“…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
“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
“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
“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
“…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 comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“A full-throated defense of economic dynamism.” - The Wall Street Journal
“…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
“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
“…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
Evidence on U.S. business formation, firm entry and exit, entrepreneurship, job creation, reallocation, venture capital, and the spread of new technologies. The archive tracks whether the economy is becoming more or less dynamic.
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 StaffThe Economist
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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
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.
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.
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 YangNational Bureau of Economic Research
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~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
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.
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.
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.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 StaffThe Economist
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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
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.
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.
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 CruickshankStripe Economics
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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
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.
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.
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 U.S. government will award about $2bn to quantum-computing firms under the 2022 Chips and Science Act, taking a minority equity stake in each company. D-Wave said its entire $100m award would be an equity investment, with Rigetti and Infleqtion describing similar structures.
Amrith Ramkumar and Heather SomervilleThe Wall Street Journal
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Lutnick’s Commerce Department is awarding $2B in Chips Act grants to nine quantum firms and taking government equity in each. IBM gets $1B (plus $1B of its own); GlobalFoundries $375M for ~1%. D-Wave, Rigetti, and Infleqtion surged 30%+.
Is the government taking equity stakes in quantum-computing companies?
Core argument: The U.S. will award quantum-computing firms $2 billion funded by the 2022 Chips and Science Act, taking a minority equity stake in each company receiving money.
The funding for the quantum deals comes from the 2022 Chips and Science Act, which includes money for earlier-stage technology projects. Commerce Secretary Howard Lutnick has overhauled the office, asking semiconductor companies to increase their domestic investments and taking a nearly 10% stake in Intel, which has seen shares surge since the unusual deal. The government will receive a minority equity stake in each quantum company, adding to similar deals including the rare-earths magnet maker Vulcan Elements and the mining company MP Materials. D-Wave said that all of its $100 million award would be an equity investment. It recently had a market value of more than $7 billion. Rigetti and Infleqtion said their deals would have a similar structure.
Takeaways by Macro Roundup® AI
The U.S. will award quantum-computing firms $2 billion funded by the 2022 Chips and Science Act, taking a minority equity stake in each company receiving money.
D-Wave, recently valued at more than $7 billion, said its entire $100 million award would be an equity investment, and Rigetti and Infleqtion said their deals would have a similar structure.
Commerce Secretary Howard Lutnick has overhauled the office, asking semiconductor companies to increase their domestic investments and taking a nearly 10% stake in Intel, whose shares have surged since the deal.
Related Articles:
New Advances Bring the Era of Quantum Computers Closer Than Ever— Estimates of the quantum computing power needed to run Shor's algorithm and break encryption have fallen from billions of qubits to a million, while existing machines have hundreds. Researchers have announced a design requiring only tens of thousands of qubits and an implementation of the algorithm 10x as efficient as the prior best.
An Old Problem Could Stop The U.S. From Leading On Quantum Computers— Many quantum computers depend on dilution refrigerators, produced by a few small firms in the US, Britain and Finland, and on critical minerals such as niobium, concentrated in Brazil, and tantalum, mined in Africa and mostly processed in China. China has announced mass production of a domestic dilution refrigerator and has been buying niobium mines.
Google Unveils Quantum Computing Breakthrough on Willow Chip— Google says its "Quantum Echoes" algorithm, run on its Willow quantum chip and detailed in a paper in Nature, is verifiable on other quantum computers and ran 13,000x faster than the world's best classical supercomputer. Google says the advance points to useful quantum applications in medicine and materials science within five years.
AI Summary.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.
Ernie TedeschiStripe Economics
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Tedeschi points to a split in new US business formation: overall applications are rising, but filings from firms likely to hire employees have stalled. He argues AI may be fueling “solopreneur” activity by making it easier to launch without staff.
Does slow early productivity growth mean a new technology won't deliver?
Core argument: For the three decades after Edison began delivering commercial electricity in New York in 1882, inflation-adjusted output per worker grew just 0.5% annually, a sluggish pace relative to what electricity would eventually enable.
For three decades after Thomas Edison began delivering commercial electricity to New York customers in 1882, inflation-adjusted output per worker grew at just 0.5% annually—a sluggish pace relative to what electricity would eventually enable. The gains became evident only as the economy's capital stock and organizational practices adapted to the new technology: new factories designed around electric motors from the ground up, rather than retrofitted from steam. Some of the impetus for this replatforming came from the weapons production spurred by World War I. In the decade after 1917, productivity growth more than doubled its prior three-decade average. The implication for AI is that a near-term absence of productivity acceleration in the aggregate data should not be read as evidence that no acceleration is coming.
Takeaways by Macro Roundup® AI
For the three decades after Edison began delivering commercial electricity in New York in 1882, inflation-adjusted output per worker grew just 0.5% annually, a sluggish pace relative to what electricity would eventually enable.
Productivity gains from electricity emerged only as the economy's capital stock and organizational practices adapted, with new factories designed around electric motors from the ground up rather than retrofitted from steam.
In the decade after 1917, productivity growth more than doubled its prior three-decade average, with some impetus for that replatforming coming from World War I weapons production.
Related Articles:
Sectors Embracing AI Are Seeing a Surge in New Business Formation— Sectors with the highest artificial intelligence adoption rates have also seen the strongest growth in new business applications, which one analysis interprets as evidence that AI is lowering the barriers to starting a company.
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.
AI Summary.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.
Torsten SløkApollo
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New business applications are ~ back at their pandemic-era level. Sløk argues the increase is “likely driven by the proliferation of AI-enabled startups, as large language models dramatically lower the barriers to entrepreneurship.”
Are AI tools driving a widening surge in high-growth business formation?
Core argument: U.S. business applications continue to rise, and breaking them into value and growth companies reveals a widening divergence between the two categories.
Breaking down business applications into value and growth companies reveals a widening divergence, likely driven by the proliferation of AI-enabled startups, as large language models dramatically lower the barriers to entrepreneurship.
Takeaways by Macro Roundup® AI
U.S. business applications continue to rise, and breaking them into value and growth companies reveals a widening divergence between the two categories.
The widening divergence in business applications is likely driven by the proliferation of AI-enabled startups.
Large language models dramatically lower the barriers to entrepreneurship.
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.
The Economics of Inequality in High-Wage Economies— Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.
AI Summary.Data indicate persistence in returns on invested capital has increased since 2000, with large companies the main beneficiaries; the information technology sector's aggregate return was 19% versus a 10.8% median from 1970 to 2024. Of about 13,800 U.S. public firms listing from 1976 to 2019, 18% survived.
Michael Mauboussin and Dan CallahanMorgan Stanley
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The Competitive Advantage Period (CAP), the period in which the market implies a firm can earn a return greater than its cost of capital, for most firms is 5–20 years, as ROIC regresses to the mean. Persistence of ROIC has increased, driven by a small number of large firms since 2000.
Have high returns on invested capital become more persistent for large companies?
Core argument: The aggregate return on invested capital for the information technology sector was 19% from 1970 to 2024 versus a median of 10.8%, and has on average exceeded the 75th-percentile company's ROIC since the Great Recession, meaning a small number of large companies determine the sector aggregate.
The data suggest that persistence in ROIC is up since 2000 and that large companies are the main beneficiaries of the implied expansion in CAPs. To illustrate the point, the aggregate ROIC for the information technology sector was 19% versus the median of 10.8% from 1970 to 2024. As striking, the aggregate ROIC for the sector has been greater on average than the ROIC for the 75th-percentile company (i.e., the ROIC below which 75% of data fall), since the Great Recession. This means a small number of large companies are determining the aggregate figure for the sector. From 1926 to 2025, the average listing time for a public company in Bessembinder’s database was 11.7 years, and the median listing time was 6.8 years. About 9% of listed companies at the beginning of 2026 were more than 50 years old. Modeling perpetual growth without considering mortality can create a mismatch. Exhibit 7 shows what happened to about 13,800 U.S. public firms that started trading between 1976 and 2019, excluding financial firms. For every 100 companies, 18 survived and 82 died. Of those that died, 43 were the result of mergers and acquisitions. The other 39 were delisted for reasons other than M&A, with the majority of those for “cause.” This happens when a company files for bankruptcy or fails to meet certain requirements set by an exchange.
Takeaways by Macro Roundup® AI
The aggregate return on invested capital for the information technology sector was 19% from 1970 to 2024 versus a median of 10.8%, and has on average exceeded the 75th-percentile company's ROIC since the Great Recession, meaning a small number of large companies determine the sector aggregate.
Of roughly 13,800 non-financial U.S. public firms that began trading between 1976 and 2019, 18 of every 100 survived and 82 died, 43 through mergers and acquisitions and 39 delisted for other reasons, the majority for cause such as bankruptcy.
The average listing time for a public company in Bessembinder's database was 11.7 years from 1926 to 2025, with a median of 6.8 years, and about 9% of companies listed at the start of 2026 were more than 50 years old.
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.
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.
The Economics of Inequality in High-Wage Economies— Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.
