Edward Conard

Top Ten New York Times Bestselling Author

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

Macro Roundup


Monday, November 3, 2025

AI Summary. Across much of the G10, 30-year government bond yields have risen even as central banks cut rates, which the author reads as a sign markets are on average becoming more averse to holding government debt. Switzerland is the only country whose 30-year yield fell, while Germany and the UK stand out as disproportionate risers.

Robin Brooks Robin Brooks Substack
Date Posted:

Only one country – Switzerland – has seen 30-year yields fall since January 2024 and the start of the cutting cycle. Robin Brooks suggests this implies “there’s a slow-motion run on government debt” underway.

Are markets growing more averse to holding long-term government debt?

Core argument: Across much of the G10, 30-year government bond yields have risen since January 2024 despite cumulative central bank rate cuts, a pattern the author reads as a potential sign that markets are becoming more averse on average to holding government debt.

I compare the rise in 30-year government bond yields across much of the G10 with central bank rate cuts. Central bank cuts should pull down yields across the curve, including at the very long end, but that hasn’t been happening during this easing cycle. [Editor’s note: In fact, since the 2008 financial crisis, there have been episodes where the Fed cut rates to support growth, yet long-term rates rose due to market fears of future inflation, such as the inflationary surge following 2021]. That’s potentially a sign that - on average - markets are becoming more averse to holding government debt. The chart zooms in on the cross-country perspective. The horizontal axis shows cumulative cuts (-) made since January 2024. The vertical axis shows the rise (+) in the 30-year government bond yield since then. Three points are worth making. First, more rate cuts - on average - tend to hold down longer-term yields. This positive relationship is to be expected and normal. Second, the only place that’s seen a fall in its 30-year yield is Switzerland, a reflection of its low debt and safe haven status. Third, Germany and the UK are outliers, in the sense that their 30-year yields look to have risen disproportionately. In contrast, and perhaps to the frustration of many, the US looks ok. The US continues to benefit from the fact that “there is no alternative.”

Takeaways by Macro Roundup® AI

  1. Across much of the G10, 30-year government bond yields have risen since January 2024 despite cumulative central bank rate cuts, a pattern the author reads as a potential sign that markets are becoming more averse on average to holding government debt.
  2. Switzerland is the only country in the comparison whose 30-year yield has fallen, which the author attributes to its low debt and safe haven status.
  3. Germany and the UK stand out as outliers whose 30-year yields appear to have risen disproportionately, while the US looks fine, continuing to benefit from the absence of an alternative.

Related Articles:

  • Across The Rich World, Fiscal Crises Loom — An analysis estimates most rich countries could keep debt stable as a share of their economies with only small primary surpluses—Britain's required surplus is 0.3% of GDP—even if all debt were refinanced immediately at current rates, but the tightening needed to stabilize debt ratios exceeds 2% of GDP in Britain and America and 3% in France.
  • Data Update 4 for 2025: Interest Rates, Inflation and Central Banks! — Interest rates are ultimately driven by macroeconomic fundamentals, with an "intrinsic risk-free rate" defined as the sum of the inflation rate and real GDP growth tracking the observed 10-year Treasury bond yield closely. On this view, central banks' influence comes from preferential access to data on those fundamentals, their capacity to alter them, and their credibility.
  • 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.

AI Summary. Investors have continued buying US government debt despite concerns over tariffs, tax cuts, budget deficits, and pressure on the Federal Reserve, with benchmark 10-year yields down about half a percentage point to roughly 4%. The $30tn Treasuries market has returned about 6%, and US 10-year yields have fallen the most among G-7 nations.

Michael MacKenzie and Ye Xie Bloomberg
Date Posted:

Investors keep “piling” into Treasuries. The 10-year yield has fallen ~50bps this year, to ~4%, by far the largest decline among the G-7 countries.

Are investors still buying US government debt despite deficit and tariff worries?

Core argument: Benchmark US 10-year Treasury yields have fallen about half a percentage point this year to roughly 4%, the largest decline among G-7 nations, despite Wall Street warnings to "Sell America.".

From sweeping tariffs and tax cuts, to yawning budget deficits and persistent attacks on the Federal Reserve — a steady drumbeat of worries had many on Wall Street sounding the same ominous alarm: "Sell America." In spite of it all, though, investors keep piling into US government debt. Benchmark 10-year yields have fallen about a half-percentage point this year, to roughly 4%. In fact, the $30 trillion Treasuries market is up about 6% this year, on its way to the best year since 2020. US 10-year yields have declined the most by far among G-7 nations this year. 

Takeaways by Macro Roundup® AI

  1. Benchmark US 10-year Treasury yields have fallen about half a percentage point this year to roughly 4%, the largest decline among G-7 nations, despite Wall Street warnings to "Sell America.".
  2. The $30 trillion Treasuries market has returned about 6% this year, putting it on track for its best year since 2020.
  3. Investors have kept buying US government debt through sweeping tariffs, tax cuts, wide budget deficits and persistent attacks on the Federal Reserve.

Related Articles:

  • Bank of America Sees US Bill Supply Boost Curbing 10-Year Yield — Bank of America expects the US Treasury to lean more heavily on short-term bill issuance, lifting bills to about 25% of outstanding debt from about 20%. Its strategists estimate the resulting reduction in longer-dated note and bond supply is equivalent to roughly $1tn of 10-year notes, worth at least 31 basis points of lower yields.
  • JPMorgan Is Worried About Who’s Going to Buy All the Bonds — JPMorgan analysts estimate that the Federal Reserve's Treasury holdings have fallen $180bn as it pursues quantitative tightening, while commercial banks' holdings are down $60bn and foreign official holdings down $50bn. The analysts describe simultaneous negative demand from all three buyer types as rare and say they remain concerned about the lack of structural demand for Treasuries.
  • 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.

AI Summary. The authors construct a long-short "AI factor" portfolio and find that firms investing in artificial intelligence shift their risk profiles, with total volatility roughly unchanged but a reallocation from firm-specific risk to market-wide risk. This increased comovement with all sectors of the economy mostly reflects greater upside exposure rather than downside.

Tania Babina, Anastassia Fedyk, Alex He and James Hodson Columbia University
Date Posted:

Btw 2014 and 2018, firms with higher than median investment in AI experienced a large and statistically significant increase in systematic risk as measured by market beta, driven by upside risks “consistent with AI investments creating growth options.”

How does investing in AI change firms' risk profiles?

Core argument: The authors' long-short "AI factor," long firms ranking above the median among those with non-zero AI investments and short all other firms, shows no statistically significant market alpha, though returns to AI-investing firms were consistently positive later in the sample.

We construct an “AI factor": a long-short portfolio with the long side comprised of firms that rank above the median among firms with non-zero AI investments and the short side comprising 20 all other firms. Figure 1 shows the time series of the estimates of the AI factor’s market alpha (α (AI) ) [a measure of “excess return”] in Panel A and beta (β (AI)) [a measure of systematic market risk] in Panel B. Panel A does not show statistically significant alpha, but the returns to AI-investing firms have been consistently positive during the later part of the sample. Panel B shows that the beta of the AI factor has been relatively low in the first few years of the sample, but starts to increase in the middle and becomes especially high at the end (in 2017 and 2018), consistent with the increasing potential to realize AI-related growth options over time. Our evidence points to a significant shift in firms’ risk profiles as they invest in AI. The total volatility of AI-investing firms does not change significantly, but there is a reallocation from idiosyncratic risks to systematic risks (higher market beta). AI-investing firms experience increases in comovement with all sectors of the economy—including their own sector, the tech sector, and other industry sectors. This increased market covariance mostly reflects increased upside, as AI-investing firms experience much larger increases in upside market beta than downside market beta.

Takeaways by Macro Roundup® AI

  1. The authors' long-short "AI factor," long firms ranking above the median among those with non-zero AI investments and short all other firms, shows no statistically significant market alpha, though returns to AI-investing firms were consistently positive later in the sample.
  2. The AI factor's market beta was relatively low in the sample's first years, rose in the middle, and became especially high in 2017–2018, which the authors read as consistent with the increasing potential to realize AI-related growth options.
  3. Total volatility of AI-investing firms does not change significantly, but risk shifts from idiosyncratic to systematic, with greater comovement with their own sector, the tech sector, and other industries, and larger increases in upside than downside market beta.

Related Articles:

  • The Golden Opportunity for American AI — Artificial intelligence is a general-purpose technology comparable to electricity, with potential to lift innovation and productivity. The authors argue the United States needs a national strategy spanning research and development, workforce skilling, AI infrastructure investment, and international partnerships to expand American AI exports, counter China's influence, and shape global standards.
  • Exploring How AI Will Impact the Economy — Artificial intelligence is projected to pass through to productivity faster than past general-purpose technologies, though peak effects remain years away. The argument rests on lower capital spending per unit of labor saved, capital spending concentrated among major software players that can distribute AI tools through platforms businesses already use, and low unemployment with high wage growth raising incentives to automate.
  • The Outlook for Long-Term Economic Growth — Growth theory holds that long-run growth in living standards is determined by growth in the worldwide number of people searching for ideas, and growth accounting for the US suggests temporary boosts from rising educational attainment and idea investment could fade. Potential offsets include China and India, better talent allocation, and artificial intelligence.

AI Summary. Big Tech raised at least $75bn from investment-grade bonds in a single month to fund AI data centers, with banks syndicating another $38bn in loans, versus an average of $37bn issued per year before the pandemic. Because AI-related capital spending growth exceeded growth in total non-residential fixed investment, spending on everything else declined.

John Authers and Richard Abbey Bloomberg
Date Posted:

Morgan Stanley shows AI-related cap-ex growth exceeds total non-residential fixed investment growth for the year. “In other words, capex in everything not related to AI has actually declined.”

Is AI borrowing and capital spending crowding out other investment?

Core argument: Big Tech raised at least $75 billion from investment-grade bonds in September alone to fund AI data centers, against an average of $37 billion issued each year before the pandemic, according to Bank of America data.

How much money is going into building out AI? In September alone, Big Tech raised at least $75 billion from investment-grade bonds to fund AI data centers. Banks are syndicating a further $38 billion in loans tied to Oracle and Vantage facilities. Before the pandemic, these companies were issuing an average of $37 billion each year, Bank of America data shows. Archimedes’ principle holds that the upward buoyant force on an object submerged in a fluid is equal to the weight of the fluid it displaces. How much is the AI splurge going to displace? The extra spending on AI could galvanize the economy, but will it crowd out everything else? AI-related capex is immense, as we’ve discussed — but as Morgan Stanley shows, its growth actually exceeds total non-residential fixed investment growth for the year. In other words, capex in everything not related to AI has actually declined. [Note that H1:2025 AI spend outpaced total non-residential fixed investment]. GDP accounting can reduce this by excluding the AI spending that goes on imports [Exhibit 4 in the gallery]. With chips mostly manufactured outside the US, that makes a big difference.

Takeaways by Macro Roundup® AI

  1. Big Tech raised at least $75 billion from investment-grade bonds in September alone to fund AI data centers, against an average of $37 billion issued each year before the pandemic, according to Bank of America data.
  2. Banks are syndicating a further $38 billion in loans tied to Oracle and Vantage facilities.
  3. Morgan Stanley shows AI-related capex growth exceeded total non-residential fixed investment growth for the year, implying capex unrelated to AI declined, while GDP accounting excludes AI spending on imports, including chips manufactured outside the US.

Related Articles:

  • How America’s AI Boom Is Squeezing The Rest Of The Economy — 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.
  • AI Data Center Boom Threatens Trump’s Manufacturing Revival — Bloomberg Economics projects the largest participants could pour as much as $4tn into artificial intelligence infrastructure by the end of the decade, with capital spending by hyperscalers such as Alphabet, Amazon, Meta, and Microsoft rising from almost $400bn to as much as $600bn. It expects AI's contribution to GDP growth could reach as much as 1.5 percentage points.
  • The Blob: Capital, China, Chips, Chicago and Chilliwack — Data center construction spending has eclipsed office construction, and the specialized power rates most data centers pay fall short of covering the cost of a new natural gas plant, leaving other customers to bear part of the bill. In the PJM grid region, data center demand accounted for 70% of the increase in electricity costs over the past year.

AI Summary. Research by finance professors Eugene Fama and Kenneth French identified an "investment factor," the tendency of stocks in companies that invest the most to lag the market, a pattern that held from the 1960s through the early 2000s except during the Nifty Fifty and dot-com booms. That factor has behaved normally recently, with higher-spending large companies tending to underperform slightly.

James Mackintosh Wall Street Journal
Date Posted:

James Mackintosh notes that the historical tendency for the total return of high investment firms to lag those with lower investment noted by Fama and French continues to hold, “with higher-spending big companies tending to underperform a little.”

Are investors still penalizing the heaviest spenders during the AI boom?

Core argument: The "investment factor," named by finance professors Eugene Fama and Kenneth French, has behaved normally this year, with higher-spending big companies tending to underperform a little.

The history of investor views of capex is neatly measured by what finance professors Eugene Fama and Kenneth French dubbed the “investment factor,” the old tendency of stocks in companies that invest the most to lag behind. From the 1960s through to the early 2000s, companies that increased capex the most were pretty consistent laggards. The two big exceptions were the Nifty Fifty boom of the late 1960s and early 1970s, briefly interrupted by a recession, and the dot-com bubble of the late 1990s. In both periods of excess, investors thought companies could invest successfully, and rushed to buy the heaviest spenders before being disappointed. [Contemporarily] there is little sign of a shift in the investment factor, which has behaved perfectly normally this year, with higher-spending big companies tending to underperform a little.

Takeaways by Macro Roundup® AI

  1. The "investment factor," named by finance professors Eugene Fama and Kenneth French, has behaved normally this year, with higher-spending big companies tending to underperform a little.
  2. From the 1960s through the early 2000s, companies that increased capital expenditure the most were pretty consistent stock market laggards, as measured by the Fama-French investment factor.
  3. The two big exceptions were the Nifty Fifty boom of the late 1960s and early 1970s and the dot-com bubble of the late 1990s, when investors rushed to buy the heaviest spenders before being disappointed.

Related Articles:

  • Surviving the AI Capex Boom — Capital spending by the largest US technology companies has risen from 4% to 15% of revenue since 2012, approaching the capital intensity of utilities, with Meta, Microsoft, and Alphabet each set to spend 21–35% of revenue. The authors argue this shift toward asset-heavy models is associated with inferior returns.
  • Minsky Moments and AI CapEx — Capital-spending forecasts for the four largest cloud providers rose nearly 50% over the year, and AI data centers are increasingly funded through leveraged and off-balance-sheet structures, including $3.2bn in senior secured notes and a roughly $30bn asset-backed financing. The author argues this marks a speculative-finance phase where borrowers must roll over principal.
  • Why We Are Not In A Bubble….Yet — The 5 largest US technology companies are worth about 16% of the global public equity market, and the top 10 US stocks nearly 25%, almost $25tn. The author argues valuations are high but not bubble-level, with the "Magnificent 7" median forward price-to-earnings ratio at 27x, roughly half that of the late-1990s leaders.

AI Summary. Six of the world's fifteen most populous countries in 2100 — including three of the top five — are projected to be places with under $7,000 in per capita GDP today, led by Pakistan, Nigeria, and the Democratic Republic of the Congo, with Ethiopia and Tanzania close behind. Over 2bn people are projected to live in those five countries.

Noah Smith Noahpinion
Date Posted:

In 75 years, 20% of the world’s population is projected to live in Pakistan, Nigeria, the DRC, Ethiopia and Tanzania. Noah Smith notes, “More and more of humanity is going to live in a few big countries that can’t manage themselves.”

Will the world's most populous countries be among its poorest?

Core argument: By 2100, six of the world's fifteen most populous countries — and three of the top five — are projected to be places with under $7,000 in per capita GDP (PPP) as of 2025.

By 2100, six out of the fifteen most populous countries in the world — and three of the top five — will be places that as of 2025 have under $7,000 in per capita GDP (PPP). The biggest ones will be Pakistan, Nigeria, and the Democratic Republic of the Congo, with Ethiopia and Tanzania not far behind. Altogether, over 2 billion people — a fifth or more of humanity’s peak population — is projected to live in those five countries. And that percentage will only grow after that, at least unless some sort of radical unexpected change happens to demographic patterns. Fertility is falling everywhere, but in the Big 5 poor countries, it’s not falling much faster than in the world as a whole.

Takeaways by Macro Roundup® AI

  1. By 2100, six of the world's fifteen most populous countries — and three of the top five — are projected to be places with under $7,000 in per capita GDP (PPP) as of 2025.
  2. Pakistan, Nigeria, the Democratic Republic of the Congo, Ethiopia, and Tanzania are projected to hold over 2 billion people, a fifth or more of humanity's peak population, with that share rising thereafter absent radical demographic change.
  3. Fertility is falling everywhere, but in those five poor countries it is not falling much faster than in the world as a whole.

Related Articles:

  • 21st-Century Africa Governance and Growth — Sub-Saharan Africa's GDP per capita has fallen relative to the world average over three decades, from 30% to 22%, reflecting the region's inability to sustain growth. Had it grown at the global pace since 1990, income per capita would be over 40% higher; at emerging East Asia's pace, nearly 3x higher.
  • Changing Sub-Saharan Africa’s Growth Trajectory — Sub-Saharan Africa's working-age population is growing nearly 3% a year, versus close to zero in much of the world, and is projected to exceed China's within about a decade and reach a quarter of the global total. With modest productivity growth near 2%, the region is likely among the world's fastest-growing.
  • Exploring the Implications of Sub-Saharan Africa’s Demographic Explosion — Sub-Saharan Africa is projected to hold a quarter of the world's working-age population within a few decades and to surpass China's working-age population in roughly a decade. Even with modest productivity growth near 2%, the region's growth is estimated at 4.5–5.5%, raising its share of global output from about 3% while remaining small.

Tuesday, November 4, 2025

AI Summary. Since 1988, total factor productivity in the information technology sector has risen about 178%, versus about 12% across all non-IT sectors combined, while aggregate productivity rose about 40%. The IT sector accounts for roughly 45% of cumulative aggregate productivity growth, once sectoral linkages to downstream industries are weighted in.

Joel David, Gustavo de Souza, Adalyn Schommer Federal Reserve Bank of Chicago
Date Posted:
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Btw 1988 and 2023, the US IT sector’s TFP rose by 178%, while TFP in all the non-IT sectors combined rose by only 12%. Taking account of sectoral linkages, the IT sector contributed ~17pp to TFP growth since 1988, and the non-IT sectors about 20pp.

How much of US productivity growth comes from the IT sector?

Core argument: The IT sector's total factor productivity rose 178% over the 36 years since the start of 1988, versus 12% for all non-IT sectors combined, while aggregate TFP increased 40%.

For a given % change in any particular sector’s TFP, the effect on aggregate TFP is equal to the sector-level change multiplied by a weight equal to the ratio of that sector’s nominal gross output to the total nominal value added of the entire private business sector. The total change in aggregate TFP is the sum of the weighted changes in sector-level TFPs. The “Domar weights,” [which] sum to more than one since the numerator includes sales of intermediate goods instead of only value added, incorporate the effects of sectoral linkages—when sector i becomes more productive, the sectors that use the output of sector i become more efficient and expand production, as do the sectors that use the output of those sectors as inputs (including possibly sector i), and so on. Fig.3, panel A shows that aggregate TFP has increased by a factor of 1.4, or 40%, in the 36 years since the start of 1988, while the IT sector’s TFP has increased by a factor of about 2.78, or 178%. In contrast, TFP in all the non-IT sectors combined has increased by a factor of only about 1.12, or 12%. Fig.3, panel B shows that the IT sector has contributed approximately 17 percentage points to cumulative TFP growth since 1988, and the non-IT sectors about 20 percentage points. Thus the IT sector accounts for roughly 45% of cumulative aggregate productivity growth.

Takeaways by Macro Roundup® AI

  1. The IT sector's total factor productivity rose 178% over the 36 years since the start of 1988, versus 12% for all non-IT sectors combined, while aggregate TFP increased 40%.
  2. The IT sector contributed roughly 17 percentage points of cumulative aggregate TFP growth since 1988 against about 20 percentage points from non-IT sectors, accounting for roughly 45% of cumulative aggregate productivity growth.
  3. Aggregate TFP change equals the sum of sector-level TFP changes weighted by Domar weights—each sector's nominal gross output over total private business value added—which sum to more than one and incorporate sectoral linkages.

Related Articles:

  • Is The Great Stagnation Actually Just a ‘So-So’ Stagnation? — Long-running U.S. tests show population average reading scores moved from 255 to 256 out of 500 and math from 266 to 271, despite educational attainment rising more than three years. The author argues that if added schooling has not raised productivity, measured total factor productivity growth has been understated, shrinking the apparent "Great Stagnation" by about a third.
  • 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.
  • Productivity During and Since the Pandemic — Total factor productivity growth since early 2021 has run only slightly above its 2010–19 average, suggesting the 2020 productivity surge reflected cyclical dynamics layered on a continuation of the slow pre-pandemic trend. Productivity has since grown somewhat faster than the authors' analysis predicted, but remains well below the 1995–2004 pace.

AI Summary. About 42m Americans — nearly 12% of households and one in five children — rely on the Supplemental Nutrition Assistance Program (food stamps) to feed their families, with recipient households split roughly evenly between counties that voted for Trump (48.5%) and Harris (51.5%). Among counties drawing more than 1% of total income from the program, 82.2% voted for Trump.

Kenan Fikri, Ben Glasner, and Sarah Eckhardt Agglomerations
Date Posted:

12% of households receive SNAP benefits, 48.5% of which live in counties that voted for Trump, compared to 51.5% who voted for Harris. Of counties in which SNAP made up > 1% of total personal income, 82.2% voted for Trump versus 17.8% for Harris.

How widely are food stamp benefits spread across political lines?

Core argument: SNAP benefits reach 42 million Americans, nearly 12% of households and one in five children, a scale highlighted by the partial lapse in benefits.

The threatened, on-again-off-again, now partial lapse in SNAP benefits has made the public aware of a disturbing statistic: that 42 million of our neighbors rely on government assistance to feed their families. That’s nearly 12% of households and, more shockingly, one in five children. SNAP has become such a salient issue for both parties during the shutdown because it affects them both. 48.5% of households receiving SNAP benefits live in counties that voted for Trump in the 2024 election and 51.5% live in those that voted for Harris. Among counties that voted for Harris, 11.9% of households received SNAP benefits, and 11.6% of households living in counties that went for Trump did. A striking political difference does emerge when looking at the counties that rely on SNAP the most. Among counties that received more than 1% of total income from SNAP, 82.2% voted for Trump and 17.8% voted for Harris.

Takeaways by Macro Roundup® AI

  1. SNAP benefits reach 42 million Americans, nearly 12% of households and one in five children, a scale highlighted by the partial lapse in benefits.
  2. SNAP recipients are split almost evenly by 2024 presidential vote, with 51.5% of recipient households in counties that voted for Harris and 48.5% in counties that voted for Trump.
  3. Among counties drawing more than 1% of total income from SNAP, 82.2% voted for Trump and 17.8% voted for Harris, while household receipt rates were 11.9% in Harris counties and 11.6% in Trump counties.

Related Articles:

  • The Great “Transfer”-mation — Government transfers rose from 8.2% of Americans' total personal income in 1970 to 17.6% in 2022, making them the third largest income source after work and investments. The share of U.S. counties drawing a quarter or more of personal income from transfers rose from under 1% in 1970 to 53% in 2022.
  • The Economic Geography Of The 2024 Elections — Counties where government transfer programs such as Social Security, Medicare, Medicaid, and unemployment insurance make up at least a quarter of personal income gave Trump 63% of the vote, while counties where transfers account for less than 15% gave Harris 56%. Transfers supplied 18% of total US personal income.
  • “Compensate the Losers?” Economic Policy and Partisan Realignment in the US — The authors argue that partisan realignment by education reflects Democrats' declining supply of "predistribution" policies such as job guarantees, higher minimum wages, protectionism, and stronger unions, which less-educated Americans favor while more-educated Americans prefer taxes and transfers. They estimate changing views of the parties' economic policies explain roughly half the shift.

AI Summary. Measured against median household income, US house prices are about 3% below their bubble peak and roughly 9% below their recent peak. Measured against the National Average Wage Index, house prices remain well above the median historical ratio and not far below the bubble peak.

Bill McBride Calculated Risk
Date Posted:

Relative to median household income, home prices are 3% under the bubble peak and ~9% below the recent peak. Measures of home prices relative to income remain elevated.

How do house prices compare to income and wages today?

Core argument: Median household income was $83,730 in 2024, up 3.87% from $80,610 in 2023 in nominal dollars, with 2025 median income estimated at a 4% annual gain.

The median household income was $83,730 in 2024, up 3.87% from $80,610 in 2023 (nominal dollars). [The First] graph uses the year-end Case-Shiller house price index - and the nominal median household income through 2024 from the Census Bureau. 2025 median income is estimated at a 4% annual gain. By this measure, house prices are 3% below the bubble peak, and about 9% below the recent peak. For the second graph I decided to look at house prices and the National Average Wage Index released in October for 2024 from Social Security. This graph shows the ratio of house price indexes divided by the National Average Wage Index (the Wage index is first divided by 1000). This uses the annual average National Case-Shiller index since 1976 (and an estimate for 2025). Note: The national wage index for 2025 is estimated. As of 2025, house prices were well above the median historical ratio - and not far below the bubble peak.

Takeaways by Macro Roundup® AI

  1. Median household income was $83,730 in 2024, up 3.87% from $80,610 in 2023 in nominal dollars, with 2025 median income estimated at a 4% annual gain.
  2. Measured against the year-end Case-Shiller house price index and nominal median household income, house prices stand 3% below the bubble peak and about 9% below the recent peak.
  3. Using the ratio of the annual average national Case-Shiller index to Social Security's National Average Wage Index since 1976, house prices as of 2025 were well above the median historical ratio and not far below the bubble peak.

Related Articles:

  • The State of Housing (Un)Affordability in the US — A slowdown in housing supply growth has weighed on affordability, with the share of housing stock available for sale or rent below its historical average, implying a gap between supply and demand. The analysis estimates that restoring affordability would require roughly 3–4mn additional units, or 2–2.6% of current stock, with California and Florida facing the largest shortages.
  • Credit Drove 125 Years Of Homeownership Gains — Drawing on over 100 million household records, the authors trace US homeownership from 47% in 1900 to a 69% peak and 65% today, arguing the major gains came from making mortgages cheaper and more accessible rather than building more homes. Homes now cost nearly 6x median household income versus 3x in the 1990s.
  • Why Are Young Adults in the English-Speaking World So Unhappy? — The share of young adults regularly experiencing stress and anger has risen sharply in the US, Canada, UK, Ireland, Australia and New Zealand while remaining largely stable elsewhere in the West. Real house prices since 1995 are up 85% in the US and over 200% in the other five countries.

AI Summary. The median age of first-time homebuyers in the US has reached a record 40, up from 33 in 2021 and 29 when the National Association of Realtors survey began in 1981. High home prices and mortgage rates are delaying homeownership for millions of Americans.

Michael Sasso Bloomberg
Date Posted:
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The median age of first-time homebuyers in the US has climbed to a record of 40, up from 33 in 2021.

Are high home prices and mortgage rates delaying first-time homebuying?

Core argument: The median age of US first-time homebuyers has reached a record 40, up from 33 in 2021, according to a National Association of Realtors survey of transactions from July 2024 through June.

The median age of first-time homebuyers in the US has climbed to a record of 40 as soaring prices and mortgage rates over the last few years delay homeownership for millions of Americans. The age at which people purchase their first home has climbed rapidly since 2021, when the median was 33, according to a National Association of Realtors survey of transactions from July 2024 through June. In 1981, when the survey was first conducted, the median age was 29 years old.

Takeaways by Macro Roundup® AI

  1. The median age of US first-time homebuyers has reached a record 40, up from 33 in 2021, according to a National Association of Realtors survey of transactions from July 2024 through June.
  2. Soaring home prices and mortgage rates over the last few years have delayed homeownership for millions of Americans.
  3. In 1981, when the National Association of Realtors first conducted the survey, the median first-time homebuyer age was 29, 11 years below the current record of 40.

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