Joy on AI in Higher Education

I was interviewed for an article “Navigating AI in Christian Higher Education“. Here’s an excerpt:

Rosenberg: What impact do you foresee in your field due to the increasing sophistication of AI, and what kind of skills do you think your students will need to be successful?

Buchanan: AI will reshape economic analysis and modeling, making complex data processing and predictive analytics more accessible. This will lead to more sophisticated economic forecasting and policy design. Economists will become more productive, and expectations will rise accordingly. While some fields might resist change, economics will be at the forefront of AI integration.

For students aiming to succeed, it’s crucial to embrace AI tools without relying on them excessively during college. Strong fundamentals in economic theory and critical thinking remain essential, coupled with data science and programming skills.

Interdisciplinary knowledge, especially in tech and social sciences, will be valuable. Adaptability and lifelong learning are key in this evolving field. Human skills like creativity, communication, and ethical reasoning will remain crucial.

While AI will alter economics, it will also present opportunities for those who can adapt and effectively combine economic thinking with technological proficiency.

More Productive than “Smart”

Public choice economists emphasize the process by which we select political leaders. Electoral and voting rules influence the type of leaders we get. Institutional economists agree and go one step further. Who we choose matters less than the environment we place them in. Leaders, regardless of their personal qualities, respond to the incentives that surround them. The ultimate policies, therefore, largely conform to those incentives. From this perspective, it’s important to adopt institutional incentives for leaders to promote policies oriented toward economic growth and provide the option to flourish.

The same principle applies to the private economy. Productivity is crucial, and higher IQ often correlates with greater productivity. Yet, genetic endowment—including IQ—is beyond individual control. Many other determinants of productivity are not exogenous when we can affect policy. Let’s adopt policies that allow individuals with lower IQ to act productively as if they had higher IQ. Protecting the freedom to contract and private property rights creates conditions whereby even those at the lower end of the cognitive ability distribution can thrive. These principles expand their opportunities. Market signals give them valuable feedback on their activities and enable them to contribute to the economy.

Continue reading

Why Podcasts Succeeded in Gaining Influence Where MOOCs Failed

When MOOCs (Massive Open Online Courses) burst onto the education scene in the early 2010s, they were hailed as the future of learning. With the promise of democratizing education by providing free access to world-class courses from top universities.

Leading universities rushed to put their courses online, venture capital poured in, and platforms like Coursera and edX grew rapidly. Yet today, while MOOCs still exist, they’ve largely retreated to the margins of education. Meanwhile, long-form podcasts have emerged as a surprisingly powerful force in American intellectual life.

Is this ironic? I wanted to learn a bit about MOOCs while I took a walk before writing this blog post. I typed “MOOCs” into the Apple Podcasts search bar.

One of the first results was: John Cochrane on Education and MOOCs

I learned about MOOCs from Russ Roberts at a reasonable pace (when I listen to podcasts, I do it at 1x speed but I’m almost always doing something like driving or folding laundry).

I consider myself a lifelong learner. I buy and read books. Like hundreds of millions of people around the world, I like podcasts. I will attend lectures sometimes, especially if I personally know someone in the room. I did sit in classrooms for course credit throughout college and graduate school. I took extra classes that I did not need to graduate purely out of interest, and yet I have never once been tempted to sign up for a MOOC.

Enough introspection from me. My viral “tweet” this week was: “MOOCs never took off, as far as I can tell, and yet long-form podcasts are shaping the nation.”

Did MOOCs fail? Many millions of people signed up for MOOCs. A much smaller percentage of people completed MOOCs. Some users find MOOCs worth paying for.

However, if you listen to the podcast with John Cochrane in 2014, you can see the promise that MOOCs failed to live up to. The idea was that many people who did not have access to a “top quality” education would get one through MOOCs. Turns out that access is not the bottleneck.

Continue reading

Paper on Finance and Economics Women Club

I am one of several founders of a club with the abbreviation F.E.W. for Finance and Economics Women. This is a student organization that we have at Samford and that Dr. Darwyyn Deyo runs at San Jose State University.

Read our report here: The Finance and Economics Women’s Network (FEW): Encouraging and Engaging Women in Undergraduate Programs published in the Journal of Economics and Finance Education

Our short paper is mostly a how-to guide including a draft of a club charter document. We describe our institutions and how we use this group to engage and encourage students. Please read it for more details on how to start a club.

Like most student groups, the FEW model relies on student leaders who take initiative. Having done this for more than 6 years, we have a growing network of alumni and local business partners who connect to current students through FEW events. Personally, I am lucky that 3 faculty members total support the club at my school.

Women are often minorities in upper-division econ and finance classes. Women also have some unique challenges when it comes to choosing career paths and navigating the workplace. These events (e.g. bringing in a manager from a local bank to talk with student over lunch) allow a space for students to ask questions they might not normally ask in a classroom setting or in a standard networking environment.

We report the results of a small survey in our paper. We can’t infer causality, nor did we run any experiments. However, we did find that women were more likely to report that a role model in their chosen profession influenced their choice of major. Part of the purpose of the FEW model is to expose students to a variety of role models who they might not otherwise connect with.

Here’s a news article with a picture of the founding group at Samford. I have great appreciation and respect for our student leaders who keep it going, and I am grateful to the graduates who stay in contact with us.

Suggested citation: Buchanan, Joy, and Darwyyn Deyo, “Finance and Economics Women’s (FEW) Network: Encouraging and Engaging Women in Undergraduate Programs” (2023) Journal of Economic and Finance Education, 22: 1, 1-14.

Interpreting New DIDs

If you didn’t know already, the past five years has been a whirl-wind of new methods in the staggered Differences-in-differences (DID) literature – a popular method to try to tease out causal effects statistically. This post restates practical advice from Jonathan Roth.

The prior standard was to use Two-Way-Fixed-Effects (TWFE). This controlled for a lot of unobserved variation over individuals or groups and time. The fancier TWFE methods were interacted with the time relative to treatment. That allowed event studies and dynamic effects.

Continue reading

Rote Education has a Purpose

A tweet that got over 2 million views and 2500 likes:

https://x.com/ianmcorbin1/status/1831353564246979017

“Why do our students (even the ones paying a jillion dollars!) *want* to skip their lessons?”

“You give us work fit for machines. You want rote answers.”

He asks why students want to cheat and what is wrong with education. Why did this tweet take off? This is obvious.

I’m not of the opinion that education is entirely signaling (see Bryan Caplan). However, anyone can see that education is partly signaling. It’s difficult to get good grades. Good grades is a noisy signal of excellence. Students want to cheat so that they can obtain the good grades and signal to employers that they are excellent. There is nothing mysterious about that.

Part of a professor’s job is to make it hard to cheat and costly if you are caught.

Now we get to the “rote answers” part. How is a professor who has over 100 students every semester supposed to monitor the students’ performance and make it hard to cheat and be fair to every student? The “rote answers” part is a technology called the multiple-choice test with auto or semi-auto (e.g. Scantron machine) grading. Multiple choice tests serve an important role in our society, and they aren’t going anywhere.

A professor who has only 10 students per semester could give personalized assignments and grade oral exams and be an Oxford tutor for the students hand-written essays or whatnot. However, that kind of education would be extremely expensive/exclusive and does not scale.

Readers are more scarce than writers. AI’s can read now. The implications that will have for education and assessment have yet to be seen.

Predicting College Closures

This week the University of the Arts in Philadelphia announced they were closing effective immediately, leaving students scrambling to transfer and faculty desperate for jobs. U Arts now joins Cabrini University and Birmingham-Southern as some the 20 US colleges closing or being forced to merge so far this year. This trend of closures is likely to accelerate given falling birth rates that mean the number of college-age Americans is set to decline for decades; short-term issues like the FAFSA snafu and rising interest rates aren’t helping either.

All this makes it more important for potential students and employees to consider the financial health of colleges they might join, lest they find themselves in a UArts type situation. But how do you predict which colleges are at significant risk of closing? One thing that jumps out from this year’s list of closures is that essentially every one is a very small (fewer than 2000 undergrad) private school. Rural schools seem especially vulnerable, though this year has also seen plenty of closures in major cities.

Source

There appear to be a number of sources tracking the financial health of colleges, though most are not kept up to date well. Forbes seems to be the best, with 2023 ratings here; UArts, Cabrini, and Birmingham-Southern all had “C” grades. If you have access to them, credit ratings would also be good to check out; Fitch offers a generally negative take on higher ed here.

In a 2020 Brookings paper, Robert Kelchen identified several statistically significant predictors of college closures:

I used publicly available data compiled by the federal government to examine factors associated with college closures within the following two to four years. I found several factors, such as sharp declines in enrollment and total revenue, that were reasonably strong predictors of closure. Poor performances on federal accountability measures, such as the cohort default rate, financial responsibility metric, and being placed on the most stringent level of Heightened Cash Monitoring, were frequently associated with a higher likelihood of closure. My resulting models were generally able to place a majority of colleges that closed into a high-risk category

The Higher Learning Commission reached similar conclusions. Of course, there is a danger in identifying at-risk colleges too publicly:

Since a majority of colleges identified of being at the highest risk of closure remained open even four years later, there are practical and ethical concerns with using these results in the policy process. The greatest concern is that these results become a self-fulfilling prophecy— being identified as at risk of closure could hasten a struggling college’s demise.

Still, would-be students, staff and faculty should do some basic research to protect themselves as they considering enrolling or accepting a job at a college. College employees would also do well to save money and keep their resumes ready; some of these closures are so sudden that employees find out they are out of a job effective immediately and no paycheck is coming next month.

Taxes & Unemployment – Know Your Bias?

Say that there is a labor market and that there is no income tax. If an income tax is introduced, then what should we expect to happen? Specifically, what will happen to employment, the size of the labor force, and the number of people unemployed? Will each rise? Fall? Remain unchanged? Change ambiguously? Take a moment and jot down a note to test yourself.

As it turns out, what your answer is depends on what your model of the labor market is. Graphically, they are all quantities of labor. The size of the labor force is the quantity of labor supplied contingent on some wage that workers receive. It’s the number of people who are willing to work. Employment is the quantity of laborers demanded by firms contingent on to wage that they pay. Finally, the quantity of people unemployed is the difference between the size of the labor force and the quantity of workers employed (Assuming that the labor force is greater than or equal to employment).

Continue reading

How to Keep Up With Economics

… other than reading our blog, of course.

I was writing up something for my graduating seniors about how to keep learning economics after school, and realized I might as well share it with everyone. This may not be the best way to do things, it is simply what I do, and I think it works reasonably well.

Blogs by Economists: There are many good ones, but besides ours Marginal Revolution is the only one where I aim to read every post

Economic News: WSJ or Bloomberg

Podcasts on the Economy: NPR’s The Indicator (short, makes abstract concepts concrete), Bloomberg’s Odd Lots (deeper dives on subjects that move financial markets)

Podcasts by Economists: Conversations with Tyler and Econtalk (note that both often cover topics well outside of economics). Macro Musings goes the other way and stays super focused on monetary policy.

Twitter/X: This is a double-edged sword, or perhaps even a ring of power that grants the wearer great abilities even as it corrupts them. The fastest way to get informed or misinformed and angry, depending on who you follow and how you process information. Following the people I do gives you a fighting chance, but even this no guarantee; even assuming you totally trust my judgement, sometimes I follow people because they are a great source on one issue, even though I think they are wrong on lots of other things. Still, by revealed preference, I spend more time reading here than other single source.

Finance/Investing: Making this its own category because it isn’t exactly economics. Matt Levine has a column that somehow makes finance consistently interesting and often funny; unlike the rest of Bloomberg, you can subscribe for free. He also now has a podcast. If you’d like to run money yourself some day, try Meb Faber’s podcast. If you’d like things that touch on finance and economics but with more of a grounding in real-world business, try the Invest Like the Best podcast or The Diff newsletter.

Economics Papers: You can get a weekly e-mail of the new papers in each field you like from NBER. But most econ papers these days are tough to read even for someone with an undergrad econ degree (often even for PhDs). The big exception is the Journal of Economic Perspectives, which puts in a big effort to make its papers actually readable.

Books: This would have to be its own post, as there are too many specific ones to recommend, and I don’t know that I have any general principle of how to choose.

This is a lot and it would be crazy to just read all the same things I do, but I hope you will look into the things you haven’t heard of, and perhaps find one or two you think are worth sticking with. Also happy to hear your suggestions of what I’m missing.

Ten Years Gone: Temple University’s Economics PhD

Last weekend brought me back to Temple University, ten years after graduating, for a conference of econ PhD alums. I had so many reactions:

  1. Mixing a research conference with what is effectively a reunion or homecoming is a great idea for a PhD program, and more schools should do it. It brought together alumni from all different years, but it especially felt like a reunion to me since it’s been ten years since I graduated (not that I really know about reunions; I’ve never been to a high school or college one).
  2. Philadelphia in general and Temple University in particular have gotten much nicer (though still gritty). Some of this I expected; the country is getting steadily richer, and it seems like every college is always on a building spree. But as with New Orleans, it is a city still well below its peak population that I first got to know in the aftermath of the great recession. Unemployment in Philly is now well under half what it was the whole time I lived there, and it shows.
  3. Life is short. I was saddened, but not shocked, to hear that one of my professors had died. I was saddened and shocked to hear that one of my fellow students had.
  4. As a kid, whenever I went back to one of my old schools, I usually felt nostalgia mixed with the feeling that everything seemed small. Then I thought this smallness was only about me having grown taller, but now I wonder. At Temple the economics department has changed buildings, but when I went back to the old building everything seemed small, despite me being the same size I was in grad school. But at the time the building loomed so large in my mind; I was so focused on the things that happened there, the classes and tests, the study sessions and writing in the computer lab, what the professors thought, and everything that it all represented. All that apparently made the rooms seem physically larger in a way they now don’t once I have graduated and the professors moved.
  5. Temple PhDs are much more successful than I would have guessed at the time. It was hard for students attending what was then a bottom-ranked program during the Great Recession to be optimistic about our job prospects, especially when we worried we might fail out of the program (a valid concern when, afaik, only 4 of the 11 students in my year finished their PhDs). But things turned out great; just in the past 10 years from a small program there are many people who are tenured or tenure track at decent schools, who have research or important supervisory positions at the Fed, or who are making a name for themselves in the private sector (like Adam Ozimek).
  6. Why have we so exceeded our low expectations? The improving economy helped. Economics PhDs from anywhere turned out to be a valuable degree. Perhaps our training was stronger than we gave it credit for at the time. I see two main tracks for success coming out of a lower-ranked program, where the school’s name alone might not open doors:
    • publish a lot (my strategy), or
    • find some way to get your foot in the door of a major institution like the Fed system or a major bank, then work your way up. The initial way in could be something less competitive, like an internship or a job you don’t necessarily need a PhD for. But once you are in you will be judged mostly on your performance within the institution, not your credentials. In a panel on non-academic jobs, several alums emphasized that conditional on having enough technical skills to get hired, at the margin people/communication skills are much more important to advancement than further technical skills.
  7. Temple’s economics PhD program paused admissions back in 2020, but is aiming to restart with a redesigned program in 2025.