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


Thursday, December 4, 2025

AI Summary. Google's Gemini 3, trained entirely on Google's own tensor processing unit chips, is the best-performing AI model across nearly all dimensions except possibly coding, leaving OpenAI without a leading model for the first time in three years. Google's vertically integrated stack from chips to data centers likely gives it the cheapest access to computing power among leading AI labs.

Greg Jensen and Jas Sekhon Bridgewater Associates
Date Posted:

Bridgewater notes that Gemini 3’s release, “trained entirely on Google’s own TPU chips,” outperforms ChatGPT in almost all tasks, implying that “Google is now the clear leader in the AI race.”

Does owning the full chip-to-model stack determine AI leadership?

Core argument: Google's Gemini 3, trained entirely on Google's own TPU chips, is the best-performing model across nearly all dimensions except possibly coding, marking the first time since GPT-3.5 launched three years ago that OpenAI lacks a leading model.

The release of Gemini 3, trained entirely on Google’s own TPU chips, confirms Google’s leading position. Across nearly all dimensions (with the possible exception of coding, as mentioned previously), Gemini 3 is the best-performing model. This marks the first time since the launch of GPT-3.5 three years ago that OpenAI doesn’t have a leading model. Looking ahead, Google has a significant advantage in training frontier models, and efficiently and cheaply servicing them—in part due to its vertically integrated ecosystem. Google has its own large, mature, and competitive hardware stack, from chips to data centers, which likely gives it the cheapest and easiest access to compute among leading AI labs. And after nearly a decade of limiting external access to its TPU chips, Google has also started exploring selling and leasing them to other AI labs and cloud providers in recent months, opening the possibility of it dominating the full AI stack, from chips to models.

Takeaways by Macro Roundup® AI

  1. Google's Gemini 3, trained entirely on Google's own TPU chips, is the best-performing model across nearly all dimensions except possibly coding, marking the first time since GPT-3.5 launched three years ago that OpenAI lacks a leading model.
  2. Google's vertically integrated stack, spanning its own chips and data centers, likely gives it the cheapest and easiest access to compute among leading AI labs for both training and servicing frontier models.
  3. After nearly a decade of limiting external access to its TPU chips, Google has begun exploring selling and leasing them to other AI labs and cloud providers, opening the possibility of dominating the full AI stack from chips to models.

Related Articles:

  • On Benchmark Games, Gemini, and Declining Returns to Scale — Composite benchmarks show Google's Gemini roughly in line with GPT-5-class models, with any gap small, and the author argues it does not lead on strict low-leakage reasoning exams. The pattern reflects growing training costs yielding modest gains concentrated in vision, video, and some coding rather than broad reasoning advances.
  • AI Capex Risk as Predictable Engineering — The 2020 scaling-laws paper fostered a belief that mixing compute, data, and parameters yields better AI models in a deterministic way, which the author argues let unusually large capital spending plans pass without investor revolt. The author contends that curve was empirical rather than physical and is now breaking, returning AI capital spending to normal economics.
  • Is AI Hitting A Wall? — Artificial intelligence gains have come from a formula of more data and more computing power, but companies have exhausted freely available internet training data and are now striking data-sharing deals with publishers and copyright holders. Training and running large models is energy-intensive, requiring vastly more Nvidia chips with each generation.

AI Summary. The author argues that frontier model pre-training is becoming uneconomic, delivering only marginal capability gains for enormous spending on chips, power, and compute. Meaningful advances have shifted to post-training, inference-time compute, and tool-augmented reasoning rather than raw model size.

Paul Kedrosky Applied Complexity
Date Posted:

Kedrosky argues that Google’s Gemini 3 suggests “scaling curves aren’t [yet] broken, but they’re exhausting and breaking.” This implies the capex super-cycle will “briefly” deepen but likely only result in marginal improvements.

Is scaling model size still economically worth the cost?

Core argument: Gemini 3 shows larger training runs still yield some capability gains, but the author argues the gains are small relative to the spending required, with pre-training's economic viability collapsing.

The takeaway shouldn't be “scaling is alive.” It should be that frontier training is becoming uneconomic, fast, and the industry is pushing ahead anyway. That means: The capex super-cycle briefly deepens: more chips, more power, more exaflop-month training runs. The economic value of scaling shrinks while the cost explodes. Advances, such as they are, have shifted to post-training, inference-time compute, and tool-augmented reasoning—not raw model size. Gemini 3 shows you can still squeeze some capability out of larger training runs. But it also shows how little you get for that prodigious spending. Pre-training's economic viability is collapsing, forcing the industry into a financially brutal and unsustainable arms race for marginal improvements.

Takeaways by Macro Roundup® AI

  1. Gemini 3 shows larger training runs still yield some capability gains, but the author argues the gains are small relative to the spending required, with pre-training's economic viability collapsing.
  2. The author contends frontier AI training is becoming uneconomic quickly while the industry pushes ahead anyway, briefly deepening the capex super-cycle through more chips, more power, and more exaflop-month training runs.
  3. Advances have shifted to post-training, inference-time compute, and tool-augmented reasoning rather than raw model size, according to the author, who describes the industry as locked in an arms race for marginal improvements.

Related Articles:

  • Google’s Gemini 3 Means AI’s “Resource Grab” Phase Is On — Google's Gemini 3, trained entirely on Google's own tensor processing unit chips, is the best-performing AI model across nearly all dimensions except possibly coding, leaving OpenAI without a leading model for the first time in three years. Google's vertically integrated stack from chips to data centers likely gives it the cheapest access to computing power among leading AI labs.
  • On Benchmark Games, Gemini, and Declining Returns to Scale — Composite benchmarks show Google's Gemini roughly in line with GPT-5-class models, with any gap small, and the author argues it does not lead on strict low-leakage reasoning exams. The pattern reflects growing training costs yielding modest gains concentrated in vision, video, and some coding rather than broad reasoning advances.
  • AI Capex – Financing The Investment Cycle — Global data center, AI infrastructure and related power buildout could cost over $5tn, requiring funding from every public capital market plus private credit, alternative capital providers and possibly governments. The largest cloud providers generate over $700bn of annual operating cash flow and reinvest roughly $500bn in capital spending, with about $300bn a year estimated to fund AI and data centers.

AI Summary. A simulation of safety-net benefits for a single mother with two children in North Carolina shows net income rising faster than earnings below $30,000 a year, then dropping abruptly as benefits phase out. She would need to earn $70,000 to exceed the net income available at $30,000.

Angela Rachidi, Matt Weidinger, Joshua Bandoch, Nic Dunn, et al. American Enterprise Institute
Date Posted:

A non-working, non-disabled mother of two in North Carolina can collect $50k in benefits. Due to benefit phase-outs, she would have to earn $70k in market income to exceed her net income from earning $30k alongside $40k of benefits.

How much must a single mother earn to surpass benefit-level income?

Core argument: A simulated single mother with two children in North Carolina would need to earn $70,000 per year to reach a higher net income than earning $30,000 per year while keeping her full safety-net benefits.

Figure 3 simulates actual safety-net benefits a single mother with two children in North Carolina would receive based on different earnings scenarios. Notably, the mother in this example generally experiences a work incentive at earnings levels below $30,000 per year—that is, her net income grows even more than her earnings alone due to the way benefits phase in. This is primarily because the EITC and CTC—and to some extent SNAP—grow with additional earnings up to a certain point. However, this work incentive shifts to a disincentive as this mother reaches earnings levels at which benefits start to phase out. The top line of Figure 3 reflects net income (i.e., total benefits plus earnings less taxes) and shows that the combined effect of phasing out all of these benefits over a similar earnings distribution results in an abrupt drop in net income as the family starts to earn more than $30,000 per year. In North Carolina, a mother receiving this package of benefits would have to earn $70,000 per year from work to reach a higher net income than if she earned $30,000 per year from work and kept her full benefits. This is a substantial work disincentive.

Takeaways by Macro Roundup® AI

  1. A simulated single mother with two children in North Carolina would need to earn $70,000 per year to reach a higher net income than earning $30,000 per year while keeping her full safety-net benefits.
  2. Below $30,000 in annual earnings, the simulated North Carolina mother's net income grows by more than her earnings alone, primarily because the EITC, the Child Tax Credit, and to some extent SNAP phase in with additional earnings.
  3. The combined phase-out of these benefits above $30,000 in earnings produces an abrupt drop in the simulated family's net income, which the analysis characterizes as a substantial work disincentive.

Related Articles:

  • Mitigating Benefits Cliffs for Low-Income Families: District of Columbia Career Mobility Action Plan as a Case Study — The authors estimate that a hypothetical low-income family with children receives $68,686 in government support at an income of $11,000 but only $22,709 at $65,000, while its tax liability rises from $842 to $12,835. The lost assistance plus higher taxes fully offsets the $54,000 income gain.
  • “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.
  • Welfare Is What’s Eating the Budget — The U.S. redistributes 29.4% of its gross domestic product through transfers and taxes, a larger share than any developed country except France at 30.1%. Counting transfers as income and taxes as income lost and adjusting for household size, average households in the bottom, second, and middle income fifths have roughly equal incomes despite large differences in work effort.

AI Summary. Long-dated forward yields such as 10-year and 20-year forwards are near their highs even as the Federal Reserve cuts rates, with the gap between those forwards and 10-year yields widening, which the author reads as a worsening buyers' strike for longer-dated government debt. Italy, France, the UK, Japan and Germany all show elevated long-term forward yields.

Robin Brooks Robin Brooks Substack
Date Posted:

Citing high 10y10y and 10y20y forward yields across advanced economies, Brooks notes the failure of traditional safe havens – particularly German and Japanese bonds, suggesting the “early stages of a global debt crisis that’s building and intensifying.”

Are investors backing away from long-dated government debt worldwide?

Core argument: Federal Reserve rate cuts are not pulling down long-term yields: 10y10y and 10y20y forward yields sit near their highs, and the gap between both measures and the 10-year yield has widened.

Fed cuts aren’t pulling down long-term yields: if you look at the long end of the yield curve properly by stripping out front-end yields, things look very worrying. 10y10y and 10y20y forward yields are near their highs and the gap of both metrics with 10-year yield has grown. The buyers’ strike for longer-dated Treasury debt looks like it’s getting worse. There’s many idiosyncratic trouble spots: a key feature of the recent rise in long-term yields is that there’s many fiscally distressed countries that run into trouble at different points and for idiosyncratic reasons. Italy, France and the UK are all part of this dynamic and have very elevated 10y20y forward yields. Traditional safe havens are failing: in the past, Japan and Germany would have been safe harbors in this kind of environment, but these days they’re at the heart of the rise in long-term yields.

Takeaways by Macro Roundup® AI

  1. Federal Reserve rate cuts are not pulling down long-term yields: 10y10y and 10y20y forward yields sit near their highs, and the gap between both measures and the 10-year yield has widened.
  2. Italy, France and the UK all show very elevated 10y20y forward yields, part of a dynamic in which many fiscally distressed countries run into trouble at different points and for idiosyncratic reasons.
  3. Japan and Germany, which in the past would have served as safe harbors, are at the heart of the rise in long-term yields, while the buyers' strike for longer-dated Treasury debt appears to be worsening.

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.
  • The Race Between Asset Supply and Asset Demand — The authors estimate that demand for assets has outpaced supply by roughly 400% of GDP versus 100%, making rising asset demand the leading contributor to falling interest rates. They project that debt sustainability requires fiscal consolidation exceeding 10% of GDP, though debt could reach 250% of GDP without raising interest rates.
  • 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. France is reviving voluntary military service as a rite of passage for young people, starting with a 10-month program aimed at recruiting 3,000 people, mostly age 18 or 19, to supplement 200,000 active troops, scaling to 50,000 a year by 2035. In a "major crisis," service would become mandatory for people with certain skills if Parliament authorizes a draft.

Stacy Meichtry and Noemie Bisserbe Wall Street Journal
Date Posted:

The French government is resurrecting a framework for large-scale mobilization in order to prepare for a war with Russia “that many believe is only three to four years away.” The program will start with 3,000 18–19-year-old volunteers this summer.

Is Europe rebuilding voluntary military service to prepare for mass mobilization?

Core argument: French President Emmanuel Macron announced a 10-month military service starting next summer, recruiting 3,000 people largely aged 18 or 19 to supplement France's 200,000 active troops, with recruitment rising to 50,000 a year by 2035.

French President Emmanuel Macron is resurrecting the concept of military service as a rite of passage for young people, part of a broader push to put Europe on a war footing to counter an expansionist Russia. Macron and other European leaders are taking a gradual approach, laying the groundwork for mass mobilization with recruitment systems they can rapidly scale up in a moment of crisis. Macron said a new 10-month service would begin next summer with the goal of recruiting 3,000 people—largely age 18 or 19—to supplement the country’s 200,000 active troops. Recruitment would gradually increase to 50,000 a year by 2035. In the event of a “major crisis,” military service would become mandatory for people with certain skills, Macron said, if Parliament authorizes such a draft.

Takeaways by Macro Roundup® AI

  1. French President Emmanuel Macron announced a 10-month military service starting next summer, recruiting 3,000 people largely aged 18 or 19 to supplement France's 200,000 active troops, with recruitment rising to 50,000 a year by 2035.
  2. Macron said military service would become mandatory for people with certain skills in the event of a "major crisis," provided Parliament authorizes such a draft.
  3. Macron and other European leaders are taking a gradual approach to putting Europe on a war footing against an expansionist Russia, laying the groundwork for mass mobilization with recruitment systems they can rapidly scale up in a crisis.

Related Articles:

  • German Army Struggles to Get Gen Z Recruits ‘Ready for War’ — Germany's armed forces commissioner warned the country is not moving closer to its target of 203,000 active troops by 2031, as the military slightly shrank amid high dropout rates, with a quarter of new recruits leaving within six months. Conscientious objector applications reached 2,998, up from 200 in 2021.
  • The Intellectual Spoils of War? Defense RD, Productivity and International Spillovers — The authors estimate that a 10% increase in government-financed R&D, largely defense, is associated with a 4.3% rise in privately funded R&D across OECD countries, indicating "crowding in" rather than "crowding out." They also find international spillovers raise private R&D abroad, though the overall effect on US productivity growth is modest.
  • Germany Backs Donald Trump Goal For Nato To Spend 5% Of GDP On Defence — Germany has backed the US demand that NATO allies spend 5% of GDP on defence, up from the alliance's current 2% target. Berlin signalled it would meet the goal via the NATO secretary-general's proposal of 3.5% of GDP on hard military spending plus 1.5% on related areas such as infrastructure and cyber security.

AI Summary. Europe, at roughly 500m people and a $26tn economy with world-class aerospace, shipbuilding, pharmaceutical, vehicle and weapons manufacturers, has the material basis to be a military superpower. National militaries' preference for home-country suppliers has left subscale defense firms, and common procurement could raise output and lower unit costs.

Matt Klein The Overshoot
Date Posted:

Klein argues that better coordination and mobilization of current resources could meaningfully increase European military capacity. He suggests $200B in Norwegian windfall profits should be used to support broader European efforts against Russia.

Can common defense procurement turn Europe into a military superpower?

Core argument: Europe, defined as the EU plus Norway, Switzerland, and the U.K., has roughly 500 million people versus about 340 million in the U.S. and a $26 trillion economy versus China's $21 trillion; if material considerations were all that mattered, it would be a military superpower.

Europe [the European Union plus Norway, Switzerland, and the U.K.] has a far larger population than the U.S. (~500 million vs. ~340 million), and an economy far larger than China’s ($26 trillion vs. $21 trillion). It also has a large and sophisticated manufacturing sector, with world-beating producers in aerospace, shipbuilding, pharmaceuticals, machine tools, motor vehicles, and weapons. If material considerations were all that mattered, Europe would be a military superpower. The trick is to make sure that the additional spending translates to greater quantities, rather than higher prices. The challenge is that Europe’s national militaries have had a tendency to favor their home country’s producers, with the result that the continent is filled with subscale defense companies that are often slow and unproductive. Common defense procurement for a continental army should lead to higher output and lower costs—a few large companies handling large orders should have better unit economics than hundreds of artisanal manufacturers—but it would require Europe’s national defense elites to change their perspective.

Takeaways by Macro Roundup® AI

  1. Europe, defined as the EU plus Norway, Switzerland, and the U.K., has roughly 500 million people versus about 340 million in the U.S. and a $26 trillion economy versus China's $21 trillion; if material considerations were all that mattered, it would be a military superpower.
  2. Europe's manufacturing base includes world-beating producers in aerospace, shipbuilding, pharmaceuticals, machine tools, motor vehicles, and weapons, but national militaries' tendency to favor home-country producers has left the continent with subscale defense companies that are often slow and unproductive.
  3. Common defense procurement for a continental army should raise output and lower costs, since a few large companies handling large orders should have better unit economics than hundreds of artisanal manufacturers, though it would require Europe's national defense elites to change their perspective.

Related Articles:

  • Will Higher Defence Spending Boost The European Economy? — Defense spending typically has a fiscal multiplier below one, meaning each euro spent raises GDP by less, so it is not a short-term growth strategy. One estimate holds that extra military spending worth 1% of GDP could lift output up to 2% long term if concentrated on research and development.
  • Why Every Country Needs To Master The Electric Tech Stack — Drones are the foundation of hard power in the early 21st century, so a country unable to produce them domestically is at a disadvantage. As electric motors overtake combustion engines as the core technology that makes machines move, the same supply chains and production processes used for electronics can also produce cars, drones, robots, and appliances.
  • Behind NATO’s 2 Percent: Measuring the True Scope of Alliance Defense Investments and the NATO Defense Deficit — NATO's collective defense spending averaged 1.72% of GDP over roughly two and a half decades, below the alliance's agreed 2% threshold, leaving a cumulative shortfall the authors estimate at over $2tn that was not invested in force structure, modernization, and readiness. The authors argue closing the gap requires years of sustained investment beyond current commitments.

Friday, December 5, 2025

AI Summary. Completed fertility for US women aged 41–44 has been stable for more than two decades, with the large decline having occurred earlier; among those with at least one native-born parent it averaged 1.88 children versus 1.87. What changed is timing: 30-year-old women averaged 1.34 children versus 0.98.

Mike Konczal Mike Konczal Substack
Date Posted:

Btw 1980 and 2000, US completed fertility fell from > 3 children per woman to < 2. Today, the oldest millennials, at 44, have 1.92 children, the same number as the youngest boomers. Birth timing is delayed relative to 2000, but fertility has not fallen.

Has completed fertility fallen, or have women just delayed childbearing?

Core argument: The average number of children for a 30-year-old woman fell from 1.34 in 2000 to 0.98 in 2024, while completed fertility ended up at the same level, reflecting a change in the timing of births.

What has changed is the timing of births. Remember this is a cross-section based on the year we are observing. In 2000, a 30-year-old woman had, on average, 1.34 children. In 2024, that number had dropped to 0.98. The two cross-years ended up in the same place, but they follow very different paths to get there. Before you ask, is this all immigration? No. We can track nativity status in this data. For women 41 to 44 who have at least one native-born parent, the weighted average number of children was 1.88 in 2000 and 1.87 in 2024. Now completed fertility used to be higher than it is today. So when did the drop happen? We can look at the average number of births for women ages 41 to 44 in each CPS Fertility Supplement, going back every two years to 1976, as shown in Figure 2. The big drop happened some time ago. But the headline is how stable completed fertility has been for more than two decades.

Takeaways by Macro Roundup® AI

  1. The average number of children for a 30-year-old woman fell from 1.34 in 2000 to 0.98 in 2024, while completed fertility ended up at the same level, reflecting a change in the timing of births.
  2. Among women ages 41–44 with at least one native-born parent, the weighted average number of children was 1.88 in 2000 and 1.87 in 2024, indicating immigration does not account for the stability.
  3. CPS Fertility Supplement data for women ages 41–44, tracked every two years back to 1976, place the large decline in completed fertility well in the past, with the measure stable for more than two decades.

Related Articles:

  • The Growing Link Between Marriage, Fertility, and Partisanship — Among US women born 1975–1979 who have completed childbearing, conservatives average 2.1 children, moderates 1.8, and liberals 1.5; among those born 1985–1989 the figures are 2.1, 1.9, and 1.7. Birthrates and marriage rates are lower for all ideological groups than before 1975.
  • Is America’s Religious Decline Responsible for Falling Birthrates? — In the United States, falling birth rates have accompanied a decline in religious participation, with the share of Americans attending worship services weekly falling from 42% to 30% over 20 years, according to Gallup. Survey data show 68% of Americans in their mid-70s or older attended weekly services in childhood, versus 48% of those in their early 20s.
  • Depopulation Globally and in the Asia-Pacific: The Shape of Things to Come — Population aging and fertility below replacement levels are connected to a revolution in family structure in which families grow smaller, fewer people marry, and voluntary childlessness becomes common across countries. As a result, families become less able to bear the demands that may be placed on them.

AI Summary. A national survey found 56% of Americans believe life in America today is worse than 50 years ago, but income data conflict with this perception of long-run decline. The typical year-round male worker earned $74,000 in 2023 including benefits and employer taxes, 46% above 1973, while the typical woman's earnings rose 121%.

Scott Winship American Enterprise Institute
Date Posted:

Scott Winship notes American worker’ earnings are “essentially” at an all-time high. In real terms, a typical year-round male worker earns 46% more than in 1973, and his female peer earns 121% more.

Have American workers' incomes risen over the past fifty years?

Core argument: The typical year-round male worker earned $74,000 in 2023 including fringe benefits and employer taxes, 46% more than in 1973.

A national Pew survey conducted in April of this year found that 56% of Americans believe that “life in America today” is worse than it was “50 years ago for people like you.” However, these perceptions of long-run decline are at odds with the facts. The typical year-round male worker in 2023 made $74,000 including fringe benefits and employer taxes. That is 46% higher than it was in 1973. The typical woman working year-round makes 121% more than in 1973 — an increase from $28,000 to $61,000 in today’s dollars.

Takeaways by Macro Roundup® AI

  1. The typical year-round male worker earned $74,000 in 2023 including fringe benefits and employer taxes, 46% more than in 1973.
  2. The typical year-round female worker's pay rose 121%, from $28,000 in 1973 to $61,000 in today's dollars.
  3. A national Pew survey found 56% of Americans believe life in America today is worse than it was 50 years ago "for people like you," perceptions the author argues are at odds with the facts.

Related Articles:

  • Don’t Choose Your Own Adventure: Understanding Middle-Class Earnings Trends — Using a standard price index, US men's earnings were flat from 1973 to 1989 and rose 0.4% a year thereafter, while an alternative middle-class cost-of-living index shows 0.7% annual growth in both periods and a 40% total rise instead of 13%. The author attributes weak growth to 1970s stagflation and early-1980s recessions rather than trade, immigration, or income concentration.
  • The American Dream Is Not a Coin Flip, and Wages Have Not Stagnated — Using an alternative cost-of-living adjustment, the typical 40-year-old's pre-tax family income rose 52% between 1979 and 2019, or 73% adjusting for family size, versus 15% under the methods behind widely cited mobility estimates. Absolute mobility is down 20 percentage points since 1979 but stood at 72% in 2023.
  • Should We Believe the Economic Data or Americans’ “Lyin’” Eyes? The Answer Is Yes — Gallup polling finds that while roughly 80% of Americans say they are dissatisfied with the way things are going in the country, about 80% are satisfied with the way things are going in their own lives, including 90% satisfied with family life, 88% with housing, and 87% each with education and work.

AI Summary. Using data on President–Federal Reserve interactions, the author estimates that political pressure to ease monetary policy raises the price level strongly and persistently without boosting real activity, working through inflation expectations more than a typical easing. Such pressure occurred mainly in the 1970s and contributed to inflationary episodes.

Thomas Drechsel University of Maryland
Date Posted:

Drechsel studies “political pressure shocks” on monetary policy as in the Nixon-Burns interactions of 1971–1972. He finds that politically pressured drops in interest rates raises inflation but not output, highlighting the importance of Fed independence.

Does political pressure on the central bank raise prices without boosting output?

Core argument: The author estimates that political pressure on the Fed to ease, sustained for six months at half the intensity of Nixon's, raises the price level by about 7% over the following decade.

I exploit an increase in the number of President-Fed interactions that satisfies two criteria. First, these interactions arise mainly for reasons that are political, and are therefore plausibly unrelated to economic conditions. Second, monetary policy [actually] changes due to the political pressure. In his desire to be re-elected in1972, President Nixon pressured Fed Chair Arthur Burns to ease monetary policy in the fall of 1971, as reflected in a spike in interactions clearly visible in Figure 3. I exploit this narrative through restrictions on a structural vector autoregression that includes the President-Fed interaction data. I find that political pressure shocks mostly occurred in the 1970s, in the Nixon, Ford, and Carter administrations. I find that political pressure to ease monetary policy (i) increases the price level strongly and persistently, (ii) does not lead to positive effects on real economic activity, (iii) contributed to inflationary episodes outside of the Nixon era, and (iv) transmits differently from a typical monetary policy easing, by having a stronger effect on inflation expectations. Increasing political pressure by half as much as Nixon, for six months, raises the price level by about 7% over the following decade.

Takeaways by Macro Roundup® AI

  1. The author estimates that political pressure on the Fed to ease, sustained for six months at half the intensity of Nixon's, raises the price level by about 7% over the following decade.
  2. Using a structural vector autoregression that includes President-Fed interaction data, the author finds political pressure shocks to ease monetary policy raise the price level strongly and persistently without positive effects on real economic activity.
  3. The author finds political pressure shocks occurred mostly in the 1970s under the Nixon, Ford, and Carter administrations, contributed to inflationary episodes outside the Nixon era, and transmitted with a stronger effect on inflation expectations than a typical monetary policy easing.

Related Articles:

  • The Global Debt Crisis Builds — Long-dated forward yields such as 10-year and 20-year forwards are near their highs even as the Federal Reserve cuts rates, with the gap between those forwards and 10-year yields widening, which the author reads as a worsening buyers' strike for longer-dated government debt. Italy, France, the UK, Japan and Germany all show elevated long-term forward yields.
  • 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.
  • 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.

AI Summary. New York City's population has historically balanced natural growth and international inflows against domestic outflows, but outflows have come to dominate, leaving the city shrinking at its fastest pace since the 1970s. Its contraction of more than 3% is twice that of Philadelphia, the next-fastest-shrinking large US city.

Aziz Sunderji Home Economics
Date Posted:

New York City’s population is shrinking due to domestic out-migration. Aziz Sunderji finds NYC’s population declined by 395,000 btw 2014 and 2024. As immigration slows, the population decline may accelerate.

Why is New York City's population shrinking faster than other large cities?

Core argument: New York City's population fell more than 3% between April 2020 and July 2024, twice the rate of Philadelphia, the next-fastest-shrinking city, while Los Angeles lost only half a percent.

New York City’s population has stagnated since the 1970s, but outright declined through the 2010s. The city’s population has historically been a balance between natural growth and international inflows offsetting domestic outflows. In recent years outflows have dominated. Looking through the recent wobbles (both down and up) to the longer term trends, New York appears to be shrinking at the fastest pace since the 1970s. Five of the country’s ten largest cities have shrunk since the Covid pandemic began. But the pace of New York’s contraction—more than 3% between April 2020 and July 2024—is twice that of the next-fastest-shrinking city, Philadelphia. Los Angeles, New York’s closest peer, lost only half a percent of its population over the same period. Although New York has recently returned to growth on the back of surging international in-migration, about half of this is asylum seekers and humanitarian flows—these are different in nature than highly skilled immigrants, in terms of contribution to growth and tax base. Moreover, these flows are collapsing.

Takeaways by Macro Roundup® AI

  1. New York City's population fell more than 3% between April 2020 and July 2024, twice the rate of Philadelphia, the next-fastest-shrinking city, while Los Angeles lost only half a percent.
  2. Five of the ten largest U.S. cities have shrunk since the Covid pandemic began, and looking past short-term swings to longer-term trends, New York appears to be shrinking at its fastest pace since the 1970s.
  3. New York's return to growth rests on surging international in-migration, about half of it asylum seekers and humanitarian flows that differ from highly skilled immigration in contribution to growth and the tax base, and those flows are collapsing.

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