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


Wednesday, June 10, 2026

AI Summary. Using AT&T's exclusive iPhone carrier period as a natural experiment, the authors estimate that smartphone diffusion reduced fertility by 8.0% among women aged 15–19 and 6.6% among those aged 20–24, with smaller but statistically significant effects at older ages. Survey data show younger cohorts socializing, dating, and drinking less.

Caitlin Myers and Ezekiel Hooper National Bureau of Economic Research
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Using spatial variation in AT&T 3G coverage, an event study of the 2007 introduction of the iPhone finds that iPhone use reduced fertility, particularly among women <24, likely because it was associated with reduced in-person interactions.

Did smartphone adoption lower fertility rates, especially among young women?

Core argument: A synthetic difference-in-differences event study estimates that iPhone carrier coverage reduced fertility by 8.0% at ages 15–19 and 6.6% at ages 20–24 (p < 0.01), with smaller but still statistically significant effects for older cohorts.

The general fertility rate (GFR) — annual live births per 1,000 women aged 15–44 — remained roughly constant at 65 to 70 from 1980 through 2007, then began a sharp decline that has continued for nearly two decades. The iPhone, which was launched in June 2007, diffused rapidly across every demographic group and is consequential for how young adults spend their time. The cohorts whose adolescence overlapped with smartphone diffusion spend sharply less time on face-to-face socialising, dating, paid work, drinking, and driving, and report fewer sexual partners and rising sexual inactivity in young adulthood. Figure 4 reports the results of an SDID (synthetic differences in differences) event study by five-year age band. At ages 15–19, the average ATT coverage effect on fertility is −8.0%, and at ages 20–24, the ATT is −6.6% (p < 0.01). It is much smaller, but still statistically significant for the older cohorts. Figure 6 uses the results of these analyses to produce adjusted predictions of the log fertility rate in an alternate world in which the iPhone was not introduced in 2007. Figure 9 shows in-person social interaction and psychological well-being, for the isolation channel; Figure 10 shows pornography access. These are descriptive trends in nationally representative survey data, consistent with the channels we propose but not a test of any of them.

Takeaways by Macro Roundup® AI

  1. A synthetic difference-in-differences event study estimates that iPhone carrier coverage reduced fertility by 8.0% at ages 15–19 and 6.6% at ages 20–24 (p < 0.01), with smaller but still statistically significant effects for older cohorts.
  2. The general fertility rate held roughly constant at 65 to 70 live births per 1,000 women aged 15–44 from 1980 through 2007, then began a sharp decline that has continued for nearly two decades.
  3. Cohorts whose adolescence overlapped with smartphone diffusion spend sharply less time on face-to-face socialising, dating, paid work, drinking, and driving, and report fewer sexual partners and rising sexual inactivity in young adulthood.

Related Articles:

  • The Collapse of Teen Fertility in the Digital Era — Teen fertility fell in countries with very different healthcare systems, welfare regimes, abortion laws, and religious traditions within roughly the same window, pointing to a global cause. Between 2007 and 2024 the US birth rate fell 71% among women 15–19 and 43% among those 20–24, while rising 9% among those 35–39.
  • US College Students’ Well-Being — A study of US college students finds moderate-to-severe depression reported by 26% of students at one elite institution, 22% reporting moderate-to-severe anxiety and 10% contemplating suicide. Poorer mental health is associated with being female, little exercise, low grades, and financial aid; financial stress is associated with higher suicidal thoughts.
  • The Happiness Crash of 2020 — Survey data show that after 2020 self-reported happiness fell across groups, compressing pre-existing differences — the black-white gap narrowed from 14 points to 6 — while the marital happiness premium of more than 30 points survived intact. Confidence in major public and private institutions declined nearly across the board, with double-digit drops common and losses spanning all parties and ideologies.

AI Summary. 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.

Kate Duguid and Emily Herbert The Financial Times
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Goldman Sachs estimates net US equity issuance in 2026 will be ~ flat for the first time since 2003, driven by the decline in buybacks and an increase in equity issuance.

Is the shrinking supply of US stocks coming to an end?

Core argument: Goldman Sachs estimates net US equity supply — new shares less buybacks and take-privates — will be almost flat in 2026, after being negative since 2003, with an even greater influx expected in 2027 as this year's IPO lock-ups expire.

Goldman Sachs estimates net supply of equity in the US — measured by new shares hitting the market less equity removed by buybacks or companies going private — will be almost flat in 2026, having been in negative territory since 2003. The bank expects an even greater influx of new shares in 2027, as lock-up periods on this year’s IPOs expire. Sixty US companies have gone public this year, raising nearly $40bn, the highest year-to-date deal value since 2021, according to data from Dealogic that excludes listings of blank-cheque companies. Goldman expects that figure to rise to a record $225bn this year following the raft of big listings. SpaceX is aiming to raise as much as $86bn in its IPO later this week. Share sales by companies already on public markets could represent a bigger shift. Alphabet last week raised nearly $85bn in a historic equity raise to fund its vast AI investment, a sale expected to turn the Google owner into a net issuer of stock for the first time in 11 years, according to George Pearkes, an analyst at Bespoke Investment Group.

Takeaways by Macro Roundup® AI

  1. Goldman Sachs estimates net US equity supply — new shares less buybacks and take-privates — will be almost flat in 2026, after being negative since 2003, with an even greater influx expected in 2027 as this year's IPO lock-ups expire.
  2. Sixty US companies have gone public this year raising nearly $40bn, the highest year-to-date deal value since 2021 according to Dealogic data excluding blank-cheque listings, and Goldman expects a record $225bn this year, with SpaceX seeking as much as $86bn.
  3. Alphabet raised nearly $85bn in an equity sale to fund its AI investment, which George Pearkes of Bespoke Investment Group expects to turn the Google owner into a net issuer of stock for the first time in 11 years.

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.
  • Capital Allocation — Internal financing has been the main source of capital for U.S. corporations, with steady new debt issuance except in recession years, consistent with a stable capital structure. Companies have retired equity on average, and net equity issuance remains negative even after accounting for stock-based compensation.
  • 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.

AI Summary. US consumer prices rose 0.5% on the month and 4.2% from a year earlier, according to Bureau of Labor Statistics data, with more than half the monthly advance coming from higher energy costs, while the measure excluding food and energy rose 0.2%. Inflation-adjusted average hourly earnings fell 0.7% from a year earlier.

Augusta Saraiva Bloomberg
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Driven by energy prices, headline CPI rose to 4.2% y/y in May and core rose to 2.9% y/y. Real wages declined .7% y/y. Noting subdued core, Bloomberg’s economic team suggests this is likely the peak on a year-over-year basis.

Is rising inflation driven by energy costs cutting into real wages?

Core argument: The U.S. consumer price index rose 0.5% from April and 4.2% from a year earlier, the most since early 2023, according to Bureau of Labor Statistics data.

The consumer price index climbed 0.5% from April and 4.2% from a year earlier, the most since early 2023, according to Bureau of Labor Statistics data. An underlying gauge of inflation that excludes food and energy, however, rose a less-than-expected 0.2% from the prior month. More than half of the advance in the overall CPI was due to higher energy costs, though prices in some categories, like transportation services, health insurance, and new vehicles, fell. Real average hourly earnings fell 0.7% from a year earlier, the biggest drop in more than three years.

Takeaways by Macro Roundup® AI

  1. The U.S. consumer price index rose 0.5% from April and 4.2% from a year earlier, the most since early 2023, according to Bureau of Labor Statistics data.
  2. Core CPI, which excludes food and energy, rose a less-than-expected 0.2% from the prior month, while more than half of the overall CPI advance came from higher energy costs and prices fell in transportation services, health insurance, and new vehicles.
  3. Real average hourly earnings fell 0.7% from a year earlier, the biggest drop in more than three years.

Related Articles:

  • Home Alone: Inflation And The New Fed Chair — Current readings on labor market tightness, manufacturing price pressures, supply chain tightness and the output gap resemble conditions that have historically preceded Federal Reserve rate increases rather than cuts, and futures markets are pricing in hikes. Averaging several monetary policy rules implies a policy rate of 4.00%–4.85% versus the current 3.50%–3.75%.
  • Do Voters Punish Inflation or Pay Cuts? Inflation and Real Wages in U.S. Elections — An analysis of U.S. counties estimates that where wages grew faster than prices, voters supported the incumbent party more, while counties with larger real wage losses than average shifted more toward the opposition. A one-standard-deviation larger real wage loss is associated with shifts of roughly 0.10 and 0.19 percentage points in vote share and margin.
  • US Consumer Sentiment Slides to Record Low on Price Concerns — The University of Michigan's consumer sentiment index fell 5 points to 44.8, a record low and weaker than all economist projections in a Bloomberg survey. Consumers expect prices to rise 3.9% annually over the next five to 10 years, up from 3.5%, and 4.8% over the coming year.

AI Summary. Governments are borrowing from syndicated bond markets — where sovereign debt is offered to investors through banks — at a record pace as public spending surges, with $504bn sold year-to-date according to data compiled by Bloomberg. That exceeds the volume issued during the first half of 2020, when nations were funding pandemic economic support.

Hannah Benjamin-Cook and Alice Gledhill Bloomberg
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Governments issued $504B of syndicated debt in H1 2026, even more than during the acute phase of the pandemic in the first half of 2020. Among other benefits, syndication can offer sovereign borrowers some insulation from auction risk.

Are governments issuing sovereign bonds at a record pace as spending rises?

Core argument: Sovereign issuers have sold $504 billion of syndicated bonds so far this year, a record pace, according to data compiled by Bloomberg.

Governments are borrowing from syndicated bond markets at a record clip as public spending surges. Sovereign issuers have sold $504 billion of the debt — which is offered to investors via banks — so far this year, according to data compiled by Bloomberg. That’s more than in the first half of 2020, when nations were paying to support their economies during Covid-19 lockdowns.

Takeaways by Macro Roundup® AI

  1. Sovereign issuers have sold $504 billion of syndicated bonds so far this year, a record pace, according to data compiled by Bloomberg.
  2. Syndicated sovereign bond issuance this year exceeds that of the first half of 2020, when nations were paying to support their economies during Covid-19 lockdowns.
  3. Governments are borrowing from syndicated bond markets, where debt is offered to investors via banks, at a record clip as public spending surges.

Related Articles:

  • The Great Bond Car Wreck — in Slow Motion — Long-term government bond yields have risen simultaneously across the US, Japan, the UK and France, which Barclays attributes to too much debt, too little fiscal discipline, and no political appetite to address either. Equities have been resilient, though the 10-year Treasury yield now exceeds the S&P 500 earnings yield by the widest margin since the dot-com bust.
  • Are Government Bonds Safe in Times of War and Pandemic? — Government bonds severely underperform in wartime, in absolute terms and relative to equities, housing, and economic growth, unlike in financial crises when bonds tend to outperform stocks. The U.S. and U.K. reduced war-driven debt-to-GDP ratios without explicit default, using surprise inflation and financial repression that shifted fiscal burdens onto bondholders.
  • Can Treasury Markets Add and Subtract? — The authors estimate that Treasury yields rise on days when official cost estimates reveal deficit-increasing legislation, with a one-time 1 percentage point increase in the deficit-to-GDP ratio raising the 10-year yield by 0.75 basis points, or 6.75 basis points for a persistent deficit shock. The response reflects higher expected inflation and term premia alongside lower convenience yields.

AI Summary. A study tracking software developers before and after adopting AI tools measured output from lines of code to discrete files edited to new software releases, and found little evidence that AI-assisted production gains translated into higher consumption. The increase in mobile app releases came without any increase in downloads, with most new apps failing to attract even a modest audience.

John Burn-Murdoch The Financial Times
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Citing Demirer’s data, Burn-Murdoch notes the release of AI coding tools drove a significant increase in app releases, which, “has not been accompanied by any increase in downloads — most of the new apps fail to capture even a modest audience.”

Do AI-driven gains in software production translate into higher consumption?

Core argument: Mert Demirer and co-authors tracked software developers before and after they adopted AI tools, measuring output at several levels: amount of code written, discrete files edited, projects or features worked on, and actual releases of new software.

Mert Demirer and co-authors tracked software developers’ work before and after they adopted AI tools. Importantly, they measured this at several different levels, from the amount of code written to the number of discrete files edited, to the number of projects or features worked on, to actual releases of new software. When the researchers looked at whether AI-assisted increases in software production have led to increased consumption, they found little evidence. The marked increase in mobile app releases over the past year has not been accompanied by any increase in downloads — most of the new apps fail to capture even a modest audience.

Takeaways by Macro Roundup® AI

  1. Mert Demirer and co-authors tracked software developers before and after they adopted AI tools, measuring output at several levels: amount of code written, discrete files edited, projects or features worked on, and actual releases of new software.
  2. Demirer and co-authors found little evidence that AI-assisted increases in software production have translated into increased consumption.
  3. A marked increase in mobile app releases has not been accompanied by any increase in downloads, as most of the new apps fail to capture even a modest audience.

Related Articles:

  • Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools — The authors estimate that AI coding tools raise developers' task-level productivity by about 40% with autocomplete, 140% including synchronous agents, and 180% with asynchronous agents, with larger effects for less active developers. Gains attenuate up the production chain: synchronous agents raise lines of code 741% and pull requests 65% but releases only 20%.
  • Commoditization, Orchestration, and the New AI Stack — The author argues that as incremental gains from larger AI training runs shrink, the return on additional computing power falls, weakening the case for the training spending that dominates data center demand. Survivors of model commoditization will be those owning the orchestration layer or the applications where outcomes are priced.
  • Chart of the Day: Small Models are Closing the Gap to Frontier AI — Achieving 60% on MMLU, a test of academic reasoning, once required a 540bn-parameter model but was reached by a 3.8bn-parameter model two years later, a 142x reduction in parameters. Models small enough to run on phones or sensors shift inference from data centers to devices, weakening the case for paying cloud providers per token.

Thursday, June 11, 2026

AI Summary. OpenAI is considering steep price cuts as it competes with Anthropic for enterprise customers, a move that could erode both companies' margins given they already lose billions of dollars on the computing costs of running AI systems. Anthropic's revenue surged after its Claude Code coding tool spread among software engineers, and it surpassed OpenAI's valuation.

Keach Hagey and Berber Jin Wall Street Journal
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The WSJ reports OpenAI may “drastically” cut token pricing in an effort to gain market share from Anthropic, as both firms race towards their IPOs.

Will a price war for enterprise AI customers erode margins?

Core argument: OpenAI is considering drastic price cuts in anticipation of a fight with Anthropic for users, cuts that could erode both companies' profit margins given they already lose billions of dollars on the computing resources needed to process queries.

Drastic price cuts could potentially erode the profit margins of both companies, which already lose billions of dollars because of the enormous cost for computing resources needed for AI systems to process queries and carry out tasks. OpenAI is trying to catch up with its younger rival in the race to win enterprise customers that are paying large amounts of money for AI tools that can improve workplace productivity. Anthropic’s revenue recently surged after its coding tool Claude Code went viral among software engineers, and the five-year-old startup surpassed OpenAI’s valuation for the first time. OpenAI has since made its own coding tool Codex a focus of the company.

Takeaways by Macro Roundup® AI

  1. OpenAI is considering drastic price cuts in anticipation of a fight with Anthropic for users, cuts that could erode both companies' profit margins given they already lose billions of dollars on the computing resources needed to process queries.
  2. Anthropic's revenue surged after its coding tool Claude Code went viral among software engineers, and the five-year-old startup surpassed OpenAI's valuation for the first time.
  3. OpenAI is trying to catch up with Anthropic in winning enterprise customers paying large sums for AI productivity tools, and has made its own coding tool Codex a company focus.

Related Articles:

  • Chart of the Day: Small Models are Closing the Gap to Frontier AI — Achieving 60% on MMLU, a test of academic reasoning, once required a 540bn-parameter model but was reached by a 3.8bn-parameter model two years later, a 142x reduction in parameters. Models small enough to run on phones or sensors shift inference from data centers to devices, weakening the case for paying cloud providers per token.
  • Commoditization, Orchestration, and the New AI Stack — The author argues that as incremental gains from larger AI training runs shrink, the return on additional computing power falls, weakening the case for the training spending that dominates data center demand. Survivors of model commoditization will be those owning the orchestration layer or the applications where outcomes are priced.
  • Four Takeaways from Microsoft’s Satya Nadella at WEF Today — Microsoft's chief executive says the price of AI model usage ("tokens") falls by roughly half every three months. Commentary argues that such rapid deflation pulls demand forward, encourages overbuilding, and commoditizes models, shifting competitive advantage to orchestration and context rather than the model layer.

AI Summary. The five largest U.S. technology firms are scaling AI capital spending about 50% a year, from $155bn to a forecast $755bn. Embedding this in a two-sector model with rare productivity booms, the authors estimate AI adds roughly 5, 20, or 58pp to cumulative growth over a seven-year transition, depending on scenario.

Jessica Wachter and Jonathan Wachter National Bureau of Economic Research
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The AI build‑out projected through 2027 is roughly PV‑neutral if there has already been one rare 2.7× productivity boom in the AI sector. In the absence of a further boom, long‑run valuations and the more aggressive 2028–30 capex plans start to look too high.

What does AI capital spending imply about future economic growth?

Core argument: The five largest U.S. technology firms are scaling AI capital expenditure at roughly 50% per year, from $155 billion in 2022 to a forecast $755 billion in 2026.

The five largest U.S. technology firms are scaling AI capital expenditure at roughly 50% per year, from $155 billion in 2022 to a forecast $755 billion in 2026. This paper embeds this observation in a two-sector model with rare productivity booms to ask what the investment path implies for growth and asset prices. Calibrating the boom size to match the observed investment ramp implies that each boom raises AI-sector productivity by a factor of roughly 2.7. A two-year window of elevated boom probability generates three scenarios: a moderate outcome (one boom only), a transformative outcome (one further boom), and a singularity scenario (two additional booms). Even in the moderate scenario, AI adds ~ 5pp to cumulative GDP growth over the seven-year transition (Figure 2), on top of the ~19% normal-times growth that would otherwise prevail. The transformative and singularity scenarios push the AI contribution to 20% and over 58%, respectively. The non-AI sector continues to grow at its historical rate, [while the] AI sector’s share of the economy rises from ~3% today to btw 8% and 39%, depending on the scenario. As this share grows, the AI sector’s rapid productivity gains increasingly dominate aggregate GDP growth.

Takeaways by Macro Roundup® AI

  1. The five largest U.S. technology firms are scaling AI capital expenditure at roughly 50% per year, from $155 billion in 2022 to a forecast $755 billion in 2026.
  2. Calibrating boom size to the observed investment ramp in a two-sector model with rare productivity booms implies that each boom raises AI-sector productivity by a factor of roughly 2.7.
  3. In the moderate scenario, AI adds about 5 percentage points to cumulative GDP growth over the seven-year transition, on top of the ~19% normal-times growth, rising to 20% in the transformative scenario and over 58% in the singularity scenario.

Related Articles:

  • 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.
  • Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools — The authors estimate that AI coding tools raise developers' task-level productivity by about 40% with autocomplete, 140% including synchronous agents, and 180% with asynchronous agents, with larger effects for less active developers. Gains attenuate up the production chain: synchronous agents raise lines of code 741% and pull requests 65% but releases only 20%.
  • Measurements Matter: The Return of SLOC Slop — Measuring developer productivity by software lines of code captures output rather than value, and AI inflates the metric by generating boilerplate, wrappers, tests, and speculative code at near-zero cost. More code also creates liabilities through added maintenance, complexity, attack surface, and debugging load.

AI Summary. Chinese robotics maker Unitree is tripling revenues year over year with 60% gross margins, plans nearly $300m of artificial intelligence research spending, and prices the cheapest humanoid robots on the market. Its flagship model's pre-tax price has fallen from over $50,000 to $27,300, which the authors estimate still yields 67% gross margins.

Reyk Knuhtsen, Niko Ciminelli, Jacob Rintamaki, Robert Ghilduta, et al. Semianalysis
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The Semianalysis team estimates that China’s Unitree has a 67% gross margin on their flagship G1 humanoid robot; hourly labor costs imply “G1 humanoids are crossing the viability threshold of real-world deployments.”

Is a Chinese robotics maker positioned to dominate global humanoid robotics?

Core argument: Unitree has cut pre-tax pricing from over $50K to $27.3K over the past 12–18 months, and the authors estimate the company still earns 67% gross margins on its flagship G1.

Unitree is tripling revenues YoY on 60% gross margin product lines, planning almost $300M of AI R&D spend, increasingly in-housing portions of manufacturing, all while pricing the cheapest humanoids on the market by far. With their upcoming highly anticipated IPO, Unitree is deservedly dominating the humanoids conversation. But historically, Unitree’s humanoid robots have a reputation for less than perfect reliability, are not viewed as useful beyond entertainment and R&D, and have a reputation for being “cheap.” Despite this, we believe Unitree's cost structure is one of its greatest advantages over competitors. Unitree has slashed pre-tax pricing from $50K+ to $27.3K over the past 12-18 months. Even at that price, we estimate they still hit 67% gross margins on their flagship G1. With their BoM set to plummet as manufacturing scales, we've already heard pricing well under $20K in some deals.

Takeaways by Macro Roundup® AI

  1. Unitree has cut pre-tax pricing from over $50K to $27.3K over the past 12–18 months, and the authors estimate the company still earns 67% gross margins on its flagship G1.
  2. Unitree is tripling revenues year-over-year on product lines carrying 60% gross margins, plans almost $300M of AI R&D spend, and is bringing portions of manufacturing in-house ahead of its upcoming IPO.
  3. Unitree's humanoid robots have a reputation for less than perfect reliability and are not viewed as useful beyond entertainment and R&D, yet the authors argue its cost structure is one of its greatest advantages over competitors, citing deals heard well under $20K.

Related Articles:

  • America Is Missing The New Labor Economy – Robotics Part 1 — Building an identical robotic arm in the US costs about 2.2x more than in China, and US-labeled components still depend heavily on Chinese parts and materials with no scalable alternative. The author argues China is the only country positioned to capture full-scale intelligent robotic automation, which would let it outcompete the US across production.
  • Speed Can Reindustrialize America — The US has a relative surplus of low-paid hourly workers and a shortage of high-skill workers, so many less productive US manufacturers could buy a robot but could not attract the talent to program it. China faces the opposite conditions, with underemployed STEM graduates, residency rules complicating coastal factory hiring, and robot programmers earning a fraction of US wages.
  • Minimum Wages and the Rise of the Robots — State-level measures of exposure to industrial robots show substantial geographic variation across the US, with the highest concentrations in the Southwest, Midwest, and Northwest and the lowest in the Mountain West, parts of the South, and northern regions. The authors find state robot exposure is positively correlated with state minimum wage increases.

AI Summary. The Bureau of Labor Statistics reported that US producer prices rose 6.5% from a year earlier, the fastest annual pace in more than two years, and 1.1% from the prior month. A core measure excluding food and energy rose 4.9% year over year.

Augusta Saraiva Bloomberg
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Headline producer prices rose 6.5% y/y in May, fueled by energy prices, which rose 10.7% in May. Core PPI rose 4.9%, suggesting broader-based cost pressures and bolstering the case for a rate increase.

Are producer prices accelerating to their fastest annual pace in years?

Core argument: The US producer price index rose 6.5% from a year earlier, the most since November 2022, according to Bureau of Labor Statistics data.

The producer price index increased 6.5% from a year earlier, the most since November 2022, according to Bureau of Labor Statistics data out Thursday. It advanced 1.1% from April. A core measure of prices that excludes food and energy increased 4.9% from a year earlier.

Takeaways by Macro Roundup® AI

  1. The US producer price index rose 6.5% from a year earlier, the most since November 2022, according to Bureau of Labor Statistics data.
  2. The US producer price index advanced 1.1% from April, according to Bureau of Labor Statistics data.
  3. A core producer price measure excluding food and energy increased 4.9% from a year earlier.

Related Articles:

  • US Inflation Picks Up to Three-Year High, Eroding Paychecks — US consumer prices rose 0.5% on the month and 4.2% from a year earlier, according to Bureau of Labor Statistics data, with more than half the monthly advance coming from higher energy costs, while the measure excluding food and energy rose 0.2%. Inflation-adjusted average hourly earnings fell 0.7% from a year earlier.
  • US Consumer Sentiment Slides to Record Low on Price Concerns — The University of Michigan's consumer sentiment index fell 5 points to 44.8, a record low and weaker than all economist projections in a Bloomberg survey. Consumers expect prices to rise 3.9% annually over the next five to 10 years, up from 3.5%, and 4.8% over the coming year.
  • Do Voters Punish Inflation or Pay Cuts? Inflation and Real Wages in U.S. Elections — An analysis of U.S. counties estimates that where wages grew faster than prices, voters supported the incumbent party more, while counties with larger real wage losses than average shifted more toward the opposition. A one-standard-deviation larger real wage loss is associated with shifts of roughly 0.10 and 0.19 percentage points in vote share and margin.