AI Summary. An analysis finds a Social Security tax-increase package lowers the debt-to-GDP ratio by 14.3 percentage points, with 97% of that coming from smaller Social Security deficits rather than economic growth. A benefit-reduction package cuts the ratio by 29.2 percentage points, raising long-run GDP by 12.1% versus 0.4%.

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A Penn-Wharton simulation finds that restoring Social Security solvency with tax increases alone would cut debt/GDP by ~14pp by 2060, while a fix based only on benefit cuts would cut it by ~29pp.

How do benefit cuts and tax increases differ in reducing debt-to-GDP?

Core argument: The benefit-reduction package cuts the debt/GDP ratio by 29.2 percentage points in the long run, more than twice the 14.3 percentage points under the tax-increase package.

The first figure [in the gallery] decomposes the tax-increase reform package’s improvement to the debt/GDP ratio into separate effects: how much does it cut debt versus how much does it raise GDP? Almost all of the tax-increase plan’s improvement in debt/GDP comes from lowering federal debt by raising taxes. The plan has a small negative effect on the economy in the short run and a small positive effect in the long run. But 97% of its 14.3 percentage point long-run reduction in debt/GDP comes simply from reducing Social Security’s deficits. The economy is little-changed relative to a baseline in which Congress simply borrows to pay Social Security benefits. The benefit-reduction package [second figure in the gallery] tells a different story. It reduces debt/GDP by 29.2 percentage points, more than twice as much as the tax-increase package. Part of that comes from a larger reduction in debt: 17.2 percentage points versus 13.9. But the real kicker comes from higher long-run GDP: 12.1% under the benefit-reduction package versus just 0.4% under the tax-increase package.

Takeaways by Macro Roundup® AI

  1. The benefit-reduction package cuts the debt/GDP ratio by 29.2 percentage points in the long run, more than twice the 14.3 percentage points under the tax-increase package.
  2. Of the tax-increase plan’s 14.3 percentage point long-run reduction in debt/GDP, 97% comes from reducing Social Security’s deficits, leaving the economy little changed relative to a baseline in which Congress borrows to pay benefits.
  3. Long-run GDP rises 12.1% under the benefit-reduction package versus 0.4% under the tax-increase package, with debt falling 17.2 percentage points versus 13.9.

AI Summary. An analysis projects that by 2030 a rapid artificial intelligence growth scenario—3.3% annualized GDP growth with a rising capital share of income—could raise US federal revenues by up to $216bn, 3.3% above the Congressional Budget Office baseline. Because capital income receives preferential tax treatment, a falling labor share of income reduces the revenue gain that output growth would otherwise produce.

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Iselin and Nunn expect AI to increase output growth but to reduce labor’s share of income. “This bias in AI-induced growth reduces the revenue increase one would otherwise expect, given the preferential tax treatment afforded to capital income.”

How much would AI-driven growth raise federal tax revenues?

Core argument: In a rapid AI growth scenario of 3.3% annualized GDP growth with a growing capital share, federal revenues by 2030 could grow by up to $216 billion, a 3.3% increase on top of CBO's 2026 baseline.

The additional output growth that is often expected from AI—a clear positive for the fiscal picture —is not the only potential impact that matters. Another widely expected consequence of AI adoption is a reduction in the labor share of income. This bias in AI-induced growth reduces the revenue increase one would otherwise expect, given the preferential tax treatment afforded to capital income. Further, any labor inequality effects of AI could increase revenues (in the case of increasing inequality) or reduce them (in the case of decreasing inequality). Because these channels are of first-order importance for understanding AI effects on tax revenues, our analysis focuses on their roles. Other channels, not considered here, could also turn out to have meaningful revenue implications. We project that by 2030, in a rapid AI growth scenario (3.3% annualized GDP growth and a growing capital share), federal revenues could grow by up to $216 billion, a 3.3% increase on top of CBO’s 2026 baseline.

Takeaways by Macro Roundup® AI

  1. In a rapid AI growth scenario of 3.3% annualized GDP growth with a growing capital share, federal revenues by 2030 could grow by up to $216 billion, a 3.3% increase on top of CBO's 2026 baseline.
  2. A reduction in the labor share of income from AI adoption would blunt the revenue gains otherwise expected from faster growth, because capital income receives preferential tax treatment.
  3. AI's labor inequality effects could raise revenues if inequality increases or reduce them if inequality decreases, a channel of first-order importance alongside the shift in labor share.

AI Summary. There is little evidence that fears of a Greek-style solvency crisis are driving U.S. interest rates, since long-term "breakeven" inflation expectations have changed little. Prices for credit default swaps, which insure against a U.S. government default, have also moved little.

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Citing the stable long-term breakeven inflation rate and minimal rise in Treasury CDS prices, Krugman argues that high long-term rates reflect heavy federal borrowing, but not fears of outright default or inflation-induced debasement.

Are bond markets signaling fears about government solvency?

Core argument: Bond markets show very little evidence that fears of a Greek-style solvency crisis are driving U.S. interest rates.

There is very little evidence that fears of a Greek-style crisis are driving interest rates now. For example, if markets were really worried about U.S. solvency and the potential for the government to inflate the debt away, this should be reflected in measures that track inflation. But there has been, in fact, very little change in the “breakeven” inflation rate, a measure of long-term inflation expectations. Another indicator is the price of credit default swaps — insurance against a possible US default. These also haven’t moved much.

Takeaways by Macro Roundup® AI

  1. Bond markets show very little evidence that fears of a Greek-style solvency crisis are driving U.S. interest rates.
  2. The breakeven inflation rate, a measure of long-term inflation expectations, has changed very little, which would be expected to move if markets feared the U.S. government would inflate away its debt.
  3. Prices of credit default swaps, which insure against a possible U.S. default, also have not moved much.

AI Summary. The average statutory US tariff rate stands at 11.1% and, under current law including scheduled increases, is projected to reach 11.8% by year-end. The authors estimate current-law tariffs will raise consumer prices by about 0.7% and generate roughly $1.9tn over ten years, with revenue somewhat lower after accounting for tariffs' negative effect on economic output.

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The US’s average statutory tariff rate stands at 11.1% and is set to rise to 11.8% by the end of year. John Iselin projects that the current regime will raise ~$1.9T in revenue over 10 years.

How much will current tariffs raise prices and revenue?

Core argument: The average U.S. statutory tariff rate stands at 11.1%, down about 0.3pp after Section 122 tariffs expired and were replaced with new tariffs under Section 301.

As of July 24th, the average statutory tariff rate stands at 11.1% after falling by about 0.3pp when Section 122 tariffs expired and were replaced with new tariffs under Section 301. Under current law, which includes several scheduled tariff increases in the coming months, this figure is set to be 11.8% by the end of this year. We estimate the ultimate consumer price impact of current-law tariff policy to be about 0.7%. Over the next ten years, we estimate that current-law tariffs will raise about $1.9 trillion. These numbers are somewhat lower, though, after taking into account the negative impact of tariffs on GDP.

Takeaways by Macro Roundup® AI

  1. The average U.S. statutory tariff rate stands at 11.1%, down about 0.3pp after Section 122 tariffs expired and were replaced with new tariffs under Section 301.
  2. Under current law, which includes several scheduled tariff increases in the coming months, the average statutory tariff rate is set to reach 11.8% by the end of this year.
  3. Current-law tariff policy is estimated to raise consumer prices by about 0.7% and to bring in about $1.9 trillion over ten years, with both figures somewhat lower after accounting for the negative impact of tariffs on GDP.

AI Summary. Modeling U.S. venture-backed startups, the authors estimate that taxing capital gains as they accrue rather than at sale would cut founders' average ownership at exit by about 25% while raising the share of entrepreneurs with positive payoffs from roughly 16% to nearly 47%. Less risk-averse founders prefer taxation at sale.

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~84% of venture backed founders end with zero exit value, while the top 2% capture ~80% of total exit value. Accrual-based taxation would reduce mean founder ownership stakes at exit by ~25%, but with fully refundable tax credits, raise the share of founders with >0 payoffs to ~47%.

How does taxing unrealized capital gains affect startup founders?

Core argument: The authors estimate that average founder shares at exit fall about 25% under accrual-based capital gains taxation relative to realization-based taxation, as advance taxation forces additional share sales before exit.

This paper examines how taxing unrealized capital gains affects entrepreneurship, combining a dynamic career-choice model with new evidence on all U.S. venture capital backed startups. Figure 1a plots a histogram of the positive company exit values. The distribution spans several orders of magnitude and is relatively similar to a lognormal, but with a right skew and fatter right tail. A stylized model highlights a key trade-off: accrual-based capital gains taxes dilute successful founders by forcing additional share sales before exit, a well known concern, yet they also provide insurance through tax credits to founders whose ventures fail, an aspect often overlooked. Quantitatively, advance taxation substantially reduces founders' ownership at exit: average founder shares fall about 25% under accrual-based taxation relative to realization based taxation. At the same time, accrual taxation increases the fraction of entrepreneurs with positive payoffs from around 16% to nearly 47%. Embedding these outcomes in a career-choice framework shows that the insurance value of accrual taxation partly offsets dilution costs: less risk-averse founders favor realization-based taxes, while more risk averse ones prefer accrual-based taxes. The strength of this insurance channel depends on the highly skewed distribution of entrepreneurial payoffs and the design of loss provisions under accrual-based taxation.

Takeaways by Macro Roundup® AI

  1. The authors estimate that average founder shares at exit fall about 25% under accrual-based capital gains taxation relative to realization-based taxation, as advance taxation forces additional share sales before exit.
  2. Accrual-based taxation raises the fraction of entrepreneurs with positive payoffs from around 16% to nearly 47%, providing insurance through tax credits to founders whose ventures fail.
  3. In the authors' career-choice framework, less risk-averse founders favor realization-based taxes while more risk-averse founders prefer accrual-based taxes, with the insurance channel's strength depending on the skewed payoff distribution and loss-provision design.

AI Summary. As labor force participation falls, a shrinking group of workers generates the income, taxes, and innovation supporting a growing number of non-workers, leaving the economy more fragile because labor shocks are concentrated among fewer participants. Labor scarcity raises the return on automation, robotics, and software, making growth depend on productivity rather than participation.

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Overall LFP is at a 50-year low. Kedrosky warns, “As fewer adults work or seek work, a larger fraction of voters experience the economy mostly as consumers, retirees, or rentiers, not as workers…[which] changes incentives around….taxation and redistribution.”

How does falling labor force participation reshape growth and fragility?

Core argument: Falling labor force participation leaves a shrinking core of workers generating the income, taxes, and innovation that support a growing number of non-workers, and makes the economy more fragile because labor shocks are concentrated among fewer participants.

As fewer adults work or seek work, a larger fraction of voters experience the economy mostly as consumers, retirees, or rentiers, not as workers. That changes political incentives around wages, immigration, AI, taxation, and redistribution. The economy becomes increasingly dependent on a shrinking core. A shrinking group of workers generates the income, taxes, and innovation that support a growing number of non-workers. The economy becomes more fragile because labor shocks are concentrated among fewer participants. Capital must increasingly substitute for labor. Labor scarcity raises the return on automation, AI, robotics, and software. The AI bet becomes as much about compensating for workers' absence as simple replacement. Growth increasingly depends on productivity, on not participation. Any [productivity] miss will be much more consequential than in the past, given that labor no longer picks up the slack.

Takeaways by Macro Roundup® AI

  1. Falling labor force participation leaves a shrinking core of workers generating the income, taxes, and innovation that support a growing number of non-workers, and makes the economy more fragile because labor shocks are concentrated among fewer participants.
  2. As more voters experience the economy as consumers, retirees, or rentiers rather than workers, political incentives shift around wages, immigration, AI, taxation, and redistribution.
  3. Labor scarcity raises the return on automation, AI, robotics, and software, making the AI bet as much about compensating for workers' absence as replacing them, with growth depending on productivity rather than participation and any productivity miss more consequential than in the past.

AI Summary. The authors estimate that about $200bn of “missing” labor compensation would account for roughly a third of the fall in the labor share since the late 1970s, which workers owning a bit above 10% of corporate profits through stock compensation would cover. Spread across the 4.2m top-decile public company employees, that implies about $40,000 in additional pay each.

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Zidar & Zwick suggest about one‑third of the post‑1970s drop in labor’s share is due to stock‑based pay to workers, in addition to the one‑third they already attribute to pass‑through income. That leaves only around one‑third for genuine shifts in technology, power, etc.

Does stock compensation explain part of the falling labor share?

Core argument: The authors report 2017 employee compensation of $7.2 trillion against corporate value added of $12.2 trillion after adjusting for the rise of pass-throughs, with unadjusted corporate profits, which exclude partnership profits, at $1.7 trillion.

In our data for 2017, after adjustments for the rise of pass-throughs, we report employee compensation of $7.2 trillion and corporate value added of $12.2 trillion. The unadjusted corporate profits number (which excludes partnership profits) is $1.7 trillion. If we could find around $200 billion of “missing” labor compensation, that would account for about a third of the fall in the labor share since the late 1970s. Thus, if workers owned a bit above 10% of those corporate profits via stock compensation, then that would cover the difference. Distributing this amount across the top 10% of public company employees, of which there are 4.2 million, this ownership would imply an additional $40,000 or so in pay. The aggregate numbers are thus quite plausible in terms of how much pay might have shifted to corporate profits serving as tax-preferred payments to high earners.

Takeaways by Macro Roundup® AI

  1. The authors report 2017 employee compensation of $7.2 trillion against corporate value added of $12.2 trillion after adjusting for the rise of pass-throughs, with unadjusted corporate profits, which exclude partnership profits, at $1.7 trillion.
  2. The authors estimate that roughly $200 billion of "missing" labor compensation would account for about a third of the fall in the labor share since the late 1970s, a sum covered if workers owned somewhat above 10% of corporate profits via stock compensation.
  3. Spread across the 4.2 million employees in the top 10% of public company workforces, that amount would imply about $40,000 in additional pay each, which the authors consider plausible as pay shifted into corporate profits serving as tax-preferred payments to high earners.

AI Summary. Europe trains more engineering graduates per capita than China and more STEM PhDs than any region outside the United States, yet the only EU-born companies to reach $100bn market value in the past fifty years, Spotify and BioNTech, listed on US exchanges. Europe captures 6% of global AI startup funding versus 61% for the United States.

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Despite top STEM talent and high savings, Europe captures just 6% of AI funding and lacks trillion-dollar firms. Between 2008 and 2021, ~30% of EU-founded unicorns relocated abroad, largely to the US, seeking deeper liquidity, higher valuations, and pro-growth regulation.

Why does Europe's world-class STEM talent fail to produce giant companies?

Core argument: Europe captures just 6% of global AI startup funding, versus 61% for the United States and 17% for China, despite training more engineering graduates per capita than China and more STEM PhDs than any region outside the U.S.

Europe produces more engineering graduates per capita than China. It trains more PhDs in STEM fields than any region outside the United States. Europe's universities rank among the world's best in dozens of disciplines. Europe's household savings rate exceeds that of America. Europe's research output, measured by publications and citations, is world-class. And yet the only EU-born companies to reach a market capitalisation of $100 billion in the past fifty years, Spotify and BioNTech, did so on the NYSE and Nasdaq respectively. Both chose American exchanges over European ones. None of the world's trillion-dollar companies is European. Europe captures just 6% of global AI startup funding, compared with 61% for the United States and 17% for China. Between 2008 and 2021, nearly 30% of European-founded unicorns relocated their headquarters abroad, overwhelmingly to the United States. They did not leave for the weather. They left because U.S. capital markets offered deeper liquidity, broader analyst coverage, higher valuations, and a regulatory environment designed for growth.

Takeaways by Macro Roundup® AI

  1. Europe captures just 6% of global AI startup funding, versus 61% for the United States and 17% for China, despite training more engineering graduates per capita than China and more STEM PhDs than any region outside the U.S.
  2. The only EU-born companies to reach $100bn market capitalisation in the past fifty years, Spotify and BioNTech, listed on the NYSE and Nasdaq respectively, and none of the world's trillion-dollar companies is European.
  3. Nearly 30% of European-founded unicorns relocated their headquarters abroad between 2008 and 2021, overwhelmingly to the United States, where capital markets offered deeper liquidity, broader analyst coverage, higher valuations, and a regulatory environment designed for growth.