Edward Conard

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Tuesday, September 8, 2020

A General Dimension Of Fenetic Sharing Across Diverse Cognitive Traits Inferred From Molecular Data

AI Summary. Analysis of molecular data estimates that a general genetic factor accounts for 58.36% of the genetic variance across seven cognitive traits. Its contribution varies widely by trait: the authors attribute 95% of the genetic variance in one trail-making test to the general factor, versus 9.5% for reaction time.

Javier de la Fuente, Gail Davies, Andrew Grotzinger, Elliot Tucker-Drob and Ian Deary Nature Human Behaviour
Date Posted:
September 8, 2020
Is Database:
Database

Genetic g factor accounts for 58.36% of genetic variance across seven cognitive traits, highlighting its significant role in cognitive performance.

Does a general genetic factor explain most variance across cognitive traits?

Core argument: A genetic g factor accounts for 58.36% of the genetic variance across seven cognitive traits inferred from molecular data.

Recent findings reveal that the genetic g factor accounts for 58.36% of the genetic variance across seven cognitive traits, highlighting its significant role in cognitive performance. For trails-B, 95% of the genetic variance is attributed to genetic g, while only 5% is specific to trails-B, indicating a strong genetic overlap with other cognitive phenotypes. Conversely, for RT [Reaction Time], only 9.5% of the genetic variance is linked to genetic g, with 90.5% being specific to RT, suggesting distinct genetic influences. This underscores the importance of understanding the extent to which genetic associations are broadly related to genetic g or specific to individual cognitive traits when analyzing performance on cognitive tests. Such insights could inform economic policies and strategies aimed at enhancing cognitive skills and productivity in the workforce, ultimately impacting GDP growth and competitiveness.

Takeaways by Macro Roundup® AI

  1. A genetic g factor accounts for 58.36% of the genetic variance across seven cognitive traits inferred from molecular data.
  2. For trails-B, genetic g accounts for 95% of the genetic variance and 5% is specific to the trait, while for reaction time genetic g accounts for 9.5% and 90.5% is trait-specific.
  3. Interpreting genetic associations with cognitive test performance requires distinguishing whether those associations relate broadly to genetic g or are specific to an individual cognitive trait.

Javier de la Fuente, Gail Davies, Andrew Grotzinger, Elliot Tucker-Drob and Ian Deary, "A General Dimension Of Fenetic Sharing Across Diverse Cognitive Traits Inferred From Molecular Data,"Nature Human Behaviour, September 7, 2020, https://www.nature.com/articles/s41562-020-00936-2

Wow, newNaturestudy finds that the genetic g factor model closely approximated the genetic covariance structure among cognitive tests. Paper says the genetic g factor accounted for 58.36% (SE = 4.84%) of the genetic variance in the seven cognitive traits.

“…The importance of our results may be seen by contrasting the results of trails-B with RT. Analyses of multivariate genome-wide architecture indicated that, for trails-B, 95% of the genetic variance is accounted for by genetic g and only 5% is specific to trails-B. Moreover, all seven loci for trails-B have previously been reported in GWAS of other cognitive phenotypes…. and four of these were implicated as relevant for genetic g at non-significant levels of heterogeneity. In contrast, for RT, analyses of multivariate genome-wide architecture indicated that 9.5% of the genetic variance is accounted for by genetic g while 90.5% of the genetic variance is specific to RT.Many of the 39 loci associated with RT have not been found in univariate GWAS of other cognitive traits…and only four were implicated as relevant for genetic g at non-significant levels of heterogeneity. Therefore, when identifying loci associated with performance on an individual cognitive test, it is essential to know the extent to which its associations are broadly related to genetic g or specifically related to the phenotype under investigation…”

Here they discuss RT (Reaction Time) that you flagged, relative low g variance versus it’s high specific variance

“…Psychometrically, a hierarchical structure of cognitive abilities is commonly agreed, with cognitive tests’ variance accounted for by three different strata of variation (Supplementary Fig. 1), representing (1) each test’s specific variance (s), (2) broad domains of cognitive function (for example, reasoning, processing speed, memory) and (3) g (ref. 5 ). All cognitive tests have some g loading, though this varies from test to test….”

And some of the variance is“…thought to bespecific to that test (its s)…”or the test specific factor.

Ed Comment:but it’s not clear they are actually measuring genes and not traits. I also don’t understand the first diagram below. Its seems to say all traits, except RT (what is RT?) are highly genetic and that only RT lowers the correlation to 58%. I don’t understand the difference between the top and bottom chart but I don’t see how you can ‘average” 58 form the bottom. Scary to rely on something that we don’t understand.

“….It has been known since 1904 that, in humans, diverse cognitive traits are positively intercorrelated. This forms the basis for the general factor of intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different cognitive tests (n = 11,263-331,679) and genome-wide autosomal single-nucleotide polymorphisms. A genetic g factor accounts for an average of 58.4% (s.e. = 4.8%) of the genetic variance in the cognitive traits considered, with the proportion varying widely across traits (range, 9-95%).We distil genetic loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute to elucidating the aetiology of a long-known yet poorly understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits….”
A General Dimension Of Fenetic Sharing Across Diverse Cognitive Traits Inferred From Molecular Data: Comments Image 1

Charles Murray Comment: the study suggests the majority of variance in cognitive traits is driven by g. He did add the inverse is possible “Or the other way around: variance in cognitive traits contributes to a general factor.”

“…The importance of our results may be seen by contrasting the results of trails-B with RT. Analyses of multivariate genome-wide architecture indicated that, for trails-B, 95% of the genetic variance is accounted for by genetic g and only 5% is specific to trails-B. Moreover, all seven loci for trails-B have previously been reported in GWAS of other cognitive phenotypes…. and four of these were implicated as relevant for genetic g at non-significant levels of heterogeneity. In contrast, for RT, analyses of multivariate genome-wide architecture indicated that 9.5% of the genetic variance is accounted for by genetic g while 90.5% of the genetic variance is specific to RT.Many of the 39 loci associated with RT have not been found in univariate GWAS of other cognitive traits…and only four were implicated as relevant for genetic g at non-significant levels of heterogeneity. Therefore, when identifying loci associated with performance on an individual cognitive test, it is essential to know the extent to which its associations are broadly related to genetic g or specifically related to the phenotype under investigation…”

Here they discuss RT (Reaction Time) that you flagged, relative low g variance versus it’s high specific variance

“…Psychometrically, a hierarchical structure of cognitive abilities is commonly agreed, with cognitive tests’ variance accounted for by three different strata of variation (Supplementary Fig. 1), representing (1) each test’s specific variance (s), (2) broad domains of cognitive function (for example, reasoning, processing speed, memory) and (3) g (ref. 5 ). All cognitive tests have some g loading, though this varies from test to test….”

And some of the variance is“…thought to bespecific to that test (its s)…”or the test specific factor.

Steve Comment: From my read of the paper the distinction is as follows“…somevariance in each cognitive test was thought to be shared with all other cognitive tests (g)…”So that’s g or general intelligence, that’s the common factor.

Ed Comment:What are g and s? what is common vs specific?

His chart is derived from this table which (I think) is showing that for some cognitive traits the genetic variance is primarily g driven while for others is s driven. Let me see if I can track down some reactions to the research from people in the field that might help me understand what it says it found.

Steve Comment: RT is “reaction time” so motor speed, “…Data for the present study came from the UK Biobank (UKB), a biomedical cohort study that collects a wide range of genetic and health-related measures from a population-based sample of community-dwelling participants in the United Kingdom. Participants were measured on up to seven cognitive traits using tests that often show substantial concurrent validity with established psychometric tests of cognitive abilities, and modest to good test-retest reliability26:reaction time (RT, n=330,024, which assesses perceptual motor speed);matrix pattern recognition (n=11,356, non-verbal reasoning);verbal numerical reasoning (VNR, n=171,304,verbal and numeric problem solving; the test is called ‘fluid intelligence’ in UKB);symbol digit substitution (n=87,741, information processing speed);memory pairs-matching test (n=331,679, episodic memory);tower rearranging (n=11,263, executive functioning);andtrail-making test-B (trails-B, n=78,547, executive functioning).Scores on all tests were coded such that higher scores represented more optimal (that is, faster or more accurate) performance….”

Charles Murray Comment: the study suggests the majority of variance in cognitive traits is driven by g. He did add the inverse is possible “Or the other way around: variance in cognitive traits contributes to a general factor.”

Steve Comment: From my read of the paper the distinction is as follows“…somevariance in each cognitive test was thought to be shared with all other cognitive tests (g)…”So that’s g or general intelligence, that’s the common factor.

Ed Comment:What are g and s? what is common vs specific?

His chart is derived from this table which (I think) is showing that for some cognitive traits the genetic variance is primarily g driven while for others is s driven. Let me see if I can track down some reactions to the research from people in the field that might help me understand what it says it found.

Steve Comment: RT is “reaction time” so motor speed, “…Data for the present study came from the UK Biobank (UKB), a biomedical cohort study that collects a wide range of genetic and health-related measures from a population-based sample of community-dwelling participants in the United Kingdom. Participants were measured on up to seven cognitive traits using tests that often show substantial concurrent validity with established psychometric tests of cognitive abilities, and modest to good test-retest reliability26:reaction time (RT, n=330,024, which assesses perceptual motor speed);matrix pattern recognition (n=11,356, non-verbal reasoning);verbal numerical reasoning (VNR, n=171,304,verbal and numeric problem solving; the test is called ‘fluid intelligence’ in UKB);symbol digit substitution (n=87,741, information processing speed);memory pairs-matching test (n=331,679, episodic memory);tower rearranging (n=11,263, executive functioning);andtrail-making test-B (trails-B, n=78,547, executive functioning).Scores on all tests were coded such that higher scores represented more optimal (that is, faster or more accurate) performance….”

  • Evolution/Heredity
  • Science

Immigration and Entrepreneurship In The United States

AI Summary. Across administrative data, the US Census Bureau's Survey of Business Owners, and Fortune 500 analysis, immigrants start firms at higher rates than the native-born and found more firms of every size. The authors argue this makes immigrants job creators who expand labor demand more than labor supply.

Pierre Azoulay, Benjamin Jones, J. Daniel Kim and Javier Miranda National Bureau of Economic Research
Date Posted:
September 8, 2020
Is Database:
Database

Immigrants start firms at higher rates than native-born individuals, expanding labor demand more than labor supply, according to @BenjaminJones and the @nberpub.

Do immigrants create more jobs than they fill?

Core argument: Immigrants in the US start firms at higher rates than native-born individuals and establish more firms of every size, a "right shift" in entrepreneurship documented across administrative data, the Census Bureau's 2012 Survey of Business Owners, and Fortune 500 analysis.

Immigrants significantly contribute to expanding labor demand in the US through entrepreneurship, as evidenced by multiple data sets including administrative data, the U.S. Census Bureau's 2012 Survey of Business Owners, and Fortune 500 analysis. Immigrants start firms at higher rates than native-born individuals and tend to establish more firms of every size, indicating a "right shift" in entrepreneurship. This shift positions immigrants as key job creators, expanding labor demand more than labor supply. The findings suggest that immigrants play larger roles as employers rather than employees, offering a more comprehensive view of their economic impact. This entrepreneurial activity helps resolve existing puzzles where empirical evidence often shows more positive economic effects from immigration than labor-supply focused perspectives suggest.

Takeaways by Macro Roundup® AI

  1. Immigrants in the US start firms at higher rates than native-born individuals and establish more firms of every size, a "right shift" in entrepreneurship documented across administrative data, the Census Bureau's 2012 Survey of Business Owners, and Fortune 500 analysis.
  2. Immigrant entrepreneurship expands US labor demand more than labor supply, positioning immigrants as job creators playing larger roles as employers than as employees.
  3. Immigrant entrepreneurship helps resolve puzzles in which empirical evidence shows more positive economic effects from immigration than labor-supply-focused perspectives suggest.

Pierre Azoulay, Benjamin Jones, J. Daniel Kim and Javier Miranda, “Immigration and Entrepreneurship In The United States,” National Bureau Of Economic Research, September 2020, https://www.nber.org/papers/w27778

“…We use three independent data sets. Our primary analysis uses administrative data to studyall new firms in the United States from 2005-2010 (“administrative data”).Our second analysis studies theU.S. Census Bureau’s 2012 Survey of Business Ownersto examine a representative sample of U.S. businesses and their founders (“representative sample”). Our third analysis studies the Fortune 500 to consider the country’s largest firms and their founders (“Fortune 500”).We describe these data sets here, with additional detail in the appendix…..”

The three datasets

Their conclusion: “….Overall, the entrepreneurial lens suggests that immigrants appear to play a relatively strong role in expanding labor demand relative to labor supply, compared to the native-born population…”

“…First, reflecting existing research, immigrants start firms at higher rates than native-born individuals do….Second, immigrants do not simply start small firms. Rather, they tend to start more firms at every size, compared to U.S.-born individuals. This is the key finding of the paper. There is effectively a “right shift” in entrepreneurship for immigrants, with immigrants playing relatively large roles as employers rather than employees, compared to U.S.-born individuals. Overall, the findings suggest that immigrants appear to “create jobs” (expand labor demand) more than they “take jobs” (expand labor supply) in the U.S. economy.By studying immigrants as both entrepreneurs and workers, one produces a fuller picture of the impact of immigration. The new facts can help resolve existing puzzles where empirical evidence, including natural experiments and longer-run historical analysis, often suggests more positive economic effects from immigration than labor-supply oriented perspectives produce….”

The net effect of this is immigrants appear to create more jobs (expand labor demand) than they take jobs (expand labor supply):

“…Using administrative data, a representative sample, and Fortune 500 data, we present new findings on the size of firms these different founder populations create. Across all three data sets,we find that immigrants present a “right shift” in new venture formation, where immigrants tend to start more firms of each size per member of their population….”

New NBER finds immigrants play an outsized role in American high-growth entrepreneurship versus native born workers:

Ed Comment:As long as the entrepreneurialism is not bodegas and cheap hotels.

  • Startups
  • Productivity
  • Workforce
    • Immigration

The Grumpy Economist: Debt Matters

AI Summary. Interest rates did not signal the inflation of the 1970s or the disinflation of the 1980s in advance, and low rates preceded both Greece's debt crisis and Lehman Brothers' collapse. The author argues that bond markets cannot be relied on to warn of a debt crisis in which government spending unmatched by taxes produces sharp inflation that devalues debt.

John Cochrane The Grumpy Economist
Date Posted:
September 8, 2020
Is Database:
Database

Interest Rates Did Not Signal The Inflation Of The 1970’s Or Disinflation Of The 1980s @JohnCochrane The bond market’s failure to signal these significant economic changes highlights the potential risk of a debt crisis.

Do bond markets warn in advance of debt trouble?

Core argument: Interest rates gave no advance warning of the 1970s inflation or the 1980s disinflation, suggesting that reliance on interest rates alone as indicators of economic shifts can mislead.

Despite common assumptions, interest rates did not provide advance warning of the inflation in the 1970s or the disinflation in the 1980s. This suggests that relying solely on interest rates as indicators of economic shifts can be misleading. The bond market's failure to signal these significant economic changes highlights the potential risk of a debt crisis, where unchecked government spending without corresponding tax increases could lead to sharp inflation. Such inflation could devalue debt, posing severe economic consequences. Historical examples, like Greece's low interest rates before their crisis and Lehman's borrowing at low rates until collapse, underscore that interest rates often fail to predict financial turmoil. This emphasizes the need for comprehensive economic analysis beyond interest rate trends to anticipate and mitigate potential crises.

Takeaways by Macro Roundup® AI

  1. Interest rates gave no advance warning of the 1970s inflation or the 1980s disinflation, suggesting that reliance on interest rates alone as indicators of economic shifts can mislead.
  2. Government spending left unmatched by tax increases could produce a debt crisis marked by sharp inflation that devalues outstanding debt.
  3. Greece borrowed at low interest rates before its crisis and Lehman borrowed at low rates until its collapse, illustrating that interest rates often fail to predict financial turmoil.

Cochrane on the risk of rising debt levels (a follow up post of his is attached) he notes that the bond market did not give advance warning of inflation during the 1970’s or the disinflation of the 1980s.

My takeaway is he thinks the government might be able to generate inflation if the government keeps spending without raising taxes

“…The danger the US faces, the danger we should repeat and keep in mind, is a debt crisis. We print our own money, so the result may be a sharp inflation that wipes away the value of debt rather than an even more disruptive default, but the consequences will be almost as dire…..Yes, I've warned about this before, and no, it hasn't happened yet. Well, if you live in California you live on an earthquake fault. That the big one hasn't happened yet doesn't mean it never will. No, interest rates do not signal such problems. (Alan Blinder, covering such matters in the Wall Street Journal, "if the U.S. Treasury starts to supply more bonds than the world's investors demand, the markets will warn us with higher interest rates and a sagging dollar. No such yellow lights are flashing.) They never do. Greek interest rates were low right up until they weren’t. Interest rates did not signal the inflation of the 1970s, or the disinflation of the 1980s. Lehman borrowed at low rates until it didn’t. Nobody expects a debt crisis, or it would have already happened….”

Also sent you a follow up post. 1/2

John Cochrane, “Debt Matters,” The Grump Economist, September 4, 2020, https://johnhcochrane.blogspot.com/2020/09/debt-matters.html

  • Taxation
  • Fiscal Policy
    • Fiscal Deficits
  • GDP
    • Inflation

The Grumpy Economist: More on debt

AI Summary. The Congressional Budget Office projects U.S. primary deficits of 6–8% of GDP over the next decade, far larger than the 1–2% contribution from the gap between interest rates and growth, implying debt relative to GDP will be driven mainly by deficits rather than that gap.

John Cochrane The Grumpy Economist
Date Posted:
September 8, 2020
Is Database:
Database

The CBO projects primary deficits of 6-8% of GDP over the next decade, overshadowing the 1-2% impact of r-g. @JohnCochrane

Are deficits, not interest rates minus growth, driving rising debt?

Core argument: CBO projects U.S. primary deficits of 6–8% of GDP over the next decade, overshadowing the 1–2% contribution of r-g (the interest rate minus the growth rate) to debt dynamics.

The Congressional Budget Office (CBO) projects that over the next decade, the U.S. will experience primary deficits ranging from 6-8% of GDP, significantly overshadowing the 1-2% impact of r-g [interest rate minus growth rate]. This suggests that debt/GDP dynamics will be primarily driven by these substantial deficits rather than variations in r-g. If crises continue to escalate annual deficits by 10% of GDP, the situation could worsen. Additionally, initiatives like the Green New Deal and federal assumptions of student, state, and local debts could further exacerbate the debt/GDP ratio, indicating a challenging fiscal landscape ahead.

Takeaways by Macro Roundup® AI

  1. CBO projects U.S. primary deficits of 6–8% of GDP over the next decade, overshadowing the 1–2% contribution of r-g (the interest rate minus the growth rate) to debt dynamics.
  2. Because projected primary deficits exceed the r-g effect several times over, debt/GDP dynamics would be driven primarily by those deficits rather than by variations in interest rates relative to growth.
  3. Crises that add 10% of GDP to annual deficits, along with the Green New Deal and federal assumption of student, state, and local debts, could push the debt/GDP ratio higher still.

John Cochrane, “More On Debt,” The Grump Economist, September 6, 2020, https://johnhcochrane.blogspot.com/2020/09/more-on-debt.html

“…As we look forward, debt/GDP dynamics for the next 20 years are going to be dominated by the primary surplus/deficit, not plausible variation in r-g. The CBO's 10 years of 6-8% of GDP overwhelm 1-2% of r-g.If each crisis continues to ratchet up 10% of GDP deficits per year, more so. The Green New Deal, and large federal assumption of student debts, state and local debts, pension obligations, and so forth would add far more to debt/GDP than decades of r vs. g...”

Cochrane argues that the debt/GDP dynamics of the next 20 years will be dominated by primary surplus or deficit not changes in r versus g. 2/2

Ed Comment:Add. I would guess this ends with inflation. At some point—in a crisis for example where they can’t sell debt, the fed just prints money and buys debt. at some point inflation expectations have to grow. That’s why I think I should be holding equity and not debt.

  • Fiscal Deficits
  • GDP
    • Growth
    • Inflation

Top Wealth in the United States: New Estimates and Implications for Taxing the Rich

AI Summary. New estimates of U.S. wealth distribution indicate the top 10% of households hold 68.7% of total wealth and the top 1% hold 31.2%, with the top 1% holding as much as the bottom 90% combined. Median wealth for white households is $171,000, about 10x the $17,100 median for Black households.

Matthew Smith, Owen Zidar and Eric Zwick National Bureau of Economic Research
Date Posted:
September 8, 2020
Is Database:
Database

The top 1% in the US holds as much wealth as the bottom 90%, with the top 10% controlling 68.7% of total wealth.

How concentrated is wealth among the richest U.S. households?

Core argument: The top 1% of U.S. households hold 31.2% of total wealth — as much as the bottom 90% combined — while the top 10% control 68.7%, according to the estimates.

The latest estimates on wealth distribution in the U.S. reveal that the top 1% holds as much wealth as the bottom 90%, highlighting significant economic inequality. The top 10% of households control 68.7% of total wealth, with the top 1% alone holding 31.2%. This concentration of wealth has implications for tax policy, as it suggests that taxing the rich could address fiscal imbalances and fund public services. The disparity is further underscored by racial wealth gaps, where white households have a median wealth of $171,000, ten times that of Black households at $17,100. These figures emphasize the need for policies that address both wealth concentration and racial disparities to promote economic equity.

Takeaways by Macro Roundup® AI

  1. The top 1% of U.S. households hold 31.2% of total wealth — as much as the bottom 90% combined — while the top 10% control 68.7%, according to the estimates.
  2. White households have a median wealth of $171,000, ten times the $17,100 median for Black households.
  3. The concentration of U.S. wealth at the top suggests that taxing the rich could address fiscal imbalances and fund public services.

Here are CBS’s claims (I used your language describing them as opposed to theirs)

I’ve added in descending order research that refutes or provides context for their claims. Please let me know if this is directionally what you were looking for.

Steve

“….40% can’t cover a $400 expense (fed) disputed…”

We read the Fed report when it was released and pointed out it’s being misrepresented. However Michael Strain refuted it effectively in the Bloomberg op-ed, “…It turns out the claim that nearly half of Americans are a flat tire away from financial crisis is largely based on an inaccurate reading of one survey question. The question comes from theannual“Report on the Economic Well-Being of U.S. Households” by the Federal Reserve. Thereportfinds, in 2018, that 61% of adults would cover a $400 unexpected expense using cash (or its equivalent). Politicians and many in the media seem to be subtracting 61 from 100, and concluding that 39% of people, to use Warren’s phrase, “can’t come up with” the money they’d need to handle this situation….”

CBS News, “Income Inequality, and coronavirus’ economic fallout,” CBS News, September 6, 2020, https://www.cbsnews.com/news/income-inequality-and-coronavirus-economic-fallout/

CBS claims live here:

Kriston McIntosh, Emily Moss, Ryan Nunn and Jay Shambaugh, “Examing The Black-White Wealth Gap,” Brookings, February 27, 2020, https://www.brookings.edu/blog/up-front/2020/02/27/examining-the-black-white-wealth-gap/

Brookings provides some context for driver of the wealth gap btw black and white families with the same income, “…Why are high- and middle-income white families so much wealthier than Black families with the same incomes? We note a few reasons. White families receive much larger inheritances on average than Black families. Economists Darrick Hamilton and Sandy Darity conclude that inheritances and other intergenerational transfers “account for more of the racial wealth gap than any other demographic and socioeconomic indicators.”In addition, the income groups in figure 2 are based on a snapshot of family income, which does not fully capture lifetime income. Black families who make it to the top of the income distribution in a particular year are more likely than white families to drop out of the top in subsequent years, and their respective wealth levels reflect this difference. Likely less important, but still notable, high- and middle-income Black families are more likely than their white counterparts to be called upon to assist family members and neighbors…”

Rakesh Kochhar and Anthony Cilluffo, “How Wealth Inequlaity Has Changed In The U.S. Since The Great Recession, By Race, Ethnicity And Income,” Pew Research Center, November 1, 2017, https://www.pewresearch.org/fact-tank/2017/11/01/how-wealth-inequality-has-changed-in-the-u-s-since-the-great-recession-by-race-ethnicity-and-income/

They are attributing this to Pew’s analysis of SCF data, “… In 2016, the median wealth of white households was $171,000. That’s 10 times the wealth of black households ($17,100)– a larger gap than in 2007 – and eight times that of Hispanic households ($20,600), about the same gap as in 2007. (Asians and other racial groups are not separately identified in the SCF data.)…”

“…Black network 10% of white federal reserve…Hispanic 12% (same source)…”

Amazon’s pre-Covid peak for 2020 2,170.22 on February 19, it’s trough was March 12 1,676.61. Currently it’s 3,182.78 From February to today it’s up 46.65% from trough to today it’s up 89.83%. From the 18thto today it’s up just over 40%.

You are correct the work is benchmarked to March 18th.

“….Net worth of 600 billionaires increased (20%), I suspect they start at the market bottom and not the day before the drop… Bezo net worth up $43.8 B (again probably at the trough)…

https://www.dol.gov/ui/data.pdf

Thomas Stengle, “Covid-19 Impact,” U.S. Department Of Labor, September 3, 2020,

According to Labor Department this checks out, as of mid august 29mm persons were getting UI insurance

“…..29mm collecting unemployment…”

USDA “How Many People Lived In Food-Insecure Households?” USDA Economic Research Service, Accessed September 8, 2020, https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics.aspx

9.5mm adults and 540,000 (.7% of children)lived in households which one of more children experienced very low food security defined as“…In these food-insecure households, normal eating patterns of one or more household members were disrupted and food intake was reduced at times during the year because they had insufficient money or other resources for food…”

If you look at the USDA statistics themselves37.2mm individual were in the broader food insecure households(this is defined as “These food-insecure households obtained enough food to avoid substantially disrupting their eating patterns or reducing food intake by using a variety of coping strategies, such as eating less varied diets, participating in Federal food assistance programs, or getting emergency food from community food pantries”

Paul Roderick Gregory, “If Children Are Hungry In America, It Is The Parents’ Fault,” The Mercury News, July 1, 2013, https://www.mercurynews.com/2013/07/01/hoover-fellow-if-children-are-hungry-in-america-it-is-the-parents-fault/

“…The 20 percent of families that are classified as “food insecure” worry food will run out, substitute cheaper foods, serve unbalanced meals or cut meal sizes at least once in the past 12 months. Such measures are far from the concept of regular hunger that celebrity media ads, sponsored by Feeding America, imply. Meanwhile, the USDA’s specific questions about child hunger are dutifully ignored. They are inconveniently low. The USDA’s most direct measures of child hunger show that around 1 percent of families with children have a child who experienced hunger (skipping meals or not eating for a whole day) at least one day in the last 12 months. This is a far cry from “1 in 5” children going to bed hungry we hear regularly in the media. The USDA’s figures for an incidence of child hunger on an average day show that one tenth of 1 percent of children were hungry on an average day. This adds up to two hungry children per ZIP code.Adult hunger should be higher than child hunger because USDA studies show children are given preference when food is low. The USDA finds, however, that on an average daily basis, one quarter of one percent of all adults do not eat for a whole day due to lack of money. That is 21/2 per thousand….”

Paul Roderick Gregory from Hoover has debunked this myth

“…54mm food insecure (feeding America)…”

His FPMis “..matches President Johnson’s initial standard. Second,these initial 1963 thresholds must be held constant in real terms over time by updating them each year using an unbiased measure of inflation. Third, the metric for evaluating success should include the full array of anti-poverty programs utilized by the government, including in-kind transfers and transfers administered through the tax code. No existing poverty measure meets all three of these conditions. We create a poverty measure, which we refer to as the Full-Income Poverty Measure (FPM), which meets all three of these conditions…”

Obviously Burkhauser finding that poverty rate based on President Johnson’s standards fell from 19.5 percent in 1963 to 2.3 percent in 2017 are also useful. What did Will Rogers say during the depression“We are the first nation in the history of the world to go to the poorhouse in an automobile”

Jeff Larrimore, Jacob Mortenson and David Splinter, “Presence and Persistence of Poverty in U.S. Tax Data,” Federal Reserve Board and Joint Committee on Taxation, February 2020, http://www.davidsplinter.com/LMS_PersistencePoverty_2020.pdf

“….There is substantial mobility in and out of poverty. For example, 41 percent of those in poverty in 2007 were out of poverty in the following year. However, many of those who are poor spend multiple years in poverty or escape poverty only to fall back into it. Of those who were in poverty in 2007, one-third are in poverty for at least half of the years through 2018….”

FRED actually has 41mm, however I think David Splinter’s research that shows the transitory nature of poverty for younger people is a better way to contextualize that number (granted he finds older people who are poor stay poor)

“…38mm in poverty (census)….”

Sarin’s SS paper may also be also useful here, she is showing that the Top 10% (so not top 5%) have around ~ 60% of total wealth with the top 1% accounting about half that with Social Security

Matthew Smith, Owen Zidar and Eric Zwick, “Top Wealth in the United States: New Estimates and Implications for Taxing the Rich,” National Bureau of Economic Research, July 19, 2019, http://ericzwick.com/wealth/wealth.pdf

Smith/Zidar/Zwick agree“…Overall, wealth is very concentrated: the top 1% holds as much wealth as the bottom 90%. However, the “P90-99” class holds more wealth than either group after accounting for heterogeneity. Relative to a top 0.1% wealth share of more than 20% under equal returns, we estimate a top 0.1% wealth share of and find that the rise since 1980 in top wealth shares falls by ….”

“Distribution Of Household Wealth In The U.S. Since 1989,” Distributional Financial Accounts Federal Reserve, Accessed September 8, 2020, https://www.federalreserve.gov/releases/z1/dataviz/dfa/distribute/chart/

This is directionally correct according to the Fed’s Z1 data the top 10% 68.7% of US wealth with the top 1% holding 31.2%, so presumably 96-99 get you there

“….5% own 2/3s of the wealth (sourced to oddly the NBER)….”

Bruce Meyer and James Sullivan, “Consumption And Income Inequality In The US Since The 1960s,” Center For Economics And Policy Research, January 15, 2018, https://voxeu.org/article/consumption-and-income-inequality-us-1960s

Meyer’s work on consumption inequality is also an effective rebuttal

Sylvain Catherine, Max Miller and Natasha Sarin, “Social Security and Trends in Inequality,” University of Pennsylvania, February 29, 2020, https://papers.ssrn.com/sol3/papers.cfm

Perhaps a better rebuttal is Sarin SS paper that found that wealth inequality has not increased in the past three decades after accounting for social security given she is Summer’s protégé

Gerald Auten and David Splinter, “Income Inequality in the United States: Using Tax Data to Measure Long-term Trends,” December 20, 2019, http://davidsplinter.com/AutenSplinter-Tax_Data_and_Inequality.pdf

Three recent paper’s come to mind that provide context, first the initial Auten/Splinter that found the top.1% income share had gone up, but not nearly as much as Saez suggests it has net taxes.

U.S. Census Bureau, “Income Gini Ratio For Households By Race Of Householder, All Races,” Federal Reserve Bank Of St. Louis, Accessed September 8, 2020, https://fred.stlouisfed.org/series/GINIALLRH

CBS is also citing Census which claims“The Gini index was significantly higher in 2018 than 2017 for the United States”but they are usingMedian Household Income showing.482 for 2017 and.485 for 2018.So that checks, even if we can point to the Household Gini to pushback.

According to FRED the Income Gini Ratio ForHouseholds By Race of Householders, All Racesticked down btw 2017 and 2018 (last year with available data from ) (from Census) from. 489 to.486

“…income inequality at highest level in 50 years Census 2109….”

Michael Strain, “Americans May Be Strapped, But the Go-To Statistic Is False,” Bloomberg, June 4, 2019, https://www.bloomberg.com/opinion/articles/2019-06-04/the-400-emergency-expense-story-is-wrong

  • Poverty/Crime
  • Workforce
    • Inequality
    • Unemployment/Participation
    • Wages/Income

Income And Poverty In The Covid-19 Pandemic

AI Summary. The fiscal response to the Covid-19 pandemic is estimated to have reduced the poverty rate by 1.5 percentage points, or 14%, through Economic Impact Payments and expanded unemployment insurance benefits. Family income at the 25th percentile rose about $3,000 (6.4%), the median $2,500 (2.8%), and the 75th percentile $1,300 (0.9%).

Jeehoon Han, Bruce Meyer and James Sullivan National Bureau of Economic Research
Date Posted:
September 8, 2020
Is Database:
Database

Fiscal Response To Covid Pandemic Reduced Poverty Rate By 1.5 Percentage Points, or 14%.

How much did pandemic fiscal relief reduce poverty and raise incomes?

Core argument: The fiscal response to the Covid-19 pandemic reduced the poverty rate by 1.5 percentage points, or 14%, a statistically significant decline driven by Economic Impact Payments and enhanced Unemployment Insurance benefits.

The fiscal response to the Covid-19 pandemic significantly reduced the poverty rate by 1.5 percentage points, or 14%, marking a statistically significant decline. This reduction was driven by government interventions such as Economic Impact Payments and enhanced Unemployment Insurance (UI) benefits. The 25th percentile of family income rose from about $46,000 in early 2020 to approximately $49,000 by mid-year, a $3,000 increase or 6.4%, reflecting the impact of these fiscal measures. Median income also saw a rise of $2,500 (2.8%), while the 75th percentile experienced a modest increase of $1,300 (0.9%). These income gains highlight the effectiveness of fiscal policies in mitigating economic hardships during the pandemic, particularly for lower-income families who benefited from targeted government support.

Takeaways by Macro Roundup® AI

  1. The fiscal response to the Covid-19 pandemic reduced the poverty rate by 1.5 percentage points, or 14%, a statistically significant decline driven by Economic Impact Payments and enhanced Unemployment Insurance benefits.
  2. Family income at the 25th percentile rose from about $46,000 in early 2020 to roughly $49,000 by mid-year, a $3,000 or 6.4% increase attributed to pandemic fiscal measures.
  3. Median family income rose $2,500, or 2.8%, while income at the 75th percentile rose $1,300, or 0.9%.

Meyer’s finds that the fiscal response to the Covid 19 pandemic lead to a fall in poverty of 1.5 percentage points:

“…The results in Figure 1 indicate that poverty was falling fairly steadily in the period leading up to the pandemic. Between November 2019 and February 2020, poverty fell by 0.9 percentage points. This decline then accelerates once the pandemic hits. Between the pre and post periods poverty fell by 1.5 percentage points (or about 14 percent), and this difference is statistically significant…”

Steve Post

Academic Paper

Government Spending

Business Cycle

Poverty/Crime

Wages/Income

Factoid

Suggusted Tags

Jeehoon Han, Bruce Meyer and James Sullivan, “Income And Poverty In The Covid-19 Pandemic,” National Bureau Of Economic Research, August 2020, https://www.nber.org/papers/w27729.pdf

“…Looking beyond poverty estimates, we also consider how the COVID-19 pandemic affected different points in the distribution of income. In Figure 2 we report estimates of the 10th, 25th, 50th, and 75th percentiles of family income (equivalized to a family with 2 adults and 2 children) for the period from January 2019 to June 2020. Then, in Table 2, we report estimates of the 25th percentile for each month between January and June of 2020, as well as changes in the 25th percentile between the pre-and post-onset of COVID-19 periods. Results similar to those in Table 2 but for the 50th and 75th percentiles are reported in Appendix Tables 8 and 9. The results in Figure 2 show that income for each of the percentiles we report remains flat for the period from January 2019 through February 2020. Then, incomes start to rise after that. The 25th percentile of family income increased from about $46,000 in January and February to about $49,000 in April, May, and June, a statistically significant increase of about $3,000, or 6.4 percent (Table 2).11 This increase seems reasonable given the government benefits low income families were potentially eligible for, including a $3,400 Economic Impact Payment (for a married couple with two children) and UI benefits that included a $600 per week top off. We also see a rise in income at higher percentiles, although the extent of the rise is smaller as we move up the distribution. Median income (Appendix Table 8) rose by about $2,500 (2.8 percent) during this period and this rise is statistically significant. At the 75th percentile (Figure 2 and Appendix Table 9), incomes rose more modestly, by about $1,300 (0.9 percent), and this rise is not statistically significant.A rise in income at the 75th percentile would not be too surprising given that those with incomes at this level would potentially still be eligible for the expanded government benefits. The equivalized income values for the 75th percentile are about $145,000 for a married couple with 2 children and about $65,000 for an individual. These values are below the income thresholds for receiving the full amount of the Economic Impact Payment….”

Meyer’s also looks at the distributional impact of the fiscal response, found the 25 percentile of family income saw an ~ $3,000 gain

  • Government Spending
  • GDP
    • Business Cycle
  • Workforce
    • Poverty/Crime
    • Wages/Income

Wednesday, September 9, 2020

What harm do minimum wages do?

AI Summary. Research finds higher minimum wages are not inherently harmful to employment: in fast food a 10% increase in the wage floor raises prices by about 0.9%, and one study found no effect on grocery prices from large wage hikes. Another study suggests firms treating higher wages as permanent may automate more, potentially slowing employment growth.

Economist Staff The Economist
Date Posted:
September 9, 2020
Is Database:
Database

Higher minimum wages can sometimes boost employment, but this isn’t always the case. A 10% wage hike in competitive sectors raises prices by only 0.9%.

Do higher minimum wages harm employment and raise prices?

Core argument: In competitive sectors such as fast food, a 10% increase in the minimum wage raises prices by 0.9%, while the price impact varies across other markets.

While higher minimum wages can sometimes lead to increased employment, this is not universally the case. In competitive sectors like fast food, a 10% wage floor increase raises prices by only 0.9%, but in other markets, the impact varies. A 2019 study in Seattle found no effect on grocery prices from significant wage hikes. Economists now recognize that higher minimum wages are not inherently detrimental, yet they caution against assuming they are always beneficial. A 2018 study suggested that if firms view higher wages as permanent, they may automate more, potentially reducing employment growth long-term. Policymakers must balance raising the wage floor without hitting economic ceilings, considering both short-term and long-term effects on employment and automation trends.

Takeaways by Macro Roundup® AI

  1. In competitive sectors such as fast food, a 10% increase in the minimum wage raises prices by 0.9%, while the price impact varies across other markets.
  2. A 2019 study of Seattle found no effect on grocery prices from significant minimum wage increases.
  3. A 2018 study suggested that firms treating higher wages as permanent may automate more, potentially reducing employment growth over the long term.

Economist who pays the minimum wage, “..In theory a higher cost base could be passed on to consumers through higher prices, or absorbed by employers through lower profit margins. In reality the answer varies by market. In competitive sectors, such as fast food, research has found that a 10% increase in the wage floor pushes up burger prices by just 0.9%. In 2019 a study of supermarkets in Seattle found no impact on grocery prices from big increases…”

On the overall state of play of the research, "...Economists no longer think higher minimum wages are always bad. But that is not the same as saying they are always good. In 2018 a paper by Isaac Sorkin and others cautioned policymakers to take a longer-term view, rather than worry about short-term unemployment. Its authors found that if firms perceived a higher wage floor to be permanent and unlikely to be eroded by inflation, it could encourage them to automate more and decrease employment growth in the future. The idea that a minimum wage can sometimes lead to higher rather than lower employment does not mean it always will.When pushing up the floor, policymakers need to ensure they do not hit the ceiling...."

Economist Staff, "What harm do minimum wages do?,"The Economist, August 13, 2020, https://www.economist.com/schools-brief/2020/08/13/what-harm-do-minimum-wages-do

  • Minimum Wage
  • Comparisons
    • Cross-country
  • Workforce
    • Unemployment/Participation
    • Wages/Income

people are really sensitive to estate taxes but in estate tax case its still net positive in term of revenue outside of CA We estimate the revenue costs and benefits for each state of having an estate tax.

AI Summary. State estate taxes are estimated to generate net positive revenue for most states, with California the exception, as one-time revenue collected when wealthy residents die outweighs income tax revenue lost to those who relocate. Research finds high earners are sensitive to tax changes, with migration eroding 45.2% of windfall revenue from one California reform.

Daniel Wilson American Economic Review
Date Posted:
September 9, 2020
Is Database:
Database

Estate taxes yield net positive revenue for most states, with California as the exception. Despite high tax mobility, the one-time revenue gain outweighs foregone income tax revenues.

Do state estate taxes raise net revenue despite wealthy residents relocating?

Core argument: Estate taxes are estimated to generate net positive revenue for most states except California, as the one-time revenue gain at a wealthy resident's death outweighs income tax revenues forgone when high earners relocate.

Despite high tax mobility, estate taxes yield net positive revenue for most states, with California as the exception. The benefit of estate taxes is the one-time revenue gain upon a wealthy resident's death, outweighing the foregone income tax revenues from those who relocate. Research indicates that while high earners are sensitive to tax changes, the overall economic impact of state personal income tax levels on growth is minimal. In California, migration of high earners eroded 45.2% of windfall tax revenues from a 2013 reform. However, for states without estate taxes, adopting them would result in revenue gains, highlighting the potential fiscal benefits of estate taxation despite taxpayer sensitivity.

Takeaways by Macro Roundup® AI

  1. Estate taxes are estimated to generate net positive revenue for most states except California, as the one-time revenue gain at a wealthy resident's death outweighs income tax revenues forgone when high earners relocate.
  2. Migration of high earners eroded 45.2% of the windfall tax revenues from California's 2013 tax reform.
  3. States without estate taxes would see revenue gains from adopting them, and research indicates the overall economic impact of state personal income tax levels on growth is minimal even though high earners are sensitive to tax changes.

As requested reviewed Stiglitz’s claims from his NYT op-ed. Here they are with context.

Steve

“…So far, states and localities have responded by slashing spending and jobs, with 1.5 million public-sector workers laid off by the end of June….”

According to BLS this checks for the end of June (-1.444mm)worth noting there has been a rebound however to -1.127mm from February

Kitty Richards and Joseph Stigliz, "Doesn't Feel LIke A Recession? You Should Be Paying More In Taxes,"New York Times, September 3, 2020, https://www.nytimes.com/2020/09/03/opinion/sunday/progressive-policies-taxes.html

Enrico Motetti Daniel Wilson, “Taxing Billionaires: Estate Taxes and Geographical Location of the Ultra-Wealthy,” National Bureau Of Economic Research, https://eml.berkeley.edu/~moretti/billionaires.pdf

Wesley Tharpe, “Rising State Income Tax Rates at the Top a Sensile Way to Fund Key Investments,” Center On Budget and Policy Priorities, February 7, 2019, https://www.cbpp.org/research/state-budget-and-tax/raising-state-income-tax-rates-at-the-top-a-sensible-way-to-fund-key

"...The bulk of mainstream academic research finds that interstate differences in taxes, including differences in top personal income tax rates, have minimal effects on state economic growth. Fifteen of the 20 major studies published in academic journals since 2000 that examined the broad economic effect of state personal income tax levels found no significant effects and one of the others produced internally inconsistent results. As a pair of university researchers described in a comprehensive literature review in 2018, “The vast majority of the academic studies that examined the relationship between state and local taxes and economic growth found little or no effect.”..."

They cite for proposition

Joshua Rauh and Ryan Shyu, "Behavioral Responses to State Income Taxation of High Earners: Evidence from California," National Bureau of Economic Research, October 2019, https://www.nber.org/papers/w26349

“.. Our estimates imply an intensive margin elasticity of 2013 income with respect to the marginal net-of-tax rate of 2.5 to 3.3. Among top-bracket California taxpayers, outward migration and behavioral responses by stayers together eroded 45.2% of the windfall tax revenues from the reform in 2013, with the extensive margin accounting for 9.5% of this total response…”

NBER from 2019 looking at CA found migration of high earners out of state cost the state half the estimated increase in tax revenue

“…We estimate the revenue costs and benefits for each state of having an estate tax. The benefit is the one-time tax revenue gain when a wealthy resident dies, while the cost is the foregone income tax revenues over the remaining lifetime of those who relocate. Surprisingly, despite the high estimated tax mobility, we find that the benefit exceeds the cost for the vast majority of states. Of the states that currently do not have estate taxes, all but one would experience revenue gains if they adopted estate taxes,with California the only exception….”

Moretti, rich people are really sensitive to estate taxes (but in estate tax case it’s still net positive in term of revenue outside of CA)

Enrico Motetti and Daniel Wilson, “The Effect Of State Taxes on the Geographical Location of Top Earners: Evidence from Start Scientists,”American Economic Review, 2017, https://eml.berkeley.edu/~moretti/taxes.pdf

We’ll see! Moretti’s cutting edge research begs to differ, “…We quantify how sensitive is migration by star scientists to changes in personal and business tax differentials across states. We uncover large, stable, and precisely estimated effects of personal and corporate taxes on star scientists’ migration patterns.The long-run elasticity of mobility relative to taxes is 1.8 for personal income taxes, 1.9 for state corporate income tax, and −1.7 for the investment tax credit. While there are many other factors that drive when innovative individuals and innovative companies decide to locate, there are enough firms and workerson the margin that state taxes matter….”

“…economic evidence shows that even in boom times progressive state tax increases don’t harm state economies or lead rich people to flee...."

Hayley Brown and Dean Baker, “Cutting State And Local Budgets Is An Attack On The Country’s Black Workers,” Center For Economic And Policy Research, June 16, 2020, https://cepr.net/cutting-state-and-local-budgets-is-an-attack-on-the-countrys-black-workers/

“…One dimension of this fiscal crisis that has not received the attention it deservesis that the state and local government workforce is disproportionately Black.In 2019, 14.0 percent of state and local government workers were Black; that is 2.4 million out of 17.2 million workers. This compares to 11.7 percent of the private sector workforce. All else being equal, the workers who lose their jobs as a result of layoffs in the public sector are 20 percent more likely to be Black than workers who lose their jobs in the private sector….”


“….They have also lost jobs and seen their incomes drop at a higher rate than white Americans, and they are disproportionately affected by public-sector layoffs….”

Richard Oppel, Robert Gebeloff, K.K. Rececca Lai, Will Wright, and Mitch Smith, “The Fullest Look Yet At The Racial Inequity Of Coronavirus,” New York Times, July 5, 2020, https://www.nytimes.com/interactive/2020/07/05/us/coronavirus-latinos-african-americans-cdc-data.html

“..And Black and Latino people have been nearly twice as likely to die from the virus as white people, the data shows…”

Checks


“…Black and Latino Americans have been infected with the coronavirus at three times the rate of whites, and died from the disease twice as often….”

Dylan Grundman and Meg Wiehe, “State Options To Shore Up Revenues And Improve Tax Codes Amid Pandemic,” Institute On Taxation And Economic Policy, April 2020, https://itep.sfo2.digitaloceanspaces.com/041520-State-Options-to-Shore-Up-Revenue-2.pdf

This will vary by state depending on how regressive tax code is. Attributed to“…ITEP’s 2018 Who Pays? report found on average, the lowest income 20 percent of taxpayers face a state and local tax rate more than 50 percent higher than the top 1 percent of households….”


“…The bottom 20 percent of earners pay, on average, a state and local effective tax rate more than 50 percent higher than that paid by the top one percent….”

U.S. Census Bureau, “Household Pulse Survey Data Tables,” Accessed September 9, 2020, https://www.census.gov/programs-surveys/household-pulse-survey/data.html

For household making more than 200k 9.5mm saw no loss out of 13.8mm69%

See employment table 1 135mm household saw no loss of income since march 13, 2020 out of 249mm households,54%

This checks


“…Tens of millions of workers have lost their jobs since the beginning of the Covid-19 crisis, but almost half of Americans report that their household has not lost any employment income at all, according to Census Bureau data. That figure jumps to two-thirds for households bringing home more than $200,000 per year….”

Misty Heggeness and Jason Fields, “Working Moms Bear Brunt Of Home Schooling While Working During COVID-19,” U.S. Census Bureau, August 18, 2020, https://www.census.gov/library/stories/2020/08/parents-juggle-work-and-child-care-during-pandemic.html

True according to Census


“…One in five out-of-work adults has stopped working because of the need to supervise online learning or care for younger children…”

Elise Gould, “Public Education Job Losses In April Are Already Greater Than In All Of The Great Recession,” Center For Budget And Policy Priorities, June 3, 2020, https://www.epi.org/blog/public-education-job-losses-in-april-are-already-greater-than-in-all-of-the-great-recession/

From your old friend Elise Gould also using NCES not BLS numbers


‘…As of mid-May, public-sector layoffs had already surpassed their total for the entire Great Recession. With the school year still going, more than 750,000 K-12 education employees had already lost their jobs….”

Nicholas Johnson, “The Great Recession Badly Hurt Kids’ Schooling; Today’s Recession Could Do Much Worse,” Center For Budget And Policy Priorities, May 27, 2020, https://www.cbpp.org/blog/the-great-recession-badly-hurt-kids-schooling-todays-recession-could-do-much-worse

Bureau Of Labor Statistics, “Employed full time: Wage and salary workers: Preschool and kindergarten teachers occupations: 16 years and over, Employed full time: Wage and salary workers: Elementary and middle school teachers occupations: 16 years and over, Employed full time: Wage and salary workers: Secondary school teachers occupations: 16 years and over,“ Federal Reserve Bank Of St. Louis, Accessed September 9, 2020, https://fred.stlouisfed.org/graph/

According toBLS teachers series(so this is the sum of three series employed fulltime, preschool/kindergarten, elementary/middle school, and secondary school teachers) there were 4.54mm teachers in 2019, versus 4.111mm in 2007so +.429mmneed to spend some time squaring the numbers given this isn’t capturing non-facility employees (note he is using NCES data and I used BLS).

Note this isall employeesso it’s capturing maintenance staff and administrators

This is from CBPP,“…The last time that states faced a budget crisis, in the wake of the Great Recession of a decade ago, emergency federal aid closed only about one-quarter of state budget shortfalls. Once the aid was gone, states started cutting funding to K-12 schools to help comply with their balanced budget requirements. By 2011, 17 states hadcutper-student funding by more than 10 percent. Local school districts responded by cutting teachers, librarians, and other staff; scaling back counseling and other services; and even reducing the number of school days. Even by 2014 — five years after the Great Recession ended — state support for K-12 schools in most states remained below pre-recession levels. School districts have never recovered from the layoffs they imposed back then. When COVID-19 hit, K-12 schools employed 77,000 fewer teachers and other workers even though they were teaching 2 million more children, andoverall funding in many states was still below pre-Great Recession levels….”

“….Just before the pandemic, public school systems had two million more students in kindergarten through 12th grade than before the Great Recession, and 77,000 fewer employees to teach them and run their schools….”

Josh Bivens, “A Prolonged Depression Is Guaranteed Without Significant Federal Aid To State And Local Governments,” Economic Policy Institute, May 19, 2020, https://www.epi.org/blog/a-prolonged-depression-is-guaranteed-without-significant-federal-aid-to-state-and-local-governments/

The counterfactual comes from Josh Biven’s logic here:“…If one takes the trajectory of spending that characterized the 1980s and assumes this had been replicated after the 2009 recovery began, state and local spending would have been$800 billion higher by the first quarter of 2013.At that point in the recovery, unemployment was still at 8%and the Federal Reserve was years away fromthinking about raising interest rates. This means that this extra spending, if financed by federal aid, would have translated directly into extra economic output and jobs. $800 billion in spending, even with modest multipliers,would have supported roughly 8 million more jobsin that year, enough to restore the economy to pre-crisis unemployment rates (4.4%) even with higher labor force participation than prevailed in 2013. In short, state and local spending austerityby itselfdelayed the recovery to pre-Great Recession unemployment rates by probably about4 years….”

“…Had federal assistance enabled state and local spending to recover fully, the unemployment rate would have dropped to 4.4 percent in 2013, but instead we didn’t hit that level until 2017….”

They don’t attribute either of these two calculation to anything, and I can’t find numbers from CBO report that line up with their arithmetic.

“….Tax increases, especially on high-income people who aren’t living paycheck to paycheck, are much less economically damaging, costing the economy only around 35 cents for every dollar raised….”

“…States and localities that raise taxes on the rich to increase spending will create at least $1.15 of economic activity for every dollar raised, and most likely closer to $2.15 or more….”

Elizabeth McNichol and Michael Leachman, “States Continue To Face Large Shortfalls Due To COVID-19 Effects,” Center On Budget And Policy Priorities, July 7, 2020, https://www.cbpp.org/sites/default/files/atoms/files/6-15-20sfp.pdf

They attribute this to a CBPP report which finds a $555 billion shortfall over FY 2020-2022, with -$290 for this FY (FY 2021 started in July for most states)So I think what this is $-290b in cuts *1.5 (CBO multiplier) =-$435b impact on GDP.

“…With state budget shortfalls forecast to approach $300 billion this fiscal year, a spending-cut-only approach to balancing state budgets will cause at least a $450 billion reduction in G.D.P.— more than 2 percent….”

Felix Reichling, “Estimated Impact Of The American Recovery And Reinvestment Act On Employment And Economic Output In 2014,” Congressional Budget Office, February 2015, https://www.cbo.gov/sites/default/files/114th-congress-2015-2016/reports/49958-ARRA.pdf

At one point the report says, “…Similarly,if a dollar in aid to a state government leads that government to spend 50 cents more on employees’ salaries (but causes no other changes in state spending or revenues, with the other 50 cents used to reduce borrowing or build up rainy-day funds), the direct impact on output is 50 cents…”so perhaps that implies a $1 cut leads to $1.5 impact on GDP.

Not quite sure about this one, they are citing a CBO analysis of the stimulus bill. However CBO estimated transfers to state budget’s had a high multiplier of 1.8 not 2.5, now maybe cuts as opposed to transfers (presumably offsetting cuts) have a more pronounced impact.

“…Using conservative estimates, these ripple effects mean that each dollar of spending the state cuts leads to a drop of at least $1.50 in the gross domestic product, and there are reasons to believe that the drop is as much as $2.50…”

U.S. Bureau Of Labor Statistics, “All Employees Lobal Government, All Employees State Government,” Federal Reserve Bank Of St. Louis, Accessed September 9, 2020, https://fred.stlouisfed.org/graph/

  • Business Cycle

The Return of Big Chinese Surpluses And Large U.S. Deficits Council on Foreign Relations

AI Summary. Global goods trade imbalances are now concentrated in a large Chinese surplus and a similarly large U.S. deficit, according to high-frequency trade data. Other imbalances have compressed, with Europe's surplus smaller and oil-exporting economies shifting into deficit amid lower oil prices.

Brad Setser Council on Foreign Relations
Date Posted:
September 9, 2020
Is Database:
Database

China dominates global trade surpluses, while the US leads in deficits, marking a new pattern in international trade dynamics.

Are global trade imbalances now concentrated in China and the US?

Core argument: High-frequency analysis of global goods trade shows China dominating the surplus side of post-pandemic trade imbalances while the United States leads on the deficit side.

Post-pandemic global trade imbalances are now primarily characterized by significant Chinese surpluses and large U.S. deficits. A high-frequency analysis of global goods trade reveals that China dominates the surplus side, while the U.S. leads in deficits. The pandemic has compressed most other trade imbalances, with Europe's surplus declining and oil-exporting economies shifting to deficits due to lower oil prices. Consequently, from Q2 onwards, the global trade landscape is marked by China's substantial surplus and the U.S.'s equally large deficit, highlighting a new pattern in international trade dynamics.

Takeaways by Macro Roundup® AI

  1. High-frequency analysis of global goods trade shows China dominating the surplus side of post-pandemic trade imbalances while the United States leads on the deficit side.
  2. Most other trade imbalances have compressed since the pandemic, with Europe's surplus declining and oil-exporting economies shifting into deficit as oil prices fell.
  3. China's substantial goods trade surplus is matched by an equally large U.S. deficit, a pattern evident from the second quarter onward.

Brad Setser, “The Return Of Big Chinese Surpluses (Are Large U.S. Deficits), Council On Foreign Relations, September 7, 2020, https://www.cfr.org/blog/return-big-chinese-surpluses-and-large-us-deficits

Would think this new pattern open’s a window to work with the EU to combat Chinese trading practices.

On the surplus side it's basically China, and on the deficit side it's basically the United States, “…But at the end of the day, a high frequency plot of global goods trade imbalances now is essentially dominated by China on one side, and the United States on the other…”

Perhaps this will change but Brad's post-pandemic trade data is showing a new story of imbalances; Europe's surplus has fallen as a result of the pandemic, and lower oil prices have eliminated surplus among the oil exporting economies (some now run significant deficits), “…What’s striking though is thatthe pandemic has led to a compression of most other trade imbalances, so almost all that is left now is the big Chinese surplus (from q2 on) and the equally big U.S. deficit (from q2 on)…”

Ed Comment:china has gone nuts

  • Savings Glut/Trade Deficit


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