“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard 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
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“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
“…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
“…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
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“A full-throated defense of economic dynamism.” - The Wall Street Journal
AI Summary.Because investors can buy bonds across borders, an investment boom in one country such as the United States can draw in loanable funds from abroad and push up interest rates in other nations. The linkage is not one-for-one, since investors also weigh expected exchange-rate changes and the resulting capital gains or losses.
Paul KrugmanKrugman Wonks Out
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The nominal 10-year Treasury yield is ~ where it was during the mid-2000s housing boom, but below its level during the late-1990s and early-2000s technology boom. Krugman asks, “If we’re now looking at an even bigger investment boom, why wouldn’t we expect to see interest rates at least that high?”
Does an investment boom in one country raise interest rates abroad?
Core argument: Because investors can buy bonds across borders, an investment boom in the United States draws loanable funds from other nations and pushes their interest rates up as well.
Investors can buy bonds across borders, so an investment boom in the United States can draw in loanable funds from other nations and drive up their interest rates. The international linkage between interest rates isn’t always one-for-one. That’s mainly because investors deciding which nation’s bonds to buy don’t just look at interest rates -- they also take into account expected changes in exchange rates. For example, there was a sharp rise in U.S. interest rates in the early 1980s that was only partially matched by a rise in German rates. The reason was that this was also a period of an extremely strong dollar, which many investors believed (correctly) would prove temporary. So German investors buying U.S. bonds had to set the high interest rates they could earn against the capital losses they were likely to experience when the dollar came back to earth.
Takeaways by Macro Roundup® AI
Because investors can buy bonds across borders, an investment boom in the United States draws loanable funds from other nations and pushes their interest rates up as well.
The international linkage between interest rates is not always one-for-one, mainly because investors choosing among nations’ bonds weigh expected exchange rate changes alongside interest rates.
The sharp rise in U.S. interest rates in the early 1980s was only partially matched by German rates, as German investors buying U.S. bonds set high yields against likely capital losses when the strong dollar fell back.
Related Articles:
Financing the AI Buildout— The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
America’s Risky Debt: What Markets See That Policymakers Don’t— Two market-based measures suggest the safety premium investors pay to hold US Treasuries has compressed toward zero and at times reversed: the spread between top-rated corporate bonds and Treasuries after stripping out default risk, and the gap between currency-hedged foreign G10 government yields and Treasury yields at the same maturity, where longer-maturity comparisons now favor foreign bonds.
Don’t Draw The Wrong Conclusion From Treasury Yields— Ten-year real yields equal the average expected overnight rate over the next decade plus a term premium, and fiscal credibility or debt sustainability concerns would show up as a higher term premium. With the term premium and inflation expectations contained, the increase in bond yields reflects higher expected long-term overnight rates.
AI Summary.Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.
Ben Inker and John PeaseGMO
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GMO estimates net US equity supply could increase by ~5% or more of total market capitalization over the next year. Inker and Pease note that in 1999–2000, “IPOs peaked at ~5% of total market cap. It doesn’t take much new supply to overwhelm the market.”
How does rising equity supply from new listings affect stock returns?
Core argument: Controlling for valuations, a 1% increase in the market share of IPOs has historically led to an approximate 4% decrease in prices, a multiplier the author applies to a coming surge in equity supply.
Controlling for valuations, a 1% increase in the market share of IPOs has historically led to an approximate 4% decrease in prices [Exhibit 2 in gallery]. Consider what is happening to equity supply. SpaceX’s non-Elon sales alone exceed 1% of the U.S. stock market’s value. We are likely to see IPOs from both Anthropic and OpenAI—together valued at about 5% of the U.S. stock market’s total investable market cap —over the next 12 months. For the first time in twenty years, with the brief exception of the GFC, we are seeing net dilution in the U.S. stock market (i.e., share issuance exceeding share buybacks), as the hyperscalers continue their capital expenditure spree. In aggregate, we are going from a world where equity supply was shrinking by roughly 1% per annum (with buybacks exceeding primary or secondary issuance) to one in which equity supply will be increasing by close to 5%, if not more. If you believe the 4x multiplier [implied by the regression line in Exhibit 2], this means we should expect returns that are some 20% below average (roughly 6% real) over the next 12–18 months from the headwind of rising equity supply alone.
Takeaways by Macro Roundup® AI
Controlling for valuations, a 1% increase in the market share of IPOs has historically led to an approximate 4% decrease in prices, a multiplier the author applies to a coming surge in equity supply.
U.S. equity supply is shifting from shrinking roughly 1% a year, with buybacks exceeding issuance, to growing close to 5% or more, the first net dilution in twenty years apart from the Global Financial Crisis.
Anthropic and OpenAI, together valued at about 5% of U.S. investable market cap, are likely to go public within 12 months, while SpaceX’s non-Elon sales alone exceed 1% of the U.S. stock market’s value.
Related Articles:
Momentum, Rotation and the Value in Growth— After a fifteen-year stretch in which US equities, technology and growth stocks led, equity gains have broadened geographically, with the US the weakest of the major regions. The five largest US stocks now trade at a price-to-earnings ratio only marginally above the other 495, after holding a consistent premium since 2017.
SpaceX and OpenAI Are Ending Wall Street’s Era of Stock Scarcity— JPMorgan projects that share sales will add roughly $1.5tn of stock to the US equity market over the next two years even after buybacks, which would be the strongest net equity issuance since at least the late 1990s. Equity has grown cheaper relative to debt as a funding source.
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.
AI Summary.The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
Stijn Van NieuwerburghBrookings Papers on Economic Activity
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Stijn Van Nieuwerburgh projects ~$10.3T will be spent on the AI buildout over 2025–2032, averaging 3.63% of GDP. He estimates 2/3 of that spending reflects IT equipment and one-third real estate and associated power infrastructure.
How much of the planned data center pipeline gets built?
Core argument: Using Cleanview project-level data from July 2026, the authors estimate roughly 57 GW of operating U.S. data center capacity against a planned development pipeline of roughly 509 GW, which they stress is not a completion forecast.
The required investment is enormous. A representative 200 MW AI training campus costs roughly $8.2 billion, about two-thirds of which reflects IT equipment and one-third the real estate and associated power infrastructure. We estimate that 183 GW is completed by 2032 with a further 118 GW completed after 2032. This pipeline will trigger about $10.3 trillion dollars of investment over 2025–2032. At an average of 3.63% of GDP per year, the projected buildout would be larger relative to the economy than the major U.S. canal, railroad, electrification, highway, and telecommunications investment booms. It would double the electricity consumption of the entire U.S. residential sector.
Takeaways by Macro Roundup® AI
Using Cleanview project-level data from July 2026, the authors estimate roughly 57 GW of operating U.S. data center capacity against a planned development pipeline of roughly 509 GW, which they stress is not a completion forecast.
The authors’ central scenario allocates the announced pipeline so that 182.8 GW of additional U.S. capacity becomes operational during 2025–32, including 19.0 GW tied to projects already operational in 2025 or 2026.
The authors’ scenario has 117.2 GW of planned data center capacity completed after 2032 and 226.9 GW never completed, applying lower realization rates to more distant and less fully documented projects.
Related Articles:
Rear Window— Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.
AI Set to be Largest CapEx Cycle Ever … and Soon Majority Externally Financed— Hyperscaler and data-center investment is tracking toward $1.5tn annually by 2030, which in real terms would exceed the 2005-06 housing boom, the 1990s fiber peak, and the 1882 railroad peak combined. External debt and equity are projected to fund close to 90% of the buildout, making it dependent on credit markets.
The Summer I Turned Pretty— A warning sign in a boom cycle is when companies closest to final demand weaken while capital spending beneficiaries keep thriving, as when telecom operators' shares rolled over while communications equipment stocks kept rising. Semiconductor stock prices and free cash flow are soaring while large cloud providers' shares stagnate and their free cash flow plummets.
AI Summary.Global investment in "deep tech" — companies whose products rest on major scientific or engineering advances — has exceeded $150bn since the start of 2024, more than the $133bn invested in the decade through 2019, excluding sums poured into AI start-ups. Failed battery and electric-vehicle bets from an earlier peak illustrate the risks of such moonshot dealmaking.
Tim BradshawFinancial Times
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Since the start of 2024, more than $150B of venture capital has been invested into non-AI “deep tech” firms whose products are rooted in significant engineering advances, exceeding the $133B invested in such firms btw 2010 and 2019.
Is the AI boom pushing venture capital toward riskier moonshot bets?
Core argument: Global "deep tech" investment excluding AI start-ups has exceeded $150bn since the start of 2024, more than the $133bn invested in the entire decade through 2019, according to Dealroom.
The AI boom is fuelling a resurgence in ambitious “moonshot” bets, as early SpaceX backers’ huge returns and falling valuations for traditional software companies force tech investors to embrace riskier and more capital-intensive dealmaking. Excluding the giant sums ploughed into AI start-ups, global investment in “deep tech” — companies whose products are rooted in big scientific or engineering advances — has exceeded $150bn since the start of 2024, more than the $133bn in the entire decade to the end of 2019, according to Dealroom. This year’s deep-tech investments have not yet surpassed 2021’s peak, which was propelled by battery and electric vehicle deals for the likes of Rivian and Northvolt — many of which turned sour, highlighting the risks involved in moonshot dealmaking.
Takeaways by Macro Roundup® AI
Global "deep tech" investment excluding AI start-ups has exceeded $150bn since the start of 2024, more than the $133bn invested in the entire decade through 2019, according to Dealroom.
Huge returns for early SpaceX backers and falling valuations for traditional software companies are pushing tech investors toward riskier, more capital-intensive "moonshot" dealmaking.
Deep-tech investment has not yet surpassed the 2021 peak, which was propelled by battery and electric vehicle deals for companies such as Rivian and Northvolt, many of which turned sour.
Related Articles:
Capital Is Making a Comeback— Tangible investment in property, factories and equipment fell from 12.5% to 8.5% of private gross domestic product, while intangible investment in intellectual property, software and process knowledge rose from about 11.5% to 16.75%. The author argues demand for tangible capital investment will now have to rise.
Public to Private Equity in the United States: A Long-Term Look— An analysis of more than 31,000 global venture capital deals finds 62% lost money and over half lost 50–100% of invested capital, though the distribution of returns has much fatter tails than buyouts or public equities. Venture funds averaged a public market equivalent ratio of about 1.4, indicating returns above public markets.
Gross and Net US Investment— Net US investment has fallen from roughly 40% of gross investment in the 1970s to about 25% in the past decade, meaning about three-quarters of gross investment now just replaces depreciating capital. The author attributes this gap to modern investment being more information-technology-related, which depreciates faster and requires more frequent replacement.
AI Summary.Employment in five industries tied to the data-centre build-out, including electrical contracting and equipment manufacturing, has risen roughly 320,000 above what broader construction and manufacturing trends would suggest. Engineers, software developers, mathematicians and data scientists have added about 730,000 jobs above the trend for professional employment overall.
Economist StaffThe Economist
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The Economist estimates that so far the AI boom has created ~1mm new jobs in the US, exceeding their estimate of ~200,000 layoffs attributed to AI since mid-2023.
Is the AI build-out adding jobs above trend?
Core argument: Employment in five industries tied to the data-centre build-out, from electrical contracting to equipment manufacturing, has risen by roughly 320,000 more since 2023 than broader construction and manufacturing trends would suggest.
[We] tracked five industries at the heart of the data-centre build-out, from electrical contracting to equipment manufacturing. Since 2023 employment in them has risen by roughly 320,000 more than broader construction and manufacturing trends would suggest. Not all of those jobs owe their existence to AI—grid upgrades and other factory building matters too. [We also] tracked employment in professional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists—and compared their growth since 2022 with professional employment overall. These roles have added roughly 730,000 jobs above trend in recent years. AI will not have created every single one of them. But it has almost certainly created quite a few.
Takeaways by Macro Roundup® AI
Employment in five industries tied to the data-centre build-out, from electrical contracting to equipment manufacturing, has risen by roughly 320,000 more since 2023 than broader construction and manufacturing trends would suggest.
Professional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists—have added roughly 730,000 jobs above the trend for professional employment overall since 2022.
Not all of these above-trend gains are attributable to AI, since grid upgrades and other factory building also matter, though AI has almost certainly created quite a few of them.
Related Articles:
The College Wage Premium in the Generative AI Era— The U.S. college wage premium fell from 0.626 to 0.575 after four decades of expansion, implying the first sustained negative growth in relative demand for college-educated labor. The authors estimate that weaker wage growth in occupations highly exposed to artificial intelligence accounts for roughly 28% of that decline, though the patterns are not causal.
Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence— Employment for workers aged 22–25 in the occupations most exposed to artificial intelligence has declined roughly 18pp relative to less-exposed peers, with no comparable decline in other age groups. The authors find this operates mainly through reduced hiring, concentrated where AI substitutes for human tasks rather than complements them.
Looking for the Ladder— The article argues that the hiring downturn in occupations most exposed to generative AI reflects interest-rate sensitivity rather than AI itself, since roughly 38% of workers in the most AI-exposed quintile work in information, finance and insurance, and professional and technical services, versus under 2% in the least-exposed quintile.
AI Summary.Net US investment has fallen from roughly 40% of gross investment in the 1970s to about 25% in the past decade, meaning about three-quarters of gross investment now just replaces depreciating capital. The author attributes this gap to modern investment being more information-technology-related, which depreciates faster and requires more frequent replacement.
Timothy TaylorConversable Economist
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U.S. real net private domestic investment—which adds to the American capital stock—is now only ~25% as large as gross investment, down from ~40% in the 1970s. Taylor suggests the widening gap between gross and net investment reflects the relatively rapid depreciation of IT-related capital.
Why does less of US gross investment add net capital?
Core argument: US net investment has run at about 25% of gross investment over the past decade, down from roughly 40% in the 1970s, meaning about three-quarters of gross investment merely replaces depreciated capital.
The figure divides net investment by gross investment. Back in the 1970s, net investment was often around 40% of gross investment, but the share has been slumping over time. For the last decade or so, net investment has been about 25% of the gross–that is, about three-quarters of gross investment is just making up for depreciation of the pre-existing capital stock. The likely reason for the growing gap between gross and net investment is that modern investment is more likely to be related to information technology [which] depreciates more rapidly and thus needs to be replaced and updated more often. If we want the average US worker to be using a greater amount of capital on the job–which was one of the key drivers of rising labor productivity in the past–it now takes a bigger rise in gross investment to lead to a given rise in net investment.
Takeaways by Macro Roundup® AI
US net investment has run at about 25% of gross investment over the past decade, down from roughly 40% in the 1970s, meaning about three-quarters of gross investment merely replaces depreciated capital.
The likely reason for the widening gap between gross and net US investment is that modern investment is more tied to information technology, which depreciates more rapidly and must be replaced and updated more often.
Raising the capital used by the average US worker—a key driver of past labor productivity growth—now requires a larger rise in gross investment to achieve a given rise in net investment.
Related Articles:
US Stock Market To Stop Shrinking For First Time In 23 Years— Goldman Sachs estimates that net supply of US equity — new shares issued less shares removed by buybacks and take-privates — will be roughly flat in 2026 after being negative since 2003, with a larger influx expected in 2027 as lock-up periods on this year's initial public offerings expire.
Capital Is Making a Comeback— Tangible investment in property, factories and equipment fell from 12.5% to 8.5% of private gross domestic product, while intangible investment in intellectual property, software and process knowledge rose from about 11.5% to 16.75%. The author argues demand for tangible capital investment will now have to rise.
The Transition to a Higher Cost of Capital— Bond yields near 4.5% sit below the 5.5% short-term interest rate, leaving little risk premium, and those yields have been enough to draw buyers back toward normal bond holdings. The author argues yields still need to rise to a sustainable cost of capital given structurally higher fiscal and inflationary spending.
AI Summary.Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.
Michael CembalestJ.P. Morgan
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Since the start of the data-center buildout, S&P earnings breadth has “eclipsed” that which would be historically implied by the ISM manufacturing survey. Cembalest argues earnings growth “appears highly contingent” on continued hyperscaler spending.
How dependent is earnings growth on hyperscaler capital spending?
Core argument: Q2 annual cloud revenue growth ran 37% at AWS, 43% at Microsoft Azure and 82% at Google Cloud, with Google Cloud's backlog up $52bn to $514bn and AWS's backlog at $496bn, up 36% q/q.
The Q2 earnings season was positive for hyperscaler annual revenue growth: AWS 37%, Microsoft Azure 43% and Google Cloud 82%. Rising revenue backlogs reinforce evidence of AI monetization: Google Cloud’s backlog increased $52B to $514B, and the AWS backlog rose to $496B, up 36% q/q. Earnings growth is also more broad-based than it was in 2024-2025 when AI was the primary driver. Earnings growth appears highly contingent on continued hyperscaler capital spending and R&D which rose from $460B in 2024 to $870B over the last 12 months. The share of S&P 500 companies with positive expected earnings growth is normally well-predicted by the ISM manufacturing survey. But since the AI capital spending boom began, earnings breadth has eclipsed the improvement in manufacturing surveys; this suggests a powerful trickle-down effect from hyperscalers to other sectors.
Takeaways by Macro Roundup® AI
Q2 annual cloud revenue growth ran 37% at AWS, 43% at Microsoft Azure and 82% at Google Cloud, with Google Cloud's backlog up $52bn to $514bn and AWS's backlog at $496bn, up 36% q/q.
Hyperscaler capital spending and R&D rose from $460bn in 2024 to $870bn over the last 12 months, and earnings growth appears highly contingent on that spending continuing.
The share of S&P 500 companies with positive expected earnings growth has eclipsed the improvement in the ISM manufacturing surveys that normally predict it, suggesting a trickle-down effect from hyperscalers to other sectors.
Related Articles:
AI Set to be Largest CapEx Cycle Ever … and Soon Majority Externally Financed— Hyperscaler and data-center investment is tracking toward $1.5tn annually by 2030, which in real terms would exceed the 2005-06 housing boom, the 1990s fiber peak, and the 1882 railroad peak combined. External debt and equity are projected to fund close to 90% of the buildout, making it dependent on credit markets.
The Summer I Turned Pretty— A warning sign in a boom cycle is when companies closest to final demand weaken while capital spending beneficiaries keep thriving, as when telecom operators' shares rolled over while communications equipment stocks kept rising. Semiconductor stock prices and free cash flow are soaring while large cloud providers' shares stagnate and their free cash flow plummets.
The Buyers of AI Are Still Waiting for the Payoff— Companies in the S&P 500 outside the technology sector are spending heavily on artificial intelligence without showing gains in profit margins, with health care margins halved since 2015, consumer staples near 6%, and consumer discretionary near 8%. So far the artificial intelligence capital spending boom appears in sellers' margins rather than buyers'.
AI Summary.Inflation-protected U.S. Treasury yields rose from about 3.5% in early 1997 to about 4.5% by 2000, compared with roughly 2.4% on the 10-year and 3% on the 30-year today. The author argues that this 1990s experience helps calibrate expectations if new software technologies produce a comparable acceleration in productivity growth.
Matt KleinThe Overshoot
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Klein compares measures of real rates from the 1990s productivity boom to today’s real rates, using TIPS, as well as “synthetic TIPS” derived by subtracting inflation expectations from nominal rates. Current real rates are very low by comparison.
Would faster productivity growth from new software technologies push real yields higher?
Core argument: Real yields on TIPS were roughly 3.5% when the securities were introduced at the start of 1997 and rose gradually to about 4.5% by the peak of the bubble in 2000.
Real yields on actual TIPS were ~3.5% when they first arrived at the beginning of 1997, and then rose gradually to ~4.5% by the peak of the bubble in 2000. Yields on “synthetic” TIPS derived by removing estimates of inflation expectations from nominal yields were also around 3.5% in early 1997 and 4.5% in the first half of 2000, though they were more volatile in between. The yield on the benchmark 10y TIPS is currently 2.4% while the yield on the 30y TIPS is around 3%. Knowing what actually happened in the 1990s is helpful for calibrating expectations about what could happen in the next decade, if new software technologies lead to a comparable acceleration in productivity growth.
Takeaways by Macro Roundup® AI
Real yields on TIPS were roughly 3.5% when the securities were introduced at the start of 1997 and rose gradually to about 4.5% by the peak of the bubble in 2000.
"Synthetic" TIPS yields, derived by stripping estimates of inflation expectations out of nominal yields, also stood near 3.5% in early 1997 and 4.5% in the first half of 2000, with more volatility in between.
The benchmark 10-year TIPS yields 2.4% and the 30-year TIPS around 3%, while the 1990s experience offers a guide for calibrating expectations if new software technologies deliver a comparable acceleration in productivity growth.
Related Articles:
AI, Productivity, and Rates: Part I— A San Francisco Federal Reserve model estimates that the growth contribution from rising resource utilization in recent quarters has been larger than in almost any comparable five-quarter stretch since 1947 outside recoveries from downturns. That measure is based on a modified version of the average worker's weekly hours rather than unemployment or capacity utilization.
AI and Productivity— The recent pickup in US labor productivity appears driven by higher utilization of existing capital—running factories, server racks, and hotel rooms harder—rather than by firm-level efficiency gains from AI. Adoption remains too thin and the cross-sectional evidence too weak to conclude that AI-driven productivity gains are already widespread.
Have We Entered an Era of High Productivity Growth?— Labor productivity has grown solidly while the San Francisco Federal Reserve's total factor productivity index, which adjusts for the equipment and technology workers use, has grown modestly, suggesting gains so far reflect better tools rather than broader advances. A regime-switching model puts the probability of a high-productivity regime at 57% using labor productivity and 21% using total factor productivity.
