Results for “education” 2287 found
The antitrust case against U.S. higher education
Thirty prestigious independent American institutions of higher education were at some time members of the 568 higher education group (often labeled a cartel). Seventeen of them were sued by the U.S. Government and representative students who alleged that their meetings and deliberations resulted in collusion that caused students to pay higher prices. Twelve of the seventeen institutions subsequently settled their cases and by 2024 collectively had paid $284 million to do so. However, an inspection of these institutions’ pricing reveals that the median 568 Group institution lowered its average real net annual cost to its undergraduate students by 19.07% between 2009 and 2022. Further, this reduction was 1.70 times larger than the average real price reduction granted during the same period by the median institution among a sample of 475 other accredited, non-profit, independent four-year institutions and 11.63 times larger than the median price reduction granted by 78 public flagship state universities. The 568 group’s real price reductions stretched across every one of the five household income categories commonly used by the Government. Thus, there is little empirical support for the allegations that the Government has levied against the representative 568 group institution, and thus multiple members of this group appear to have paid unmerited fines to the Government to settle claims against them.
That is from a new paper by James V. Koch. Via the excellent Kevin Lewis.
What Explains Growing Gender and Racial Education Gaps?
In the 1960 cohort, American men and women graduated from college at similar rates, and this was true for Whites, Blacks and Hispanics. But in more recent cohorts, women graduate at much higher rates than men. Gaps between race/ethnic groups have also widened. To understand these patterns, we develop a model of individual and family decision-making where education, labor supply, marriage and fertility are all endogenous. Assuming stable preferences, our model explains changes in education for the ‘60-‘80 cohorts based on three exogenous factors: family background, labor market and marriage market constraints. We find changes in parental background account for 1/4 of the growth in women’s college graduation from the ’60 to ’80 cohort. The marriage market accounts for 1/5 and the labor market explains the rest. Thus, parent education plays an important role in generating social mobility, enabling us to predict future evolution of college graduation rates due to this factor. We predict White women’s graduation rate will plateau, while that of Hispanic and Black women will grow rapidly. But the aggregate graduation rate will grow very slowly due to the increasing Hispanic share of the population.
That is from a new NBER working paper by
Some history of higher education
To Dr. Damrosch, who has studied academic culture at colleges, the current turmoil was vaguely reminiscent of a 1940s episode at the school now known as Iowa State University.
The school’s economics department — in a paper on economic policy for wartime food production — had proposed replacing butter with margarine, said Dr. Damrosch. The dairy industry and its supporters in the state legislature “went ballistic,” he said, pressuring the school’s president to place the department under receivership.
The move triggered an immediate backlash and mass departure of faculty members.
It might have also played a small role in the reshaping of the higher education landscape: At least six professors fled to Chicago, where they helped build one of the most renowned economics departments in the world.
Here is the full NYT piece, mostly about Columbia, via Anecdotal.
Gender gaps in education and declining marriage rates
Over the past half-century, the share of men enrolled in college has steadily declined relative to women. Today, 1.6 million more women than men attend four-year colleges in the U.S. This trend has not lowered marriage rates for college women, a substantial share of whom have historically married economically stable men without college degrees. Both historical evidence and cross-area comparisons suggest that worsening male outcomes primarily undermine the marriage prospects of non-college women. The gap in marriage rates between college-and non-college women is more than 50% smaller in areas where men have the lowest rates of joblessness and incarceration.
That is from a new paper by Clara Chambers, Benny Goldman, and Joseph Winkelmann. Via the excellent Kevin Lewis.
Kevin Bryan and Joshua Gans have a new AI educational project
Just wanted to ping you about a tool Joshua Gans and I launched publicly today after a year of trials at universities all over the world (and just a stupid amount of work!) which I think is up your alley.
Idea is simple: AI should be 1) personalized to the student, 2) personalized to the professor’s content, and 3) structured to improve rather than degrade learning. In a perfect world, we want every student to have individual-level assistance, at any time, in any language, in the format they want (a chatbot TA, a question bank, a sample test grader, etc.). We want all assignments to be adaptive “mastery learning”. We want the professor to have insight on a weekly basis into how students are doing, and even into topics they may have taught in a somewhat confusing way. And we want to do this basically for free.
Right now, we have either raw GPT or Claude accomplishing 1 but not 2 or 3 (and some evidence it degrades learning for some students), or we have classes big enough to build custom AI-driven classes (like Khan Academy for basic algebra). For the thousands of classes where the professor’s teaching is idiosyncratic, the latter set of tools is basically “give the students a random textbook off the library shelf on the topic and have them study it” – not at all what I want my students to do!
We set up a team including proper UX designers and backend devs and built this guy here: https://www.alldayta.com/. It’s drag-and-drop for your course audio/video, slides, handouts, etc., preprocesses everything is a much deeper raw than raw OCR or LLMs, then preps a set of tools. Right now, there is a student-facing “virtual TA” and an autosummary weekly of where students are having trouble with the rest rolling out once we’re convinced the beta version is high enough quality. In my classes, I’ve had up to 10000 interactions in a term with this, and we ran trials at [redacted]. And we can do it at like a buck or two a student across a term, spun up in like 30 minutes of professor time for smaller courses.
There’s a free trial anyone can just sign up for; if your colleagues or the MR crowd would be interested, definitely send it along. I put a Twitter thread up about it as well with some examples of where we are going and why we think this is where higher ed is headed: https://x.com/Afinetheorem/status/1867632900956365307
Higher education is getting cheaper
That is the topic of my latest Bloomberg column, here is one excerpt:
There are a lot of numbers, but here is the comparison I find most impressive: Adjusting for grants, rather than taking sticker prices at face value, the inflation-adjusted tuition cost for an in-state freshman at a four-year public university is $2,480 for this school year. That is a 40% decline from a decade ago…
As might be expected, the trajectory for student debt is down as well. About half of last year’s graduates had no student debt. In 2013, only 40% did. That famous saying from economics — if something cannot go on forever, it will stop — is basically true. Due to changes in the formula, aid for Pell Grants is up, which helps to limit both student debt and the expenses of college.
Is quality going down? Probably a bit, but with a caveat:
,,,various adjustments kick in to limit the scope of the potential damage. Rather than cutting classes in computer science, a university might decide (as mine did) not to field a football team. Or a school might rely less on full-time professors and more on adjuncts. That is often a negative, but again schools can and do adjust, for instance by paying their adjuncts more and putting more effort into finding and keeping the good ones. A school might also reduce courses that attract few students and put more emphasis on subject areas with high enrollments.
Granted, none of this is ideal. But such adjustments can keep much of the damage at manageable levels. Many schools also are easing off their DEI bureaucracies.
And students will make adjustments of their own. If their classes give them less than what they want, they may turn more to the internet — to online education or, these days, AI. To argue that a large-language model is not as good as a professor is to miss the point. These innovations only have to make up some of the marginal deteriorations of quality.
With apologies to Peter Thiel, I believe U.S. higher education is going to muddle through.
Instructor value-added in higher education
On average, moving to a 1 standard deviation better instructor would increase a student’s next semester GPA by 0.13 points, and earnings six years after college entry by 17%. Strikingly, value-added is only weakly correlated with student evaluations. An instructor retention policy based on value-added would result in 2.7% higher earnings for students attending Texas universities.
That is from a new job market paper by Merrill Warnick, Jacob Light, and Anthony Yim from Stanford. Here is Warnick’s job market portfolio.
Further evidence for the babysitting theory of education
Bryan Caplan will feel vindicated:
This paper asks whether universal pre-kindergarten (UPK) raises parents’ earnings and how much these earnings effects matter for evaluating the economic returns to UPK programs. Using a randomized lottery design, we estimate the effects of enrolling in a full-day UPK program in New Haven, Connecticut on parents’ labor market outcomes as well as educational expenditures and children’s academic performance. During children’s pre-kindergarten years, UPK enrollment increases weekly childcare coverage by 11 hours. Enrollment has limited impacts on children’s academic outcomes between kindergarten and 8th grade, likely due to a combination of rapid effect fadeout and substitution away from other programs of similar quality but with shorter days. In contrast, parents work more hours, and their earnings increase by 21.7%. Parents’ earnings gains persist for at least six years after the end of pre-kindergarten. Excluding impacts on children, each dollar of net government expenditure yields $5.51 in after-tax benefits for families, almost entirely from parents’ earnings gains. This return is large compared to other labor market policies. Conversely, excluding earnings gains for parents, each dollar of net government expenditure yields only $0.46 to $1.32 in benefits, lower than many other education and children’s health interventions. We conclude that the economic returns to investing in UPK are high, largely because of full-day UPK’s effectiveness as an active labor market policy.
Here is more from Note by the way that these externalities end up internalized in higher wages for the parents, so at least in this data set there is no obvious case for public provision of a subsidized alternative.
Is assortative mating by education declining?
Recent social and economic trends in the United States, including increasing economic inequality, women’s growing educational advantage, and the rise of online dating, have ambiguous implications for patterns of educational homogamy. In this research note, we examine changes in educational assortative mating in the United States over the last eight decades (1940 to 2020) using the U.S. decennial censuses and the American Community Survey, extending and expanding earlier work by Schwartz and Mare. We find that the rise in educational homogamy noted by Schwartz and Mare has not continued. Increases in educational homogamy stalled around 1990 and began reversing in the 2000s. We find a growing tendency for marriages to cross educational boundaries, but a college degree remains the strongest dividing line to intermarriage. A key trend explaining this new pattern is women’s increasing tendency to marry men with less education than themselves. If not for this trend, homogamy would have continued increasing until the early 2010s. We also show substantial heterogeneity by race, ethnicity, and nativity and among same- versus different-sex couples.
That is from a new paper by Noah Hirschl, Christine R. Schwartz, and Elia Boschetti, via the excellent Kevin Lewis.
The Long-Run Impacts of Banning Affirmative Action in US Higher Education
This paper estimates the long-run impacts of banning affirmative action on men and women from under-represented minority (URM) racial and ethnic groups in the United States. Using data from the US Census and American Community Survey, we use a difference-in-differences framework to compare the college degree completion, graduate degree completion, earnings, and employment of URM individuals to non-URM individuals before and after affirmative action bans went into effect across several US states. We also employ event study analyses and alternative estimators to confirm the validity of our approach and discuss the generalizability of the findings. Results suggest that banning affirmative action results in a decline in URM women’s college degree completion, earnings, and employment relative to non-Hispanic White women, driven largely by impacts on Hispanic women. Thus, affirmative action bans resulted in an increase in racial/ethnic disparities in both college degree completion and earnings among women. Effects on URM men are more ambiguous and indicate significant heterogeneity across states, with some estimates pointing to a possible positive impact on labor market outcomes of Black men. These results suggest that the relative magnitude of college quality versus mismatch effects vary for URM men and women and highlight the importance of disaggregating results by gender, race, and ethnicity. We conclude by discussing how our results compare with others in the literature and directions for future research.
No comparison with the losers from these policies? And wasn’t the original motivation for these policies supposed to be for blacks? That is all from a new NBER working paper by
Andrej Karpathy is founding Eureka Labs, an AI education company
Here is the tweet, which connects to various links of relevance.
Website: eurekalabs.ai GitHub: github.com/EurekaLabsAI 𝕏:@EurekaLabsAI
Why is the Biden Administration Against Fee Transparency in Education?
President Biden has made a big deal of simplifying fees:
The FTC is proposing a rule that…would ban businesses from charging hidden and misleading fees and require them to show the full price up front. The rule would also require companies disclose up front whether fees are refundable. This would mean no more surprise resort fees at check out or unexpected service fees to buy a live event ticket.
Like everyone, I dislike these kinds of fees, although I don’t think they are a good subject for legislation. But I would certainly not prevent firms from offering a simple, up-front fee. And yet that is exactly what the Biden administration is doing in higher education.
So called Inclusive Access programs let colleges package textbooks with tuition and other fees. Students get one bill and access to textbooks on the first day of college. It’s convenient, no more hunting for textbooks or sticker shock. In addition, inclusive access programs give colleges bargaining power when negotiating prices.
Strangely, the Biden administration’s Department of Education wants to ban colleges from offering inclusive access programs. Thus, the Dept. of Education is arguing that simplified pricing is bad for consumers at the same time as the FTC is arguing that simplified pricing is good for consumers. What makes this contradiction even more baffling is that Inclusive Access was a program promoted in 2015 by the Obama-Biden Administration!
Proponents of the ban argue that letting students negotiate their own purchases lets them better tailor the outcome. Maybe, but that’s the same argument for letting airlines unbundle seat choice and baggage allowances. Hard to have it both ways. Pricing is complex.
Tyler and I are textbook authors so you might wonder where our interests lie. I actually have no idea. It’s complicated. I suspect inclusive access leads to a more winner-take-all market on textbooks. Modern Principles is a winner, thus on those grounds I would favor. More generally, however, I would get the FTC and the Dept. of Education out of pricing decisions and let colleges and firms negotiate. Pricing decisions are more complicated and contextual than simplified bans or regulations.
How is AI education going to work?
That is the topic of my latest Bloomberg column. Here is the first part of the argument:
Two kinds of AI-driven education are likely to take off, and they will have very different effects. Both approaches have real promise, but neither will make everyone happy.
The first category will resemble learning platforms such as Khan Academy, Duolingo, GPT-4, and many other services. Over time, these sources will become more multimedia, quicker in response, deeper in their answers, and better at in creating quizzes, exercises and other feedback. For those with a highly individualized learning style — preferring videos to text, say, or wanting lessons slower or faster — the AIs will oblige. The price will be relatively low; Khan Academy currently is free and GPT-4 costs $20 a month, and those markets will become more competitive.
For those who want it, they will be able to access a kind of universal tutor as envisioned by Neal Stephenson in his novel The Diamond Age. But how many people will really want to go this route? My guess is that it will be a clear minority of the population, well below 50%, whether at younger or older age groups…
Chatbots will probably make education more fun, but for most people there is a limit to just how fun instruction can be.
And the second part:
There is, however, another way AI education could go — and it may end up far more widespread, even if it makes some people uneasy. Imagine a chatbot programmed to be your child’s friend. It would be exactly the kind of friend your kid wants, even (you hope) the kind of friend your kid needs. Your child might talk with this chatbot for hours each day.
Over time, these chatbots would indeed teach children valuable things, including about math and science. But it would happen slowly, subtly. When I was in high school, I had two close (human) friends with whom I often talked economics. We learned a lot from each other, but we were friends first and foremost, and the conversations grew out of that. As it turns out, all three of us ended up becoming professional economists.
This could be the path the most popular and effective AI chatbots follow: the “friendship first” model. Under that scenario, an AI chatbot doesn’t have to be more fun than spending time with friends, because it is itself a kind of friend. Through a kind of osmosis, the child could grow interested in some topics raised by the AI chatbot, and the chatbot could feed the child more information and inspiration in those areas. But friendship would still come first.
Worth a ponder.
Finland education fact of the day
Returns to Education for Women in the Mid-20th Century: Evidence from Compulsory Schooling Laws
Abstract: Women had a similar level of schooling to men during the mid-twentieth century United States, but research on the returns to education for women is scarce. Using compulsory schooling laws as instrumental variables, this paper examines the causal effect of education on women’s labor market and marriage market outcomes. I examine both outcomes because women frequently traded off employment and marriage due to marriage bars and gender norms against married women working. I show that an additional year of schooling increases women’s probability of gainful employment by 7.9 pp. and women’s wage earnings by 15 percent, which can be explained by women’s entry into skilled occupations. Given the large returns on earnings, education surprisingly does not increase women’s probability of never marrying, but it does increase the probability of divorce and separation. In addition, women’s education positively affects the husband’s and the household’s labor supply and earnings, conditional on marriage formation and the husband’s education.
That is from Sophie Li, who is on the job market from Boston University. Her actual job market paper is: “The Effect of a Woman-Friendly Occupation on Employment: U.S. Postmasters Before WWII .” Some of you will wince to hear me say this, but many of the most interesting job market papers this year are on the economics of gender.