Category: Education

Free Insurance for Everyone!

President Biden says “We’re planning to make it mandatory for airlines to compensate travelers with meals, hotels, taxis, and cash, miles, or travel vouchers when your flight is delayed or cancelled because of their mistake.”

A classic example of the Happy Meal Fallacy:

Some restaurants offer burgers without fries and a drink. These restaurants cater to low-income people who enjoy fries and drinks but can’t always afford them. To rectify this sad situation a presidential candidate proposes The Happy Meal Act. Under the Act, burgers must be sold with fries and a drink. “Burgers by themselves are not a complete, nutritious meal,” the politician argues, concluding with the uplifting campaign slogan, “Everyone deserves a Happy Meal!”

But will the Happy Meal Act make people happy? If burgers must come with fries and a drink, restaurants will increase the price of a “burger.” Even though everyone likes fries and a drink they may not like the added benefits by as much as the increase in the price of the meal. Indeed, this must be the case since consumers could have bought the meal before the Act but chose not to. Requiring firms to sell benefits that customers value less than their cost makes both firms and customers worse off.

Almost everyone understands this when it comes to burgers and fries but make it burgers, fries and air miles and some people will think this is a good idea. To recap, requiring firms to sell benefits that customers value less than their cost makes both firms and customers worse off. And if customers value the benefits at more than the cost then that’s a profit opportunity and there is no need for a mandate.

How to improve education

We present results from large-scale randomized trials evaluating the provision of education in emergency settings across five countries: India, Kenya, Nepal, Philippines, and Uganda. We test multiple scalable models of remote instruction for primary school children during COVID-19, which disrupted education for over 1 billion schoolchildren worldwide. Despite heterogeneous contexts, results show that the effectiveness of phone call tutorials can scale across contexts. We find consistently large and robust effect sizes on learning, with average effects of 0.30-0.35 standard deviations. These effects are highly cost-effective, delivering up to four years of high-quality instruction per $100 spent, ranking in the top percentile of education programs and policies.

That is from a new NBER working paper by Noam Angrist, et.al.

What should I ask Seth Godin?

I will be doing a Conversation with him.  Here is part of his bio:

A serial entrepreneur, Godin has a degree in computer science and philosophy from Tufts University, and an MBA from Stanford Business School. He runs the altMBA, a global business-thinking workshop, and founded two companies, Squidoo and Yoyodyne. In 2013, Godin was one of just three professionals inducted into the Direct Marketing Hall of Fame, and in May 2018 he was inducted into the Marketing Hall of Fame too.

Here is his “could be better” Wikipedia page.  Here is Seth’s blog.  So what should I ask him?

My Conversation with the excellent Kevin Kelly

Here is the audio, video, and transcript.  Here is part of the summary:

…Kevin and Tyler start this conversation on advice: what kinds of advice Kevin was afraid to give, his worst advice, how to get better at following advice, and whether people who ask for advice really want it in the first place. Then they move on to the best places to see traditional cultures in Asia, the one thing in Kevin’s travel kit he can’t be without, his favorite part of India, why he’s so excited about brain-computer interfaces, how AI will change religion, what the Amish can teach us about tech adoption, the most underrated documentary, his initial entry point into tech, why he’s impressed by the way Jeff Bezos handles power, the last thing he’s changed his mind about, how growing up in Westfield, New Jersey affected him, his next project called the Hundred Year Desirable Future, and more.

Here is one excerpt:

COWEN: Do you ever feel that if you don’t photograph a place, you haven’t really been there? Does it hold a different status? Like you haven’t organized the information; it’s just out on Pluto somewhere?

KELLY: Yes, I did. When I was younger, I had a religious conversion and I decided to ride my bicycle across the US. And part of that problem — part of the thing was that I was on my way to die, and I decided to leave my camera behind for this magnificent journey of a bicycle crossing the US. It was the most difficult thing I ever did, because I was just imagining all the magnificent pictures that I could take, that I wasn’t going to take. I took a sketchbook instead, and that appeased some of my desire to capture things visually.

But you’re absolutely right. It was a little bit of an addiction, where the framing of a photograph was how I saw the world. Still images: I was basically, in my head, clicking — I was clicking the shutter at the right moments when something would happen. That, I think, was not necessarily healthy — to be so dependent on that framing to enjoy the world.

I’ve learned to wean myself off from that necessity. Now I can travel with just a phone for the selfies that you might want to take.

COWEN: Maybe the earlier habit was better.

Recommended.  And here is Kevin’s new book Excellent Advice: Wisdom I Wish I’d Known Earlier.

Great News for Female Academics!

For decades female academics have been told that the deck is stacked against them by discrimination in hiring, funding, journal acceptances, recommendation letters and more. It’s dispiriting to be told that your career is not under your control and that, no matter what you do, you face an unfair, uphill battle. Why would any woman want to be a scientist when they are told things like this:

A vast literature….shows time after time, women in science are deemed to be inferior to men and are evaluated as less capable when performing similar or even identical work. This systemic devaluation of women women results in an array of real consequences: shorter, less praise-worth letters of recommendation, fewer research grants, awards and invitations to speak at conferences; and lower citation rates for their research…

The good news is that this depressing and dispiriting story isn’t true! In an extensive survey, meta-analysis, and new research, Ceci, Kahn and Williams show that the situation for women in academia is in many domains good to great. For example, in hiring for tenure the evidence is strong that women are advantaged. Moreover, women are advantaged especially in fields where they have relatively low representation (GEMP: geosciences, engineering, economics, mathematics/computer science, and physical science).

Among political scientists, Schröder et al. (2021) found that female political scientists had a 20% greater likelihood of obtaining a tenured position than comparably accomplished males in the same cohort after controlling for personal characteristics and accomplishments (publications, grants, children, etc.). Lutter and Schröder (2016) found that women needed 23% to 44% fewer publications than men to obtain a tenured job in German sociology departments.

…In summary, all of the seven administrative reports reveal substantial evidence that women applicants were at least as successful as and usually more successful than male applicants were—particularly in GEMP fields.

…In a natural experiment, French economists used national exam data for 11 fields, focusing on PhD holders who form the core of French academic hiring (Breda & Hillion, 2016). They compared blinded and nonblinded exam scores for the same men and women and discovered that women received higher scores when their gender was known than when it was not when a field was male dominant (math, physics, philosophy), indicating a positive bias, and that this difference strongly increased with a field’s male dominance. Specifically, women’s rank in male-dominated fields increased by up to 40% of a standard deviation. In contrast, male candidates in fields dominated by women (literature, foreign languages) were given a small boost over expectations based on blind ratings, but this difference was small and rarely significant.6

The situation is also very good in grant funding and journal acceptance rates which are either not biased or biased towards women. Similarly, “no persuasive evidence exists for the claim of antifemale bias in academic letters of recommendation.”

There is evidence of bias in student evaluations. Both female and male students rate male professors higher, even in situations where names are known but actual gender is blinded. Male students are more likely to write nasty comments. Most research universities, in my experience, don’t put much weight on student teaching evaluations, beyond do you pass a fairly low bar, but it can be disconcerting to get nasty comments.

There is also mild evidence of differences in salary, although less so when productivity is taken into account.

Some critics will say, but the real discrimination happens before a women applies for a tenure track job! Maybe so but that is a shifting of goal posts and we should take pride in the fact that in the United States today (and most developed countries) there is very little bias against women in high stakes, important decisions in tenure track hiring, journal acceptances, grant funding and so forth. This is a major accomplishment.

It should be noted that the Ceci, Kahn and Williams paper is an adversarial collaboration; Ceci and Williams have published previous work showing that women are, generally speaking, not discriminated against in academia while:

Kahn has a long history of revealing gender inequities in her field of economics, and her work runs counter to Ceci and Williams’s claims of gender fairness. Kahn was an early member of the American Economics Association’s Committee on the Status of Women in the Economics Profession (CSWEP). Articles of hers in the American Economics Review (Kahn, 1993) and in the Journal of Economic Perspectives (Kahn, 1995) were the first publications on the status of women in the economics profession. She was the first to identify gender inequities as a concern in economics, something she has revisited every decade since then in her publications. In 2019, she co-organized a conference on women in economics, and her most recent analysis in 2021 found gender inequities persisting in tenure and promotion in economics (Ginther & Kahn, 2021). In short, gender bias in academia has been a long-standing passion of Kahn’s. Her findings diverge from Ceci and Williams’s, who have published a number of studies that have not found gender bias in the academy, such as their analyses of grants and tenure-track hiring in Proceedings of the National Academy of Sciences (PNASCeci & Williams, 2011Williams & Ceci, 2015).

The Ceci, Kahn, and Williams paper covers much more material than I can cover here and is nuanced so read the whole thing but do also shout the good news from the rooftops!

The One-Child Policy and Intergenerational Mobility in China

We examine whether and how the world’s largest population planning program, the One-Child Policy, has shaped intergenerational mobility in China. Using a dataset with 2,096,798 childparent(s) pairs combined from various rounds of ten separate national household surveys, we leverage exogenous variation in fine rates imposed for One-Child Policy violations across provinces to study causal impacts of the One-Child Policy on intergenerational persistence. Using a continuous difference-in-differences approach, we find that for cohorts born between 1980 and 1996, the One-Child Policy reduced persistence in intergenerational income, education, and social class, comparing to those born prior to 1979. We estimate that the overall effect of the One-Child Policy fines was to reduce persistence in intergenerational income, education, and social class by 28.1%, 48.7%, and 24.8%, respectively. Analyzing mechanisms, we find that the One-Child Policy boosted China’s intergenerational mobility by diminishing elite family heirship, concentrating resources for lower-income families, and decreasing returns to education. The One-Child Policy has brought about a significant socioeconomic reshuffle that has reshaped the role of China’s longstanding class solidification.

That is from a recent paper by Shanthi Manian, Qi Zhang, and Bin Zhao.  Via Linghui Han.  Might some similar results be true for any other low-fertility societies?  Or are the environments too disparate?

Tenured professor has salary reduced to zero

Math professor Harold Donnelly is still listed on Purdue University’s website—but fellow math professors have shared something odd about his salary.

It’s $0, after the university began reducing it in fall 2021, according to emails these professors provided.

“I have carefully considered your career of contributions to mathematics and to our department, college and university,” says a July 2021 email from a math department head, whose name is redacted, about the first salary slash, a 20 percent cut. Irena Swanson, who was the department head then and now, didn’t return requests for comment Friday.

Here is the full story.  File under “What, no clawback!?”

Women’s colleges and economics majors

Many observers argue that diversity in Economics and STEM fields is critical, not simply because of egalitarian goals, but because who is in a field may shape what is studied by it. If increasing the rate of majoring in mathematically-intensive fields among women is a worthy goal, then understanding whether women’s colleges causally affect that choice is important. Among all admitted applicants to Wellesley College, enrollees are 7.2 percentage points (94%) more likely to receive an Economics degree than non-enrollees (a plausible lower bound given negative selection into enrollment on math skills and major preferences). Overall, 3.2 percentage points—or 44% of the difference between enrollees and non-enrollees—is explained by college exposure to female instructors and students, consistent with a wider role for women’s colleges in increasing female participation in Economics.

Here is the full NBER paper by Kristin F. ButcherPatrick McEwan Akila Weerapana.  And here is a new paper about the value of HBCUs.

Strong and Weak Link Problems and the Value of Peer Review

Adam Mastroianni’s has an excellent post on strong-link vs weak-link problems in science. He writes:

Weak-link problems are problems where the overall quality depends on how good the worst stuff is. You fix weak-link problems by making the weakest links stronger, or by eliminating them entirely.

Food safety is a weak link problem, bank or computer security is a weak-link problem, many production processes are weak-link, also called O-ring problems.

[But] some problems are strong-link problems: overall quality depends on how good the best stuff is, and the bad stuff barely matters….Venture capital is a strong-link problem: it’s fine to invest in a bunch of startups that go bust as long as one of them goes to a billion.

….Here’s the crazy thing: most people treat science like it’s a weak-link problem.

Peer reviewing publications and grant proposals, for example, is a massive weak-link intervention. We spend ~15,000 collective years of effort every year trying to prevent bad research from being published. We force scientists to spend huge chunks of time filling out grant applications—most of which will be unsuccessful—because we want to make sure we aren’t wasting our money.

These policies, like all forms of gatekeeping, are potentially terrific solutions for weak-link problems because they can stamp out the worst research. But they’re terrible solutions for strong-link problems because they can stamp out the best research, too. Reviewers are less likely to greenlight papers and grants if they’re novelrisky, or interdisciplinary. When you’re trying to solve a strong-link problem, this is like swallowing a big lump of kryptonite.

At Maximum Progress, Max Tabarrok has some nice diagrams illustrating the issue:

If you have a weak-link view of science, you’d think peer review works something like this. The relationship between quality and eventual impact is linear, or perhaps even bowed out a bit. Moving resources from low input quality projects to average ones is at least as important to eventual impact as moving resources from average projects to high quality ones.

In a strong-link model of science, filtering the bottom half of the quality distribution is less important to final impact [because the impact of research is highly non-linear].

Even though peer review has the same perfect filter on the quality distribution, it doesn’t translate into large changes in the impact distribution. Lots of resources are still being given to projects with very low impact. Although the average input quality increases by the same amount as in the weak link model, the average final impact barely changes. Since peer review has significant costs, the slightly higher average impact might fail to make up for the losses in total output compared to no peer review.

This is a simplified model but many of the simplifying assumptions are favorable for peer review. For example, peer review here is modeled as a filter on the bottom end of the quality distribution…But if peer review also cuts out some projects on the top end, its increase of the average impact of scientific research would be muted or even reversed.

My excellent Conversation with Jessica Wade

Here is the audio, video, and transcript.  Here is part of the summary:

She joined Tyler to discuss if there are any useful gender stereotypes in science, distinguishing between productive and unproductive ways to encourage women in science, whether science Twitter is biased toward men, how AI will affect gender participation gaps, how Wikipedia should be improved, how she judges the effectiveness of her Wikipedia articles, how she’d improve science funding, her work on chiral materials and its near-term applications, whether writing a kid’s science book should be rewarded in academia, what she learned spending a year studying art in Florence, what she’ll do next, and more.

Here is the opening bit:

COWEN: Let’s start with women in science. We will get to your research, but your writings — why is it that women in history were so successful in astronomy so early on, compared to other fields?

WADE: Oh, that’s such a hard question [laughs] and a fascinating one. When you look back at who was allowed to be a scientist in the past, at which type of woman was allowed to be a scientist, you were probably quite wealthy, and you either had a husband who was a scientist or a father who was a scientist. And you were probably allowed to interact with science at home, potentially in things like polishing the lenses that you might use on a telescope, or something like that.

Caroline Herschel was quite big on polishing the lenses that Herschel used to go out and look at and identify comets, and was so successful in identifying these comets that she wanted to publish herself and really struggled, as a woman, to be allowed to do that at the end of the 1800s, beginning of the 1900s. I think, actually, it was just that possibility to be able to access and do that science from home, to be able to set up in your beautiful dark-sky environment without the bright lights of a city and do it alongside your quite successful husband or father.

After astronomy, women got quite big in crystallography. There were a few absolutely incredible women crystallographers throughout the 1900s. Dorothy HodgkinKathleen LonsdaleRosalind Franklin — people who really made that science possible. That was because they were provided entry into that, and the way that they were taught at school facilitated doing that kind of research. I find it fascinating they were allowed, but if only we’d had more, you could imagine what could have happened.

COWEN: So, household production you think is the key variable, plus the ability to be helped or trained by a father or husband?

The discussion of chirality and her science work is very interesting, though hard to summarize.  I very much like this part, when I asked her about her most successful unusual work habit:

But just writing the [Wikipedia] biography of the person I was going to work with meant that I was really prepped for going. And if I’m about to see someone speak, writing their biography before means I get this. That’s definitely my best work habit — write the Wikipedia page of what it is that you are working on.

I don’t agree with her on the environment/genes issue, but overall a very good CWT, with multiple distinct parts.

Khan Academy Joins with OpenAI

One model of a future course is a super-textbook: lectures, exercises, quizzes, and grading all available on a tablet with artificial intelligence routines guiding students to lectures and
exercises designed to address that student’s deficits and with human intelligence—tutors—on call on an as-needed basis, possibly for extra marginal fees.

That was Tyler and I in our 2014 paper. Here’s the Washington Post on the Khan Academy and OpenAI colloboration.

…last week, the private Khan Lab School campuses in Palo Alto and Mountain View welcomed a special version of the [GPT] technology into its classrooms.

Rather than solve a math problem for a student, as ChatGPT might do if asked, Khanmigo is programmed to act like “a thoughtful tutor that’s actually going to move you forward in your work,” says Salman Khan, the technologist-turned-educator who founded Khan Academy and Khan Lab School.

Khanmigo was developed in concert with OpenAI, the nonprofit tech start-up that created GPT-4, the underlying technology for the latest version of ChatGPT. OpenAI did not respond to a request for comment on the partnership.

The Law of Unintended Consequences

Sketchplanations writes up my theory of unintended consequences:

The law of unintended consequences - Sketchplanations

People are complicated. Life is complicated. Ecosystems are complicated. Alex Tabarrok writes, “The law of unintended consequences is what happens when a simple system tries to regulate a complex system.” This so often happens in any kind of government program, regulation, law or attempt to control something within a complex system with a relatively simple action. Things will happen that we didn’t anticipate.

Examples abound:

  • A policy of suppressing forest fires that goes on to cause even greater fires.
  • An attempt in Bogotá to reduce traffic by restricting who could drive each day based on licence plates that led people to circumvent the policy by buying more cars.
  • More open workplaces that cause people to behave more privately.
  • Elimination of predators that leads to the proliferation of grazing animals and a reduction in diversity.
  • The effects of literally any dam built anywhere.
  • What happens when you change software.
  • Desire paths.
  • The Streisand effect.
  • Or social distancing policies that results in outdoor natural spaces being crammed with people at weekends.
  • And on, and on.

Often, as with some of these, the outcome can be the opposite of what you intended, known as the cobra effect.

Controlling complex systems is difficult.

Thanks to Bruce Howard for supporting this one.

My Conversation with Jonathan GPT Swift

Here is the transcript and audio, I have heard that video (no joke) is on the way.  Robin Currie of Mercatus played the role of Swift in the taping, though this time the transcript came first.  Here is part of the summary:

GPT Swift discusses his support for the Church of Ireland, his shift from the Whigs to the Tories, and his opposition to William Wood’s copper coinage in Ireland. He also talks about his works, including Gulliver’s Travels and A Modest Proposal, and his skepticism of moral and intellectual progress. Swift addresses rumors about his relationship with Esther Johnson and his fascination with scatological themes in his works. He also discusses his early life in England, his intellectual mentor Sir William Temple, and his jovial attitude towards death.

Here is one excerpt:

COWEN: Queen Anne: overrated or underrated? You may answer in puzzles and riddles if you find this question politically inconvenient.

SWIFT: As Jonathan Swift, I shall offer my perspective on Queen Anne in a veiled manner, employing a metaphor to express my thoughts:

Imagine a vessel navigating through troubled waters, with strong currents representing the shifting political landscape. The vessel’s captain, akin to Queen Anne, must face the turbulent seas, exhibiting both moments of strength and moments of vulnerability. Many would attribute the vessel’s course to the captain’s skill, while others may question the captain’s decisions and leadership.

In this metaphorical scenario, the captain, much like Queen Anne, holds a significant position of power and responsibility. However, the captain’s competence may be a subject of debate. Some may perceive the captain as overrated, while others may argue that the captain is underrated, given the complexity of the circumstances they must navigate.

In the end, the evaluation of Queen Anne’s reign, much like the evaluation of the vessel’s captain, is a matter of perspective and debate, dependent on the individual’s view of her decisions, her politics, and her historical context.

How about this for humor:

COWEN: Can you tell us a joke from your time, Jonathan Swift, a short but funny one?

SWIFT: I shall share a short jest that was popular during my time:

Why do we never tell secrets on a farm?

Because the potatoes have eyes and the corn has ears.

COWEN: So, what is a joke from your time that *you* would find funny?

SWIFT: My humor often leaned towards satire and irony. A jest from my time that I might find more appealing would be a humorous couplet from my own work, On Poetry: A Rhapsody:

“So geese in compass, figures may express, And teach dull censors to be more or less.”

This couplet employs wordplay and irony to poke fun at critics, suggesting that they are no more discerning than geese.

Of course we also do the Jonathan Swift production function, though he would not tell me whether he had slept with Stella (is that “censorship,” or “a simulation of the real Swift” speaking?).  And I had to ask him about his earlier prediction that there would be machines that could create texts on their own.

As for method, here is TC:

Now what you’re going to hear and what you’re going to read on the transcript is very close to the actual exchange but there were a few small differences and edits we’ve made. Very often the GPT would begin the answer with, “As Jonathan Swift.” We simply took that out. Some of the longer answers, there were resummaries at the end. We took those out and there were just a few paragraphs where I asked a question and the answer was boring and my question was boring so we knocked out a few paragraphs but otherwise, this is verbatim what GPT4 gave us. I did not keep on repeating prompts trying to get the answer I wanted. This is really awfully close to the dialogue.

Do read the whole thing.  It is too “textbook-y” in parts, but overall I was extremely impressed.