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


Friday, November 8, 2019

AI Summary. The U.S. share of the Global Top 100 companies by market value rose from 45% in 2009 to 63% in 2019, driven by growth in the U.S. technology sector. Over the same period European firms' combined market value fell from nearly $4tn to $3.2tn, with their Top 100 count dropping from 30 to 20.

Statista Statista
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U.S. companies now account for 63% of the Global Top 100 firms, driven by the growth of the U.S. tech sector. Microsoft surpassed Apple in market cap, reaching $905bn in March 2019.

Are U.S. companies pulling ahead of other regions in market value?

Core argument: U.S. companies' share of the Global Top 100 firms by market cap rose from 45% in 2009 to 63% in 2019, driven by growth in the U.S. tech sector.

In 2009, U.S. companies accounted for 45% of the Global Top 100 firms, but by 2019, this figure rose to 63%, driven by the robust growth of the U.S. tech sector. Notably, Microsoft surpassed Apple in market cap, reaching $905bn in March 2019, largely due to its thriving cloud business. In contrast, European companies saw a decline in market cap from nearly $4tn in 2014 to $3.2tn in 2019, with their representation in the Global Top 100 dropping from 30 to 20 firms. Meanwhile, China's market cap has grown to match Europe's, although it experienced a 5% year-over-year decline due to the U.S.-China trade war. This data underscores the dominance of U.S. firms in the global market, highlighting significant regional shifts in economic power over the past decade.

Takeaways by Macro Roundup® AI

  1. U.S. companies' share of the Global Top 100 firms by market cap rose from 45% in 2009 to 63% in 2019, driven by growth in the U.S. tech sector.
  2. European companies' market cap fell from nearly $4tn in 2014 to $3.2tn in 2019, with their representation in the Global Top 100 dropping from 30 firms to 20.
  3. Microsoft surpassed Apple in market cap, reaching $905bn in March 2019, largely on its cloud business, while China's market cap matched Europe's despite a 5% year-over-year decline attributed to the U.S.-China trade war.

"Market Cap for U.S. Companies Outpaces Other Regions," Statista, August 30, 2019, https://www.statista.com/chart/19182/market-capitalization-by-region/

Market Cap for U.S. Companies Outpaces Other Regions

In 2009, U.S. companies made up 45 percent of the Global Top 100 companies, according to PwC and Bloomberg. A decade later, U.S. firms now comprise 63 percent of organizations on the Global Top 100.

This advancement is partly due to growth in the United States tech sector. The tech sector has the most representation on the Global Top 100. As a testament to the booming industry, Microsoft topped Apple in terms of market cap for the first time in a decade. Apple was eclipsed by Microsoft for the highest market cap, reaching $905 billion in March 2019, largely fueled by Microsoft’s booming cloud business.

The market cap for European companies in the Global Top 100 has shrunk between 2014 and 2019, moving from nearly $4.0 trillion to $3.2 trillion over that time period. This is partly fueled by the actual number of European companies on the Global Top 100. Five years ago, 30 European organizations were in the Global Top 100, falling to just 20 in 2019.

China’s market cap has steadily rose and is now on-par with European countries on the list. Though, year-over-year China’s market cap fell by 5 percent, due to contractions from the U.S.-China trade war.

PwC and Bloomberg report on the ranks of the largest public companies based on their market capitalization in U.S. dollars. The analysis compares values between March of each year and exclude Exchange Traded funds and closed end funds.

AI Summary. The technology sector's share of the S&P 500 rose from 6% to over 20%, while the energy sector's weighting fell from 29% to less than 5%. Financials peaked at 22% before declining after the financial crisis.

Siblis Research Staff Siblis Research
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The tech sector surged from 6% in 1979 to over 20% by 2019, while energy declined from 29% in 1980 to less than 5% in 2019.

How have stock market sector weightings shifted over recent decades?

Core argument: The technology sector's share of the S&P 500 rose from 6% in 1979 to over 20% by 2019, attributed to rapid innovation and digitalization.

From 1979 to 2019, the S&P 500 sector weightings underwent significant shifts, reflecting broader economic transformations. The technology sector's share surged from 6% in 1979 to over 20% by 2019, driven by rapid innovation and digitalization. Conversely, the energy sector's weighting declined from 29% in 1980 to less than 5% in 2019, influenced by fluctuating oil prices and a shift towards renewable energy. Financials also saw a rise, peaking at 22% in 2006 before the financial crisis led to a reduction. These changes highlight the evolving landscape of the U.S. economy, with implications for investors and policymakers as they navigate sector-specific risks and opportunities. The data underscores the importance of diversification and adaptability in investment strategies to align with macroeconomic trends.

Takeaways by Macro Roundup® AI

  1. The technology sector's share of the S&P 500 rose from 6% in 1979 to over 20% by 2019, attributed to rapid innovation and digitalization.
  2. The energy sector's S&P 500 weighting fell from 29% in 1980 to under 5% in 2019, influenced by fluctuating oil prices and a shift toward renewable energy.
  3. Financials' S&P 500 weighting peaked at 22% in 2006, after which the financial crisis led to a reduction.

“U.S. Stock Market Sector Weighting,” Siblis Research, December 31, 2019, https://siblisresearch.com/data/sp-500-sector-weightings/

AI Summary. Comparing Congressional Budget Office forecasts made before and after the 2016 election, unemployment is now expected at 3.7% versus a projected 4.8%, with 157m Americans employed — 3m more than anticipated — and nominal GDP above the earlier estimate. The author argues deregulation and tax cuts raised household real incomes and provide a buffer against recession.

Kevin Hassett CNN
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@KevinHassett According To Side By Side Of August 2016 CBO # 2019 CBO Forcast There Has Been A “Trump Bump”.

Have deregulation and tax cuts outperformed pre-election economic forecasts?

Core argument: The 2019 unemployment rate is expected to be 3.7%, versus the 4.8% the Congressional Budget Office projected for 2019 in its August 2016 forecast, a comparison the former White House chief economist calls the "Trump Bump.".

The "Trump Bump" is evident when comparing the August 2016 CBO [Congressional Budget Office] forecast with the 2019 outlook, highlighting significant economic improvements. The unemployment rate, initially projected at 4.8% for 2019, is now expected to be 3.7%. Employment figures have surpassed expectations, with 157m Americans employed, 3m more than anticipated. Nominal GDP is projected at $21.4bn, $800m higher than the 2016 estimate. These figures underscore the positive impact of policies such as deregulation and tax cuts, which have increased real incomes by $3,100 per household over a decade and boosted real disposable personal income by $5,205 per household. Despite global economic slowdowns and trade tensions, these policies provide a buffer against recession, challenging earlier pessimistic forecasts.

Takeaways by Macro Roundup® AI

  1. The 2019 unemployment rate is expected to be 3.7%, versus the 4.8% the Congressional Budget Office projected for 2019 in its August 2016 forecast, a comparison the former White House chief economist calls the "Trump Bump.".
  2. Employment reached 157m Americans, 3m more than anticipated in the 2016 Congressional Budget Office forecast, while nominal GDP is projected at $21.4bn, $800m above the 2016 estimate.
  3. The former White House chief economist credits deregulation and tax cuts with raising real incomes by $3,100 per household over a decade and real disposable personal income by $5,205 per household, arguing they buffer against recession amid global slowdowns and trade tensions.

“A nice way to summarize the current state of the economy and quantify the positive impact of the president's policies is to compare the latest Congressional Budget Office economic outlook to the one it published in August of 2016. In 2016, the CBO thought that the unemployment rate for 2019 would be 4.8%. It now thinks it will be 3.7%. The CBO thought that nearly 154 million Americans would have jobs this year; it now puts the number at 157 million — roughly 3 million jobs higher. It estimated in 2016 that nominal GDP this year would be $20.6 billion; it now places it at $21.4 billion, $800 million more GDP than expected. To put the scale of these numbers in perspective, if a recession did arise, imposing job losses comparable to those that occurred in the 2001 recessions, American workers would still be better off than the CBO thought they would be looking ahead from 2016.”

Kevin Hassett, "Former White House chief economist: The case for the Trump economy," CNN, August 27, 2019, https://www.cnn.com/2019/08/26/perspectives/kevin-hassett-trump-economy/index.html

Former White House chief economist: The case for the Trump economy

Kevin Hassett was formerly chairman of the Council of Economic Advisers under President Trump. He's vice president and managing director of the Lindsey Group, distinguished visiting fellow at the Hoover Institution and a CNN Economics Commentator. The opinions expressed in this commentary are his own.

Before President Donald Trump was elected in 2016, the US economy was inching along with 1.5% growth. Many economists were so convinced the stagnation was here to stay that they called it the "new normal." After the president took office and began pursuing his agenda's three pillars of deregulation, tax cuts and trade reform, the "new normal" crowd said it couldn't work.

Many of the same analysts now say we are headed for recession. There is, if nothing else, logical consistency in their position since they didn't believe Trump's economic plan would work in the first place.
To evaluate the odds of recession, however, it is essential to review the policy record's effects, which we should expect to continue. It's not surprising that policy pessimists are worried about a recession given their views of the impact of the president's policies. But their pessimism is misplaced given the evidence.

Indeed, for the most part, things are working exactly as planned.

Start with deregulation. President Trump revolutionized regulatory practice when he came into office, giving agencies a regulatory budget. If they wanted to increase regulatory costs with a new regulation, they had to find something else to cut. And the successes have been impressive. For example, the 2017 Drug Competition Action Plan and subsequent reforms have led the Food and Drug Administration to approve dramatically more generic drugs, which has increased competition and helped push prices for prescription drugs 1.2% lower during the 12 months through February 2019.

In June, my last month as the chairman of the President's Council of Economic Advisers, we published a detailed study of this and other deregulatory changes. We documented that reforms already enacted will raise real incomes by $3,100 per household over the next decade. Since deregulation continues, it is likely that the final benefit of this pillar of the administration's economic policy will be much larger. Momentum, indeed.

As for corporate tax reform, the White House used economic models that predicted they would spur significant growth. Firms would build new factories, hire more workers and bid up wages.

Each of these effects happened as expected. While capital spending growth has slowed, the level of investment jumped after the tax cuts and stayed high. That has pushed up the growth in the amount of capital per worker, which has driven up productivity and wages. The bottom line for workers has, if anything, improved faster than the administration's forecasts constructed during the tax debate. Since the tax cuts were passed, the typical household (of 2.5 people) has seen a $5,205 increase in real disposable personal income, according to calculations by the White House's Council of Economic Advisers.

The administration came into office with a mandate to reform America's trade deals to benefit our workers and our businesses. The status quo on trade left much room for improvement as President Trump took office. The president has already partially delivered on this promise. There is an improved U.S.-Korea Trade Agreement (KORUS) and an improved deal with our neighbors to the North and the South now in the hands of Congress. What is left is a major dispute with China, a dispute that seemed close to resolution in the spring, but now seems less so.

It may well be that the near-term costs of the dispute with China are a significant risk to the outlook, but the upside of successful reform is large as well. The rewards justify the risks. China's theft of US intellectual property alone imposes, by some credible estimates, hundreds of billions of dollars in damage to the US economy per year. To put that in perspective, the largest property heist in US history was the approximately $500 million robbery of the Isabella Stewart Gardner Museum in Boston in 1990. When President Trump took office, China's average take per day was about that much — between $225 billion and $600 billion annually, or about $500 million each day.

A nice way to summarize the current state of the economy and quantify the positive impact of the president's policies is to compare the latest Congressional Budget Office economic outlook to the one it published in August of 2016. In 2016, the CBO thought that the unemployment rate for 2019 would be 4.8%.

It now thinks it will be 3.7%. The CBO thought that nearly 154 million Americans would have jobs this year; it now puts the number at 157 million — roughly 3 million jobs higher. It estimated in 2016 that nominal GDP this year would be $20.6 billion; it now places it at $21.4 billion, $800 million more GDP than expected.

To put the scale of these numbers in perspective, if a recession did arise, imposing job losses comparable to those that occurred in the 2001 recessions, American workers would still be better off than the CBO thought they would be looking ahead from 2016. The CBO, like other forecasters that underestimated the positive impact of recent policy changes, is calling for slowing growth in the future, but there is no reason to expect them to be more right in the future than they have been since 2016, assuming the president's policies stay in place.

The world economy is slowing sharply, and the demand for US exports is a major negative for the outlook compared to a year ago. But the positive momentum from ongoing deregulation and the continuing impact of the tax cuts provide an insurance policy against recession, and President Trump's policies have bought us that insurance policy.

AI Summary. More than 40% of California residents are cost-burdened, spending over 30% of their income on housing. McKinsey & Co. estimated the state needs 3.5m additional homes within a decade, a target that may not be reached until 2050, as home prices nationally rise faster than incomes.

Noah Buhayar Bloomberg
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40% of CA residents spend more than 30% of their income on shelter.

Are housing costs outpacing incomes and leaving residents cost-burdened?

Core argument: Over 40% of California residents are cost-burdened, spending more than 30% of their income on shelter, with even high-income earners stretching budgets to afford housing.

California's housing crisis is underscored by the fact that over 40% of its residents are cost-burdened, spending more than 30% of their income on shelter. This issue affects even high-income earners who find themselves stretching budgets to afford housing. In 2016, McKinsey & Co. estimated a need for 3.5m additional homes by the next decade, a target that may not be met until 2050. This shortfall is part of a broader national trend where housing construction has lagged during the longest economic expansion on record, exacerbating affordability issues as home prices rise faster than incomes. As California grapples with these challenges, it serves as a cautionary tale for the rest of the U.S., which is increasingly mirroring its housing market dynamics.

Takeaways by Macro Roundup® AI

  1. Over 40% of California residents are cost-burdened, spending more than 30% of their income on shelter, with even high-income earners stretching budgets to afford housing.
  2. McKinsey & Co. estimated in 2016 that California needed 3.5m additional homes within a decade, a target that may not be reached until 2050.
  3. U.S. housing construction lagged during the longest economic expansion on record, with home prices rising faster than incomes.

great chart

"...In a state where more than40% of residents are considered cost burdened for housing—paying more than 30% of their income toward shelter—even people in high income brackets are often stretching their budgets.....McKinsey & Co. estimated in 2016 that California needed some 3.5 million more homes by the middle of next decade—a figure that Governor Gavin Newsom made a central part of his administration’s goals. A more Analysis suggests it may take the state until 2050 to meet the target. As severe as this sounds, the rest of the country is becoming more—not less—like California. During the longest economic expansion on record, the U.S. has been building far fewer houses than it usually does, pushing prices further out of reach for a vast portion of the population that has barely seen incomes rise....."
Noah Buhayar and Christopher Cannon, "How California Became America’s Housing Market Nightmare," Bloomberg, November 6, 2019, https://www.bloomberg.com/graphics/2019-california-housing-crisis/

AI Summary. The share of prime-age men who are employed has returned to its pre-recession level, marking the end of the "mancession," even as more people in that age group are out of the labor force due to schooling and early retirement.

Justin Fox Bloomberg
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The male prime age employment-population ratio has returned to pre-recession levels, signaling the end of the “mancession.” @JustinFox

Has prime-age male employment recovered to pre-recession levels?

Core argument: The prime-age male employment-population ratio has returned to its pre-recession level, marking the end of the "mancession.".

The male prime age employment-population ratio has returned to pre-recession levels, signaling the end of the "mancession." This recovery is notable despite an increase in the number of individuals out of the labor force due to schooling and early retirement. The employment-population ratio, a key indicator of labor market health, suggests that the economic conditions have improved sufficiently to absorb more prime-age men into employment. However, questions remain about the demographic composition of those who are classified as "retired" within this age group. This trend reflects broader macroeconomic stability and could influence future policy decisions regarding labor force participation and retirement planning.

Takeaways by Macro Roundup® AI

  1. The prime-age male employment-population ratio has returned to its pre-recession level, marking the end of the "mancession.".
  2. The recovery in prime-age male employment occurred despite a rise in the number of men out of the labor force because of schooling and early retirement.
  3. Questions remain about the demographic composition of prime-age men classified as "retired.".

male prime age employment-population ratio ~ back to pre-recession levels. but for increase # of people out of labor force in school and "retired." wonder who these prime-age "retirees" are?

The Mancession Is Finally Over: Extended Excerpt Image 1


The Mancession Is Finally Over: Extended Excerpt Image 2

Justin Fox, "The Mancession Is Finally Over," Bloomberg, November 7, 2019, https://www.bloomberg.com/opinion/articles/2019-11-07/the-low-unemployment-rate-is-hiding-millions-of-jobless-men

Monday, November 11, 2019

AI Summary. The Organisation for Economic Co-operation and Development reports household disposable income — income after taxes, social contributions, and net interest and dividends — in US dollars per person, adjusted for differences in purchasing power to allow comparison across countries. A gross adjusted measure includes in-kind transfers such as government-provided health and education services.

OECD Staff OECD
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Household Disposable Income USD/capita measures the income of households after taxes, social contributions, and net interest & dividends. @OECD presents this data in terms of USD per capita at current prices andppPs.

How is household disposable income measured and compared across countries?

Core argument: The OECD measures household disposable income as income after taxes, social contributions, and net interest and dividends received, reporting it in USD per capita at current prices and purchasing power parities for cross-country comparison.

Household disposable income, a key economic indicator, measures the income of households after accounting for taxes, social contributions, and net interest and dividends received. This metric is crucial for understanding economic well-being as it reflects the actual purchasing power of households. The OECD presents this data in terms of USD per capita at current prices andppPs [Purchasing Power Parities], providing a standardized comparison across countries. The "gross" series includes transfers in kind, such as government-provided health or education services, which are adjusted for in the gross adjusted disposable income measure. This indicator is available both as annual growth rates for real net disposable income and as gross adjusted disposable income per capita. All OECD countries compile their data according to the 2008 System of National Accounts (SNA 2008), ensuring consistency and comparability in the data presented.

Takeaways by Macro Roundup® AI

  1. The OECD measures household disposable income as income after taxes, social contributions, and net interest and dividends received, reporting it in USD per capita at current prices and purchasing power parities for cross-country comparison.
  2. The OECD's gross adjusted disposable income measure accounts for transfers in kind such as government-provided health and education services, and the indicator is also published as annual growth rates for real net disposable income.
  3. All OECD countries compile household disposable income data under the 2008 System of National Accounts, which the OECD states ensures consistency and comparability across the data presented.

OECD also has the household disposable income measure we've looked at in the past. The "gross" series captures transfers

Household disposable income OECD: Extended Excerpt Image 1


https://data.oecd.org/hha/household-disposable-income.htm
"....Disposable income is closest to the concept of income as generally understood in economics. Household disposable income measures the income of households (wages and salaries, self-employed income, income from unincorporated enterprises, social benefits, etc.), after taking into account net interest and dividends received and the payment of taxes and social contributions. Net signifies that depreciation costs have been subtracted from the income presented. "Real” means that the indicator has been adjusted to remove the effects of price changes.Household gross adjusted disposable income is the income adjusted for transfers in kind received by households, such health or education provided for free or at reduced prices by government and NPISHs. This indicator is presented both in terms of annual growth rates (for real net disposable income) and in terms of USD per capita at current prices and ppPs (gross adjusted disposable income). All OECD countries compile their data according to the 2008 System of National Accounts (SNA 2008)...."

AI Summary. Actual individual consumption per person, measured at 2010 price levels and purchasing power parities, varies significantly across OECD member countries, indicating disparities in living standards. Gross household disposable income per person in US dollars provides a complementary measure of household financial health.

OECD Staff National Accounts Of OECD Countries
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OECD reports Actual Individual Consumption (AIC) per head varied significantly among member countries in 2019, highlighting disparities in economic well-being.

How much do living standards vary across developed countries?

Core argument: Actual Individual Consumption per head, measured at 2010 price levels and Purchasing Power Parities, varied significantly across OECD member countries in 2019, according to the OECD's National Accounts data.

Actual Individual Consumption (AIC) per head, measured at the price levels and Purchasing Power Parities (PPP) of 2010, provides a crucial insight into living standards across OECD countries. This metric, derived from the National Accounts data, reflects the value of goods and services consumed by individuals, adjusted for price level differences. In 2019, the OECD reported that AIC per head varied significantly among member countries, highlighting disparities in economic well-being. Additionally, Gross Household Disposable Income (GHDI) in US dollars per capita, as of 2018 or the latest available data, offers a complementary perspective on household financial health. These indicators are vital for economists and policymakers to assess economic performance and formulate strategies to enhance consumer welfare and address income inequality. Understanding these metrics helps in evaluating the real purchasing power and consumption capacity of households, which are essential for informed economic decision-making.

Takeaways by Macro Roundup® AI

  1. Actual Individual Consumption per head, measured at 2010 price levels and Purchasing Power Parities, varied significantly across OECD member countries in 2019, according to the OECD's National Accounts data.
  2. Gross Household Disposable Income in US dollars per capita, reported as of 2018 or the latest available year, complements Actual Individual Consumption per head as a measure of household financial health.
  3. Actual Individual Consumption per head captures the value of goods and services consumed by individuals adjusted for price level differences, which economists and policymakers use to assess real purchasing power and consumption capacity.

Here are (some of) OECD's AIC series from the National Accounts data

OECD “Actual Individual Consumption Per Head At The Price Levels And ppP Of Year 2010,” National Accounts Of OECD Countries, 2019, https://read.oecd-ilibrary.org/economics/national-accounts-of-oecd-countries/volume-2019/issue-1_g2g9fe48-en

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OECD “Household Disposable Income Gross Adjusted US Dollars/Capita 2018 Or Latest Available,” OECD, Accessed May 2020, https://data.oecd.org/hha/household-disposable-income.htm

AI Summary. A study of U.S. household data estimates that the share of lifetime resources consumed falls from about 0.09 for the bottom 20% of households to roughly 0.01 for the top 20%, where resources are private wealth plus human wealth minus net taxes. The authors attribute the pattern to bequest motives and household heterogeneity.

Elias Ilin, Victor Ye and Manni Yu Boston University
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Wealthier individuals tend to consume less & save more, driven by bequest motives & heterogeneity. APC decreases from 0.09 for bottom 20% to 0.01 for top 20% of resource quintiles.

Do wealthier households consume a smaller share of lifetime resources?

Core argument: Elias Ilin, Victor Ye, and Manni Yu find the average propensity to consume falls from 0.09 for the bottom 20% of lifetime-resource quintiles to about 0.01 for the top 20%, a gap of roughly three standard deviations.

The study by Elias Ilin, Victor Ye, and Manni Yu reveals a significant negative relationship between the average propensity to consume (APC) and lifetime net resources, defined as the sum of private wealth and human wealth minus net taxes. Using data from the Health and Retirement Study, the research identifies that the APC decreases notably from 0.09 for the bottom 20% of resource quintiles to about 0.01 for the top 20%, a difference of approximately three standard deviations. This indicates that wealthier individuals tend to consume less and save more, driven by factors such as bequest motives and heterogeneity. The analysis, which accounts for heterogeneous borrowing constraints, shows that while consumption rates do not decrease in liquid assets, they do decrease in overall resources, highlighting the economic implications of wealth accumulation and consumption behavior across different income levels.

Takeaways by Macro Roundup® AI

  1. Elias Ilin, Victor Ye, and Manni Yu find the average propensity to consume falls from 0.09 for the bottom 20% of lifetime-resource quintiles to about 0.01 for the top 20%, a gap of roughly three standard deviations.
  2. The study defines lifetime net resources as private wealth plus human wealth minus net taxes, and using Health and Retirement Study data identifies a significant negative relationship between that measure and the average propensity to consume.
  3. Accounting for heterogeneous borrowing constraints, Ilin, Ye, and Yu find consumption rates do not decrease in liquid assets but do decrease in overall resources, and attribute wealthier households' higher saving to bequest motives and heterogeneity.

This is an interesting job market paper from some Boston University gradate students on the average propensity to consume by income level, note that Kotlikoff and Restrepo offered comments on it.

"....The answer to the old question whether the rich save more is still debatable. We define the average propensity to consume (APC) out of remaining lifetime net resources. Lifetime net resources consist of lifetime private wealth and human wealth, deducting net taxes....We define remaining lifetime net resources (also referred as net resources or resources) as the sum of private wealth and human wealth, deducting lifetime net taxes..... We use a novel software TFA, a detailed life-cycle consumption-smoothing program, to calculate human wealth and net taxes using the Health and Retirement Study data. Because of potential consumption behavioral factors that are linked to the ability to accumulate wealth, we construct wealth luck instruments to resolve the endogeneity issue. We identify a strong negative relationship between the APC and lifetime net resources. We divide households into five quintile groups by resources. The predicted APC of the highest resources cohort is about 0.01, which is three standard deviations smaller than the lowest resource cohort. Our finding shows that the rich consume less and save more. Testable implications of models indicate that both bequest motives and heterogeneity explain why the rich save more. The results do not change if we consider heterogeneous borrowing constraints among households. Breakdown of resources into four components, including liquid and illiquid assets, human wealth, and net taxes, shows that consumption rate does not decrease in liquid assets...."Abnormally large return rates causally increase resources and we assume households receive large return rates because of pure luck. Our key result is that consumption rate decreases in resources in the IV regression. Average propensity to consume (APC) decreases significantly and economically fast from 0.09 for the bottom 20% resources quintile to about 0.01 for the top 20% resources quintile. The difference is about 3 standard deviations. By testable implications in the model part, we conclude that bequest motives can explain why the rich save more..."

Elias Ilin, Victor Ye and Manni Yu, "Do the Rich Save More?," Boston University, October 2019, https://drive.google.com/file/d/1jPbGQX7Ngx6Pa_-Qg9am9m-iq1q8wBMg/view

AI Summary. A study of 10,073 US adolescents aged 13–18 estimates that generational gains in fluid intelligence are not uniform: scores fell 4.9 points per decade among those with IQ at or below 70 while rising 3.5 points among those at or above 130. The authors also estimate gains at age 13 and declines at age 18.

Jonathan Platt, Katherine Keyes, KatieMcLaughlin, and Alan Kaufman Intelligence
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Research reveals a negative Flynn Effect for individuals with IQ ≤ 70, declining 4.9 points per decade, contrasting with a 3.5-point increase for those with IQ ≥ 130. @JonathanPlatt

Do generational IQ gains differ across ability levels and ages?

Core argument: Fluid IQ declined 4.9 points per decade (95% CI = −4.9, −4.8) among US adolescents with IQ ≤ 70, while rising 3.5 points (95% CI = 3.4, 3.6) among those with IQ ≥ 130.

Recent research highlights a negative Flynn Effect for individuals with IQ ≤ 70, indicating a decline of 4.9 points per decade (95% CI = −4.9, −4.8) among this group. This contrasts with a 3.5-point increase for those with IQ ≥ 130 (95% CI = 3.4, 3.6). The study, involving 10,073 US adolescents aged 13-18, reveals significant heterogeneity in fluid IQ changes over time, challenging the notion of uniform generational IQ gains. While the overall Flynn Effect was not significant, variations by age and ability level were notable, with IQs increasing by 2.3 points at age 13 but decreasing by 1.6 points at age 18. These findings suggest that economic and educational policies should consider the diverse impacts of cognitive trends across different ability levels to address potential socioeconomic disparities.

Takeaways by Macro Roundup® AI

  1. Fluid IQ declined 4.9 points per decade (95% CI = −4.9, −4.8) among US adolescents with IQ ≤ 70, while rising 3.5 points (95% CI = 3.4, 3.6) among those with IQ ≥ 130.
  2. In a population-based study of 10,073 US adolescents aged 13–18, the overall Flynn Effect was not significant, but fluid IQ rose 2.3 points at age 13 and fell 1.6 points at age 18.
  3. The study suggests economic and educational policies should account for the diverse impacts of cognitive trends across ability levels to address potential socioeconomic disparities.

new study finds a Flynn Effect was found for IQs ≥ 130, and a negative effect for IQs ≤ 70 though the negative Flynn effect for those with lower ability was worth highlighting"....lower ability levels are exhibiting worsening IQ over time..."

Jonathan Platt,Katherine Keyes, KatieMcLaughlin, Alan Kaufman, "The Flynn effect for fluid IQ may not generalize to all ages or ability levels: A population-based study of 10,000 US adolescents,"Intelligence, November-December 2019, https://www.sciencedirect.com/science/article/abs/pii/S0160289619301679

"....Generational changes in IQ (the Flynn Effect) have been extensively researched and debated. Within the US, gains of 3 points per decade have been accepted as consistent across age and ability level, suggesting that tests with outdated norms yield spuriously high IQs. However, findings are generally based on small samples, have not been validated across ability levels, and conflict with reverse effects recently identified in Scandinavia and other countries. Using a well-validated measure of fluid intelligence, we investigated the Flynn Effect by comparing scores normed in 1989 and 2003, among a representative sample of American adolescents ages 13-18 (n = 10,073). Additionally, we examined Flynn Effect variation by age, sex, ability level, parental age, and SES. Adjusted mean IQ differences per decade were calculated using generalized linear models. Overall the Flynn Effect was not significant; however, effects varied substantially by age and ability level. IQs increased 2.3 points at age 13 (95% CI = 2.0, 2.7), but decreased 1.6 points at age 18 (95% CI = −2.1, −1.2). IQs decreased 4.9 points for those with IQ ≤ 70 (95% CI = −4.9, −4.8), but increased 3.5 points among those with IQ ≥ 130 (95% CI = 3.4, 3.6).The Flynn Effect was not meaningfully related to other background variables. Using the largest sample of US adolescent IQs to date, we demonstrate significant heterogeneity in fluid IQ changes over time. Reverse Flynn Effects at age 18 are consistent with previous data, and those with lower ability levels are exhibiting worsening IQ over time. Findings by age and ability level challenge generalizing IQ trends throughout the general population...".