Making the Varsity Cut: Who Plays High School Varsity Sports and Who Doesn’t
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AI Summary. Firms' wage-setting norms are sticky, rising only from 2.7% to 3.5% even as inflation peaked near 7%, causing real wages for workers who stayed in their jobs to fall systematically. By the time inflation subsided, the median firm's wage rule had converged to ~3%, roughly matching inflation.
Core argument: Firm-level modal wage rules peaked at 3.5% in 2022–2023 against roughly 7% inflation, meaning nominal rigidity systematically eroded real wages for job stayers throughout the inflationary episode.
Roughly 42% of all nominal wage increases below 6% were within 0.01 percentage points of a whole or half number [Figure 6]. Figure 9 plots the employment-weighted average modal wage change across firms (solid line) alongside inflation rate (dashed line) from 2016 through 2025. In the pre-pandemic period, firm-level wage rules were relatively stable at a median of 2.7%, modestly above the rate of inflation. Beginning in 2021, inflation rose sharply, peaking at approximately seven percent in 2022. The average modal wage change also rose, reaching a peak of 3.5% in 2022 and 2023. By 2025, the median firm had a wage rule granting increases of three percent, roughly in line with inflation. The stickiness of firms’ wage rules in the face of inflationary pressure contributed to the systematic fall in real wages for job stayers. Evidence from Belgium [which has strong wage indexation], suggests that declining real wages, rather than inflation itself, helps explain the persistence of depressed consumer sentiment during the 2021–2024 period.AI Summary. Prime-age (25–54) and older (55–64) employment rates in Europe exceed those in the U.S., disproving the claim that European welfare systems suppress work. Higher-welfare northern European countries tend to have higher employment rates than lower-welfare southern ones.
Core argument: Prime-age adults (25–54) and older workers (55–64) both achieve higher employment rates in Europe than in the U.S., refuting the premise that generous welfare systems suppress labor force participation.
It does not matter whether you use EU or Eurozone data, prime-age adults (between 25 and 54) in Europe are more likely to be in work than those in the US. Older people (between 55 and 64) also have higher employment rates in Europe. Younger people (between 15 and 24) are more likely to have a job in the US, but that results from Europeans educating themselves for longer. The proportion of young people not in education, employment or training is higher in the US than in Europe. So welfare is not stopping work. More than that, the higher-welfare north of Europe tends to have higher employment rates than the south, although there is convergence within the Eurozone. Spain, in particular, has enjoyed rapid improvements.AI Summary. The Current Population Survey systematically understates income receipt, with nearly half of measured variables showing downward bias of 40% or more when benchmarked against administrative tax and program records. Bias is modest for Social Security programs (under 15%) but exceeds 40% for pensions, unemployment insurance, and food stamps.
AI Summary. AI-driven data-center expansion and related professional hiring have added roughly 1.05m jobs above trend since 2022–2023, spanning electrical contracting, equipment manufacturing, software development, and data science. The job gains exceed what broader construction, manufacturing, and professional employment trends would predict.
Core argument: AI-linked demand has generated roughly 730,000 above-trend jobs in engineering, software development, and data science since 2022, substantially outpacing near-term displacement effects.
[We] tracked five industries at the heart of the data-centre build-out, from electrical contracting to equipment manufacturing. Since 2023 employment in them has risen by roughly 320,000 more than broader construction and manufacturing trends would suggest. Not all of those jobs owe their existence to AI—grid upgrades and other factory building matters too. [We also] tracked employment in professional occupations closest to the AI boom—engineers, software developers, mathematicians and data scientists—and compared their growth since 2022 with professional employment overall. These roles have added roughly 730,000 jobs above trend in recent years. AI will not have created every single one of them. But it has almost certainly created quite a few.AI Summary. Non-college workers ages 22–34 are experiencing historically low unemployment relative to their own two-decade range, outperforming college-educated peers on that relative measure. College graduates still hold an absolute advantage, with a 2.7% unemployment rate versus 4.7% for high-school-only workers.
Core argument: Non-college workers ages 22–34 are experiencing one of their strongest job markets in two decades, with unemployment rates near historic lows relative to their own 2003–present range, outperforming their college-educated peers on that relative measure.
The unemployment rate for workers ages 22 to 34 who never graduated from college has rarely been lower in the past two decades. To gauge how the job market has shifted for each cohort, [Gad Levanon, Burning Glass’s chief economist] compared current unemployment rates for the different groups with their own range of unemployment rates since 2003. The analysis included data through July. By that measure, the job market looks much better for blue-collar workers, including those in construction and on manufacturing lines, and manual-service workers. It is [however] still easier to find a job with a college degree. The unemployment rate for degree-holders in their prime working years—ages 25 to 54—averaged 2.7% for the 12 months ending in July - well below the 3.6% rate for workers with just some college education, and 4.7% for people with a high-school diploma only.AI Summary. Global student performance in mathematics and reading has declined sharply since 2018, with reading scores falling 14 points and math scores falling 9 points between 2022 and 2025 alone.
Core argument: The share of “hasty readers” — students giving fast, incorrect responses — nearly doubled from 7% in 2018 to 11% in 2025, with math showing a parallel rise between 2022 and 2025, signaling deteriorating effort and engagement rather than pure skill loss.
In math, performance remained close to the 2003 level up to 2018, then dropped sharply btw 2018 and 2025. Mean performance dropped by 9 score points in mathematics and about 14 score points in reading btw 2022 and 2025. Over the 2018-2025 period, the largest drops [in reading] were among the most advantaged 25% of socio-economic status, and the socio-economic gap with the most disadvantaged students reduced somewhat, by 11 points, on average across 35 OECD countries. In mathematics, the share of disadvantaged students scoring below proficiency Level 2 increased in previous cycles and remained high in 2025; among advantaged students, the share scoring below proficiency Level 2 increased, reaching 18% in 2025, about 4pp. Students’ reports of their motivation for learning and engagement with school also declined between 2022 and 2025. The proportion of “hasty readers” – those who gave fast and incorrect responses – increased by about five percentage points, on average, from almost 7% in 2018 to 11% in 2025. Analyses for math, also show an increase in the proportion of hasty responses between 2022 and 2025.AI Summary. New York City's top 1% captured nearly two-thirds of real income growth between 2019 and 2024, versus under 40% nationally, driven by capital gains, dividends, and business income rather than wages.
Core argument: Nearly two-thirds of New York City’s real income growth from 2019–2024 accrued to the top 1%, versus under 40% nationally, driven by faster-rising capital gains, dividends, and business income rather than wage divergence.
Between 2019 and 2024, the New York City’s income shares at the top of the distribution rose faster than the nation's, and nearly two-thirds of the real income growth over the period accrued to the top 1%, compared with under 40% nationally. The result also holds when volatile capital gains are excluded. Real median income fell over the period, and real average income for the bottom 90% of tax units was essentially flat. Adjusted for local prices (but not for transfer programs), the purchasing power of income for the lower 90% of New Yorkers is close to one-fifth below that of the bottom 90% nationally. The divergence at the top is predominantly a story of non-wage income. Wage and salary income shows a much milder widening, and occupational wage data that exclude bonuses show base pay growing faster in lower-wage occupations than in higher-wage ones, and within many occupational groups wages are converging rather than growing more unequal.