Edward Conard

Top Ten New York Times Bestselling Author

  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “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 very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…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
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…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 full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…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
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Friday, April 19, 2024

AI Summary. High-tech industries accounted for a disproportionate share of the surge in net new business establishments after 2019, with net entry higher in tech than non-tech industries. The authors find suggestive evidence that tech establishment births rose more for existing firms than new firms, though both categories saw elevated openings.

Ryan Decker and John Haltiwanger Federal Reserve Board
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New high-tech establishments were founded at a disproportionately high rate after 2019; the uptick in this sort of firm could imply future productivity gains. @UpdatedPriors @JHaltiwanger_UM

Did high tech drive the surge in new business establishments?

Core argument: High tech industries made a disproportionately large contribution to the surge in aggregate net establishment entry after 2019, with net entry exceeding that of non-tech industries even relative to pre-pandemic levels.

High tech industries made a large, disproportionate contribution to the aggregate net establishment entry surge after 2019. Net entry in high tech industries was higher than in non-tech industries during the post-2019 period, even relative to the time before the pandemic; this can be seen in figure 1. We find suggestive evidence that, at least through early 2023, high tech establishment births rose more for incumbent firms than for new firms. However, both kinds of firms saw elevated tech births, and timely business application data suggest new firm creation in key tech industries has remained strong through early 2024—pointing to high anticipated new firm entry over the next couple of years. Both kinds of investment can be thought of as an extensive margin of business activity. Such investments, regardless of organizational form, could be important contributors to aggregate productivity growth over time and may provide hints into the dynamics of high tech investments in the pandemic and post-pandemic economy.

Takeaways by Macro Roundup® AI

  1. High tech industries made a disproportionately large contribution to the surge in aggregate net establishment entry after 2019, with net entry exceeding that of non-tech industries even relative to pre-pandemic levels.
  2. Suggestive evidence indicates that, through early 2023, high tech establishment births rose more for incumbent firms than for new firms, though both types of firms saw elevated tech births.
  3. Business application data suggest new firm creation in key tech industries remained strong through early 2024, pointing to high anticipated new firm entry over the next couple of years, which could contribute to aggregate productivity growth over time.

Related Articles:

  • Surging Business Formation in the Pandemic: Causes and Consequences? — Shifts in consumer demand and in preferences for work and lifestyle during the pandemic created entrepreneurial opportunities, and applications to start businesses produced new firms and establishments that hired workers in large numbers. The authors argue these new businesses drew in quitting workers as founders or hires, implying economic restructuring across industry, geography, and firm size and age.
  • The Startup Surge Continues: Business Applications on Track for Second-Largest Annual Total on Record — Americans filed nearly 2.7m business applications in the first half of the year, up 5% from the prior year and 52% above the same period in 2019. One-third were applications with a high likelihood of hiring employees, 36% above the comparable 2019 total.
  • Latinos Are Starting U.S. Businesses at a Torrid Pace — Immigrants accounted for 36% of new U.S. business launches last year, up from 25% in 2019, driven by a rise in Latino entrepreneurship, while business creation by white and native-born Americans has slowed. Hispanic-owned startups tend to be smaller, with 46% reporting over $100,000 in annual revenue versus 62% of white-owned firms.

AI Summary. Research finds that most of the stock market's reaction to Federal Reserve announcements is explained by changes in default-free bond yields rather than shifts in the equity risk premium, contradicting earlier work that attributed much of the response to risk premium effects.

John Cochrane The Grumpy Economist
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.@JohnHCochrane cites research by @ProfStefanNagel and Serhiy Kozak that almost all of the entire effect of policy-driven interest-rate movements on stock prices comes from riskless rates with no effect on risk premia.

.@JohnHCochrane cites research by @ProfStefanNagel and Serhiy Kozak that almost all of the entire effect of policy-driven...

Do bond yields, not risk premiums, drive stocks after Fed announcements?

Core argument: Stefan Nagel and Zhengyang Xu find that the bulk of the stock market reaction in FOMC announcement windows is explained by changes in the default-free term structure of yields, without equity premium effects.

It’s perfectly natural that lower interest rates lower stock expected returns and raise stock prices. The question is, how much. Is there a “risk premium” [or “reach for yield”] effect in addition to the “interest rate” effect? If the Fed lowers the risk free rate, stock prices do go up. But in the Wall Street view, the risk premium goes down with the risk free rate and stocks go up even more. Not so, says a recent excellent paper, “Movements in Yields, not the Equity Premium: Bernanke-Kuttner Redux” by Stefan Nagel and Zhengyang Xu. The bulk of the stock market reaction in FOMC announcement windows is explained by changes in the default-free term structure of yields, without equity premium effects. The previous famous result on this question, by Bernanke and Kuttner, came to the opposite conclusion. Nagel and Xu explain the difference. By using a VAR, Bernanke, and Kuttner use how all stock price changes represent risk premiums (a lot) and interest rates (not so much) to estimate that decomposition on announcement days. But Fed shocks may be different from the shocks that move asset prices on other days.

Takeaways by Macro Roundup® AI

  1. Stefan Nagel and Zhengyang Xu find that the bulk of the stock market reaction in FOMC announcement windows is explained by changes in the default-free term structure of yields, without equity premium effects.
  2. The Nagel-Xu finding contradicts Bernanke and Kuttner's earlier conclusion that Fed rate cuts lower the equity risk premium, raising stock prices beyond the interest-rate effect alone.
  3. Nagel and Xu attribute the difference to Bernanke and Kuttner's VAR approach, which applies the decomposition of stock price moves on ordinary days to announcement days, though Fed shocks may differ from other shocks.

Related Articles:

AI Summary. Data from Cambridge Mobile Telematics show US drivers spend more than twice as much time using phones at the wheel as Canadians, and Americans are twice as likely to say phone use while driving is acceptable. Americans are also less likely to wear seat belts than most Europeans and have higher drink-driving rates.

John Burn-Murdoch Financial Times
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US fatalities per mile driven are double that of other advanced economies, and the US road mortality rate is up 25% over the last decade; @jburnmurdoch suggests American attitudes toward alcohol and cell phone use are the driver.

Do driver behaviors explain why American roads are more dangerous?

Core argument: Americans are twice as likely as Canadians or Europeans to say using a phone while driving is acceptable, and Canadian drivers spend less than half as much time on their devices at the wheel, according to Cambridge Mobile Telematics data.

Using phones at the wheel is a big problem in the US, according to data from Cambridge Mobile Telematics. But just across the border, Canadians, who also drive automatics, spend less than half as much time using their devices while driving. The determining factor seems to be different attitudes to safety, with Americans twice as likely as Canadians or Europeans to say they find it acceptable to use a phone while driving. The same pattern shows up in other behaviours. Americans are much less likely to wear seat belts than most Europeans and also have higher rates of drink-driving. Given that studies find a lack of seat belts, alcohol, and distracted driving all increase either the likelihood or lethality of a collision by a greater amount than vehicle size or shape — and that American drivers are more exceptional in these behaviours than in their car size — these factors may be the determining ones.

Takeaways by Macro Roundup® AI

  1. Americans are twice as likely as Canadians or Europeans to say using a phone while driving is acceptable, and Canadian drivers spend less than half as much time on their devices at the wheel, according to Cambridge Mobile Telematics data.
  2. American drivers are much less likely to wear seat belts than most Europeans and have higher rates of drink-driving, echoing the pattern seen in phone use behind the wheel.
  3. Studies find that a lack of seat belts, alcohol, and distracted driving each raise the likelihood or lethality of a collision by more than vehicle size or shape, and American drivers are more exceptional in those behaviours than in their car size.

Related Articles:

  • Is Life Expectancy Really Falling? — Cohort life expectancy projects the average age of death for people born or turning 65 in a given year: those born in 1940 had a cohort life expectancy of 73, those born today about 85, and those born in 2100 a projected 89. Life expectancy is higher still for people who reach age 65.
  • The (Surprisingly) Good News on Life Expectancy: It’s Still Going Up — Commonly reported "period" life expectancy assumes current age-specific death rates persist for a newborn's entire life, while "cohort" life expectancy better measures how long a child born today will actually live. Death rates from cancer, heart disease, and stroke have fallen substantially over the past two decades, and the author argues that progress should continue.
  • Comments On: “Accounting For the Widening Mortality Gap Between American Adults With and Without a BA” By Anne Case and Angus Deaton — Selection plausibly accounts for most or all of the widening mortality gap between US adults with and without a bachelor's degree: high school achievement measures have not risen since the early 1970s while the share earning degrees rose, and national youth survey data show non-graduates increasingly negatively selected on aptitude scores.

AI Summary. Recent polling averages show the Democratic presidential candidate winning white college-educated voters by 18 points and losing white voters without college degrees by 27 points, a 45-point education gap. Earlier decades saw the two groups vote much more similarly, with one election producing a divide of just two points.

Nate Moore The Liberal Patriot
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Polling suggests Biden has increased his advantage over Trump with college-educated white voters from 9ppt in 2016 to 18ppt in 2024 while increasing his disadvantage among non-college white voters from 26ppt to 27ppt. @NateMoore1287

Has the education divide among white voters widened dramatically?

Core argument: An average of recent polls finds Joe Biden leading white college-educated voters by 18 points while trailing among white non-college voters by 27 points, a 45-point education gap.

An average of recent polls finds Joe Biden winning white college-educated voters by 18 points and losing white non-college voters by 27 points—a colossal gap of 45 points. Compared to 2020 results, Trump’s margin with non-college whites is holding steady, while Biden has significantly improved his standing with degree-holding whites. White voters were not always polarized by education level. Throughout the 1980s and '90s, the white college and non-college vote tracked relatively closely. In 1992, for example, the divide was just two points: Bill Clinton lost college whites by one point and won non-college whites by one point. Such margins are unthinkable today.

Takeaways by Macro Roundup® AI

  1. An average of recent polls finds Joe Biden leading white college-educated voters by 18 points while trailing among white non-college voters by 27 points, a 45-point education gap.
  2. Compared with 2020 results, Trump's margin among non-college whites is holding steady while Biden has significantly improved his standing among white degree-holders.
  3. White voters were not always split by education: in 1992 the divide was two points, with Bill Clinton losing college whites by one point and winning non-college whites by one point.

Related Articles:

  • The Road to A Political Realignment in American Politics — College-educated voters are now more likely to identify as Democrats while those without degrees back Republicans, with educational attainment increasingly correlated with views on abortion, LGBTQ+ rights, and religion's relationship to government. This sorting leaves most states politically uncompetitive, with eight states near the national average in education levels holding 97 electoral votes in play.
  • American Politics Is Undergoing A Racial Realignment — National election surveys and Gallup polling show the Democratic Party's advantage among Black, Latino, and Asian voters at its lowest level since 1960. The article argues this shift reflects fading civil rights-era ties, a weakening link between income and party choice, and non-white voters with long-held conservative views aligning their votes with those views.
  • How ‘All in the Family’ Explains Biden’s Strength Among Seniors — Baby boomers are more liberal than voters older than them, and their aging into the 65-and-older group — alongside the shrinking ranks of those older — helps explain Democratic gains among seniors. Because the relatively conservative Gen X now dominates ages 45 to 64, that group has become more conservative.

AI Summary. Chinese authorities ordered Apple to remove WhatsApp, Threads, Signal and Telegram from its App Store in China, citing national security concerns. The apps, which together have roughly 3bn users globally, were already accessible in China only through virtual private networks but remained commonly used.

Aaron Tilley, Liza Lin and Jeff Horwitz Wall Street Journal
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Citing national security concerns, China ordered Apple to remove Meta’s WhatsApp and Threads, as well as Signal and Telegram, from the Apple store. Apple has 17% of the Chinese smartphone market.

Citing national security concerns, China ordered Apple to remove Meta’s WhatsApp and Threads, as well as Signal and...

Is China removing foreign messaging apps from its app stores?

Core argument: WhatsApp, Threads, Signal and Telegram, which together have around three billion users globally, were removed from Apple's Chinese App Store on Friday after Apple was told to take down certain apps over national security concerns.

Meta Platforms’ WhatsApp and Threads as well as messaging platforms Signal and Telegram were taken off the Chinese App Store Friday. Apple said it was told to remove certain apps because of national security concerns, without specifying which. “We are obligated to follow the laws in the countries where we operate, even when we disagree,” an Apple spokesperson said. These messaging apps, which allow users to exchange messages and share files individually and in large groups, combined have around three billion users globally. They can only be accessed in China through virtual private networks that take users outside China’s Great Firewall, but are still commonly used. Beijing has often viewed such platforms with caution, concerned that these apps could be used by its citizens to spread negative content and cause social unrest. Much of the news China censors at home often makes it beyond the Great Firewall through such channels.

Takeaways by Macro Roundup® AI

  1. WhatsApp, Threads, Signal and Telegram, which together have around three billion users globally, were removed from Apple's Chinese App Store on Friday after Apple was told to take down certain apps over national security concerns.
  2. Apple said it is obligated to follow the laws of countries where it operates even when it disagrees, after being told to remove certain apps from the Chinese App Store.
  3. The removed messaging apps can be reached in China only through virtual private networks that take users beyond the Great Firewall, yet remain commonly used, and much of the news China censors at home travels through such channels.

Related Articles:

  • Apple’s India iPhone Output Hits $14 Billion in China Shift — Apple assembled $14bn of iPhones in India in its last fiscal year, doubling output there to roughly 14%, or about 1 in 7, of its iPhones. China remains Apple's largest iPhone-making hub and biggest overseas market, though its revenue there is falling amid competition from rivals such as Huawei.
  • China Blocks Use of Intel and AMD Chips in Government Computers — China has issued government procurement guidelines that phase out US microprocessors from Intel and AMD in state PCs and servers and sideline Microsoft's Windows and foreign database software in favor of domestic alternatives. China accounted for 27% of Intel's $54bn in sales and 15% of AMD's $23bn.
  • TikTok Crackdown Shifts Into Overdrive, With Sale or Shutdown on Table — U.S. legislation that would ban TikTok or force its sale by Chinese parent ByteDance advanced out of the House Energy and Commerce Committee on a 50-0 vote. TikTok's campaign urging users to call their congressional representatives against the bill appeared to harden supporters' resolve.

Monday, April 22, 2024

AI Summary. The author estimates that artificial intelligence will raise total factor productivity by less than 0.55% over the next decade, and argues that even when AI raises low-skill workers' productivity in some tasks, inequality may widen rather than narrow. The author finds no evidence AI will reduce labor income inequality and predicts a wider gap between capital and labor income.

Daron Acemoglu Massachusetts Institute of Technology
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.@DAcemogluMIT estimates that AI will have a modest 0.55% impact on total factor productivity over ten years, and may not have much effect on inequality.

Will AI deliver modest productivity gains while widening inequality?

Core argument: Total factor productivity gains from AI over the next 10 years are predicted to be modest, at less than 0.55%.

Predicted TFP gains over the next 10 years are modest and are predicted to be less than 0.55%. I also explore AI’s wage and inequality effects. I show theoretically that even when AI improves the productivity of low-skill workers in certain tasks (without creating new tasks for them), this may increase rather than reduce inequality. Empirically, I find that AI advances are unlikely to increase inequality as much as previous automation technologies because their impact is more equally distributed across demographic groups, but there is also no evidence that AI will reduce labor income inequality. AI is also predicted to widen the gap between capital and labor income. Finally, some of the new tasks created by AI may have negative social value (such as design of algorithms for online manipulation), and I discuss how to incorporate the macroeconomic effects of new tasks that may have negative social value.

Takeaways by Macro Roundup® AI

  1. Total factor productivity gains from AI over the next 10 years are predicted to be modest, at less than 0.55%.
  2. AI is predicted to widen the gap between capital and labor income, and some new tasks it creates, such as designing algorithms for online manipulation, may carry negative social value.

Related Articles:

  • Assessing the Implications of a Productivity Miracle — If artificial intelligence can perform economically valuable cognitive tasks at very low marginal cost, consumers would buy far more of the cheapened goods and spend the savings in other categories, expanding activity and employment in sectors facing new demand. Where supply is inherently limited, such as real estate, those savings could bid up prices and produce inflation.
  • The AI Transition One Year Later: On Track, but Macro Impact Still Several Years Off — Investment in AI hardware is projected to rise substantially as a precursor to integrating AI into business processes, with the investment cycle estimated to peak at 2–2½% of GDP and early signs visible among AI-enabling companies. The authors estimate generative AI could raise developed-market labor productivity growth by 1.5pp annually over a 10-year adoption period, roughly 15% cumulatively.
  • Erik Brynjolfsson: ‘This Could Be The Best Decade in History — Or The Worst’ — Studies of large language models across tasks including software coding, consulting, and writing find double-digit productivity gains appearing within months, with less-skilled workers typically benefiting most. Given the large share of modern work these tools can augment, the author projects US productivity growth near 3% annually in the 2020s, roughly double the Congressional Budget Office's 1.4% projection.

AI Summary. A critique argues that estimates of small productivity gains from artificial intelligence rest on a misleading method, because they omit gains from eliminating the least productive firms and from entirely new goods whose prices were previously effectively infinite. The critique also notes the analysis excludes gains from improved science on the grounds they fall outside a ten-year window.

Tyler Cowen Marginal Revolution
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.@tylercowen argues the @DAcemogluMIT estimate of AI’s productivity impact fails to account for new tasks that labor has not yet performed, gains from better science, or the departure of the least productive firms.

.@tylercowen argues the @DAcemogluMIT estimate of AI’s productivity impact fails to account for new tasks that labor has not...

Do standard estimates understate AI's productivity gains?

Core argument: Cowen argues that Acemoglu's "The Simple Macroeconomics of AI" is wrong in method rather than in its estimate, and does not establish the small-gains claim advanced in its abstract.

Mostly I think [the Acemoglu] piece is wrong, and I think it is wrong for reasons of economics. It is not that I think the estimate is off, I think the method is misleading altogether. As with international trade, a lot of the benefits of AI will come from getting rid of the least productive firms from within the distribution. This factor is never considered. And as with international trade, a lot of the benefits of AI will come from “new goods.” Since the prices of those new goods previously were infinity (do note the degree of substitutability matters), those gains can be much higher than what we get from incremental productivity improvements. Acemoglu explicitly rules out gains from doing better science, as they may not come within the ten-year time frame. In sum, I don’t think this paper at all establishes the “small gains point” it is trying to promote in the abstract. It is perfectly fair to point out that the optimists have not shown large gains, but in this paper, the deck is entirely — and unfairly — stacked in the opposite direction.

Takeaways by Macro Roundup® AI

  1. Cowen argues that Acemoglu's "The Simple Macroeconomics of AI" is wrong in method rather than in its estimate, and does not establish the small-gains claim advanced in its abstract.
  2. Cowen contends that, as with international trade, much of AI's benefit will come from eliminating the least productive firms within the distribution, a channel Acemoglu's framework never considers.
  3. Cowen notes that Acemoglu explicitly rules out gains from better science as falling outside the ten-year time frame, and omits gains from new goods whose prices were previously infinite.

Related Articles:

  • Society’s Technical Debt and Software’s Gutenberg Moment — Every wave of technological innovation has been unleashed by something costly becoming cheap enough to waste, and large language models are collapsing the cost and complexity of producing software. The authors argue that decades of underproduced software have left society with immense technical debt that is poised to contract, releasing a wave of innovation.
  • Generative AI at Work — A study of 5,179 customer support agents finds that access to a generative AI conversational assistant raised issues resolved per hour by 14% on average, with the largest gains for novice and low-skilled workers and minimal effect on experienced, highly skilled ones. The authors also find AI assistance improved customer sentiment, reduced requests for managerial intervention, and improved employee retention.
  • The Simple Macroeconomics of AI — The author estimates that artificial intelligence will raise total factor productivity by less than 0.55% over the next decade, and argues that even when AI raises low-skill workers' productivity in some tasks, inequality may widen rather than narrow. The author finds no evidence AI will reduce labor income inequality and predicts a wider gap between capital and labor income.

AI Summary. 87% of US firms with revenue above $100m are privately held rather than publicly traded.

Torsten Sløk Apollo
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Torsten Sløk @apolloglobal notes that 87% of US firms with revenue greater than $100 million are private.

Are most large US firms privately held rather than publicly traded?

Core argument: 87% of US firms with trailing-12-month revenue above $100 million are private rather than publicly listed, according to S&P Capital IQ data cited by Apollo's chief economist.

In financial markets, a lot of conversations are about public companies, but the reality is that in the US, 87% of firms with revenue greater than $100 million are private. Source: S&P Capital IQ, Apollo Chief Economist. Note: For companies with last 12-month revenue greater then $100 million by count.

Takeaways by Macro Roundup® AI

  1. 87% of US firms with trailing-12-month revenue above $100 million are private rather than publicly listed, according to S&P Capital IQ data cited by Apollo's chief economist.
  2. Financial market conversations center on public companies, though by count most US firms with revenue above $100 million are private.

Related Articles:

  • Birth, Death, and Wealth Creation — The median age at which US companies went public rose from 7.9 years in 1976–2000 to 9.5 years in 2001–2022, implying that more wealth creation now occurs in private markets. Research on more than 28,000 US-listed companies since 1926 finds that just under 60% destroyed $9.1tn of wealth while about 2% created $50tn.
  • 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.
  • The Economics of Inequality in High-Wage Economies — United States Income, Wealth, Consumption, and Inequality Diana Furchtgott-Roth

AI Summary. The relationship between interest rates and equity prices has varied across time and countries, with past bull markets occurring alongside higher rates: the late-1990s Nasdaq surge coincided with a 6.5% 10-year Treasury yield and the 1920s boom with double-digit margin rates. Early 20th-century commentators read rising rates as bullish, signaling strong money demand and growth.

Joseph Wang Fed Guy Blog
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.@FedGuy12 notes the tech bubble played out with 10-year Treasury yields at 6.5%, and argues that higher rates won’t necessarily cause a selloff in US equity markets, given strong nominal growth and chronic fiscal deficits.

Do higher interest rates prevent stock market booms?

Core argument: The late-1990s Nasdaq surge occurred with a 10-year Treasury yield of 6.5%, and the 1920s bull market occurred with double-digit margin interest rates, indicating that high rates have coincided with strong equity markets.

The relationship between interest rates and equity prices varies across time and across countries. While a 5% 10-year Treasury yield appears high after a decade of zero interest rates, even higher interest rates have in the past coincided with strong bull markets. The epic surge in the Nasdaq during the late 1990s happened with a 6.5% 10-year, and the roaring 1920s happened when margin interest rates were double digits. Higher interest rates were a hindrance, but investors expected future gains to be even higher. This speculative mindset can be seen today in the surge in the price of various crypto assets, which have no obvious utility. Also note that commentators in the early 20th century actually perceived rising interest rates to be bullish rather than bearish. Rising rates implied a strong demand for money, and thus economic growth.

Takeaways by Macro Roundup® AI

  1. The late-1990s Nasdaq surge occurred with a 10-year Treasury yield of 6.5%, and the 1920s bull market occurred with double-digit margin interest rates, indicating that high rates have coincided with strong equity markets.
  2. Higher interest rates acted as a hindrance, but investors expected future gains to be even higher, a speculative mindset visible in the surge in prices of crypto assets that have no obvious utility.
  3. Commentators in the early 20th century perceived rising interest rates as bullish rather than bearish, taking them to imply strong demand for money and thus economic growth.

Related Articles:

  • The Expensive Stock Market — Falling interest rates reduced interest payments as a share of corporate profits, raising profits and stock market valuations. Measured against GDP, the US stock market is historically expensive, and since rates cannot fall as sharply as they have over the past four decades, expected future returns are low.
  • End of an Era: The Coming Long-Run Slowdown in Corporate Profit Growth and Stock Returns — The authors estimate that declining interest and corporate tax rates accounted for over 40% of real corporate profit growth from 1989 to 2019, while falling risk-free rates explain the entire expansion in price-to-earnings multiples. Real earnings before interest and taxes grew slightly more slowly than in 1962–1989, at 2.2% versus 2.4% per year.
  • The Curious Incident of the Elevated Profit Margins — The US fiscal deficit averaged just under 3% of gross national product from 1950 to 2011 but 6.6% from 2012 to 2022, driven mainly by health and social security spending, a pattern that holds excluding pandemic years. Even assuming permanently elevated profit margins, US equity valuations imply low long-run returns.

AI Summary. Earnings per share for Japan's 500 largest stocks have risen 5.8x over the past 14 years, nearly twice the rate of US peers, after Japanese companies barely grew earnings per share in the 2000s. The authors attribute this largely to corporate deleveraging following Japan's non-performing loan crisis, which left firms well capitalized with low borrowing costs and minimal interest expense.

Nick Schmitz Verdad
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Since 2010 the largest 500 Japanese stocks have increased their EPS by 5.8x, twice the rate as their US peers. A @verdadcap analysis argues this outperformance was driven by the success of Corporate Japan’s deleveraging.

Has corporate deleveraging driven Japanese earnings growth past US peers?

Core argument: The EPS of Japan's 500 largest stocks has risen 5.8x over 14 years, almost twice the rate of their American peers, after Japanese companies barely grew EPS at all from 2000 to 2010.

Japanese companies lagged the US in revenue growth from 2000 to 2010, barely growing EPS at all. But since then, the EPS of the biggest 500 Japanese stocks has increased by 5.8x over the last 14 years, almost twice the rate of their American peers now. These results make it difficult for us to concede that Japanese companies were somehow much worse run than their S&P 500 counterparts. They seem to have improved much more and allocated capital primarily when it increased per-share earnings. But how did this happen? We believe one of the primary reasons is deleveraging balance sheets in Japan. As Japan deleveraged coming out of the non-performing loan crisis at the turn of the century, it became one of the most well capitalized corporate markets in global equities and still enjoys some of the lowest corporate borrowing rates in the world. As a result, very little of every dollar of earnings before interest and taxes (EBIT) goes to interest payments for the typical company.

Takeaways by Macro Roundup® AI

  1. The EPS of Japan's 500 largest stocks has risen 5.8x over 14 years, almost twice the rate of their American peers, after Japanese companies barely grew EPS at all from 2000 to 2010.
  2. Japan's earnings gains are attributed primarily to balance-sheet deleveraging following the non-performing loan crisis at the turn of the century, leaving Japan one of the most well capitalized corporate markets in global equities.
  3. Japanese companies borrow at some of the lowest corporate rates in the world, and very little of each dollar of EBIT goes to interest payments for the typical company.

Related Articles:

  • Japan’s Native Population Declines At Record Rate As Births Plunge — Japan's population of Japanese nationals fell by 837,000 over a year, the largest annual decline since comparable records began in 1950, while the overall population, buoyed by rising numbers of foreign residents, fell by 595,000 to 124.3mn. The number of foreign nationals living in Japan reached a record 3.2mn.
  • Japanese Workers Secure Biggest Pay Rise In Three Decades — Japanese companies including Honda, Nippon Steel, and ANA Holdings granted workers their largest pay rise in more than three decades, with economists expecting large firms to give unionised workers average increases above 4%, up from 3.6% the prior year. The increases strengthen the case for the Bank of Japan to begin raising interest rates.
  • How Japan’s Nikkei 225 Got Its Mojo Back — Japan's Nikkei 225 stock index has reclaimed the record peak it set more than 34 years ago, closing at 39,098.68, as global investors bet the country has escaped deflation and is on a path of sustainable growth. Gains in technology and chip-equipment shares drove the advance, with the index up over 16% since the start of the year.

AI Summary. South Korea made two industrial leaps—from basic goods to heavy industry, then to high-tech manufacturing—but between 2005 and 2022 only one new sector, displays, joined its top ten export products. Chinese technology firms have caught up with Korean competitors in nearly every area except the most advanced semiconductors, turning former customers and suppliers into rivals.

Christian Davies Financial Times
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The Bank of Korea is forecasting South Korean GDP growth of 2.1%/yr this decade, down from 6.4% from 1970-2022, as “Chinese companies that were once customers or suppliers have become rivals.” @FT

Has South Korea's export growth model stalled as Chinese rivals caught up?

Core argument: Between 2005 and 2022, only one new sector — displays — entered South Korea's list of top ten export products, according to Seungheon Song, managing partner of McKinsey's Seoul practice.

Seungheon Song, managing partner of McKinsey’s practice in Seoul, notes that South Korea made two great leaps — one between the 1960s and the 1980s, when the country moved from basic goods to petrochemicals and heavy industry, and the second between the 1980s and 2000s when it moved to high-tech manufacturing. Between 2005 and 2022, however, only one new sector — displays — entered the country’s list of top ten export products. Park argues that the present model reached its apogee in 2011, after a decade during which Korean tech exports were driven by the related twin demand shocks of the rise of China and the global technology boom, as well as by massive investments by Samsung and LG to seize control of the global display industry from their Japanese counterparts. Since then, however, Chinese tech companies have caught up with their Korean competitors in almost every area except the most advanced semiconductors, meaning that Chinese companies that were once customers or suppliers have become rivals.

Takeaways by Macro Roundup® AI

  1. Between 2005 and 2022, only one new sector — displays — entered South Korea's list of top ten export products, according to Seungheon Song, managing partner of McKinsey's Seoul practice.
  2. South Korea made two great leaps, from basic goods to petrochemicals and heavy industry between the 1960s and 1980s, and to high-tech manufacturing between the 1980s and 2000s.
  3. Park argues that South Korea's present model reached its apogee in 2011, after a decade in which tech exports were driven by the rise of China, the global technology boom, and Samsung and LG investments in displays.

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