“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“A full-throated defense of economic dynamism.” - The Wall Street Journal
“Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
“…a 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
“…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
“…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
“There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
Evidence on college access, completion, fields of study, costs, admissions, student performance, and labor-market returns. The archive examines when higher education builds skills and how outcomes vary across students and institutions.
AI Summary.An analysis of federal aid recipients' tax-reported earnings finds the highest-earning bachelor's programs are concentrated at highly selective schools and in computer science, mathematics and electrical engineering. Nursing programs at several California schools produce graduates earning around $150,000 annually, placing them in the top 100 of nearly 25,000 programs analyzed.
Arfa Momin and Ron LieberNew York Times
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A HEA Group analysis of the earnings of 2018 and 2019 college graduates four years after graduation finds earnings are widely dispersed across schools in higher-earning fields such as computer science and economics and have a narrow dispersion in lower-earning fields such as English and drama.
Which college majors and schools produce the highest-earning graduates?
Core argument: HEA Group’s analysis of nearly 25,000 bachelor’s programs found computer science, mathematics and electrical engineering majors top the earnings list, with graduates of highly rejective schools including the Ivies, M.I.T., Stanford and U.C.L.A. dominating.
HEA Group tracked students who received federal financial aid and graduated during the 2017-18 and 2018-19 periods. The top of the earnings list is dominated by graduates of highly rejective schools — the Ivies and others, like M.I.T., Stanford and U.C.L.A. The majors that top the list are computer science, mathematics and electrical engineering. The income data come from whatever people reported on their federal tax returns. That means certain stock awards and other potential deferred compensation aren’t part of the totals. Nursing programs at a handful of California schools, including California State University, East Bay; San Francisco State University; and Samuel Merritt University, produce graduates earning around $150,000 annually, putting them in the top 100 out of the nearly 25,000 bachelor’s programs the HEA Group analyzed nationwide. They stick out amid quantitative and science majors from institutions like the California Institute of Technology and Cornell.
Takeaways by Macro Roundup® AI
HEA Group’s analysis of nearly 25,000 bachelor’s programs found computer science, mathematics and electrical engineering majors top the earnings list, with graduates of highly rejective schools including the Ivies, M.I.T., Stanford and U.C.L.A. dominating.
Nursing graduates of California State University, East Bay; San Francisco State University; and Samuel Merritt University earn around $150,000 annually, placing those programs in the top 100 amid quantitative and science majors from institutions like the California Institute of Technology and Cornell.
HEA Group tracked federal financial aid recipients who graduated during the 2017-18 and 2018-19 periods, using income reported on federal tax returns, which excludes certain stock awards and other potential deferred compensation.
Related Articles:
Do Adults Have the Skills They Need to Thrive in a Changing World?— An international assessment of adult skills describes numeracy proficiency levels ranging from counting objects and adding small whole numbers at the lowest level, to extracting information from tables and graphs and performing basic arithmetic with money and percentages at Level 1, up to analysing complex mathematical information and critically evaluating whether data support a claim at Level 5.
Have Humans Passed Peak Brain Power?— The share of Americans reporting they read a book in the past year has fallen below half, alongside declining performance in numeracy and problem-solving in most countries. The share of adults unable to use mathematical reasoning to evaluate the validity of statements averages 25% in high-income countries and 35% in the US.
Standardized Test Scores and Academic Performance at a Public University System— A study of a large public urban university system finds that high school grade point average is a far stronger predictor of student academic success than SAT scores, contrasting with analyses of highly selective colleges that found the SAT superior. Under-represented minority students were less likely to graduate within six years at every grade point average level.
AI Summary.An analysis of authors at a leading AI research conference finds China is the largest originating source of elite AI talent, with its share of researchers holding Chinese undergraduate degrees rising 11 percentage points to 57%, while the US share fell to 13%. The US remains a net importer of AI researchers, gaining 2,145 while China lost 1,729.
Damien Ma and Binyi YangCarnegie Endowment for International Peace
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Surveying education/employment histories of authors at the Neural Information Processing Systems conference, Ma and Yang infer China educated 57% of elite AI talent as of 2025, versus 13% for the US. Yet the US gained 2,145 researchers y/y while China lost 1,729.
Does China produce the most elite AI talent while America attracts it?
Core argument: Damien Ma and Binyi Yang find China’s share of elite AI talent, defined by undergraduate degrees earned in China, rose 11 percentage points to 57% in 2025 versus 2022, while the U.S. share fell to 13%.
[Using a methodology based on paper authors from the Neural Information Processing Systems conference (NeurIPS) Damien Ma and Binyi Yang find] China has established a commanding lead as the largest originating source of elite AI talent globally. Compared to 2022, the share of Chinese-origin AI talent, defined as those who received undergraduate degrees in China, increased 11 percentage points to 57% in 2025, while the U.S. share fell to 13%. The United States remains a magnet for global AI talent, particularly Chinese talent. Despite U.S.-China tensions, among AI researchers working in the United States, the 2025 share of those holding undergraduate degrees from China rose by 4 percentage points. When it comes to brain gain vs. brain drain, the United States saw a net gain of +2,145 researchers in 2025 while China registered a net loss of -1,729 researchers.
Takeaways by Macro Roundup® AI
Damien Ma and Binyi Yang find China’s share of elite AI talent, defined by undergraduate degrees earned in China, rose 11 percentage points to 57% in 2025 versus 2022, while the U.S. share fell to 13%.
Among AI researchers working in the United States, the share holding Chinese undergraduate degrees rose 4 percentage points in 2025, despite U.S.-China tensions.
The United States recorded a net gain of 2,145 AI researchers in 2025, while China registered a net loss of 1,729, under Ma and Yang’s methodology based on NeurIPS paper authors.
Related Articles:
China Lures Home Its Top AI Talent From Silicon Valley— Elite artificial intelligence researchers have left US firms including Google DeepMind and OpenAI for Chinese companies such as ByteDance, Tencent, and Alibaba. Three China- and San Francisco-based headhunters say they relocated more than 30 US-based researchers to China over 12 months, up from low single digits the prior year.
China and the Future Of Science— China graduates about 5x as many medical and biomedical students as the US each year, 7x as many engineers, and nearly double the number of science and engineering PhDs, while one-sixth to one-fifth of US science and engineering graduates are themselves Chinese. One study found returning Chinese scientists lead-author 2.5x more papers than peers who stay in the US.
Why Europe Produces Nobel Prize Winners but Not Elon Musks— Europe trains more engineering graduates per capita than China and more STEM PhDs than any region outside the United States, yet the only EU-born companies to reach $100bn market value in the past fifty years, Spotify and BioNTech, listed on US exchanges. Europe captures 6% of global AI startup funding versus 61% for the United States.
AI Summary.The unemployment rate for workers ages 22 to 34 without a college degree has rarely been lower in the past two decades, and relative to their own historical ranges the job market looks much better for blue-collar and manual-service workers. Degree-holders still face lower unemployment rates overall.
Theo Francis and Ray SmithWall Street Journal
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In 2026, the 12-month moving-average unemployment for college-educated 22–34-year-olds is above its post-2003 mean, while the rate for non-college peers is historically low. Prime-age college grads still have lower unemployment than those with no degree.
Is the job market unusually strong for workers without college degrees?
Core argument: The unemployment rate for workers ages 22 to 34 who never graduated from college has rarely been lower in the past two decades, based on data through July.
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.
Takeaways by Macro Roundup® AI
The unemployment rate for workers ages 22 to 34 who never graduated from college has rarely been lower in the past two decades, based on data through July.
Burning Glass chief economist Gad Levanon compared each cohort's current unemployment rate against its own range since 2003, and by that measure the job market looks much better for blue-collar workers in construction and manufacturing and for manual-service workers.
College graduates ages 25 to 54 averaged a 2.7% unemployment rate for the 12 months ending in July, below the 3.6% rate for workers with some college education and 4.7% for those with only a high-school diploma.
Related Articles:
College Grads Struggle to Find Jobs. Non-Grads Are Giving Up— The narrowing gap in unemployment rates between young college graduates and non-graduates appears driven mainly by non-graduates dropping out of the labor force rather than by diplomas losing value, since people not seeking work aren't counted as unemployed. The share of young non-graduates employed is 1.7 percentage points below pre-pandemic levels.
To Fix Education, Fix The Economy First— 30% of US adults have literacy skills typical of a 10-year-old, yet US workers scoring at that low level earn an average of nearly $30 an hour and two-thirds are employed, compared with about $20 and fewer than half employed in Britain. The author argues this reflects stronger economic growth rather than vocational education policy.
The College Wage Premium in the Generative AI Era— The U.S. college wage premium fell from 0.626 to 0.575 after four decades of expansion, implying the first sustained negative growth in relative demand for college-educated labor. The authors estimate that weaker wage growth in occupations highly exposed to artificial intelligence accounts for roughly 28% of that decline, though the patterns are not causal.
AI Summary.The U.S. college wage premium fell from 0.626 to 0.575 after four decades of expansion, implying the first sustained negative growth in relative demand for college-educated labor. The authors estimate that weaker wage growth in occupations highly exposed to artificial intelligence accounts for roughly 28% of that decline, though the patterns are not causal.
José Azar, Mireia Gine and Javier Sanz-EspínSocial Science Research Network
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The college wage premium flattened in the mid-2010s and has fallen ~8% since 2022. The authors argue that this compression reflects a broad decline in the returns to formal schooling, rather than a decline in the upper tail.
Is AI exposure driving the decline in the college wage premium?
Core argument: The U.S. college wage premium fell from 0.626 in 2022 to 0.575 in 2026 after expanding for four decades, with Current Population Survey data implying the first sustained negative relative demand growth for college labor.
After expanding for four decades, the U.S. college wage premium [dropped] sharply from 0.626 in 2022 to 0.575 in 2026. Current Population Survey data through 2026 implies an unprecedented drop in relative demand for college labor—the first sustained negative relative demand growth. Post-2022 wage growth slowed disproportionately in high-exposure occupations, which employ a disproportionate share of college graduates. By 2026, going from zero occupational AI exposure to full exposure had a negative effect on wages of−0.086. Combined with the college–non-college exposure gap, this mechanism accounts for roughly 28% of the total drop in the college wage premium from 2022 to 2026. While non-causal, these patterns indicate that task displacement in AI-exposed white-collar occupations plays a quantitatively meaningful role in the recent compression of the aggregate skill premium.
Takeaways by Macro Roundup® AI
The U.S. college wage premium fell from 0.626 in 2022 to 0.575 in 2026 after expanding for four decades, with Current Population Survey data implying the first sustained negative relative demand growth for college labor.
By 2026, moving from zero occupational AI exposure to full exposure had a -0.086 effect on wages, and combined with the college–non-college exposure gap this mechanism accounts for roughly 28% of the 2022–2026 drop in the college wage premium.
Post-2022 wage growth slowed disproportionately in high-exposure occupations that employ a disproportionate share of college graduates, patterns that, while non-causal, indicate task displacement in AI-exposed white-collar occupations plays a quantitatively meaningful role in compressing the skill premium.
Related Articles:
Looking for the Ladder— The article argues that the hiring downturn in occupations most exposed to generative AI reflects interest-rate sensitivity rather than AI itself, since roughly 38% of workers in the most AI-exposed quintile work in information, finance and insurance, and professional and technical services, versus under 2% in the least-exposed quintile.
How Students and Recent Grads are Responding to the Rise of AI— Undergraduate enrollment in degrees tied to the most AI-exposed jobs has risen 8%, indicating students are moving toward rather than away from fields exposed to artificial intelligence. A decline in computer science degrees is more than offset by growth in other exposed fields such as engineering.
AI and Young-adult Jobs: The Real Mystery— Employment rates have declined for young adults both with and without college degrees, with non-degree holders faring marginally worse, and employment growth for young workers of all education levels has lagged that of other workers. Artificial intelligence can replace some lower-skilled jobs, but those jobs are too few to drive youth labor market weakness.
AI Summary.The narrowing gap in unemployment rates between young college graduates and non-graduates appears driven mainly by non-graduates dropping out of the labor force rather than by diplomas losing value, since people not seeking work aren't counted as unemployed. The share of young non-graduates employed is 1.7 percentage points below pre-pandemic levels.
Justin FoxBloomberg
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Labor force participation is rising for American college graduates aged 25–29, and is now at 89.4% – above its pre-pandemic level. Participation among non-college members of that age cohort is falling; at 78.7%, it is now below its pre-pandemic level.
Is the narrowing unemployment gap driven by non-graduates leaving the workforce?
Core argument: The employment-population ratio for young adults without college degrees is 1.7 percentage points below its pre-pandemic level and trending downward, while the ratio for young college graduates sits near its pre-pandemic level.
The narrowing of [the unemployment gap btw college and non-college workers] in recent years has lent support to narratives that college diplomas are losing their value amid the rise of large language models, the purported return of blue-collar work, and other job market changes. But while it may well be that diplomas have lost value, the recent shrinking of the young-adult education-unemployment gap seems to be driven mainly by a different phenomenon. Growing numbers of young adults without college degrees simply aren’t trying to find work and thus aren’t counted in unemployment calculations. The employment-population ratio for young college grads is not far off from where it was just before the pandemic and seems as if it might be headed upward again after a sharp drop in 2023 and 2024, for non-grads it is 1.7 percentage points lower than before the pandemic and clearly trending downward.
Takeaways by Macro Roundup® AI
The employment-population ratio for young adults without college degrees is 1.7 percentage points below its pre-pandemic level and trending downward, while the ratio for young college graduates sits near its pre-pandemic level.
The narrowing unemployment gap between young college and non-college workers appears driven mainly by growing numbers of non-graduates who are not seeking work and therefore are not counted as unemployed.
The employment-population ratio for young college graduates fell sharply in 2023 and 2024 and appears as if it might be headed upward again.
Related Articles:
Labor Force Participation Is High If You Measure It Right— The headline labor force participation rate — the share of people 16 and older working or looking for work — is a limited gauge of labor market health because participation varies greatly by age. Aging baby boomers and the addition of nearly 1.7m Americans 65 and older to population estimates add distortion.
How Labor Force Participation Has Diverged Across Genders— Between 1976 and 2024 the trend labor force participation rate fell 10.1 percentage points for men and rose 8.2 points for women. Population aging lowered participation by about 4 points for each gender and rising education raised it (+6 for women, +3 for men), but the divergence is dominated by participation trends within age-gender groups.
AI, Immigration, and Collapsing Labor Force Participation— As labor force participation falls, a shrinking group of workers generates the income, taxes, and innovation supporting a growing number of non-workers, leaving the economy more fragile because labor shocks are concentrated among fewer participants. Labor scarcity raises the return on automation, robotics, and software, making growth depend on productivity rather than participation.
AI Summary.Undergraduate enrollment in degrees tied to the most AI-exposed jobs has risen 8%, indicating students are moving toward rather than away from fields exposed to artificial intelligence. A decline in computer science degrees is more than offset by growth in other exposed fields such as engineering.
Sarah Eckhardt and Nathan GoldschlagAgglomerations
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Far from shying away from AI, American undergraduates “are flocking towards the most-AI-exposed degrees,” with enrollment in these majors up 8% last year compared to 2017.
Are students moving toward or away from degrees exposed to AI?
Core argument: Undergraduate enrollment in the most-AI-exposed degrees rose 8% last year compared with 2017, indicating students are moving toward fields whose likely jobs have greater AI exposure.
Are students shying away from fields that have more exposure to AI, perhaps worried that AI will shrink the number of jobs available to them? Or are students shifting towards those fields, preparing for a future in which they will have to be comfortable using AI? To find out, we can check enrollment for groups of degrees based on the AI exposure of the jobs that students with those degrees are likely to take, as shown in Figure 1. As is clear, undergraduates are flocking towards the most-AI-exposed degrees, with enrollment in those degrees up 8% last year compared to 2017. This trend holds despite a notable decline in Computer Science degrees, one of the most-AI-exposed degrees, but whose decline is more than offset by increases in other exposed degrees like Engineering.
Takeaways by Macro Roundup® AI
Undergraduate enrollment in the most-AI-exposed degrees rose 8% last year compared with 2017, indicating students are moving toward fields whose likely jobs have greater AI exposure.
Computer Science, one of the most-AI-exposed degrees, saw a notable enrollment decline that was more than offset by increases in other exposed fields such as Engineering.
Grouping degrees by the AI exposure of the jobs their graduates are likely to take offers a way to test whether students are avoiding or embracing AI-exposed fields.
Related Articles:
Attention (And Money) Is All You Need: Why Universities Are Struggling to Keep AI Talent— The annual compensation gap between top industry and academic artificial intelligence researchers widened from roughly $294,000 to $1.5m, coinciding with accelerating academic out-migration toward large incumbent technology firms. Researchers who move to industry cut paper production by about 63% while increasing patent filings nearly sixfold, consistent with a shift from open science toward proprietary innovation.
AI and Young-adult Jobs: The Real Mystery— Employment rates have declined for young adults both with and without college degrees, with non-degree holders faring marginally worse, and employment growth for young workers of all education levels has lagged that of other workers. Artificial intelligence can replace some lower-skilled jobs, but those jobs are too few to drive youth labor market weakness.
Tracking the Impact of AI on the Labor Market— US labor force survey data show occupational stability rather than economy-wide disruption from generative artificial intelligence, with the dissimilarity in occupational mix between older and more recent college graduates rarely deviating outside a 30–33% range. The authors note this limited early impact resembles the pace of change in previous periods of technological disruption.
AI Summary.A study of a large public urban university system finds that high school grade point average is a far stronger predictor of student academic success than SAT scores, contrasting with analyses of highly selective colleges that found the SAT superior. Under-represented minority students were less likely to graduate within six years at every grade point average level.
Theodore Joyce, Mina Afrouzi Khosroshahi, Sarah Truelsch, Kerstin Gentsch, et al.National Bureau of Economic Research
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SAT scores are known to be better predictors of college and post-college success in Ivy+ universities. By contrast, this study of a public urban university system with 11 colleges shows that for the 2010–2019 cohort, high school GPA strongly dominates SAT scores.
Do high school grades predict college success better than test scores?
Core argument: In a study of 2010–2019 cohorts at a large public urban university system, high school GPA predicts student academic success far better than the SAT, contrary to analyses of Ivy-plus colleges that found the SAT superior.
Many of the country’s most selective colleges have returned to requiring the SAT, based on evidence that the test not only predicts student success, but facilitates the identification of qualified applicants from disadvantaged backgrounds. The results from our study of a large public urban university system find the opposite: high school grades are a vastly superior predictor of student academic success than is the SAT. We undertake an exercise with binned scatter plots of six year graduation rates against HSGPA [High School Grade Point Average] stratified by URM [under-represented minority] and whether the student received the maximum Pell grant (Figures 1a and 1b). [Note that SAT is included in the regression so the monotonic linear effect of GDP remains after controlling for SAT score]. We find that URM are less likely to graduate in six years at every level of HSGPA than are non-URM. In contrast, we find no similar difference when we stratify the plot by whether the student received the max Pell grant or not, a strong proxy for a low-income household (Figure 1b). The clear takeaway from the analysis of the 2010-2019 cohorts is the dominance of HSGPA in predicting student academic success. The results are in direct contrast to recent high-profile analyses of students from Ivy-plus colleges that demonstrated the superiority of SAT over HSGPA in predicting not only first-year academic outcomes, but post-college success as well.
Takeaways by Macro Roundup® AI
In a study of 2010–2019 cohorts at a large public urban university system, high school GPA predicts student academic success far better than the SAT, contrary to analyses of Ivy-plus colleges that found the SAT superior.
Binned scatter plots of six-year graduation rates against high school GPA, controlling for SAT score, show under-represented minority students are less likely to graduate in six years at every level of high school GPA than non-URM students.
Stratifying six-year graduation rates by receipt of the maximum Pell grant, a proxy for a low-income household, shows no similar gap to the one found between under-represented minority and non-URM students.
Military Officer Quality in the All-Volunteer Force— The authors find a steady decline in U.S. Marine Corps officers' General Classification Test scores, which is statistically associated with the expansion of college attendance and explains 96% of the measured change. They also find a positive association between African American officers and mean test scores, arguing affirmative action has not lowered officer quality.
Do Adults Have the Skills They Need to Thrive in a Changing World?— An international assessment of adult skills describes numeracy proficiency levels ranging from counting objects and adding small whole numbers at the lowest level, to extracting information from tables and graphs and performing basic arithmetic with money and percentages at Level 1, up to analysing complex mathematical information and critically evaluating whether data support a claim at Level 5.
AI Summary.The authors estimate that students assigned teachers who inflate average grades have lower future test scores, high school graduation, college enrollment, and earnings, with a one standard deviation increase in a teacher's average grade inflation reducing the present value of students' lifetime earnings by $213,872. Inflating passing grades instead raises graduation with limited long-run effects.
Jeffrey Denning, Rachel Nesbit, Nolan Pope and Merrill WarnickNational Bureau of Economic Research
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Data from Los Angeles and Maryland linking high school, postsecondary, and earnings records suggest that one class-year with a teacher with 1 SD higher mean grade inflation reduces the PDV of their students’ lifetime earnings by ~$213,872.
How does teacher grade inflation affect students' long-term outcomes and earnings?
Core argument: The authors estimate that assignment to a teacher with one standard deviation higher average grade inflation reduces the present discounted value of students' lifetime earnings by $213,872 per year.
We develop two teacher-level measures of grade inflation: one measuring average grade inflation (the year-specific teacher fixed effect showing the teacher’s average contribution to grades after controlling for the student's contemporaneous performance in the focal subject as measured by the corresponding subject test score as well as prior test scores, prior grades, and other background characteristics), and another measuring a teacher's propensity to give a passing grade [which affects primarily students near the bottom of the distribution]. A [separate] cognitive value-added measure [included in the regressions] is a teacher fixed effect capturing how much a teacher raises students' standardized test scores relative to what would be predicted from the students' prior test scores and background characteristics. Grade-inflating teachers have moderately lower cognitive value-added and slightly higher noncognitive value-added. The two [grade-inflation] measures differentially impact students' long-term outcomes. Being assigned a higher average grade inflating teacher reduces a student's future test scores, the likelihood of graduating from high school, college enrollment, and ultimately earnings. A teacher with one standard deviation higher average grade inflation reduces the present discounted value [PDV] of lifetime earnings of their students by $213,872 per year. In contrast, passing grade inflation reduces the likelihood of being held back and increases high school graduation, with limited long-run effects. [Figure 7 in the gallery].
Takeaways by Macro Roundup® AI
The authors estimate that assignment to a teacher with one standard deviation higher average grade inflation reduces the present discounted value of students' lifetime earnings by $213,872 per year.
Higher average grade inflation by teachers lowers students' future test scores, high school graduation likelihood, college enrollment, and earnings, while passing-grade inflation instead reduces grade retention and raises high school graduation with limited long-run effects.
Grade-inflating teachers have moderately lower cognitive value-added, measured as a teacher's contribution to standardized test scores beyond what students' prior scores and background characteristics predict, and slightly higher noncognitive value-added.
Related Articles:
Steeper At The Top: Cognitive Ability and Earnings in Finland and Norway— Administrative data on over 350,000 men each in Finland and Norway show a convex relationship between earnings rank and cognitive ability measured by military conscription tests: top-percentile earners score about 1 standard deviation above median earners, who score about 0.5 above bottom-percentile earners. The lowest scores are almost absent among top earners.
Never Enough: Dynamic Status Incentives in Organizations— Data on over 5,000 German fighter pilots show performance rose markedly as pilots approached the eligibility threshold for each medal in a tiered awards ladder and slumped immediately after receiving it, with the effect repeating at each successive rung. The authors estimate the ladder added 3,000–5,000 aerial victories, 5–10% of the total.
Killer Incentives: Status Competition and Pilot Performance during World War II— Analysis of over 5,000 German World War II fighter pilots finds that public peer recognition was associated with higher victory scores among skilled pilots without higher mortality, while average pilots gained little in victories but died at higher rates. The authors conclude status-based awards can have uneven effects in high-risk settings.
