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
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…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 comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Thursday, September 5, 2024

AI Summary. Studies linking Census Bureau survey responses to administrative records find greater measurement error for Black and Hispanic individuals than whites, mainly underreporting of program receipt across food stamps, Social Security, unemployment insurance, Medicaid, Medicare, and pensions. The authors conclude the safety net supports minority groups more than survey data suggest.

Bruce Meyer, Nikolas Mittag and Derek Wu National Bureau Of Economic Research
Date Posted:
Is Database:
Database

Bruce Meyer finds that when recipients of a variety of US government assistance programs complete Census Bureau surveys, they significantly underreport program participation. Black and Hispanic recipients show the highest rates of underreporting.

Does survey underreporting understate safety net support for minorities?

Core argument: Reviewing linked survey–administrative data for SNAP, Social Security, Unemployment Insurance, TANF, Medicaid, Medicare, and private pensions in major Census Bureau surveys, the authors find a strong and robust pattern of greater measurement error for Black and Hispanic individuals and households than for whites.

We review existing studies that use linked data to assess the reporting of key programs (including SNAP, Social Security, Unemployment Insurance, TANF [Temporary Assistance for Needy Families], Medicaid, Medicare, and private pensions) in major Census Bureau surveys, aiming to extract the evidence on differences in survey accuracy by race and ethnicity. Our key finding is a strong and robust pattern of greater measurement error for Black and Hispanic individuals and households relative to whites. The dominant error is underreporting for a wide variety of programs, samples, and surveys. Table 4 shows that receipt rates [for all groups] are markedly higher using the administrative values than the survey values. The increases in receipt rates tend to be largest for Black and Hispanic individuals. For white individuals, the biases in receipt rates are smaller in fractional terms, with SNAP and pension receipt less than doubling and TANF and UI receipt increasing by about a third. The implication is that the safety net better supports minority groups than the survey data suggest, through higher program receipt and greater poverty reduction.

Takeaways by Macro Roundup® AI

  1. Reviewing linked survey–administrative data for SNAP, Social Security, Unemployment Insurance, TANF, Medicaid, Medicare, and private pensions in major Census Bureau surveys, the authors find a strong and robust pattern of greater measurement error for Black and Hispanic individuals and households than for whites.
  2. Administrative records show markedly higher program receipt rates than Census Bureau survey values for all groups, with the largest increases for Black and Hispanic individuals; for whites, SNAP and pension receipt less than double and TANF and UI receipt rise by about a third.
  3. Underreporting is the dominant error across a wide variety of programs, samples, and surveys, implying that the safety net supports minority groups better than survey data suggest, through higher program receipt and greater poverty reduction.

Related Articles:

  • Evaluating the Success of the War on Poverty since 1963 Using an Absolute Full-Income Poverty Measure — The authors estimate that an absolute full-income poverty measure, which counts a fuller set of income sources and adjusts thresholds only for inflation, fell from 19.5% to 1.6%, versus an official decline to 10.5%. They also find relative poverty reductions modest and government dependence more than doubled among working-age adults.
  • Another Wrong Way to Measure Poverty — The official U.S. poverty measure has barely changed in over 50 years because most social benefits aren't counted as recipient income, even as benefits to the average household in the bottom 20% rose from $9,700 to $45,000 in inflation-adjusted dollars; counting all benefits puts poverty at 2.5%.
  • Homelessness and the Persistence of Deprivation: Income, Employment, and Safety Net Participation — Linking census records of sheltered and unsheltered homeless adults to tax and benefit data, the authors find nearly half had formal employment while homeless and nearly all worked or received at least one safety net program, yet incomes stayed low across the surrounding decade, suggesting homelessness arises amid long-term deprivation rather than sudden income loss.

AI Summary. Valuations of AI-related stocks remain well below levels seen in past bubbles, with the median price-to-earnings and enterprise-value-to-sales ratios of the 7 largest technology companies roughly half those of the dominant 7 at the 2000 technology peak. But leading AI firms are no longer capital-light, and a major capital-spending boom threatens the high returns current valuations imply will continue.

Peter Oppenheimer, Guillaume Jaisson, Sharon Bell and Lilia Peytavin Goldman Sachs
Date Posted:

Peter Oppenheimer argues for “Tech’s rational exuberance,” noting the median PE and EC/Sales of the 7 largest tech firms are ~ half of those seen in the tech bubble. But the capital-intensive AI buildout “threatens to stifle the high rates of return.”

Are AI stock valuations at bubble levels?

Core argument: The median PE and enterprise value/sales of the 7 biggest technology companies today is roughly half that of the dominant 7 at the peak of the 2000 technology bubble.

Despite the significant interest that AI has generated, it still does not appear to have driven a bubble in valuations which sets it apart, so far at least, from previous narrative investment cycles like the internet in the late 1990s. Current valuations are much lower than have been typical in recent bubble periods, stretching back to the Nifty 50 era of the early 1970s, the Japanese bubble in the late 1980s, and the technology bubble in 2000. The median PE and EC/Sales of the 7 biggest technology companies today is roughly half that of the dominant 7 at the peak of the technology bubble in 2000. [But] AI winners of today are no longer capital-light businesses. Just as we saw with the networking companies of the internet, AI is driving a major capex boom and threatens to stifle the high rates of returns that have characterised the sector over the past 15 years and which current valuations imply will continue. Many leading tech companies are now ramping up their spending at an extraordinary rate.

Takeaways by Macro Roundup® AI

  1. The median PE and enterprise value/sales of the 7 biggest technology companies today is roughly half that of the dominant 7 at the peak of the 2000 technology bubble.
  2. Current valuations sit well below those typical of prior bubble periods, including the Nifty 50 era of the early 1970s, Japan's late-1980s bubble, and the 2000 technology bubble.
  3. Today's AI winners are no longer capital-light businesses, as AI drives a major capex boom that threatens the high rates of return of the past 15 years that current valuations imply will continue.

Related Articles:

  • A Severe Case of COVIDIA: Prognosis For An AI-Driven US Equity Market — Computing cycles move from infrastructure to platforms to applications, and NVIDIA data center revenues as a share of market-wide capital spending are projected to reach levels last seen at the 1969 mainframe peak and the dot-com boom. Large cloud providers spend more than twice as much training foundational models as running them for customers.
  • Gen AI: Too Much Spend, Too Little Benefit? — The author argues generative AI is unlikely to drive revenue expansion because it helps employees find information faster rather than find better information. If AI's benefits remain limited to efficiency gains, competitors can adopt the same tools, so cost savings get arbitraged away rather than raising prices or margins.
  • Are We on the Brink of an AI Investment Arms Race? — Spending on AI chips and data centers was a bit below $100bn in 2023, around 0.4% of US GDP, and the broader set of companies exposed to AI-related investment has not yet seen a major jump in sales. The authors argue the underlying dynamics point to a spending surge large enough to shape the business cycle.

AI Summary. The U.S. marriage rate has fallen more than 60% since 1970, from 85.9 to 30.5 marriages per 1,000 unmarried Americans aged 15 and older, and the share of adults who are married has dropped from 72% to about 50%. Demographers project roughly one in three young adults may never marry.

W. Bradford Wilcox and Alan Hawkins Journal of Policy Analysis and Management
Date Posted:

Only ~ 50% of American adults are currently married, down from 72% in 1960. @BradWilcoxIFS notes that children raised in single-parent families, “are about 4 times more likely to be poor, compared to those raised in married families.”

How far has American marriage declined in recent decades?

Core argument: The U.S. marriage rate has fallen more than 60% since 1970, from 85.9 marriages per 1,000 unmarried Americans aged 15 and up to 30.5 per 1,000 by 2021.

The U.S. marriage rate has fallen by more than 60% since 1970. In 1970, 85.9 men and women married per 1,000 unmarried Americans 15 and up. By 2021, that number had fallen to 30.5 per 1,000. Likewise, the median age of marriage has risen for men from 23 in 1970 to 30.5 in 2022 and for women from 21 in 1970 to 28.6 in 2022. The practical significance of this is that only about 50% of American adults are currently married, down from 72% in 1960. Moreover, demographers now project that a record share of young adults, about one in three, may never marry.

Takeaways by Macro Roundup® AI

  1. The U.S. marriage rate has fallen more than 60% since 1970, from 85.9 marriages per 1,000 unmarried Americans aged 15 and up to 30.5 per 1,000 by 2021.
  2. About 50% of American adults are married, down from 72% in 1960, and demographers project that roughly one in three young adults may never marry.
  3. The median age at marriage rose from 23 in 1970 to 30.5 in 2022 for men, and from 21 to 28.6 over the same period for women.

Related Articles:

  • Young Adults in the U.S. Are Reaching Key Life Milestones Later Than in the Past — Pew Research Center analysis of Census Bureau data finds 21-year-olds in the US are less likely than their counterparts four decades earlier to have a full-time job, be financially independent, live on their own, be married, or have a child. Among 21-year-olds, 39% worked full time versus 64% four decades earlier, and a quarter were financially independent versus 42%.
  • In a Growing Share of U.S. Marriages, Husbands and Wives Earn About the Same — In 29% of U.S. opposite-sex marriages both spouses earn about the same, 55% have a husband as primary or sole earner, and 16% have a primary-earning wife. The share of marriages in which the husband is the sole provider fell from 49% to 23% over the past 50 years.
  • Intermarriage in America Post-Loving v. Virginia — US interracial marriage rates showed no decline despite heightened public discourse about racial tension, a metric where increased racial tension would be expected to register. The author argues America's ethnoracial composition is more mixed than it has ever been, resembling a Latin American country more than a European one.

AI Summary. US public investment spending has defended Rust Belt economies while accelerating growth in the already-booming Sun Belt, and at the local level has benefited rural, conservative areas more than urban, liberal ones — a design lawmakers intended to counter regional inequality and build political durability for the projects.

Joseph Politano Apricitas Economics
Date Posted:

.@JosephPolitano cites 18 House Republicans’ efforts to protect clean energy tax credits in the IRA from repeal and argues that spending from the infrastructure bill, IRA, and CHIPS Act may create a coalition inside the GOP to protect these bills.

How is public investment spending reshaping regional and local economies?

Core argument: America's public investment boom has primarily defended the economies of the long-struggling Rust Belt while accelerating growth in the long-booming Sun Belt.

At a broader regional level, spending has primarily served to defend the economies of the long-struggling Rust Belt while accelerating growth in the long-booming Sun Belt. At the most local levels, the growth in public investment has benefitted America’s rural, conservative areas more than its urban, liberal ones—an intentional effort crafted by lawmakers to combat the regional inequalities of the 2010s and buy political staying power for the projects’ end goals. There’s some evidence this strategy is already working—no Republican voted for the Inflation Reduction Act when it was passed two years ago, but this month 18 House Republicans signed a letter pleading for Speaker Johnson to spare the bill’s clean energy tax credits from possible repeal efforts. Those signers included representatives from Georgia, Arizona, Indiana, Virginia, Utah, and Nebraska.

Takeaways by Macro Roundup® AI

  1. America's public investment boom has primarily defended the economies of the long-struggling Rust Belt while accelerating growth in the long-booming Sun Belt.
  2. At the most local level, growth in U.S. public investment has benefitted rural, conservative areas more than urban, liberal ones, an intentional design by lawmakers to counter the regional inequalities of the 2010s and build political staying power for the projects.
  3. No Republican voted for the Inflation Reduction Act when it passed two years ago, yet 18 House Republicans—including members from Georgia, Arizona, Indiana, Virginia, Utah, and Nebraska—signed a letter asking Speaker Johnson to spare its clean energy tax credits from repeal.

Related Articles:

  • Business Spending Is Lining Up to Reinforce Growth — Around 70% of sectors are posting positive year-over-year profit growth, with big tech showing the largest acceleration in demand and profits but strength broadening across the economy. Companies are responding with rising capital spending growth and more optimistic investment plans, as firms typically add capacity with a slight lag after real demand picks up.
  • With US Chips Act Money Mostly Divvied Up, the Real Test Begins — The US Chips Act is a bet that Intel, Micron, Taiwan Semiconductor Manufacturing, and Samsung can return advanced chip production to the US, with an explicit goal of making a fifth of the world's most advanced processors by 2030, up from roughly zero. Nearly 100 companies have pledged about $400bn in US facilities.
  • Republican Districts Dominate US Clean Technology Investment Boom — A Financial Times analysis found that more than 80% of pledged investment in large-scale clean energy and semiconductor manufacturing is destined for Republican congressional districts. The analysis attributes this partly to those districts' available land and cheap labor, and to state-level tax breaks and subsidies in states such as Georgia and Ohio.

Friday, September 6, 2024

AI Summary. Markets are never perfectly efficient because betting against other investors' errors carries risk, and the author argues social media, investor overconfidence, and gamified 24/7 trading have made markets meaningfully less efficient, with indexing and very low interest rates a smaller contributor. The recommended response is to adopt the longest possible investment time horizon.

Clifford Asness The Journal of Portfolio Management
Date Posted:

.@CliffordAsness notes large and prolonged swings in US stock market valuations since 1990, and contends that the market has become “less informationally efficient.” He advocates having “the longest time horizon possible” to wait out bubbles.

Have markets become less efficient, and how should investors respond?

Core argument: Asness argues markets are never perfectly efficient because betting against other investors' errors, even when correctly identified, is not riskless; efficiency rises as more rational investors take the other side and falls as more irrational traders act more irrationally.

Markets are never perfectly efficient, as taking the other side of other investors’ errors, even if you correctly identify them, is still not riskless. The more rational investors taking the other side, the more efficient. The more minnows doing crazy things, and the crazier they are, the less so. I think the rise of indexing and the super low interest rates of the last 10-15 years may have had exactly this effect (more crazy, and crazier, minnows, fewer rational G&D disciples), but I conjecture that’s a relatively small part of the story. I’m far more certain that social media, the overconfidence that comes when people think all the world’s data is at their fingertips, and gamified, fake-free, instant, 24/7 trading has done so in a significant way. Assuming a valuation change will continue to go on forever is obvious folly. So, pushing yourself (and whoever you report to!) to have the longest time horizon possible is definitely #1 on the list. Quoting myself, “A long-term horizon is the closest thing to an investing superpower.”

Takeaways by Macro Roundup® AI

  1. Asness argues markets are never perfectly efficient because betting against other investors' errors, even when correctly identified, is not riskless; efficiency rises as more rational investors take the other side and falls as more irrational traders act more irrationally.
  2. Asness expresses greater certainty that social media, the overconfidence that comes when people think all the world's data is at their fingertips, and gamified, fee-free, instant, 24/7 trading have made markets significantly less efficient.
  3. Asness conjectures that the rise of indexing and the very low interest rates of the past 10–15 years produced more and crazier small irrational traders and fewer Graham-and-Dodd disciples, but calls this a relatively small part of the story.

Related Articles:

  • Cliff Asness: AI is ‘Still Just Statistics’ — Artificial intelligence in investing is still statistics — data goes in and a forecast comes out — and is not as revolutionary as many claim, the author argues. Questions such as the premium for high- versus low-quality stocks or value versus growth involve a small-data problem, not a big-data one, so more computation cannot answer them.
  • Economist Eugene Fama: ‘Efficient Markets Is A Hypothesis. It’s Not Reality’ — Technology stocks surged and then collapsed in the late 1990s, but the underlying premise that the internet would create hugely profitable new companies proved correct, with some prices too low even as most were too high. Amazon is now worth about a quarter of the Nasdaq's entire market capitalization at its dotcom peak.
  • Which U.S. Stocks Generated the Highest Long-Term Returns? — Of the 29,078 U.S. common stocks in a database spanning nearly a century, 51.6% had negative cumulative returns, while 17 stocks returned more than 5m% — led by Altria at 265m%. Those top performers averaged annualized returns of just 13.47%, underscoring the value of time invested.

AI Summary. Taiwan Semiconductor Manufacturing Co.'s trial production yields at its first advanced Arizona plant, which uses 4-nanometer process technology, are similar to those at comparable facilities in Tainan, Taiwan, according to a person familiar with the company. The company had delayed full production at the site, citing a lack of skilled workers.

Debby Wu Bloomberg
Date Posted:

Initial production yields at TSMC’s Arizona facility are on par with the yields at comparable Taiwanese fabs. There have been concerns about the efficiency of their US facilities due to a lack of skilled workers.

Can advanced chip plants in the US match yields achieved in Taiwan?

Core argument: TSMC's Arizona plant reached trial-production yields similar to comparable facilities in Tainan, Taiwan, according to a person familiar with the company, an early indicator the US project is on track to meet its targets.

Taiwan Semiconductor Manufacturing Co. achieved production yields at its Arizona facility on par with established plants back home, an early indicator that its marquee US project is on track to achieve its targets. The Taiwanese chipmaker’s yield rate in trial production at its first advanced US plant is similar to comparable facilities in the southern Taiwanese city of Tainan, according to a person familiar with the company, who asked not to be identified discussing private corporate matters. TSMC had said it started engineering wafer production in April with advanced 4-nanometer process technology. TSMC originally planned to have its first Arizona plant start full production in 2024, but pushed back the target to 2025 due to a lack of skilled workers. The delay fueled concerns that the company might not be able to make chips in the US as efficiently as in Taiwan.

Takeaways by Macro Roundup® AI

  1. TSMC's Arizona plant reached trial-production yields similar to comparable facilities in Tainan, Taiwan, according to a person familiar with the company, an early indicator the US project is on track to meet its targets.
  2. TSMC said it began engineering wafer production at its first advanced Arizona plant in April using 4-nanometer process technology.
  3. TSMC pushed its Arizona full-production target from 2024 to 2025 due to a lack of skilled workers, a delay that fueled concerns the company could not make chips in the US as efficiently as in Taiwan.

Related Articles:

  • With US Chips Act Money Mostly Divvied Up, the Real Test Begins — The US Chips Act is a bet that Intel, Micron, Taiwan Semiconductor Manufacturing, and Samsung can return advanced chip production to the US, with an explicit goal of making a fifth of the world's most advanced processors by 2030, up from roughly zero. Nearly 100 companies have pledged about $400bn in US facilities.
  • The Chips Act Has Been Surprisingly Successful So Far — The US government has spent over half of its $39bn in Chips Act semiconductor incentives, and chip companies and supply chain partners have announced $327bn of investments over the next 10 years, according to Semiconductor Industry Association calculations. US data show a 15-fold increase in construction of computing and electronics manufacturing facilities.
  • Business Spending Is Lining Up to Reinforce Growth — Around 70% of sectors are posting positive year-over-year profit growth, with big tech showing the largest acceleration in demand and profits but strength broadening across the economy. Companies are responding with rising capital spending growth and more optimistic investment plans, as firms typically add capacity with a slight lag after real demand picks up.

AI Summary. Polling shows Kamala Harris underperforming in swing states relative to her national numbers, a pattern especially evident in Pennsylvania. Donald Trump has also been gaining ground in most state polling averages, which are not affected by the forecast's convention bounce adjustment.

Nate Silver and Eli McKown-Dawson Silver Bulletin
Date Posted:

Noting “Harris is underperforming in swing states relative to her national numbers” (she is up 3pp nationally). @NateSilver538 gives Trump a 61.7% chance of winning PA and a 61.5% chance of winning the electoral college. The first debate is Tuesday.

Is the Democratic candidate underperforming in swing states relative to national polling?

Core argument: Polls show Kamala Harris underperforming in swing states relative to her national numbers, a recurring pattern in the Silver Bulletin forecast, especially in Pennsylvania.

Another day, another set of polls showing Kamala Harris underperforming in swing states relative to her national numbers. No, it’s not from the world’s best pollster, but this has been a theme lately, especially in Pennsylvania. Yes, Harris’s forecast — remains subject to a convention bounce adjustment, although the impact is decreasing a bit. But Trump has been gaining ground on her in most of our state polling averages, too — and they aren’t impacted by the convention bounce adjustment at all.

Takeaways by Macro Roundup® AI

  1. Polls show Kamala Harris underperforming in swing states relative to her national numbers, a recurring pattern in the Silver Bulletin forecast, especially in Pennsylvania.
  2. Donald Trump has been gaining ground on Harris in most of the Silver Bulletin's state polling averages, which are not affected by the convention bounce adjustment.
  3. Harris's Silver Bulletin forecast remains subject to a convention bounce adjustment, though that adjustment's impact is decreasing.

Related Articles:

  • Many Gen Z Men Feel Left Behind. Some See Trump As An Answer — National polling shows a gender gap of roughly 39 to 51 percentage points among voters under 30, with young men favoring the Republican candidate and young women favoring the Democrat. The Republican message resonates particularly with young men without college degrees and young men of color.
  • Disconnected: The Growing Class Divide in American Civic Life — 17% of Americans report having no close friends, and survey data show a wide educational gap: 24% of those with a high school education or less have no close friends versus 10% of college graduates. Three decades ago, Americans with less formal education reported social circles at least as large.
  • An Unsettled Electorate: How Uncertainty and Apathy Are Shaping the 2024 Election — A survey of young registered voters finds 54% backing Biden and 46% backing Trump, with 60% of young women supporting Biden while 52% of young men support Trump. Young men are more likely than young women to say the country has gone too far in giving women equal rights, 19% versus 9%.

AI Summary. In a study where 200 participants watched a crime video and were then questioned with misleading questions, a generative AI chatbot induced over 3x more immediate false memories than the control condition and 1.7x more than a survey, misleading 36.4% of users' responses.

Samantha Chan, Pat Pataranutaporn, Aditya Suri, et al. MIT Media Lab
Date Posted:

Researchers at MIT @medialab found that after viewing a video of a simulated crime, participants who were asked misleading questions by an AI chatbot generated 3x more false memories than a control group.

Do AI chatbots induce more false memories than surveys?

Core argument: In an experiment with 200 participants who watched a crime video, a generative AI chatbot interviewer induced over three times more immediate false memories than the control condition and 1.7 times more than a survey method.

Participants (N=200) watched a crime video, then interacted with their assigned AI interviewer or survey, answering questions including five misleading ones. False memories were assessed immediately and after one week. Results show the generative chatbot condition significantly increased false memory formation, inducing over 3 times more immediate false memories than the control and 1.7 times more than the survey method. 36.4% of users' responses to the generative chatbot were misled through the interaction. After one week, the number of false memories induced by generative chatbots remained constant. However, confidence in these false memories remained higher than the control after one week. Moderating factors were explored: users who were less familiar with chatbots but more familiar with AI technology, and more interested in crime investigations, were more susceptible to false memories. These findings highlight the potential risks of using advanced AI in sensitive contexts, like police interviews, emphasizing the need for ethical considerations.

Takeaways by Macro Roundup® AI

  1. In an experiment with 200 participants who watched a crime video, a generative AI chatbot interviewer induced over three times more immediate false memories than the control condition and 1.7 times more than a survey method.
  2. Some 36.4% of users' responses to the generative chatbot were misled through the interaction, and the number of false memories it induced remained constant after one week, with confidence in those memories staying higher than in the control condition.
  3. Participants less familiar with chatbots but more familiar with AI technology, and those more interested in crime investigations, were more susceptible to false memories, which the authors link to risks of using advanced AI in settings such as police interviews.

Related Articles:

  • Exploring How AI Will Impact the Economy — Artificial intelligence is projected to pass through to productivity faster than past general-purpose technologies, though peak effects remain years away. The argument rests on lower capital spending per unit of labor saved, capital spending concentrated among major software players that can distribute AI tools through platforms businesses already use, and low unemployment with high wage growth raising incentives to automate.
  • Erik Brynjolfsson: ‘This Could Be The Best Decade in History — Or The Worst’ — Studies of large language models across tasks including software coding, consulting, and writing find double-digit productivity gains appearing within months, with less-skilled workers typically benefiting most. Given the large share of modern work these tools can augment, the author projects US productivity growth near 3% annually in the 2020s, roughly double the Congressional Budget Office's 1.4% projection.