less-exposed peers, driven by reduced hiring rather than job losses, and concentrated in roles where AI replaces rather than complements human tasks.
  • Looking for the Ladder — The downtick in hiring in AI-exposed occupations started 6 months prior to the release of ChatGPT, and is “perfectly” aligned with the start of Fed rate hikes…

AI Summary. Global student performance in mathematics and reading has declined sharply since 2018, with reading scores falling 14 points and math scores falling 9 points between 2022 and 2025 alone.

OECD Staff Organisation for Economic Co-operation and Development
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Mean OECD math and reading scores fell roughly 25 PISA points—about a year of schooling—between 2018 and 2025, alongside reduced motivation and engagement and increased carelessness, exemplified by a near-doubling of “hasty readers.”

Are global education systems failing to teach core skills?

Core argument: The share of “hasty readers” — students giving fast, incorrect responses — nearly doubled from 7% in 2018 to 11% in 2025, with math showing a parallel rise between 2022 and 2025, signaling deteriorating effort and engagement rather than pure skill loss.

In math, performance remained close to the 2003 level up to 2018, then dropped sharply btw 2018 and 2025. Mean performance dropped by 9 score points in mathematics and about 14 score points in reading btw 2022 and 2025. Over the 2018-2025 period, the largest drops [in reading] were among the most advantaged 25% of socio-economic status, and the socio-economic gap with the most disadvantaged students reduced somewhat, by 11 points, on average across 35 OECD countries. In mathematics, the share of disadvantaged students scoring below proficiency Level 2 increased in previous cycles and remained high in 2025; among advantaged students, the share scoring below proficiency Level 2 increased, reaching 18% in 2025, about 4pp. Students’ reports of their motivation for learning and engagement with school also declined between 2022 and 2025. The proportion of “hasty readers” – those who gave fast and incorrect responses – increased by about five percentage points, on average, from almost 7% in 2018 to 11% in 2025. Analyses for math, also show an increase in the proportion of hasty responses between 2022 and 2025.

Takeaways by Macro Roundup® AI

  1. The share of “hasty readers” — students giving fast, incorrect responses — nearly doubled from 7% in 2018 to 11% in 2025, with math showing a parallel rise between 2022 and 2025, signaling deteriorating effort and engagement rather than pure skill loss.
  2. Among the most advantaged quartile of students, the share scoring below math proficiency Level 2 reached 18% in 2025, up approximately 4 percentage points, indicating that academic decline is no longer concentrated among disadvantaged populations.

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AI Summary. New York City's top 1% captured nearly two-thirds of real income growth between 2019 and 2024, versus under 40% nationally, driven by capital gains, dividends, and business income rather than wages.

Jonathan Siegel and Jason Bram Office of the New York City Comptroller
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Btw 2019 and 2024, pre-tax, pre-transfer real median income in New York City fell 3.2%. The top .1% tax units, ~ households, (mean income ~$24mm) saw real growth of ~25%, whereas the bottom 90% (mean income ~$45,000) fell 0.8%.

Is capital income concentration widening faster in major cities than nationally?

Core argument: Nearly two-thirds of New York City’s real income growth from 2019–2024 accrued to the top 1%, versus under 40% nationally, driven by faster-rising capital gains, dividends, and business income rather than wage divergence.

Between 2019 and 2024, the New York City’s income shares at the top of the distribution rose faster than the nation's, and nearly two-thirds of the real income growth over the period accrued to the top 1%, compared with under 40% nationally. The result also holds when volatile capital gains are excluded. Real median income fell over the period, and real average income for the bottom 90% of tax units was essentially flat. Adjusted for local prices (but not for transfer programs), the purchasing power of income for the lower 90% of New Yorkers is close to one-fifth below that of the bottom 90% nationally. The divergence at the top is predominantly a story of non-wage income. Wage and salary income shows a much milder widening, and occupational wage data that exclude bonuses show base pay growing faster in lower-wage occupations than in higher-wage ones, and within many occupational groups wages are converging rather than growing more unequal.

Takeaways by Macro Roundup® AI

  1. Nearly two-thirds of New York City’s real income growth from 2019–2024 accrued to the top 1%, versus under 40% nationally, driven by faster-rising capital gains, dividends, and business income rather than wage divergence.
  2. The bottom 90% of New York City earners hold purchasing power roughly one-fifth below their national counterparts after adjusting for local prices, even before accounting for transfer programs.

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AI Summary. Non-college workers ages 22–34 are experiencing historically low unemployment relative to their own two-decade range, outperforming college-educated peers on that relative measure. College graduates still hold an absolute advantage, with a 2.7% unemployment rate versus 4.7% for high-school-only workers.

Theo Francis and Ray Smith Wall Street Journal
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In 2026, the 12-month moving-average unemployment for college-educated 22–34-year-olds is above its post-2003 mean, while the rate for non-college peers is historically low. Prime-age college grads still have lower unemployment than those with no degree.

Is the job market finally tightening for workers without degrees?

Core argument: Non-college workers ages 22–34 are experiencing one of their strongest job markets in two decades, with unemployment rates near historic lows relative to their own 2003–present range, outperforming their college-educated peers on that relative measure.

The unemployment rate for workers ages 22 to 34 who never graduated from college has rarely been lower in the past two decades. To gauge how the job market has shifted for each cohort, [Gad Levanon, Burning Glass’s chief economist] compared current unemployment rates for the different groups with their own range of unemployment rates since 2003. The analysis included data through July. By that measure, the job market looks much better for blue-collar workers, including those in construction and on manufacturing lines, and manual-service workers. It is [however] still easier to find a job with a college degree. The unemployment rate for degree-holders in their prime working years—ages 25 to 54—averaged 2.7% for the 12 months ending in July - well below the 3.6% rate for workers with just some college education, and 4.7% for people with a high-school diploma only.

Takeaways by Macro Roundup® AI

  1. Non-college workers ages 22–34 are experiencing one of their strongest job markets in two decades, with unemployment rates near historic lows relative to their own 2003–present range, outperforming their college-educated peers on that relative measure.
  2. On an absolute basis, a college degree still confers a significant labor-market advantage: prime-age degree-holders averaged 2.7% unemployment versus 3.6% for some-college workers and 4.7% for high-school-only workers over the 12 months ending July.

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  • College Grads Struggle to Find Jobs. Non-Grads Are Giving Up — The narrowing unemployment gap between young college graduates and non-graduates reflects rising labor force dropout among non-graduates, not equal job market outcomes; the share of young non-graduates who are employed is 1.7 percentage points below pre-pandemic levels and falling, while graduates are near recovery.
  • To Fix Education, Fix The Economy First — Using OECD skills data and the Luxembourg Income Study, Burn-Murdoch finds US workers at the lowest levels of literacy and numeracy earn ~ on par with British…
  • The College Wage Premium in the Generative AI Era — S. 575 between 2022 and 2026, the first sustained decline in relative demand for college-educated labor in four decades. AI exposure in white-collar occupations accounts for roughly 28% of that drop, as wage growth slowed disproportionately in high-AI-exposure jobs where college graduates are concentrated.

AI Summary. Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment merely replaces depreciating assets. The shift toward faster-depreciating information technology assets requires larger gross investment increases to achieve any given gain in productive capital per worker.

Timothy Taylor Conversable Economist
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U.S. real net private domestic investment—which adds to the American capital stock—is now only ~25% as large as gross investment, down from ~40% in the 1970s. Taylor suggests the widening gap between gross and net investment reflects the relatively rapid depreciation of IT-related capital.

Does faster asset depreciation explain slowing productivity growth?

Core argument: Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment now merely replaces depreciating capital rather than expanding the productive stock.

The figure divides net investment by gross investment. Back in the 1970s, net investment was often around 40% of gross investment, but the share has been slumping over time. For the last decade or so, net investment has been about 25% of the gross–that is, about three-quarters of gross investment is just making up for depreciation of the pre-existing capital stock. The likely reason for the growing gap between gross and net investment is that modern investment is more likely to be related to information technology [which] depreciates more rapidly and thus needs to be replaced and updated more often. If we want the average US worker to be using a greater amount of capital on the job–which was one of the key drivers of rising labor productivity in the past–it now takes a bigger rise in gross investment to lead to a given rise in net investment.

Takeaways by Macro Roundup® AI

  1. Net investment has fallen from ~40% of gross investment in the 1970s to ~25% today, meaning three-quarters of gross investment now merely replaces depreciating capital rather than expanding the productive stock.
  2. The shift toward information technology — which depreciates faster than physical machinery — is the primary driver of the widening gap between gross and net investment.
  3. Raising capital per worker, a historic engine of labor productivity growth, now requires a substantially larger increase in gross investment than it did several decades ago.

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AI Summary. S. 575 between 2022 and 2026, the first sustained decline in relative demand for college-educated labor in four decades. AI exposure in white-collar occupations accounts for roughly 28% of that drop, as wage growth slowed disproportionately in high-AI-exposure jobs where college graduates are concentrated.

José Azar, Mireia Gine and Javier Sanz-Espín Social Science Research Network
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The college wage premium flattened in the mid-2010s and has fallen ~8% since 2022. The authors argue that this compression reflects a broad decline in the returns to formal schooling, rather than a decline in the upper tail.

Is the college degree losing its economic value to artificial intelligence?

Core argument: The U.S. college wage premium fell from 0.626 to 0.575 between 2022 and 2026—the first sustained decline in relative demand for college labor after four decades of uninterrupted expansion.

After expanding for four decades, the U.S. college wage premium [dropped] sharply from 0.626 in 2022 to 0.575 in 2026. Current Population Survey data through 2026 implies an unprecedented drop in relative demand for college labor—the first sustained negative relative demand growth. Post-2022 wage growth slowed disproportionately in high-exposure occupations, which employ a disproportionate share of college graduates. By 2026, going from zero occupational AI exposure to full exposure had a negative effect on wages of−0.086. Combined with the college–non-college exposure gap, this mechanism accounts for roughly 28% of the total drop in the college wage premium from 2022 to 2026. While non-causal, these patterns indicate that task displacement in AI-exposed white-collar occupations plays a quantitatively meaningful role in the recent compression of the aggregate skill premium.

Takeaways by Macro Roundup® AI

  1. The U.S. college wage premium fell from 0.626 to 0.575 between 2022 and 2026—the first sustained decline in relative demand for college labor after four decades of uninterrupted expansion.
  2. Moving from zero to full occupational AI exposure reduced wages by 0.086 log points by 2026.
  3. the college–non-college AI-exposure gap accounts for roughly 28% of the total premium compression over that period.

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