Edward Conard

Top Ten New York Times Bestselling Author

  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “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
  • “…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 fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Friday, August 30, 2024

AI Summary. Classifying 129 inherently social activities, the authors find social capital rises with post-tax, post-transfer income but at a diminishing rate, with the association strongest for black individuals and weakest for Hispanic individuals. Individuals receiving a greater share of income from government sources tend to have lower social capital, even after accounting for demographics.

Kevin Corinth, Scott Winship and Thomas O’Rourke American Enterprise Institute
Date Posted:

.@kevincorinth @Tqorourke @swinship find that social capital —the value inherent in relationships— has a strong positive relationship with socioeconomic status, including market income and education. @AEI

How does income relate to social capital across individuals?

Core argument: Classifying 129 activities as inherently social across five categories, the authors find social capital rises with post-tax, post-transfer (full) income but at a diminishing rate.

We classify 129 activities as inherently social and group them into five major categories—caring for and helping household members, caring for and helping non-household members, socializing/relaxing/leisure, religious and spiritual activities, and volunteering. Social capital rises with post tax, post transfer (full) income but at a diminishing rate. The association between social capital and income is strongest for black individuals and weakest for Hispanic individuals. Individuals who receive a greater share of their income from government sources tend to have lower levels of social capital, even conditional on demographics. Racial and ethnic minorities in the United States have weaker social capital, although for different reasons. On average, non-Hispanic black individuals have relatively weaker family strength, but relatively stronger social connection. Hispanic individuals have relatively strong family strength and work scores but have lower scores for other components of social capital.

Takeaways by Macro Roundup® AI

  1. Classifying 129 activities as inherently social across five categories, the authors find social capital rises with post-tax, post-transfer (full) income but at a diminishing rate.
  2. The association between social capital and income is strongest for black individuals and weakest for Hispanic individuals, and individuals receiving a greater share of income from government sources tend to have lower social capital even conditional on demographics.
  3. Racial and ethnic minorities in the United States have weaker social capital for different reasons: non-Hispanic black individuals show relatively weaker family strength but stronger social connection, while Hispanic individuals show strong family strength and work scores but lower scores on other components.

Related Articles:

  • Measuring Social Capital: Can We Tell If Some Places Are Richer in Social Capital Than Others? — The Joint Economic Committee's Social Capital Index ranks Louisiana, Nevada, New Mexico, Florida, and Arizona lowest and Utah, Minnesota, Wisconsin, New Hampshire, Vermont, and Colorado highest, with low- and high-ranking states falling consistently below or above the median across subindexes. All but one of the 21 cross-state correlations among the seven subindexes are positive.
  • Post-Pandemic Recovery for America’s Prime Age Labor Force: A Tale of Two Sexes — Prime-age women's labor force participation climbed about 5 points above its pre-pandemic level over a decade, while prime-age men's rose barely a point, only just regaining pre-pandemic levels. Despite economic expansion and labor shortages, work rates for prime-age American men are barely as high as at the trough of the severe Reagan-era recession.

AI Summary. US multinational companies employ 44 million people worldwide, with about 70% — roughly 30 million jobs — in the United States and 14 million abroad. Against total US nonfarm payrolls of 159 million, that means multinationals account for 19% of US employment, leaving more than 80% of US jobs outside large publicly listed firms.

Torsten Sløk Apollo
Date Posted:
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Noting that 80% of American jobs are outside of the S&P 500, Torsten Sløk argues that “privately owned companies continue to be the lifeblood of the US economy.”

How much of US employment lies outside large multinational companies?

Core argument: US multinational enterprises employ 44 million people worldwide, with about 70%, or roughly 30 million jobs, located in the US and 14 million outside it.

Worldwide employment in all US multinational companies is 44 million. About 70% of employment in US multinational enterprises, or about 30 million jobs, are in the US, and 14 million jobs in US multinational firms are outside the US. With total nonfarm payrolls in the US at 159 million, 19% of US employment is in multinational enterprises. Put differently, more than 80% of jobs in the US economy are outside the S&P 500 companies, and privately owned companies continue to be the lifeblood of the US economy.

Takeaways by Macro Roundup® AI

  1. US multinational enterprises employ 44 million people worldwide, with about 70%, or roughly 30 million jobs, located in the US and 14 million outside it.
  2. Against total US nonfarm payrolls of 159 million, employment at US multinational enterprises represents 19% of US employment.
  3. More than 80% of US jobs sit outside S&P 500 companies, with privately owned companies serving as the lifeblood of the US economy.

Related Articles:

  • Many More Private Firms in the US — 87% of US firms with revenue above $100m are privately held rather than publicly traded.
  • Profit Puzzles — The authors propose that the divergence between rising US aggregate profit rates and falling financial market rates reflects a mismatch: national accounts measure returns on capital for all firms, while market rates capture the cost of capital for public firms only. They find public-firm profit rates halved while private-firm profit rates rose, averaging 10% above public firms.
  • The Economics of Inequality in High-Wage Economies — Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.

AI Summary. 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.

Robin Wigglesworth and Eugene Fama Financial Times
Date Posted:

Efficient Markets pioneer Eugene Fama contextualizes the current stock market, “The world is betting that AI is going to rule the world and that Nvidia will have a near monopoly, but who really knows? Efficient markets is a hypothesis. It’s not reality.”

Were technology stock prices during the dotcom boom all too high?

Core argument: Amazon is now worth about a quarter of the Nasdaq's entire market capitalisation at its 2000 dotcom peak, an illustration of Fama's point that some companies made up for the pricing mistakes made on others.

Fama points out how technology stocks also went on a rampage in the late 1990s before collapsing, but that the fundamental premise — that the internet would create huge, vastly profitable new companies — proved to be correct. “Most of the prices were too high [in the dotcom bubble], but some were too low as well. Some companies made up for all the mistakes that were made on the other ones.” Indeed, Amazon is now worth about a quarter of the Nasdaq’s entire market capitalisation at its 2000 dotcom peak. Some of the backlash against the efficient market hypothesis may simply be down to hang-ups around the word “efficient”, which Fama admits he can understand. “I just couldn’t think of a better word. It’s basically saying that prices are right.”

Takeaways by Macro Roundup® AI

  1. Amazon is now worth about a quarter of the Nasdaq's entire market capitalisation at its 2000 dotcom peak, an illustration of Fama's point that some companies made up for the pricing mistakes made on others.
  2. Fama argues that the premise underlying the late-1990s technology stock rampage — that the internet would create huge, vastly profitable new companies — proved correct, even though most prices were too high and some were too low.
  3. Fama says part of the backlash against the efficient market hypothesis stems from hang-ups over the word "efficient," which he used only because he could not think of a better term for the idea that prices are right.

Related Articles:

  • 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.
  • 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.
  • Long-Term Shareholder Returns: Evidence From 64,000 Global Stocks — A study of about 64,000 global stocks estimates net global stock market wealth creation of $75.7tn, with returns highly concentrated: the top 159 firms (0.25%) account for half of net wealth creation and the top 1,526 (2.39%) account for all of it. Fewer than half of stocks beat one-month US Treasury bills, 42.6% of non-US and 44.8% of US stocks.

AI Summary. An election forecasting model shows the Democratic presidential candidate's national polling lead narrowing from 3.8 points to 3.3, with state polls mostly favorable apart from Michigan. The model applies a convention bounce adjustment, and close polling in Pennsylvania remains a concern for her campaign.

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

.@NateSilver538 shows Harris’s lead in national polls shrinking from 3.8pp to 3.3pp. He gives Harris a 46.6% probability of winning the electoral college versus 53.1% for Trump. “Tight polls in Pennsylvania are a worry for the vice president.”

Is the Democratic candidate's polling lead narrowing nationally?

Core argument: Kamala Harris's national polling lead narrowed from 3.8 points to 3.3 points, though she fared well in state polls apart from an exception in Michigan.

Kamala Harris’s lead in national polls shrunk from 3.8 points to 3.3 — although with a big exception in Michigan, she had a pretty good day in state polls. The model is making a convention bounce adjustment to Harris’s numbers; if she holds her current standing for another week or two, she’ll begin to move up in the forecast again. Still, the tight polls in Pennsylvania are a worry for the vice president.

Takeaways by Macro Roundup® AI

  1. Kamala Harris's national polling lead narrowed from 3.8 points to 3.3 points, though she fared well in state polls apart from an exception in Michigan.
  2. The Silver Bulletin model applies a convention bounce adjustment to Harris's numbers, and if she holds her current standing for another week or two she will begin moving up in the forecast again.
  3. Tight polling in Pennsylvania is a worry for Harris in the Silver Bulletin 2024 presidential forecast.

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%.

Tuesday, September 3, 2024

AI Summary. Using matched manufacturer cost and online retail price data, the authors find total supply-chain markups in the US were stable even as retail prices rose, indicating the increase in consumer prices for these products came from higher production costs rather than a net rise in markups. Manufacturer and retail markups varied over time in offsetting directions.

Santiago Alvarez, Alberto Cavallo, Alexander MacKay and Paolo Mengano Working Paper
Date Posted:
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.@albertocavallo @SEAlvarezBlaser @_amackay and @Paolo_Mengano find that the total US markup of prices over production costs was stable over June 2018-June 2023. Increased production costs rather than markups explain soaring retail prices during 2022.

Did rising production costs, rather than higher markups, drive consumer price increases?

Core argument: US total supply-chain markups were stable from June 2018 through June 2023, covering the pandemic and the inflationary period; for the products sampled, rising production costs rather than a net increase in markups were the primary driver of higher consumer prices.

We study markups and pricing strategies along the supply chain. Our dataset combines detailed price and cost information from a large global manufacturer with matched retail prices collected online for the period July 2018 through June 2023. The supply-chain markup reflects the wedge between the price that consumers pay and the production costs, and it usually takes on values between 0 (price equals cost) and 1 (prices substantially greater than costs). In the US, total markups were stable from June 2018 through June 2023, covering the pandemic and the recent inflationary period. Retail prices increased in 2022, but total markups did not. Thus, for the products in our sample, the primary driver of increased consumer prices was an increase in production costs, rather than a net increase in markups. However, when we examine each stage of the supply chain separately, we do find time-series variation in markups at the firm level. In the second half of 2020, manufacturer markups increased while retail markups fell. In 2022, retail markups increased while manufacturer markups fell. As a result, although manufacturer and retail markups vary over time, they lead to limited fluctuations in total markups.

Takeaways by Macro Roundup® AI

  1. US total supply-chain markups were stable from June 2018 through June 2023, covering the pandemic and the inflationary period; for the products sampled, rising production costs rather than a net increase in markups were the primary driver of higher consumer prices.
  2. Manufacturer markups rose while retail markups fell in the second half of 2020, and retail markups rose while manufacturer markups fell in 2022, leaving total markups with limited fluctuation.
  3. The dataset combines price and cost information from a large global manufacturer with matched retail prices collected online from July 2018 through June 2023, with the supply-chain markup measuring the wedge between consumer prices and production costs.

Related Articles:

  • Are Markups Driving the Ups and Downs of Inflation? — Aggregate markups have stayed roughly constant during the current recovery and the recoveries following the 1991, 2001, and 2008 recessions, making their recent path unexceptional by historical standards.
  • Corporate Profits in the Aftermath of COVID-19 — Nonfinancial corporate profit margins—profits as a share of gross value added—rose to about 19% before easing to 15%, compared with about 13% before the pandemic. The authors attribute much of the increase to large direct government support for small and medium-sized U.S. businesses and to lower net interest expenses under accommodative monetary policy.
  • An Analysis of Pandemic-Era Inflation In 11 Economies — A cross-country analysis of 11 economies finds wide agreement that global energy and food price increases and supply disruptions in key sectors drove pandemic-era inflation, and that their recession accounts for most of the global cooling of inflation. The authors find tight labor markets had smaller but more persistent inflationary effects, leaving wage inflation as the larger remaining factor.

AI Summary. 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.

Michael Cembalest J.P. Morgan
Date Posted:

AI-related capex as a % of total is on par with the levels of the fiber optic deployment of the late 1990s. Mike Cembalest argues “there needs to be several hundred $B/year of AI-related demand from the corporate sector to pay for AI infrastructure.”

Is AI infrastructure spending outpacing the applications needed to justify it?

Core argument: NVIDIA data center revenues as a share of market-wide capital spending are projected to reach levels seen at the 1969 mainframe peak and during the dot-com boom.

Every computing cycle entails infrastructure first, then platforms and then applications. It’s probably too soon to worry that there’s no killer generative AI app yet akin to the enterprise resource planning software of the 1990s or the search and e-commerce applications of the 2000s. But the clock is ticking: NVIDIA data center revenues as a share of market-wide capital spending are projected to reach heights seen at the peak of the mainframe era in 1969 and the dot-com boom. [Hyperscalers] spend more than twice as much training complex foundational models than they do on running completed production models on a day-to-day basis for their end-use customers. That will probably continue for another year or so: highly profitable hyperscalers will keep the AI capital spending machine moving on their own. Some AI demand will be sourced from the military which is price inelastic due to national security reasons. Within the next two years, corporate AI adoption trends need to move higher, there needs to be several hundred billion dollars a year of AI-related demand from the corporate sector to pay for AI infrastructure

Takeaways by Macro Roundup® AI

  1. NVIDIA data center revenues as a share of market-wide capital spending are projected to reach levels seen at the 1969 mainframe peak and during the dot-com boom.
  2. Hyperscalers spend more than twice as much training complex foundational models as running completed production models day-to-day for end-use customers, a pattern likely to continue for about another year.
  3. Corporate AI adoption needs to rise within two years to generate several hundred billion dollars a year of AI-related demand to pay for AI infrastructure, with some demand coming from the price-inelastic military.

Related Articles:

  • AI’s $600B Question — Comparing spending on AI chips to historical railroad construction overlooks that high-fixed-cost, low-marginal-cost businesses without monopoly or oligopoly power tend to see prices competed down to marginal cost, and that semiconductors continually improve in cost versus performance, unlike physical infrastructure. Speculative frenzies accompany technology, but the payoff will take a long time.
  • 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. A long-running study that gave the SAT to 12- and 13-year-olds and tracked roughly 2,000 participants found that those in the top quartile of the top 1% of measured ability were over 2x as likely to earn a doctorate or patent, and over 4x as likely to publish science research, as the bottom quartile, with no plateau in the relationship.

Charles Murray Wall Street Journal
Date Posted:

.@charlesmurray argues that our highest educational priority should be identifying students in the top 0.5% of cognitive ability and channeling them to elite schools in STEM fields. The top 0.5% of the US working-age population is ~650,000.

Does measured ability keep predicting achievement within the top 1%?

Core argument: Among Study of Mathematically Precocious Youth participants, those in the top quartile of the top 1% of ability (IQ 142 and higher) were more than twice as likely to earn a doctorate or be awarded a patent as those in the bottom quartile of that percentile.

In the 1970s, Johns Hopkins psychologist Julian Stanley established the Study of Mathematically Precocious Youth by administering the SAT to 12- and 13-year-olds. Some 2,000 of the participants have been followed throughout their careers. Measures of productivity varied substantially within the top percentile, equivalent to an IQ of 135 or higher. Those in the top quartile of the top 1%, equivalent to IQs of 142 and higher, were more than twice as likely to earn a doctorate or be awarded a patent as those in the bottom quartile and more than four times as likely to publish an article on a STEM topic in a refereed journal. There was no plateau. Greater measured cognitive ability was correlated with greater adult accomplishment throughout the range. These results suggest that we should be thinking in terms of at least the top half of the top percentile of ability when defining the set of people who have the potential to make major contributions in a STEM field.

Takeaways by Macro Roundup® AI

  1. Among Study of Mathematically Precocious Youth participants, those in the top quartile of the top 1% of ability (IQ 142 and higher) were more than twice as likely to earn a doctorate or be awarded a patent as those in the bottom quartile of that percentile.
  2. Participants in the top quartile of the top 1% were more than four times as likely to publish a STEM article in a refereed journal, and greater measured cognitive ability correlated with greater adult accomplishment throughout the range, with no plateau.
  3. Julian Stanley's Study of Mathematically Precocious Youth, which administered the SAT to 12- and 13-year-olds in the 1970s and followed some 2,000 participants through their careers, suggests defining STEM potential as at least the top half of the top percentile of ability.

Related Articles:

  • The Economics of Inequality in High-Wage Economies — Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.
  • The Extreme Shortage of High IQ Workers — Semiconductor manufacturing requires workers of above-average intelligence, with the most demanding roles needing IQs in the top 1 in 1,000 — a pool of about 164,000 people in the US, of whom perhaps 100,000 can be placed in such professions. The author argues this scarcity explains reliance on high-IQ workers abroad and on smarter tools and non-human intelligence.
  • Multidimensional Human Capital and the Wage Structure — The wage return to cognitive skills has declined, from about 10% higher hourly wages per standard deviation of test score in the 1980s and early 1990s to 4.5% in the 2000s and early 2010s, while returns to a bachelor's degree rose. Social skill-intensive occupations grew as a share of US jobs, with faster real wage growth.

AI Summary. The highest-paying fifth of occupations are projected to grow 8.9% over a decade, versus under 3% for middle- and lower-paying occupations, and jobs requiring a graduate degree are projected to grow 9.3% versus 2.5% for those requiring only a high school degree. This skew toward higher-paying, higher-education jobs is greater than in the prior pre-pandemic projection.

Jed Kolko Jedkolko.com
Date Posted:
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.@BLS_gov projects that jobs in the top wage quartile will grow by 8.9% per year from 2023-33, over 3X the rate for bottom-quartile jobs. @JedKolko notes this is a shift from the pre-pandemic period.

Is job growth increasingly concentrated in higher-paying, higher-education occupations?

Core argument: The highest-paying fifth of U.S. occupations are projected to grow 8.9% between 2023 and 2033, while middle- and lower-paying occupations are projected to grow less than 3% over the same period.

In general, high-pay, high-education jobs are projected to grow more than lower-pay jobs and those requiring less education. The highest-paying fifth of occupations are projected to growth 8.9% between 2023 and 2033. Middle and lower paying occupations are projected to grow less than 3% over this period. In these latest projections, job growth is more skewed toward the highest-paying occupations than in the last pre-pandemic projection, for the period 2019-2029, which called for fast job growth in both the highest and lowest paying occupations. Jobs requiring more education are projected to grow faster than those requiring less: 9.3% for those requiring a graduate degree versus just 2.5% for those requiring a high school degree only and 1.8% for those that don’t require a high school degree. Job growth is more skewed toward jobs requiring more education in the 2023 projection than it was in the pre-pandemic 2019 projection — mirroring the increasing skew toward higher-paying jobs.

Takeaways by Macro Roundup® AI

  1. The highest-paying fifth of U.S. occupations are projected to grow 8.9% between 2023 and 2033, while middle- and lower-paying occupations are projected to grow less than 3% over the same period.
  2. Occupations requiring a graduate degree are projected to grow 9.3% from 2023 to 2033, versus 2.5% for those requiring only a high school degree and 1.8% for those requiring no high school degree.
  3. The 2023 projections skew job growth more toward the highest-paying occupations and those requiring more education than the pre-pandemic 2019–2029 projection, which called for fast growth in both the highest- and lowest-paying occupations.

Related Articles:

  • The American Worker — Inflation-adjusted hourly wages for the median U.S. worker grew 35.9% from 1980 to 2023, and weekly compensation including benefits grew roughly 45%. Gains were uneven by sex: women's real hourly wages rose 59.9% over that period while men's rose 15.6%.
  • Perspectives on the Labor Share — The share of US income going to labor reached its lowest level since the Great Depression, falling roughly 5 percentage points between 1929 and 2022 across most industries, alongside a worldwide decline of about 6 percentage points since 1980. The author argues the most plausible causes are technological, including capital-augmenting technology.
  • Foreign-born Skilled Workers Play a Critical Role in Strategically Significant Industries — Foreign-born workers make up 20.3% of the roughly 19.9mn workers in strategically significant US industries—those ranking in the top fifth for research spending per worker and above average in use of science and engineering workers—compared with 18.4% of the workforce overall. Manufacturing and professional services account for 83% of employment in these industries.

AI Summary. An illustrative calculation shows that if US growth had been 0.25 to 1 percentage point lower per quarter over the postwar period, compounding would leave GDP per capita dramatically below its actual level — with a 1 percentage point quarterly shortfall leaving the US as poor as Tunisia.

Cremieux Cremieux Recueil
Date Posted:

.@cremieux notes that if the US had 0.25 ppts lower quarterly growth since 1947, 2023 US GDP/capita would have been on a par with today’s Italy, not 115% higher. “Once one starts to think about economic growth, it is hard to think about anything else.”

How much poorer would slightly slower growth have left America?

Core argument: A chart shows that if U.S. growth had been 1 percentage point lower each quarter since 1947, American GDP per capita in 2023 would be as low as Tunisia's.

This chart depicts what American GDP per capita would be [in 2023] if America had a 0.25 to 1 percentage point lower growth rate per quarter since 1947. So if America actually grew 3% in a year, in this model, you might see it growing at about 2% per annum (-0.25 percentage points per quarter). That compounding effect would be to make America incredibly poor compared to where it is now. Having 1 percentage point knocked out of growth each quarter, America becomes as poor as Tunisia by the modern day.

Takeaways by Macro Roundup® AI

  1. A chart shows that if U.S. growth had been 1 percentage point lower each quarter since 1947, American GDP per capita in 2023 would be as low as Tunisia's.
  2. Shaving 0.25 percentage points off quarterly growth since 1947 — turning an actual 3% annual pace into roughly 2% — would compound into a much poorer United States by 2023.
  3. The model tests reductions of 0.25 to 1 percentage point in quarterly U.S. growth since 1947, with compounding pushing GDP per capita far below its actual 2023 level.

Related Articles:

  • The Economics of Inequality in High-Wage Economies — Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.
  • Is Britain Really As Poor As Mississippi? — Excluding London's output and population would reduce British living standards by 14%, enough to fall below the poorest US state; by comparison, removing Amsterdam would cut the Netherlands by 5%, removing Munich would cut Germany by 1%, and removing the entire San Francisco Bay Area would cut US GDP per capita by 4%.
  • From Strength To Strength — The US produced $25.5tn in GDP, about 25% of the world total—roughly its 1990 share—while China's share stands at 18%; the US share of the G7's nominal GDP rose from 40% in 1990 to 58%. Income per person is now about 30% above western Europe and 54% above Japan, adjusted for purchasing power.

AI Summary. A simulation using a simplified version of the Federal Reserve's model of the US economy estimates that a 100bps cut in the federal funds rate plus guidance for 150bps more would raise GDP by 2% and inflation by 1%. The author argues such cuts would lift stock prices, tighten credit spreads, and risk reaccelerating growth and inflation.

Torsten Sløk Apollo
Date Posted:

Torsten Sløk conducts a simulation with the Fed’s FRBUS model and concludes that two years of Fed cuts with a terminal rate of 3% will likely cause peak inflation to rise by 1 pp and peak GDP by 2% vs. the Fed’s baseline forecast.

How much would rate cuts boost GDP and inflation?

Core argument: A simulation of a simplified version of the Fed's FRB/US model finds that a 100bps cut to the fed funds rate this year plus forward guidance for 150bps more would boost GDP by 2% and inflation by 1%.

The Fed is saying that monetary policy is restrictive and the Fed funds rate needs to normalize and come down to r-star, which they estimate to be around 3%. We ran a simulation on a simplified version of the Fed’s model for the US economy, FRBUS, to quantify what the normalization of interest rates means for GDP and inflation. Assuming a 100bps cut to the Fed funds rate this year and an additional 150bps in forward guidance about more cuts coming will boost GDP by 2% and inflation by 1%. In short, the current excitement about a dramatic amount of rate cuts is ignoring the significant positive effects these cuts will have on the stock market, credit spreads, consumer spending, capex spending, corporate earnings, and inflation. Combined with a continued strong tailwind to the economy from fiscal policy and massive investments in AI, the risks are rising that Fed cuts are going to boost stock prices and tighten credit spreads and trigger a reacceleration in GDP and inflation.

Takeaways by Macro Roundup® AI

  1. A simulation of a simplified version of the Fed's FRB/US model finds that a 100bps cut to the fed funds rate this year plus forward guidance for 150bps more would boost GDP by 2% and inflation by 1%.
  2. The Fed describes monetary policy as restrictive and says the fed funds rate needs to normalize toward r-star, which it estimates at around 3%.
  3. Rate cuts, combined with a continued tailwind from fiscal policy and large investments in AI, raise the risk of higher stock prices, tighter credit spreads, and a reacceleration in GDP and inflation.

Related Articles:

  • Larry Summers and Bob Rubin Join Our CIOs to Discuss the Surprising Economic Cycle — Adopting the Simpson-Bowles fiscal consolidation when interest rates were at zero would have risked excessive disinflation, since long rates had no room to fall to provide an offsetting expansionary impulse. After the large run-up in debt and rise in real interest rates, the developing fiscal situation risks inflationary pressure, Treasury market disruption, or crowding out of private investment.
  • An Update from Our CIOs: How Durable Is the Economy? — Central banks will likely struggle to deliver the stimulus already priced into rate markets, and the cost of capital must rise enough to offset structurally higher government borrowing and durable private demand. Artificial intelligence spending is inflationary near-term while building capacity, but its deflationary potential is massive and could arrive fast.
  • U.S. Business Investment in the Post-COVID Expansion — Business fixed investment has held at roughly the same share of U.S. GDP as before COVID, a better outcome than after every other recession since 1980, when investment typically fell as a share of GDP and contributed less well into the recovery. American businesses invested $430bn more than if investment had followed its usual historical pattern.