Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…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


Wednesday, February 5, 2025

AI Summary. The Budget Lab estimates that a 10% tariff on Chinese goods raises the overall US price level by just over 0.1%, equivalent to an average decline in disposable income of $223 per household. The policy is projected to raise roughly $400bn over 10 years, less after accounting for a 0.1% lower level of GDP.

Ernie Tedeschi Yale University
Date Posted:
Is Database:
Database

.@ernietedeschi estimates that the 10% China tariffs would raise prices by 0.1%, costing the average household $223/year. The policy is expected to raise $360 billion net of a projected 0.1% decline in GDP.

How much do tariffs on Chinese goods cost households and raise?

Core argument: The Budget Lab estimates the proposed 10% tariffs on China raise the overall price level by just over 0.1%, equivalent to an average decline in disposable income of $223 per household.

The Budget Lab estimates that the 10% China tariffs raise the overall price level by just over 0.1%, which is the equivalent of a decline in disposable income of $223 per household on average. The policy raises roughly $400 billion over 10 years, but less when the -0.1% lower level of GDP that results is taken into account.

Takeaways by Macro Roundup® AI

  1. The Budget Lab estimates the proposed 10% tariffs on China raise the overall price level by just over 0.1%, equivalent to an average decline in disposable income of $223 per household.
  2. The Budget Lab estimates the China tariffs raise roughly $400 billion over 10 years, though less once the resulting 0.1% lower level of GDP is taken into account.

Related Articles:

  • What Trump’s Trade War Would Mean, in Nine Charts — Imports and exports make up about a quarter of U.S. gross domestic product, less than in Germany, Japan, and the United Kingdom, and U.S. imports come from a fairly broad set of countries. Trade accounts for roughly 70% of Canadian and Mexican output, giving the U.S. significant leverage in negotiations with both.
  • A User’s Guide to Restructuring the Global Trading System — During the 2018–2019 U.S.–China trade war, the effective tariff rate on Chinese imports rose 17.9 percentage points while the renminbi depreciated 13.7% against the dollar, leaving after-tariff import prices in dollars up just 4.1%. The author argues this currency offset of more than three-fourths of the tariff explains why inflation pressure was negligible.

AI Summary. China is the main trade partner for most countries in the world, a position the US held in 2000. Canada, China, and Mexico together account for 43% of US imports and 40% of US exports, and 41% of S&P 500 company revenue comes from abroad.

Torsten Sløk, Rajvi Shah, and Shruti Galwankar Apollo
Date Posted:

Torsten Sløk notes that 41% of the S&P 500’s revenue comes from abroad.

Has China replaced the US as most countries' main trade partner?

Core argument: Canada, China, and Mexico together account for 43% of US imports and 40% of US exports.

In 2000, the US was the main trade partner for most countries in the world. In 2020, China is the main trade partner for most countries in the world. Canada, China and Mexico make up 43% of US imports and 40% of US exports. 41% of revenue in S&P 500 companies comes from abroad.

Takeaways by Macro Roundup® AI

  1. Canada, China, and Mexico together account for 43% of US imports and 40% of US exports.
  2. The US was the main trade partner for most countries in the world in 2000, while China holds that position for most countries in 2020.
  3. Foreign markets generate 41% of revenue for S&P 500 companies.

Related Articles:

  • What Trump’s Trade War Would Mean, in Nine Charts — Imports and exports make up about a quarter of U.S. gross domestic product, less than in Germany, Japan, and the United Kingdom, and U.S. imports come from a fairly broad set of countries. Trade accounts for roughly 70% of Canadian and Mexican output, giving the U.S. significant leverage in negotiations with both.
  • A User’s Guide to Restructuring the Global Trading System — During the 2018–2019 U.S.–China trade war, the effective tariff rate on Chinese imports rose 17.9 percentage points while the renminbi depreciated 13.7% against the dollar, leaving after-tariff import prices in dollars up just 4.1%. The author argues this currency offset of more than three-fourths of the tariff explains why inflation pressure was negligible.
  • China Hits Back Against Trump’s Tariffs With Targeted Actions — China responded to new US tariffs with a 15% levy on less than $5bn of US energy imports, a 10% fee on American oil and agricultural equipment, an antitrust investigation into Google, and export controls on tungsten and other critical metals used in electronics, aviation, and defense.

AI Summary. Comparing US counties that won large manufacturing plants with runner-up counties considered for the same plants, the author estimates that plant openings raised manufacturing and total employment but left average manufacturing pay and overall average pay unchanged, suggesting industrial policy's core goals may conflict with helping left-behind workers.

Andrew Garin National Bureau of Economic Research
Date Posted:

.@andy_garin notes that WWII-era government plants boosted earnings for disadvantaged workers, but “million-dollar plant” policies in the 1980s failed to lift wages, highlighting limits of approaches that lack upskilling of “left-behind” workers.

Do new manufacturing plants raise local employment without raising pay?

Core argument: Using the event study specification from a replication of Greenstone et al., the author estimates that manufacturing plant openings raised both manufacturing employment and total employment in treated counties, while average manufacturing pay and average pay overall did not change.

Arguably, that alignment was mostly coincidental in the case of WWII and not a consequence of explicit distributional objectives. In many other cases, the core objectives of industrial policy may be in tension with hopes of making meaningful improvements in the outcomes of left-behind workers. Greenstone et al. compare regions where large million dollar plants were sited during the 1980s and 1990s to the runner-up regions that were also under serious consideration for each plant. While the original study finds significant impacts of plant construction on productivity at neighboring establishments, the incidence on the local labor market is less clear. I follow the event study specification from a replication of Greenstone et al. to estimate the effects of manufacturing plant openings on county-level employment and pay. Whereas both manufacturing employment and total employment expanded in treated counties, average manufacturing pay and average pay more generally did not change.

Takeaways by Macro Roundup® AI

  1. Using the event study specification from a replication of Greenstone et al., the author estimates that manufacturing plant openings raised both manufacturing employment and total employment in treated counties, while average manufacturing pay and average pay overall did not change.
  2. Greenstone et al. compare regions where large "million dollar plants" were sited during the 1980s and 1990s with runner-up regions also under serious consideration, finding significant impacts of plant construction on productivity at neighboring establishments but less clear incidence on the local labor market.
  3. The author argues that any alignment between industrial policy and gains for left-behind workers was mostly coincidental in the WWII case rather than a product of explicit distributional objectives, and that industrial policy's core objectives may conflict with improving left-behind workers' outcomes.

Related Articles:

AI Summary. A budget package allowing up to $5.5tn of net deficit increases, largely through tax cuts, is estimated to add $6.5tn to the debt with interest over ten years, pushing debt from 100% of GDP to 133%. That 33 percentage-point rise is nearly double the 18-point increase projected under current law.

CRFB Staff Committee for a Responsible Federal Budget
Date Posted:

The House preliminary reconciliation bill would double the growth of the US debt-to-GDP ratio, leaving it at 133% of GDP in 2035 relative to the current 118% baseline. @MarcGoldwein

How much would a $5.5 trillion budget package raise debt-to-GDP?

Core argument: A budget resolution allowing up to $5.5 trillion of net deficit increases, largely through tax cuts, is estimated to add $6.5 trillion to the debt with interest by FY2035, pushing debt from 100% of GDP at the end of this year to 133% by 2035.

According to press reports, House lawmakers were recently considering a budget resolution with reconciliation instructions to allow up to $5.5 trillion of net deficit increases, largely through tax cuts. With interest, we estimate it would add $6.5 trillion to the debt by Fiscal Year (FY) 2035. As a result, debt would rise from 100% of Gross Domestic Product (GDP) at the end of this year to 133 percent by 2035. This 33pp increase is nearly double the current projected growth of 18pp under current law. In nominal dollars, the government is currently projected to borrow roughly $22 trillion over the next ten years. A $5.5 trillion reconciliation package would increase that by 30 percent, with debt nearing $59 trillion by 2035. Although these figures do not include potential dynamic effects, that feedback is likely to be modest – no more than $600 billion based on the most generous outside estimate, and possibly even deficit increasing.

Takeaways by Macro Roundup® AI

  1. A budget resolution allowing up to $5.5 trillion of net deficit increases, largely through tax cuts, is estimated to add $6.5 trillion to the debt with interest by FY2035, pushing debt from 100% of GDP at the end of this year to 133% by 2035.
  2. That projected 33-percentage-point rise in debt-to-GDP is nearly double the 18-percentage-point increase projected under current law, and would raise projected ten-year borrowing of roughly $22 trillion by 30%, with debt nearing $59 trillion by 2035.
  3. Dynamic economic feedback from a $5.5 trillion reconciliation package is likely to be modest — no more than $600 billion based on the most generous outside estimate, and possibly deficit increasing.

Related Articles:

  • The Budget and Economic Outlook: 2025 to 2035 — The Congressional Budget Office projects the federal deficit will grow from $1.9tn (6.2% of GDP) to $2.7tn by 2035, well above the 3.8% of GDP average of the past 50 years. Outlays are projected to rise to 24.4% of GDP, driven by growth in Social Security and Medicare spending and rising net interest costs, while revenues reach 18.3%.
  • Robust Fiscal Stabilization — The authors find that Congress reduced deficits in response to rising projected deficits from 1984 to 2003 but that this year-to-year response disappeared over 2004-2024. They estimate that holding the debt ratio below 250% with 95% probability would require gradual deficit reduction averaging 0.5%-1.2% of GDP over the next decade.
  • Long Rates Are Too High — A simple model of the relationship between long-term interest rates and Federal Reserve policy expectations shows 10-year rates sitting 40 basis points above what those expectations would predict, consistent with increases in term premium measures from the New York and San Francisco Federal Reserve Banks. Markets worry this extra premium reflects fears about fiscal sustainability.

AI Summary. Klarna says artificial intelligence saves it about $10m annually in marketing, cuts standard contract drafting by in-house lawyers from an hour to roughly 10 minutes, and powers a chatbot doing the work of 700 customer service agents while resolving cases about nine minutes faster. The company says headcount fell from about 5,000 to under 4,000.

Noam Scheiber New York Times
Date Posted:

The CEO of Swedish payments company Klarna expects that AI-driven automation will eventually reduce headcount from 5,000 in 2023 to 2,000. The company’s chatbot resolves service cases 9 minutes faster than human customer service agents.

How much can AI cut costs and headcount at a company?

Core argument: Klarna says it has saved the equivalent of $10 million annually by using A.I. for marketing, partly by reducing its reliance on human artists to generate advertising images.

According to Klarna, the company has saved the equivalent of $10 million annually using A.I. for its marketing needs, partly by reducing its reliance on human artists to generate images for advertising. The company said that using A.I. tools had cut back on the time that its in-house lawyers spend generating standard contracts — to about 10 minutes from an hour — and that its communications staff uses the technology to classify press coverage as positive or negative. Klarna has said that the company’s chatbot does the work of 700 customer service agents and that the bot resolves cases an average of nine minutes faster than humans (under two minutes versus 11). Sebastian Siemiatkowski, the chief executive of Klarna said that A.I. had allowed his company to largely stop hiring entirely as of September 2023, which he said reduced its overall headcount to under 4,000 from about 5,000. He said he expected Klarna’s work force to eventually fall to about 2,000 as a result of its A.I. adoption.

Takeaways by Macro Roundup® AI

  1. Klarna says it has saved the equivalent of $10 million annually by using A.I. for marketing, partly by reducing its reliance on human artists to generate advertising images.
  2. Klarna says its chatbot does the work of 700 customer service agents and resolves cases an average of nine minutes faster than humans, in under two minutes versus 11.
  3. Chief executive Sebastian Siemiatkowski said A.I. allowed Klarna to largely stop hiring as of September 2023, reducing headcount to under 4,000 from about 5,000, and he expects the work force to eventually fall to about 2,000.

Related Articles:

  • Technological Disruption in the Labor Market — The authors measure US labor market structure since 1880 and find 1990–2017 less disruptive than any earlier period, because past changes from general-purpose technologies like steam and electricity were so profound. They identify four recent signs of accelerating change, including a 50%+ rise in science and technology employment share since 2010.
  • Use of Artificial Intelligence and Productivity: Evidence from Firm and Worker Surveys — A survey of Japanese firms and workers finds that firms using artificial intelligence have higher productivity, mean wages, and expected medium-term growth, and that more-educated firms and workers are more likely to use it. Workers using artificial intelligence report their own productivity rose by about 20% on average.
  • The Rapid Adoption of Generative AI — A nationally representative U.S. survey found 39% of people aged 18-64 used generative AI, with more than 24% of workers using it in the prior week and nearly one in nine using it every workday. The authors estimate 0.5-3.5% of U.S. work hours are currently assisted by generative AI.

AI Summary. An Economist/YouGov poll found 45% favor ending diversity, equity, and inclusion programs in schools and government while 40% oppose, with differences by gender, race, party, and age. A Reuters/Ipsos poll found 44% favor closing all federal diversity offices and firing the employees working on them, with 51% opposed.

Karlyn Bowman American Enterprise Institute
Date Posted:
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Karlyn Bowman cites a new Economist/YouGov survey finding that 45% of Americans favor ending DEI programs in schools and government and 40% oppose ending the programs. A Reuters poll showed 44% in favor, 51% opposed.

Do Americans support ending diversity, equity, and inclusion programs?

Core argument: An Economist/YouGov poll found 45% favor ending diversity, equity, and inclusion programs in schools and government, with 40% opposed, alongside deep gender, racial, and partisan differences.

A new Economist/YouGov poll found 45% in favor of ending diversity, equity, and inclusion programs (DEI) in school and government with 40% opposed. There were deep gender, racial, and partisan differences. Among age groups, only the youngest one opposed ending the programs, by a narrow 39% to 37% percent. A new Reuters/Ipsos poll found a similar 44% in favor of closing all federal government DEI offices and firing federal employees working on the issue, with 51% opposed.

Takeaways by Macro Roundup® AI

  1. An Economist/YouGov poll found 45% favor ending diversity, equity, and inclusion programs in schools and government, with 40% opposed, alongside deep gender, racial, and partisan differences.
  2. Among age groups in the Economist/YouGov poll, only the youngest opposed ending DEI programs, by a narrow 39% to 37%.
  3. A Reuters/Ipsos poll found 44% favor closing all federal government DEI offices and firing federal employees working on the issue, with 51% opposed.

Related Articles:

AI Summary. MIT chemists have developed a generative artificial intelligence model, ChromoGen, that predicts thousands of 3D genome structures in about 20 minutes on a single graphics processor, compared with months of laboratory experiments for a few dozen structures. The AI-generated structures matched experimentally determined conformations while capturing the diversity of possible 3D arrangements.

Anne Trafton MIT
Date Posted:

MIT chemists have developed a generative AI method to predict 3D genome structures in minutes rather than months, potentially advancing the understanding of gene expression and cellular functions.

Can generative AI predict 3D genome structures faster than experiments?

Core argument: MIT chemists' ChromoGen model generates 1,000 3D genome structures for a given region in 20 minutes on a single GPU, compared with roughly six months of experiments to obtain a few dozen structures in a cell type, according to graduate student Greg Schuette.

MIT chemists have come up with a new way to determine 3D genome structures, using generative artificial intelligence. Their technique can predict thousands of structures in just minutes “Whereas you might spend six months running experiments to get a few dozen structures in a given cell type, you can generate a thousand structures in a particular region with our model in 20 minutes on just one GPU,’ says graduate student Greg Schuette.The ChromoGen model combines a deep learning component that analyzes DNA sequences and chromatin accessibility data with a generative AI component trained on over 11 million chromatin conformations from Dip-C experiments. Researchers found the AI-generated structures matched experimentally determined conformations while capturing the inherent diversity of possible 3D arrangements. The team has made the model publicly available to explore mutations’ structural impacts and other genomic mysteries.”

Takeaways by Macro Roundup® AI

  1. MIT chemists' ChromoGen model generates 1,000 3D genome structures for a given region in 20 minutes on a single GPU, compared with roughly six months of experiments to obtain a few dozen structures in a cell type, according to graduate student Greg Schuette.
  2. ChromoGen pairs a deep learning component analyzing DNA sequences and chromatin accessibility data with a generative AI component trained on over 11 million chromatin conformations from Dip-C experiments.
  3. The MIT researchers found ChromoGen's AI-generated structures matched experimentally determined conformations while capturing the diversity of possible 3D arrangements, and they have made the model publicly available to explore mutations' structural impacts.

Related Articles:

  • AI Protein-Prediction Tool AlphaFold3 Is Now More Open — DeepMind's AlphaFold3, which can model proteins together with other molecules, was initially released only through a web server that limited predictions, drawing criticism from scientists that withholding the code and model weights undermined reproducibility. The code is now downloadable for non-commercial use, with training weights available to academics on request.
  • AlphaProteo Generates Novel Proteins for Biology and Health Research — AlphaProteo, an AI system trained on protein structure data, generates novel protein binders for target molecules, including the first successful AI-designed binder for VEGF-A, a protein associated with cancer and diabetes complications. Across seven tested targets it achieved higher experimental success rates and 3x to 300x better binding affinities than the best existing methods.
  • Accurate Structure Prediction of Biomolecular Interactions With AlphaFold 3 — AlphaFold 3, a single deep learning model with a diffusion-based architecture, jointly predicts the structures of complexes containing proteins, nucleic acids, small molecules, ions, and modified residues. The authors report accuracy exceeding specialised tools for protein-ligand docking, protein-nucleic acid interactions, and antibody-antigen prediction.

Thursday, February 6, 2025

AI Summary. Estimates of workplace AI adoption vary widely with survey design: the U.S. Census Bureau's biweekly Business Trends and Outlook Survey puts firm-level adoption at 5%, while employment-weighted firm surveys and individual worker surveys range from about 20% to 40%. All available surveys show adoption growing rapidly.

Leland Crane, Michael Green, and Paul Soto Federal Reserve Board
Date Posted:

Crane et al find that existing studies of AI adoption by firms and workers show that between 20-40% of workers are using AI in the workplace, with much higher rates in occupations like computer programming. All surveys suggest rapid growth in adoption.

Why do estimates of workplace AI adoption vary so widely?

Core argument: The U.S. Census Bureau's Business Trends and Outlook Survey, conducted every two weeks, puts firm-level AI adoption at 5 percent, below other surveys, with employment weighting and question phrasing closing much of the gap.

Firm-level adoption may be measured as quite low or fairly high depending on the details of the question asked and the weighting used. Notably, only a few of these surveys were conducted on a recurring basis. A standout example is the top-line U.S. Census Bureau's Business Trends and Outlook Survey (BTOS), which is conducted every two weeks, and shows a number of 5 percent, much lower than other surveys. Employment weighting and the phrasing of the question closes much of the gap. Treating the other firm-level surveys as approximately employment-weighted, estimates of AI adoption range from about 20% to 40%. Individual level surveys of AI use at work find a similar range of adoption rates. Similar levels of individual AI adoption and employment-weighted firm AI adoption can be mutually consistent if some workers are using AI at work without the knowledge of their managers. Regardless of measured AI adoption levels, all available surveys show adoption growing rapidly.

Takeaways by Macro Roundup® AI

  1. The U.S. Census Bureau's Business Trends and Outlook Survey, conducted every two weeks, puts firm-level AI adoption at 5 percent, below other surveys, with employment weighting and question phrasing closing much of the gap.
  2. Treating other firm-level surveys as approximately employment-weighted places AI adoption at roughly 20 to 40 percent, a range similar to that found in individual-level surveys of AI use at work.
  3. Similar rates of individual AI use and employment-weighted firm adoption can be mutually consistent if some workers use AI at work without their managers' knowledge, and all available surveys show adoption growing rapidly.

Related Articles:

  • The Rapid Adoption of Generative AI — A nationally representative U.S. survey found 39% of people aged 18-64 used generative AI, with more than 24% of workers using it in the prior week and nearly one in nine using it every workday. The authors estimate 0.5-3.5% of U.S. work hours are currently assisted by generative AI.
  • Technological Disruption in the Labor Market — The authors measure US labor market structure since 1880 and find 1990–2017 less disruptive than any earlier period, because past changes from general-purpose technologies like steam and electricity were so profound. They identify four recent signs of accelerating change, including a 50%+ rise in science and technology employment share since 2010.
  • A Data-Driven Case That AI Has Already Changed The U.S. Labor Market — Retail employment began declining in the early 2010s after holding steady for more than two decades, coinciding with heavy big tech investment in deep learning and the commercial adoption of AI-directed warehouse robots and predictive pricing and inventory tools. The author argues this circumstantial evidence suggests AI has already affected the US labor market, but does not constitute proof.

AI Summary. US student test scores peaked in the early 2010s; from that peak to the pandemic, scores fell for students at the 10th and 25th percentiles while rising slightly at the 75th and 90th. After the pandemic, scores fell across all percentile groups, with much larger declines among lower-performing students.

Nat Malkus American Enterprise Institute
Date Posted:

.@natmalkus notes the decline in US fourth-grade math scores since 2013 has been driven by large declines at the bottom of the distribution, while the scores of top 10% performers have been relatively stable.

Are declines in US student test scores concentrated among lower-performing students?

Core argument: US student test scores across numerous assessments peaked in the early 2010s, and indexing each percentile group's score to its 2013 peak shrinks the figure's scale from 100 to 30 points.

Student test scores across numerous assessments peaked in the early 2010s. In Figure 3, Panel B, I show how percentile scores change from their peak in 2013. Subtracting the peak 2013 score for each group from that group’s score in a given year makes the 2013 score for each group equal to zero and shrinks the figure’s scale markedly, from 100 to 30 points. Panel B makes the relative changes within percentile groups come into sharp relief: between 2013 and the pandemic, scores for the 10th and 25th percentiles fell, while those for the 75th and 90th percentiles rose slightly. After the pandemic, scores fell across the board, but much more for students in the lower percentiles.

Takeaways by Macro Roundup® AI

  1. US student test scores across numerous assessments peaked in the early 2010s, and indexing each percentile group's score to its 2013 peak shrinks the figure's scale from 100 to 30 points.
  2. Between 2013 and the pandemic, scores for students at the 10th and 25th percentiles fell while scores at the 75th and 90th percentiles rose slightly.
  3. After the pandemic, US student scores fell across all percentile groups, with much larger declines for students in the lower percentiles.

Related Articles:

  • Do Adults Have the Skills They Need to Thrive in a Changing World? — An international assessment of adult skills describes numeracy proficiency levels ranging from counting objects and adding small whole numbers at the lowest level, to extracting information from tables and graphs and performing basic arithmetic with money and percentages at Level 1, up to analysing complex mathematical information and critically evaluating whether data support a claim at Level 5.
  • TIMSS Shows the Bottom Is Falling Out for US Test Scores — US math scores on the international Trends in Mathematics and Science Study fell 18 points for fourth graders and 27 points for eighth graders, on a scale where about 30 points equates to a year of learning. Declines were concentrated among the lowest-performing students, with fourth-grade scores above the 75th percentile barely moving.
  • 2024 SAT Data Drop — Race gaps in SAT scores are consistent across years, with most differences within the range expected from sampling error; the exceptions are Amerindian scores falling and Asian scores rising relative to White scores. The author attributes those shifts to changes in who selects into SAT test-taking rather than genuine population changes.

AI Summary. The US Treasury Secretary said the administration's effort to lower borrowing costs targets 10-year Treasury yields rather than the Federal Reserve's short-term benchmark rate, arguing that spending cuts, a smaller government, and lower energy prices can deliver non-inflationary growth. The Treasury maintained its guidance to keep sales of longer-term debt unchanged.

Viktoria Dendrinou Bloomberg
Date Posted:

Scott Bessent reported that he and President Trump are “focused on the 10-year Treasury [yield].” When asked if Trump wants lower rates, Bessent noted, “[Trump] is not calling for the Fed to lower rates.”

Can spending cuts and lower energy prices bring down long-term yields?

Core argument: Treasury Secretary Scott Bessent said the Trump administration's focus for lowering borrowing costs is the 10-year Treasury yield rather than the Federal Reserve's benchmark short-term rate.

Treasury Secretary Scott Bessent said the Trump administration’s focus with regard to bringing down borrowing costs is 10-year Treasury yields, rather than the Federal Reserve’s benchmark short-term interest rate. “The bond market is recognizing that” under Trump “energy prices will be lower and we can have non-inflationary growth,” Bessent said of the drop in yields in recent weeks. “We cut the spending, we cut the size of government, we get more efficiency in government. And we’re going to go into a good interest-rate cycle. ”Earlier, the US Treasury maintained its guidance on keeping sales of longer-term debt unchanged well into 2025, despite Bessent having criticized the issuance strategy of his predecessor before he was picked for the job.

Takeaways by Macro Roundup® AI

  1. Treasury Secretary Scott Bessent said the Trump administration's focus for lowering borrowing costs is the 10-year Treasury yield rather than the Federal Reserve's benchmark short-term rate.
  2. Bessent attributed the recent drop in yields to the bond market recognizing that energy prices will be lower under Trump and that non-inflationary growth is possible, pointing to cuts in spending and the size of government.
  3. The US Treasury maintained its guidance to keep sales of longer-term debt unchanged well into 2025, despite Bessent having criticized his predecessor's issuance strategy before being picked for the job.

Related Articles:

  • 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.
  • ATI: Activist Treasury Issuance and the Tug-of-War Over Monetary Policy — The authors argue that by shifting its debt issuance toward shorter maturities, the US Treasury is managing financial conditions in a way that takes on core Federal Reserve functions, a practice they call "activist Treasury issuance." They estimate it has lowered 10-year yields by about 0.25 percentage points, comparable to a one-point cut in the Federal Reserve's policy rate.
  • Resilience Redux in the US Treasury Market — The authors argue that large, persistent US federal deficits and limited dealer balance-sheet flexibility will cause outstanding Treasury debt to grow rapidly relative to the market's capacity to intermediate trades, absent significant changes in market structure. They contend broad central clearing, all-to-all trading, real-time post-trade reporting, capital-regulation changes, and transparent official purchase programs could strengthen market capacity and resilience.

AI Summary. Analysts estimate that enacting $5.5tn of unoffset tax cuts and spending would raise federal interest costs by about $1.3tn over a decade, lifting annual net interest payments to $2tn, or 4.7% of GDP, by 2035 — above the prior record of 3.2% — and interest as a share of revenue to 27%.

CRFB Staff Committee for a Responsible Federal Budget
Date Posted:
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The House preliminary reconciliation bill would allow up to $5.5T of net primary deficit. @MarcGoldwein estimates that if passed, the bill would increase interest costs by ~ $1.3T over the decade, rising to $2T or 4.7% of GDP by 2035.

How much would unoffset tax cuts raise federal interest costs?

Core argument: The authors estimate that $5.5 trillion of unoffset new and extended tax cuts and spending would raise federal interest costs by about $1.3 trillion over the next decade, exceeding $250 billion per year by 2035.

We estimate that passing an additional $5.5 trillion of new and extended tax cuts and spending without offsets would: boost interest costs by about $1.3T over the next decade, exceeding $250 billion per year by 2035. Increase annual federal net interest payments to $2T or 4.7% of GDP by 2035, far above the previous record of 3.2%. Boost the interest-to-revenue ratio from 9% back in 2021 and 18% today to 27% by 2035 (compared to 22% under current law). Increase the risk of a debt spiral by pushing up long-term interest rates (R) and potentially slowing the long-term growth rate (G).

Takeaways by Macro Roundup® AI

  1. The authors estimate that $5.5 trillion of unoffset new and extended tax cuts and spending would raise federal interest costs by about $1.3 trillion over the next decade, exceeding $250 billion per year by 2035.
  2. Annual federal net interest payments would reach $2 trillion, or 4.7% of GDP, by 2035 under the $5.5 trillion package, above the previous record of 3.2%, according to the authors' estimates.
  3. The interest-to-revenue ratio would climb from 9% in 2021 and 18% today to 27% by 2035 under the package, compared with 22% under current law, with the authors warning of a heightened debt-spiral risk as long-term interest rates rise and growth potentially slows.

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AI Summary. Asteroid 2024 YR4, detected by a NASA-funded network of near-Earth object telescopes, is estimated by the European Space Agency to be between 130 and 330 feet long, a range derived from the sunlight it reflects because its surface reflectivity is unknown. A more precise radar measurement will be possible when it makes another safe close pass by Earth.

Robin George Andrews New York Times
Date Posted:

A newly discovered asteroid, estimated at 130-330 ft. long, has a 2.3% chance of hitting Earth in 2032 according to NASA. Last year NASA’s Double Asteroid Redirection Test (DART) changed the orbit of a large asteroid in a defense experiment..

How precisely can astronomers measure a newly detected asteroid's size?

Core argument: Asteroid 2024 YR4 measures between 130 and 330 feet long, according to the European Space Agency's Near-Earth Object Coordination Centre, a range derived from the sunlight it reflects because its surface reflectivity is unknown.

Asteroid 2024 YR4 was identified by the Asteroid Terrestrial-impact Last Alert System four telescopes around the world that hunt near-Earth objects and are funded by NASA. Its telescope in Chile found 2024 YR4 on Dec. 27, just two days after a close approach to Earth. It’s now speeding away from the planet and getting fainter by the day. According to the European Space Agency’s Near-Earth Object Coordination Centre, it is between 130 and 330 feet long. This size range is based on the amount of sunlight it is reflecting. Without knowing exactly how reflective 2024 YR4’s surface is, only a range of sizes can be given. A more accurate estimate could be made using radar, but that won’t be possible until the asteroid makes another close, but perfectly safe, pass by Earth on Dec. 17, 2028. A 130-foot asteroid is comparable to the Tunguska impactor, a meteor that exploded over a remote patch of Siberia in 1908 and decimated an 800-square-mile forest.

Takeaways by Macro Roundup® AI

  1. Asteroid 2024 YR4 measures between 130 and 330 feet long, according to the European Space Agency's Near-Earth Object Coordination Centre, a range derived from the sunlight it reflects because its surface reflectivity is unknown.
  2. The NASA-funded Asteroid Terrestrial-impact Last Alert System's telescope in Chile found 2024 YR4 on Dec. 27, two days after the asteroid's close approach to Earth, and it is now speeding away and growing fainter.
  3. A more accurate size estimate of 2024 YR4 using radar must wait until the asteroid makes another close but safe pass by Earth on Dec. 17, 2028.

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