Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…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
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…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
  • “…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
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
Upside of Inequality Oxford Unintended Consequences

Startups

Evidence on startups, founders, venture capital, firm formation, scaling, exits, and the policies and markets that support entrepreneurship. The archive follows how young firms contribute to innovation, competition, jobs, and productivity.

AI Summary. Entrepreneurship by businesses with employees is flat or declining, including in AI-intensive information and professional services, where establishment entry has been flat or falling and young-firm employment in AI-exposed industries is falling. Applications for likely solo businesses with no employees rose steeply in those AI-intensive sectors, but self-employment as a main job is flat, suggesting side hustles.

Nathan Goldschlag Economic Innovation Group
Date Posted:
Is Database:
Database

Nathan Goldschlag finds that available federal data do not yet establish that AI is boosting entrepreneurship. “Across different cuts of the data, there is no clear evidence of AI affecting entrepreneurship, either for likely employers or nonemployers.”

Is AI driving a boom in new employer businesses?

Core argument: Business applications likely to become employer businesses were flat in 2025 and began rising in 2026, with fewer applications of the kind having the highest chance of becoming an employer business.

Employer entrepreneurship is at best rising modestly, and at worst has been falling for several years already. The number of business applications likely to become an employer business was flat in 2025 and began rising in 2026. Fewer of those applications have been the kind that have the highest chance of becoming an employer. Nonemployer entrepreneurship, or “solopreneurship,” is likely rising, but not as the main job of the solopreneurs. These are probably side hustles. Likely nonemployer business applications rose significantly in 2025 and early 2026. But the share of workers claiming to be self-employed nonemployers in their main job — in other words, business owners with no employees — is flat (though noisy). AI-intensive sectors and industries are no exception. Establishment entry in AI-intensive sectors (information and professional services) has been flat or falling in recent years.

Takeaways by Macro Roundup® AI

  1. Business applications likely to become employer businesses were flat in 2025 and began rising in 2026, with fewer applications of the kind having the highest chance of becoming an employer business.
  2. Likely nonemployer business applications rose significantly in 2025 and early 2026, going vertical in the most AI-intensive sectors of information and professional services, while other sectors kept pace until early 2026 and then flattened.
  3. The share of workers reporting self-employment as nonemployers in their main job is flat, though noisy, including among workers in AI-exposed occupations in 2025 and early 2026.

Related Articles:

  • The Age Of The Solopreneur — A surge in US business formation is being driven by solo entrepreneurs, with growth in AI tool usage and in solopreneur activity in high-AI-adoption sectors suggesting artificial intelligence accounts for a meaningful portion of the increase. The authors argue AI is lowering barriers to starting and growing a business by expanding what one-person firms can do.
  • America Has Become An Entrepreneur’s Paradise — US growth in new-business applications is concentrated in professional services (up 25% over four years), retail (18%), and health care and social assistance (18%) rather than artificial-intelligence startups. The share of applications the Census Bureau deems likely to hire at least one employee has fallen to 30% from 38%.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.

AI Summary. US growth in new-business applications is concentrated in professional services (up 25% over four years), retail (18%), and health care and social assistance (18%) rather than artificial-intelligence startups. The share of applications the Census Bureau deems likely to hire at least one employee has fallen to 30% from 38%.

Economist Staff The Economist
Date Posted:
Is Database:
Database

New business formation in the US is back at its pre-pandemic level. The share of new-business applications deemed likely to employ someone other than the founder in the near future was 30% in 2025, down from 38% in 2019 perhaps suggesting AI is driving “solopreneurship.”

Is the surge in new-business applications driven by AI startups?

Core argument: New-business applications rose most in professional services (+25% between 2021 and 2025), retail (+18%), and health care and social assistance (+18%), with AI startups in Silicon Valley accounting for only a small part of the increase.

Buzzy artificial-intelligence startups in Silicon Valley account for only a small part of the increase. The industries witnessing the biggest flurry of applications are professional services (up 25% between 2021 and 2025), retail (18%), and health care and social assistance (18%). The share of new-business applications that the Census Bureau deems “high-propensity” (meaning they are likely to employ at least one person other than the founder in the near future) was only 30% last year, down from 38% in 2019. Aaron Terrazas, an economist at Gusto [a payroll platform] reckons that much of the value generated by AI could end up accruing not to corporate giants, but to Etsy sellers and small-town accountants.

Takeaways by Macro Roundup® AI

  1. New-business applications rose most in professional services (+25% between 2021 and 2025), retail (+18%), and health care and social assistance (+18%), with AI startups in Silicon Valley accounting for only a small part of the increase.
  2. The share of U.S. new-business applications the Census Bureau deems "high-propensity," meaning likely to employ at least one person besides the founder soon, was 30% last year, down from 38% in 2019.
  3. Aaron Terrazas, an economist at the payroll platform Gusto, reckons much of the value generated by AI could accrue to Etsy sellers and small-town accountants rather than corporate giants.

Related Articles:

  • The Age Of The Solopreneur — A surge in US business formation is being driven by solo entrepreneurs, with growth in AI tool usage and in solopreneur activity in high-AI-adoption sectors suggesting artificial intelligence accounts for a meaningful portion of the increase. The authors argue AI is lowering barriers to starting and growing a business by expanding what one-person firms can do.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
  • Continued Rise in Business Formation — The gap between growth-oriented and value-oriented new business applications is widening, a divergence likely driven by a proliferation of startups built around artificial intelligence. Large language models are lowering the barriers to starting a business.

AI Summary. Modeling U.S. venture-backed startups, the authors estimate that taxing capital gains as they accrue rather than at sale would cut founders' average ownership at exit by about 25% while raising the share of entrepreneurs with positive payoffs from roughly 16% to nearly 47%. Less risk-averse founders prefer taxation at sale.

Eduardo Azevedo, Florian Scheuer, Kent Smetters and Min Yang National Bureau of Economic Research
Date Posted:
Is Database:
Database
Is Important:
Important

~84% of venture backed founders end with zero exit value, while the top 2% capture ~80% of total exit value. Accrual-based taxation would reduce mean founder ownership stakes at exit by ~25%, but with fully refundable tax credits, raise the share of founders with >0 payoffs to ~47%.

How does taxing unrealized capital gains affect startup founders?

Core argument: The authors estimate that average founder shares at exit fall about 25% under accrual-based capital gains taxation relative to realization-based taxation, as advance taxation forces additional share sales before exit.

This paper examines how taxing unrealized capital gains affects entrepreneurship, combining a dynamic career-choice model with new evidence on all U.S. venture capital backed startups. Figure 1a plots a histogram of the positive company exit values. The distribution spans several orders of magnitude and is relatively similar to a lognormal, but with a right skew and fatter right tail. A stylized model highlights a key trade-off: accrual-based capital gains taxes dilute successful founders by forcing additional share sales before exit, a well known concern, yet they also provide insurance through tax credits to founders whose ventures fail, an aspect often overlooked. Quantitatively, advance taxation substantially reduces founders' ownership at exit: average founder shares fall about 25% under accrual-based taxation relative to realization based taxation. At the same time, accrual taxation increases the fraction of entrepreneurs with positive payoffs from around 16% to nearly 47%. Embedding these outcomes in a career-choice framework shows that the insurance value of accrual taxation partly offsets dilution costs: less risk-averse founders favor realization-based taxes, while more risk averse ones prefer accrual-based taxes. The strength of this insurance channel depends on the highly skewed distribution of entrepreneurial payoffs and the design of loss provisions under accrual-based taxation.

Takeaways by Macro Roundup® AI

  1. The authors estimate that average founder shares at exit fall about 25% under accrual-based capital gains taxation relative to realization-based taxation, as advance taxation forces additional share sales before exit.
  2. Accrual-based taxation raises the fraction of entrepreneurs with positive payoffs from around 16% to nearly 47%, providing insurance through tax credits to founders whose ventures fail.
  3. In the authors' career-choice framework, less risk-averse founders favor realization-based taxes while more risk-averse founders prefer accrual-based taxes, with the insurance channel's strength depending on the skewed payoff distribution and loss-provision design.

Related Articles:

  • Killer Incentives: Status Competition and Pilot Performance during World War II — Analysis of over 5,000 German World War II fighter pilots finds that public peer recognition was associated with higher victory scores among skilled pilots without higher mortality, while average pilots gained little in victories but died at higher rates. The authors conclude status-based awards can have uneven effects in high-risk settings.
  • One Hundred Years in the U.S. Stock Markets — Over a century, U.S. publicly traded stocks generated roughly $91tn in shareholder wealth enhancement, with returns strongly positively skewed and dominated by a relatively small number of high-performing firms. Because most possible outcomes fall below the mean in a skewed distribution, the authors argue financial planning should focus on median outcomes or the full distribution.
  • Never Enough: Dynamic Status Incentives in Organizations — Data on over 5,000 German fighter pilots show performance rose markedly as pilots approached the eligibility threshold for each medal in a tiered awards ladder and slumped immediately after receiving it, with the effect repeating at each successive rung. The authors estimate the ladder added 3,000–5,000 aerial victories, 5–10% of the total.

AI Summary. US technology and finance firms offer new engineering graduates higher pay and greater prestige than large industrial companies like Boeing, whereas engineering graduates in France, Japan, China, and Germany take industrial jobs such as Airbus at a fraction of US engineering pay. The author argues this talent pull is a genuine obstacle to re-industrializing the US.

Louis-Vincent Gave Gavekal
Date Posted:
Is Database:
Database

Louis-Vincent Gave notes that while “Airbus can hire the cream of the French, or even European, crop,” established American industrial firms like Boeing may struggle to attract engineering talent due to competition from startups and Wall Street.

Does tech and finance pay pull engineering talent away from US industry?

Core argument: Engineering graduates in France, Japan, China, and Germany take jobs at industrial firms such as Airbus for a fraction of US engineering pay, while US graduates target Google, Microsoft, Meta, Goldman Sachs, or Morgan Stanley.

Shifts in staff compensation stacked the decks against Boeing and other big US industrial companies—at least relative to other industrial powers. In France, for example, graduates of engineering schools will gladly take jobs at Airbus and be paid a fraction of what an engineer makes in the US. The same is true in Japan, China, and Germany. In the US, however, a new engineering graduate today likely has his or her sights on a job at Google, Microsoft, or Meta, or alternatively at Goldman Sachs or Morgan Stanley. Such jobs offer better pay and more social prestige, along with the promise of stock options and potential riches. Now the SpaceX IPO has turned this dial all the way up to 11. In short, for the past 15 years or so, the US tech industry has sucked most of the oxygen out of the room. This is true for capital allocation and stock market performance, and it follows that the same has also been true for human resources and talent acquisition. This seems like a genuine hurdle to today’s widespread hopes of re-industrializing the US.

Takeaways by Macro Roundup® AI

  1. Engineering graduates in France, Japan, China, and Germany take jobs at industrial firms such as Airbus for a fraction of US engineering pay, while US graduates target Google, Microsoft, Meta, Goldman Sachs, or Morgan Stanley.
  2. US technology and finance jobs offer better pay and more social prestige than industrial employers, along with stock options and the promise of riches, shifting compensation against Boeing and other large US industrial companies.
  3. The US tech industry has drawn most capital allocation, stock market performance, and talent for roughly 15 years, and the SpaceX IPO intensifies that pull, posing a hurdle to hopes of re-industrializing the US.

Related Articles:

  • Military Officer Quality in the All-Volunteer Force — The authors find a steady decline in U.S. Marine Corps officers' General Classification Test scores, which is statistically associated with the expansion of college attendance and explains 96% of the measured change. They also find a positive association between African American officers and mean test scores, arguing affirmative action has not lowered officer quality.
  • Boeing Battles Brain Drain As Engineers Chase the Allure of Space — The average tenure of a Boeing engineer has fallen from 16.4 years to 12.6 years, according to data from the union representing 12,000 Boeing engineers, with tenure shortening in almost every age bracket. Analysts, recruiters and union officials describe this "brain drain" as a drag on operations that could make launching a new plane harder.
  • Speed Can Reindustrialize America — The US has a relative surplus of low-paid hourly workers and a shortage of high-skill workers, so many less productive US manufacturers could buy a robot but could not attract the talent to program it. China faces the opposite conditions, with underemployed STEM graduates, residency rules complicating coastal factory hiring, and robot programmers earning a fraction of US wages.

AI Summary. Of roughly 1,900 startups valued at $1bn or more in a Stanford-maintained database, 332 had raised money at or below their peak valuation and 383 had disclosed no new funding in the prior three years. Research firm Pitchbook expects net valuation cuts of $500bn–$1tn as these firms reprice, seek buyers, or fail.

Economist Staff The Economist
Date Posted:
Is Database:
Database

As of May of this year, 17% of unicorns in a Stanford database had raised funds at a valuation at or below their peaks; ~ half the firms in the database were valued under their peak valuation, implying significant write-downs going forward.

How many billion-dollar startups are struggling to justify their valuations?

Core argument: By May 2026, 332 of the 1,900 unicorns in Ilya Strebulaev's Stanford database had raised money at or below their peak valuation, and 212 of those were valued at under $1bn.

By May 2026, 332 of the 1,900 unicorns in a database maintained by Ilya Strebulaev of Stanford University had raised money at a valuation at or below their peak. Of those, 212 were valued at under $1bn. As many as 383 had disclosed no new funding in the previous three years; 41 of these had lost unicorn status. As Mr Strebulaev notes, data on startups are notoriously noisy. Some unicorns may have raised no money because they did not need it. But others may be struggling to justify mythical valuations. It seems that a fair proportion of unicorns have joined the undead. Nearly half of the firms in Mr Strebulaev’s database valued at less than their peak raised money in 2021. From late next year, their investors will start demanding results. Pitchbook expects net cuts in valuations of between $500bn and $1trn as firms reprice, scramble to find a buyer, or go bust. That is quite a cull: Pitchbook puts the total value of unicorns below the ten most valuable at around $5trn.

Takeaways by Macro Roundup® AI

  1. By May 2026, 332 of the 1,900 unicorns in Ilya Strebulaev's Stanford database had raised money at or below their peak valuation, and 212 of those were valued at under $1bn.
  2. As many as 383 unicorns in Strebulaev's database had disclosed no new funding in the previous three years, and 41 of them had lost unicorn status, though Strebulaev notes startup data are notoriously noisy and some firms may not have needed capital.
  3. Pitchbook expects net valuation cuts of between $500bn and $1trn as firms reprice, scramble to find a buyer, or go bust, against roughly $5trn in total value for unicorns below the ten most valuable.

Related Articles:

  • Trampled Underfoot by a Stampede of Unicorns — A database trawl counts 1,727 private companies valued above $1bn globally, and if private market valuations are accurate, the largest of them have outperformed public markets since the pandemic. Several, led by SpaceX and OpenAI, plan initial public offerings, which can signal trouble ahead since insiders are choosing to sell.
  • The Deep End: 2025 Alternative Investments Review — In venture capital, only consistently investing with top-quartile managers outperformed the S&P 500, while the median manager at best matched public equity markets and fourth-quartile managers destroyed value relative to equities. Fees are part of the issue: an 11.7% annualized NASDAQ 100 return falls to 7.4% under a 2%/20% fee structure.
  • Valuing AI: Extreme Bubble, New Golden Era, or Both — By the investment firm's definition of a bubble — a price two standard deviations above an asset class's long-term real trend — U.S. equities are in bubble territory and extremely overpriced on historically effective valuation metrics, with a cyclically adjusted price-earnings ratio of 40 and a record share of the market trading above 10x sales.

AI Summary. A surge in US business formation is being driven by solo entrepreneurs, with growth in AI tool usage and in solopreneur activity in high-AI-adoption sectors suggesting artificial intelligence accounts for a meaningful portion of the increase. The authors argue AI is lowering barriers to starting and growing a business by expanding what one-person firms can do.

Ernie Tedeschi, Marisa Rama and Chris Cruickshank Stripe Economics
Date Posted:
Is Database:
Database

New US business applications have surged since late 2024, driven mainly by “likely nonemployer” filings representing “solopreneurs” rather than businesses expected to hire. Data suggest AI may be enabling this by filling capability gaps without hiring.

Is AI driving the surge in one-person business formation?

Core argument: The recent surge in US business formation is not reflected in high-propensity applications, but the evidence points toward a structural increase in genuine small business activity over 2025 and 2026, driven by solopreneurs.

While the recent surge in US business formation is not reflected in high-propensity applications, the evidence points toward a structural increase in genuine small business activity over 2025 and 2026, driven by solopreneurs. Preliminary evidence of growth in AI tool usage and solopreneur growth in high-AI-adoption sectors suggests that advances in AI are responsible for a meaningful portion of this growth. We believe AI is lowering barriers to business formation and growth by expanding the capabilities of solopreneurs, further improving tools and platforms that cater to new businesses, and creating a new set of opportunities for entrepreneurs to pursue. Whether the magnitude of this effect is as large as the most optimistic readings of the data suggest remains to be seen, but we believe we might be in the early innings of a fundamental acceleration in business formation—which could have ripple effects throughout the economy.

Takeaways by Macro Roundup® AI

  1. The recent surge in US business formation is not reflected in high-propensity applications, but the evidence points toward a structural increase in genuine small business activity over 2025 and 2026, driven by solopreneurs.
  2. Preliminary evidence of growth in AI tool usage and solopreneur growth in high-AI-adoption sectors suggests that advances in AI are responsible for a meaningful portion of this growth.
  3. AI appears to be lowering barriers to business formation and growth by expanding solopreneur capabilities, improving tools and platforms serving new businesses, and creating opportunities for entrepreneurs, with possible ripple effects throughout the economy.

Related Articles:

  • Solopreneurs, Solow, and the SaaSpocalypse — For three decades after commercial electricity delivery began in 1882, inflation-adjusted output per worker grew just 0.5% annually, accelerating to more than double that pace only after factories were redesigned around electric motors rather than retrofitted from steam. The author argues a near-term absence of productivity acceleration from AI is not evidence none is coming.
  • AI-Native Firms∗ — The authors find AI-native U.S. startups are 25% smaller than non-AI startups in the same industry and cohort, with 13% higher engineer shares, roughly 15% lower shares of entry-level workers and managers, flatter hierarchies, and comparable valuations. They argue embedding AI into products lets firms scale knowledge work without large teams.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.

AI Summary. The authors find AI-native U.S. startups are 25% smaller than non-AI startups in the same industry and cohort, with 13% higher engineer shares, roughly 15% lower shares of entry-level workers and managers, flatter hierarchies, and comparable valuations. They argue embedding AI into products lets firms scale knowledge work without large teams.

Hyunjin Kim and Rembrand Koning Social Science Research Network
Date Posted:

“AI native” firms – firms organized around AI founded btw 2020 and 2024 – had headcounts ~25% lower than their industry peers. These firms’ share of engineers is ~13% higher, while their share of entry-level workers and managers is ~15% lower.

How do AI-native startups differ from other startups in workforce structure?

Core argument: AI-native startups are 25% smaller than non-AI startups in the same industry-cohort, yet their valuations are comparable, which the authors say suggests higher value created per employee.

Drawing on Y Combinator batches W20–F24 and U.S. venture-backed startups whose first financing closed between 2020 and 2024, we classify each firm’s AI-native status and link it to workforce microdata on team size, function, seniority, and hierarchy. Relative to non-AI startups in the same industry-cohort, AI-native firms are 25% smaller. Their share of engineers is 13% greater, and the shares of entry-level workers and managers are each roughly 15% lower. Their hierarchies are half a seniority level flatter—yet valuations are comparable, suggesting higher value created per employee. We argue these patterns reflect two channels: a process channel, in which AI changes how people work inside the firm, and a product channel, in which AI capabilities are built into what the firm sells. Using text from product descriptions and job postings, we find that embedding AI into the product, beyond layering on AI tools into existing workflows, is a primary way startups are scaling “knowledge work” without large teams of knowledge workers.

Takeaways by Macro Roundup® AI

  1. AI-native startups are 25% smaller than non-AI startups in the same industry-cohort, yet their valuations are comparable, which the authors say suggests higher value created per employee.
  2. In AI-native firms, the share of engineers is 13% greater, the shares of entry-level workers and managers are each roughly 15% lower, and hierarchies are half a seniority level flatter.
  3. Drawing on text from product descriptions and job postings for Y Combinator batches W20–F24 and U.S. venture-backed startups first financed between 2020 and 2024, the authors find embedding AI into the product is a primary way startups scale knowledge work without large teams.

Related Articles:

  • Attention (And Money) Is All You Need: Why Universities Are Struggling to Keep AI Talent — The annual compensation gap between top industry and academic artificial intelligence researchers widened from roughly $294,000 to $1.5m, coinciding with accelerating academic out-migration toward large incumbent technology firms. Researchers who move to industry cut paper production by about 63% while increasing patent filings nearly sixfold, consistent with a shift from open science toward proprietary innovation.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
  • Solopreneurs, Solow, and the SaaSpocalypse — For three decades after commercial electricity delivery began in 1882, inflation-adjusted output per worker grew just 0.5% annually, accelerating to more than double that pace only after factories were redesigned around electric motors rather than retrofitted from steam. The author argues a near-term absence of productivity acceleration from AI is not evidence none is coming.

AI Summary. A database trawl counts 1,727 private companies valued above $1bn globally, and if private market valuations are accurate, the largest of them have outperformed public markets since the pandemic. Several, led by SpaceX and OpenAI, plan initial public offerings, which can signal trouble ahead since insiders are choosing to sell.

John Authers Bloomberg
Date Posted:
Is Database:
Database

“Brace for a thundering herd of unicorns.” John Authers notes that in recent years, large IPOs have marked the peak for multiple asset classes, citing Blackstone’s June 2007 IPO and the 2011 Glencore deal, which saw the peak of the metals market.

Do large private company listings signal market peaks?

Core argument: BestBrokers' trawl of databases counts 1,727 unicorns globally, with 70 added in the first quarter of this year.

A trawl of databases by BestBrokers finds that there are now 1,727 globally, with their numbers swelling by 70 in the first quarter of this year. If private market valuations are right, the biggest unicorns have far outperformed public markets since the pandemic. Several unicorns, led by SpaceX and OpenAI, are planning initial public offerings this year. That’s not necessarily good news. As ever when insiders at a company decide to sell, IPOs can signal trouble ahead. Two of this century’s biggest IPOs marked the top for entire markets and asset classes.

Takeaways by Macro Roundup® AI

  1. BestBrokers' trawl of databases counts 1,727 unicorns globally, with 70 added in the first quarter of this year.
  2. If private market valuations are accurate, the biggest unicorns have far outperformed public markets since the pandemic.
  3. Several unicorns, led by SpaceX and OpenAI, plan initial public offerings this year, and two of this century's biggest IPOs marked the top for entire markets and asset classes.

Related Articles:

  • One Hundred Years in the U.S. Stock Markets — Over a century, U.S. publicly traded stocks generated roughly $91tn in shareholder wealth enhancement, with returns strongly positively skewed and dominated by a relatively small number of high-performing firms. Because most possible outcomes fall below the mean in a skewed distribution, the authors argue financial planning should focus on median outcomes or the full distribution.
  • Public Markets Are a Shrinking Part of the US Economy — S&P 500 companies account for 18% of total US employment, 21% of total US capital expenditure, roughly half of economy-wide corporate profits, and less than half of outstanding corporate debt. Privately owned firms account for almost 80% of job openings, and 81% of firms with revenues above $100m are private.
  • The Deep End: 2025 Alternative Investments Review — In venture capital, only consistently investing with top-quartile managers outperformed the S&P 500, while the median manager at best matched public equity markets and fourth-quartile managers destroyed value relative to equities. Fees are part of the issue: an 11.7% annualized NASDAQ 100 return falls to 7.4% under a 2%/20% fee structure.