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Has the Stock Market Become Less Representative of the Economy?

AI Summary. The correlation between firms' employment and market capitalization has declined, with employment explaining over 50% of the variation in market capitalization in the 1970s but 21.8% in the 2010s, while the share of non-farm workers at public firms fell from 41.4% to 29.0%. Value added remains a better predictor, explaining roughly 68% in both periods.

Frederik Schlingemann National Bureau of Economic Growth
Date Posted:
October 13, 2020
Is Database:
Database

The correlation btw firms’ employment and market capitalization has significantly declined since 1973, indicating a growing disconnect btw the stock market and the broader economy.

Does the stock market still reflect where Americans work?

Core argument: Employment explained more than 50% of the variation in firms' market capitalization in the 1970s but 21.8% in the 2010s, indicating a growing disconnect between the stock market and the broader economy.

From 1973 to 2019, the correlation between firms' employment and market capitalization has significantly declined, indicating a growing disconnect between the stock market and the broader economy. In the 1970s, employment explained over 50% of the variation in market capitalization, but by the 2010s, this figure dropped to 21.8%. The percentage of non-farm workers employed by public firms fell from 41.4% in 1973 to 29.0% in 2019. While value added remains a better predictor of market capitalization, explaining 68.2% of its variation in the 1970s and 67.7% in the 2010s, the stock market's representativeness concerning employment has worsened over time, reflecting structural shifts in the economy and the rise of intangible capital investments.

Takeaways by Macro Roundup® AI

  1. Employment explained more than 50% of the variation in firms' market capitalization in the 1970s but 21.8% in the 2010s, indicating a growing disconnect between the stock market and the broader economy.
  2. The share of non-farm workers employed by public firms fell from 41.4% in 1973 to 29.0% in 2019.
  3. Value added remains a better predictor of market capitalization, explaining 68.2% of its variation in the 1970s and 67.7% in the 2010s.

Has the Stock Market Become Less Representative of the Economy?: Extended Excerpt Image 1


Frederik Schlingemann and René Stulz, "Has the Stock Market Become Less Representative of the Economy?," National Bureau Of Economic Growth, October 2020, https://www.nber.org/papers/w27942

Core of their employment argument, “…. how much the stock market reflects the economy is an empirical question. Employment is a reliable benchmark for the state of the economy.Employment data for the whole economy is available for our sample period, does not depend on accounting rules, and is collected by the Federal government irrespective of whether a firm is public or not. For public corporations, employment is available for most corporations annually since the early 1970s. We find that, from 1973 to 2019, the percentage of employees working for public firms is highest at the start of the sample period and falls sharply in the 1980s. At the beginning of that period, more than 41.4 percent of non-farm workers in the private sector work for public firms, but in 2019, that percentage is 29.0 percent. In 2019, the percentage of non-farm workers in the private sector working for public firms is the lowest for our sample period for industrial firms and for all firms, including financial firms, it is the lowest except for 1989 and 1990. We create a measure of unrepresentativeness to capture how poorly market capitalization proxies for a firm’s contribution to employment over time. For each firm, we measure the absolute value of the difference between the firm’s market capitalization as a share of the market capitalization of the stock market and the firm’s employment share among public firms defined as the firm’s employment divided by the employment of all stock market firms. The measure of unrepresentativeness is proportional to the sum of these differences. Intuitively, it is the difference between a portfolio that holds the stock market and a portfolio with weights equal to the employment weights of firms. The unrepresentativeness measure increases as the two portfolios differ more. We call this measure our employment unrepresentativeness measure. This measure follows a w-shape, with its lowest values in the 1980s and 1990s and its highest values in the 1970s, around 2000, and in the recent past. The stock market is more unrepresentative at the end of our sample period with respect to employment than at any time except around the year 2000. Another way to show that market capitalizations are not instructive about firms’ contribution to employment is to estimate how much of the variation in market capitalizations can be explained by variation in employment. We find that from 1973 to 2019 a firm’s employment never explains as little of its market capitalization as in 2019. In most years in the 1970s and early 1980s, firm employment explains more than 50% of the variation in market capitalization. In each of the last four sample years but one, firm employment explains less than 20% of the variation in market capitalization…”

Core of their value added argument, “…Assessing a firm’s contribution to GDP is more fraught with difficulties. A firm’s value added depends on the total compensation it pays to its employees. However, most firms do not disclose how much they pay to their employees separately…. we find that the contribution of public firms to GDP is higher in the 1970s than in the 2000s.This result is insensitive to the approximations we make. Using the same approach to measure unrepresentativeness as with employment, we construct a measure of unrepresentativeness for value added. The stock market’s unrepresentativeness for value added follows a w-shape with unrepresentativeness high early in the sample period, around 2000, and late in the sample period. In contrast to employment, the unrepresentativeness at the end of the sample period is less than at the beginning of the sample period….We find that variation in value-added best explains the variation in market capitalization in the late 1970s and early 1980s. While employment explains less of the variation in market capitalization in the 2010s than in the 1970s, the same is not the case for value added. The variation in value-added explains the variation in market capitalization less well at the end of the sample period than in a number of years, but it explains it better than in the period from 1988 (1991 for industrial firms) to 2003…”

Conclusions, “….we examine how listed firms contribute to the economy over time and how their market capitalization is related to their contribution to the economy. We find that stock market firms as a group contribute less to employment and to GDP than in the 1970s. Since 1973, industrial stock market firms never contribute as little to employment as they do in 2019 and all firms on the stock market contribute less than in 2019 only two years.Though the contribution to GDP of stock market firms is less in recent years than in the 1970s, the decline in contribution to GDP is less than the decline in contribution to employment. Our estimates for the contribution of listed firms to GDP come with some important caveats. Listed firms generally do not disclose their employment expenses, so that we have to approximate them using approaches developed in the recent literature. Further, though listed firms disclose employment, they do not generally disclose separately domestic and foreign employment. As a result, our estimates of employment and value added for listed firms are estimates for worldwide employment and worldwide value added of these firms. To the extent that foreign activities of firms increase over time, our estimates likely understate the decrease in the contribution of listed firms to the US economy. It is well-known that the relative importance of investments in intangible capital has increased over time. These investments are mostly expensed under GAAP. Though we can adjust firm income for investment in intangible capital, we cannot adjust employment for employees who work on projects that increase invested capital. If we adjust income for investment in intangible capital, our conclusions about the evolution of the contribution of value added of listed firms to GDP are unchanged. We measure how representative the market capitalization of firms is of their contribution to the economy. We find that our measure of unrepresentativeness follows a w shape for both employment and value added: the measure is high in the 1970s, around 2000, and at the end of the sample period.For labor, unrepresentativeness increases over time, but not for value added. We also find that the relation between firm market capitalization and firm employment collapses during our sample period. In the 1970s, employment explains 50.7% on average of the variation in market capitalization across firms. In the 2010s, it explains 21.8% on average.A firm’s value added explains much more its market capitalization than its employment. This is true throughout our sample period. Strikingly, there is no consistent degradation in the ability of value added to explain the variation in market capitalization across firms. In the 1970s, value added explains 68.2% of the variation in market capitalization in average. In the 2010s, it explains 67.7%.Perhaps not surprisingly, the top market capitalization firm evolves in the same way as the market as a whole. In the 1950s, the top market capitalization firm was the top employer in the country. In the 2010s, it is the 40th. However, the top market capitalization firm is in the top ten of firms by value added in the 2010s as in the 1970s. The evolution we document is largely the result of the decline of manufacturing in the US. Not all firms are equally suited to be public firms. Small firms and service firms are much less likely to be listed on stock exchanges. Over our sample period, employment by the manufacturing industry falls sharply in importance while employment by the service industries grows dramatically in importance. A large fraction of the employees of manufacturing firms work for public firms. A small fraction of employees of service firms work for public firms. As a result, the fraction of employees working for public firms falls….”

This was a very interesting factoid (see their Table 5 below), “…. Strikingly, from 1950 to 2019, only seven distinct firms have the top market capitalization in at least one year. Only two of these firms, General Motors and AT&T, ever have the largest number of employees in the US. The percentage of US non-farm payrolls represented by the largest market capitalization firm declines steadily over time, so that it is at its lowest in the 2000s. The percentage of US GDP represented by the largest market capitalization firm is also lower in the 2000s than before 1980. The contribution of the top market capitalization firm to the economy in 2019 is a fraction of GM’s contribution in 1953. …”

They find representativeness is worst when the market is most highly valued and worsens over time for employment, but not for value added. “…we measure the extent to which a firm’s market capitalization reflects its concurrent contribution to the economy. We show a strong downward trend in the extent to which a firm’s market capitalization reflects its concurrent contribution to employment. With value added, market capitalizations are least instructive about a firms’ contemporaneous contribution to GDP around 2000, but market capitalizations appear to be as instructive about firms’ contribution to GDP in the 1970s as in the 2010s…..In the 1970s, employment explains 50.7% on average of the variation in market capitalization across firms. In the 2010s, it explains 21.8% on average.A firm’s value added explains much more its market capitalization than its employment. This is true throughout our sample period. Strikingly, there is no consistent degradation in the ability of value added to explain the variation in market capitalization across firms. In the 1970s, value added explains 68.2% of the variation in market capitalization in average. In the 2010s, it explains 67.7%...”

New NBER argues that there is a declining correlation btw a firm's share of employment and its share of stock market value.

Ed Comment: not surprised. When google, Microsoft, apple and Facebook are rocketing in value with no employees.

  • Business Cycle
  • GDP
    • Financial Markets
Previous articleOctober 12, 2020The COVID-19 Pandemic and the $16 Trillion VirusThe economic impact of COVID-19 is estimated at $16tn, 90% of US GDP. Lost GDP over the next decade totals $7.6tn, while excess deaths are valued at $4.4tn. @DavidCutler @LHSummers, Journal of the American Medical Association.Next articleOctober 13, 2020The Tax Elasticity of Capital Gains and Revenue-Maximizing RatesResearch by @OleAgersnap finds that the revenue-maximizing federal capital gains tax rate is btw 38-47%. A 5 percentage point increase in capital gains tax rates could generate $18-30bn in annual federal revenue.
Showing 218 database articles primarily about Business Cycle

3% vs. 60%

AI Summary. The direct lending market is roughly $2tn, or about 3% of total US household and business debt outstanding, compared with mortgages accounting for about 60% of total household and corporate debt at the peak of the housing bubble.

Torsten Sløk Apollo
Date Posted:
April 8, 2026
Is Database:
Database

Torsten Sløk notes the direct lending market is ~$2T or 3% of household and non-financial debt outstanding. To provide context, he shows that in 2006, on the eve of the crisis, mortgages accounted for ~60% of such debt.

Is direct lending too small to threaten the financial system?

Core argument: The direct lending market totals roughly $2 trillion, about 3% of total debt outstanding for US households and businesses.

The direct lending market is roughly $2 trillion, or about 3% of total debt outstanding for US households and businesses. By comparison, mortgages accounted for about 60% of total household and corporate debt at the peak of the housing bubble in 2006.

Takeaways by Macro Roundup® AI

  1. The direct lending market totals roughly $2 trillion, about 3% of total debt outstanding for US households and businesses.
  2. Mortgages accounted for about 60% of total US household and corporate debt at the peak of the housing bubble in 2006, compared with direct lending's roughly 3% share.

Related Articles:

  • JPMorgan Marking Down Loan Portfolios Of Private Credit Groups — JPMorgan has marked down the value of certain loans in private credit funds' portfolios that serve as collateral for the funds' borrowing from the bank, limiting how much it will lend against them. Unlike most banks, which require triggers such as missed interest payments, JPMorgan reserves the right to revalue those assets at any time.
  • Data Update 7 for 2026: Debt and Taxes — The author argues that companies are collectively over-investing in artificial intelligence and that markets will correct when that belief dissipates. Because debt, particularly private credit, now finances much of this investment, the author contends a correction would spread beyond equity holders and produce a banking-style crisis driven by non-bank lenders.
  • Business Cycle
  • GDP
    • Financial Markets

Top 10% of Earners Drive a Growing Share of US Consumer Spending

AI Summary. An analysis of Federal Reserve data found the top 10% of US earners accounted for 49.2% of total consumer spending, up from 48.5% the prior quarter and the highest share in data going back to 1989. Spending by the bottom 80%, those making under roughly $175,000, has merely kept pace with inflation.

Jonnelle Marte Bloomberg
Date Posted:
September 17, 2025
Is Database:
Database

Mark Zandi finds Americans in the top 10% of the income distribution accounted for 49.2% of consumer spending in Q2, the highest level since 1989.

Are top earners accounting for a record share of consumer spending?

Core argument: The top 10% of US earners accounted for 49.2% of total consumer spending in the second quarter, up from 48.5% in the first quarter and the highest share in data going back to 1989, according to Mark Zandi's analysis of Federal Reserve data.

Consumers in the top 10% of the income distribution accounted for 49.2% of total spending in the second quarter, up from 48.5% in the first quarter, reaching the highest level in data going back to 1989, according to an analysis of Federal Reserve data by Mark Zandi, chief economist for Moody’s Analytics. In contrast, the bottom 80% of the income distribution, or consumers making less than roughly $175,000 a year, have seen their spending merely keep pace with inflation since the pandemic.

Takeaways by Macro Roundup® AI

  1. The top 10% of US earners accounted for 49.2% of total consumer spending in the second quarter, up from 48.5% in the first quarter and the highest share in data going back to 1989, according to Mark Zandi's analysis of Federal Reserve data.
  2. Consumers in the bottom 80% of the income distribution, making less than roughly $175,000 a year, have seen their spending merely keep pace with inflation since the pandemic, according to Moody's Analytics chief economist Mark Zandi.

Related Articles:

  • The U.S. Economy Depends More Than Ever on Rich People — Moody's Analytics estimates the top 10% of earners account for 49.7% of all U.S. consumer spending, a record in data going back to 1989, up from about 36% three decades ago, with their spending alone equal to almost one-third of gross domestic product.
  • To Understand America Today, Study the Zero-Sum Mindset — Younger generations in the United States and other rich countries hold more zero-sum views than older ones, a pattern researchers link to growing up amid slower economic growth and lower mobility. People who have surpassed their parents, or whose families rose over generations, are less likely to think in zero-sum terms.
  • Zero-Sum Thinking and the Roots of U.S. Political Divides — Zero-sum thinking — viewing gains for one group as losses for another — is associated with greater support for liberal economic policies, stronger alignment with the Democratic Party, and weaker alignment with the Republican Party. The authors also find it linked to believing the QAnon conspiracy theory holds some truth and to sympathy for the attack on the U.S. Capitol.
  • Business Cycle
  • GDP
  • Workforce
    • Inequality

Litigation Nation, Engineering Empire

AI Summary. Regrouping US college majors to match Chinese disciplines yields a 2:1 ratio of science and engineering to humanities and social sciences, the same ratio as in China. The author argues America's building slowdown reflects structural economic shifts—urbanization reached 70% by 1960 and 85% by 2020, shifting needs toward maintenance—rather than a lawyerly culture.

Jonathon Sine Cogitations
Date Posted:
September 2, 2025
Is Database:
Database
Is Important:
Important

Jonathon Sine argues China “is moving beyond its breakneck industrial prime, facing similar dilemmas to those America confronted in the 1960s and 70s.” The ratio of science/engineering to humanities undergraduate majors is 2:1 in both the PRC and US.

Does America's building slowdown reflect structural shifts rather than lawyerly culture?

Core argument: Regrouping US college majors according to Chinese disciplines yields a 2:1 ratio of science/engineering to humanities/social sciences, the same ratio as in China when management is grouped with science/engineering in both.

Dan Wang’s “big idea” [is] “China is an engineering state, building big at breakneck speed, in contrast to the United States’ lawyerly society, blocking everything it can, good and bad.” I re-group US college majors according to Chinese disciplines to allow for rough comparison. Surprisingly, the ratio of science/engineering to humanities/social sciences is 2:1, the same as in China (if one groups management with science/engineering, as I also do for China). As with China today, America’s breakneck building phase was decidedly winding down by the 1960s. Urbanization went from 40% in 1900 to 70% by 1960, and grew much more incrementally over the next 60 years to 85% by 2020. The country simply did not need to continue building dams, expressways, and energy production facilities at breakneck pace. It became much more a matter of maintaining and upgrading (which has not gone well, at least according to the American Society of Civil Engineers’ report card). The American [building/investment slowdown that started after the 1970s] may be more about structural economic shifts than lawyers.

Takeaways by Macro Roundup® AI

  1. Regrouping US college majors according to Chinese disciplines yields a 2:1 ratio of science/engineering to humanities/social sciences, the same ratio as in China when management is grouped with science/engineering in both.
  2. US urbanization rose from 40% in 1900 to 70% by 1960, then grew more incrementally to 85% by 2020, with America's breakneck building phase winding down by the 1960s.
  3. The US building and investment slowdown that began after the 1970s may owe more to structural economic shifts than to lawyers, qualifying Dan Wang's contrast between China's engineering state and America's lawyerly society.

Related Articles:

  • Industrial Colossus: China vs 1950s America — China's growth in its share of global manufacturing has slowed from roughly 1.5 percentage points per year in the early 2010s to just over 0.5 percentage points annually, about one-third the earlier pace. The author argues China's share of global manufacturing is likely near its peak.
  • The Real China Model — China generates more electricity annually than the United States and European Union combined, having added capacity equivalent to the United Kingdom's total supply each year. Electricity makes up nearly 30% of China's energy use, versus 22% in the US and 21% globally, and its share is growing about 6% a year.
  • America’s Housing Affordability Crisis and the Decline of Housing Supply — Housing production intensity has fallen substantially, especially in fast-growing Sunbelt markets once known for building, converging toward the low rates long seen on the coasts and in declining industrial centers. The authors argue incumbent-controlled regulation explains the weakening link between high prices, high demand areas, and new construction.
  • Business Cycle
  • GDP
    • Growth

How America’s AI Boom Is Squeezing The Rest Of The Economy

AI Summary. About a sixth of America's 2% real GDP growth over the past year came from investment in computer and communications equipment and data centres, and one estimate puts the artificial intelligence boom's total contribution to growth at 40%. Average electricity bills rose 7%, attributed in part to data-centre demand, while housebuilding and non-AI business investment slumped and real consumption flatlined.

Economist Staff The Economist
Date Posted:
August 19, 2025
Is Database:
Database
Is Important:
Important

As AI-related investment has risen since 2023, residential and nonresidential investment have declined or flatlined. This may suggest that a relatively rate-insensitive AI buildout is crowding out more interest-sensitive forms of investment.

Is the AI investment boom crowding out the rest of the economy?

Core argument: Roughly a sixth of the 2% rise in American real GDP over the past year came from investment in computer and communications equipment, including chips, and data centres; one estimate puts the AI boom's contribution at 40% once grid upgrades and software intellectual property are included.

Something like a sixth of the 2% rise in American real GDP over the past year has come from investments in computer and communications equipment, including chips, and data centres. Add in the grid upgrades to power AI models, plus the intellectual-property value of the software itself, and one estimate puts the boom’s contribution to real GDP growth at 40%. The trouble is that the very sector powering so much of America’s economic growth is squeezing the rest of its output. Housebuilders, for instance, cannot afford to be blithe about higher borrowing costs. Data centres have also constrained the rest of the economy by keeping energy prices high. Average American electricity bills have risen by 7% so far in 2025, at least in part due to the extra strain data centres have put on the grid. Real consumption has flatlined since December. Housebuilding has slumped, as has non-AI business investment.

Takeaways by Macro Roundup® AI

  1. Roughly a sixth of the 2% rise in American real GDP over the past year came from investment in computer and communications equipment, including chips, and data centres; one estimate puts the AI boom's contribution at 40% once grid upgrades and software intellectual property are included.
  2. Average American electricity bills have risen by 7% so far in 2025, at least in part due to the extra strain data centres have put on the grid.

Related Articles:

  • Honey, AI Capex is Eating the Economy — Capital spending on AI data centers is around 20% of railroads' peak spending as a share of GDP and is rising quickly, having already surpassed the dot-com era peak in telecom investment. Unlike long-lived rail infrastructure, data centers are short-lived assets requiring frequent hardware replacement, and the capital is being reallocated from other sectors.
  • Back to Our Regularly Scheduled Programming — The four largest US hyperscalers spent $440bn on capital expenditure and research in 2024, with $596bn projected for 2025, a 35% increase, leaving large gaps between AI spending and AI revenues. These firms account for more than half of all capital expenditure growth in the US equity market.
  • The AI Boom’s Hidden Risk to the Economy — Net income at Alphabet, Amazon, Meta and Microsoft rose 73% to $91bn in a quarter two years on, while their combined free cash flow fell 30% to $40bn, as heavy AI investment absorbs cash these firms once recycled into financial markets. That spare cash previously helped hold down long-term interest rates despite large federal deficits.
  • Business Cycle
  • GDP
  • Productivity
    • Innovation/Research
    • Investment

Is it Over?

AI Summary. Benchmark scores show only modest capability gains in the latest large language model releases compared with the larger jump seen two generations earlier, alongside a broader convergence in performance across competing AI models. Commentators attribute this to inherent limits of the technology and the exhaustion of new training data, raising doubts that the spending on AI hardware is justified.

Joseph Wang Fed Guy Blog
Date Posted:
August 18, 2025
Is Database:
Database

Following tepid reactions to the release of GTP-5, Joe Wang observes, “It is looking more like companies are spending hundreds of billions on rapidly depreciating GPUs that produce a commoditized product that most clients only modestly benefit from.”

Are AI capability gains slowing enough to question hardware spending?

Core argument: GPT-5 users widely expressed disappointment with the release, which seemed in some ways a step back, and benchmarks show only modest capability gains since the significant improvement delivered by version 4 two years earlier.

GPT-5 users widely expressed disappointment in the capabilities of the new release, which seemed in some ways a step back. This sentiment is reflected in benchmarks that show a modest improvement in capabilities since the significant improvement in version 4 released two years ago. In addition, the benchmarks suggest a broader convergence in the capabilities of AI models. Commentary suggests this could be due to inherent limitations in the LLM technology and exhaustion of new training data. AI is fascinating technology, but it may not justify the enormous sums spent in its pursuit. It is looking more like companies are spending hundreds of billions on rapidly depreciating GPUs that produce a commoditized product that most clients only modestly benefit from. The entire macro landscape would look very different without the support of the AI boom.

Takeaways by Macro Roundup® AI

  1. GPT-5 users widely expressed disappointment with the release, which seemed in some ways a step back, and benchmarks show only modest capability gains since the significant improvement delivered by version 4 two years earlier.
  2. Benchmarks suggest a broader convergence in AI model capabilities, with commentary attributing this to inherent limitations of large language model technology and exhaustion of new training data.
  3. Companies appear to be spending hundreds of billions on rapidly depreciating GPUs producing a commoditized product that most clients only modestly benefit from, and the entire macro landscape would look very different without the support of the AI boom.

Related Articles:

  • Honey, AI Capex is Eating the Economy — Capital spending on AI data centers is around 20% of railroads' peak spending as a share of GDP and is rising quickly, having already surpassed the dot-com era peak in telecom investment. Unlike long-lived rail infrastructure, data centers are short-lived assets requiring frequent hardware replacement, and the capital is being reallocated from other sectors.
  • Back to Our Regularly Scheduled Programming — The four largest US hyperscalers spent $440bn on capital expenditure and research in 2024, with $596bn projected for 2025, a 35% increase, leaving large gaps between AI spending and AI revenues. These firms account for more than half of all capital expenditure growth in the US equity market.
  • 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.
  • Business Cycle
  • GDP
    • Financial Markets
  • Productivity
    • Innovation/Research
    • Investment

US Households and Firms Are in Great Shape

AI Summary. Household and banking sector leverage in the US have declined significantly since 2008, while corporate leverage has moved sideways and federal government leverage has risen significantly. On this measure, the US private sector is in strong financial shape.

Torsten Sløk Apollo
Date Posted:
March 31, 2025
Is Database:
Database

​​Torsten Sløk notes that US household and banking sector debt has fallen to its lowest level in decades as a % of GDP, while corporate leverage has moved sideways. “The bottom line is that the private sector in the US is in incredibly good shape.”

Is the US private sector in strong financial shape?

Core argument: US household sector leverage and banking sector leverage have both declined significantly since 2008, leaving the US private sector in what the author characterizes as incredibly good shape.

Household sector leverage and banking sector leverage have declined significantly since 2008. Over the same period, federal government leverage has increased significantly, and corporate leverage has moved sideways. The bottom line is that the private sector in the US is in incredibly good shape.

Takeaways by Macro Roundup® AI

  1. US household sector leverage and banking sector leverage have both declined significantly since 2008, leaving the US private sector in what the author characterizes as incredibly good shape.
  2. US federal government leverage has increased significantly since 2008, moving in the opposite direction from the deleveraging in the household and banking sectors.
  3. US corporate leverage has moved sideways since 2008, neither declining like household and banking leverage nor rising like federal government leverage.

Related Articles:

  • Global Debt Report 2025 — About 60% of fixed-rate government debt in advanced economies maturing by 2027 — roughly $9tn — was issued before the recent interest-rate tightening, with weighted average yields below 2% versus projected 10-year rates near 3.6%, implying refinancing at nearly double the original cost. France, Spain, the UK, and the US face heightened vulnerability, with maturing debt exceeding 15% of GDP.
  • The Long-Term Budget Outlook: 2025 to 2055 — The Congressional Budget Office projects the 10-year Treasury note interest rate will average 3.8% over 2025–2055, close to its 3.7% average over the prior three decades, with the inflation-adjusted rate averaging 1.5%. It assesses that long-run rates are largely set by structural factors including demographics, saving and investment behavior, and federal debt.
  • Our Thoughts on Large US Deficits and Their Impact on Bond Yields — Total borrowing in the US is about average despite high government deficits, as high public borrowing has contributed to the need for higher interest rates that have depressed private sector borrowing. Risk premiums on long-dated debt look about average, with no market signs that economic or debt limits are currently being hit.
  • Business Cycle
  • Fiscal Policy
    • Fiscal Deficits
    • Government Spending
  • GDP
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