Author: Joy Buchanan

Why Podcasts Succeeded in Gaining Influence Where MOOCs Failed

Joy Buchanan4 Comments

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.”

https://twitter.com/aboutJoy/status/1854188563757158517

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.

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Effort Transparency and Fairness Published at Public Choice

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Please see my latest paper, out at Public Choice: Effort transparency and fairness

The published version is better, but you can find our old working paper at SSRN “Effort Transparency and Fairness”

Abstract: We study how transparent information about effort impacts the allocation of earnings in a dictator game experiment. We manipulate information about the respective contributions to a joint endowment that a dictator can keep or share with a counterpart…

Employees within an organization are sensitive to whether they are being treated fairly. Greater organizational fairness is shown to improve job satisfaction, reduce employee turnover, and boost the organization’s reputation. To study how transparent information impacts fairness perceptions, we conduct a dictator game with a jointly earned endowment. 

The endowment is earned by completing a real effort task in the experiment, an analog to the labor employees contribute to employers. First, two players work independently to create a pool of money. Then, the subject assigned the role of the “dictator” allocates the final earnings between them.

In the transparent treatment, both dictators and recipients have access to complete information about their own effort levels and contributions, as well as those of their counterparts. In the non-transparent treatment, dictators have full information about the relative contributions of both players, but recipients do not know how much each person contributed to the endowment. The two treatments allow us to compare the behaviors of dictators who know they could be judged and held to reciprocity norms with dictators who do not face the same level of scrutiny.

*drumroll* results:

This graph shows the amount of money the dictators take from the recipient contribution, in cents.  There are two ways to look at this. Notice the spike next to zero. Most dictators do not take much from what their counterpart earned. They are *dictators*, meaning they could take everything. Most take almost nothing, regardless of the treatment. We interpret this to mean that they are acting out of a sense of fairness, and we apply a humanomics framework to explain this in the paper.

Also, there is significantly more taken in non-transparency. When the worker does not have good information on the meritocratic outcome, then some dictators feel like they can get away with taking more. Some of this happens through what we call “shading down” of the amount sent by the dictator under the cover of non-transparency.

There is more in the paper, but the last thing I’ll point out here is that the “worker” subjects (recipients) anticipate that this will happen. The recipients forecast that the dictator would take more under non-transparency. In our conclusion, we mention that, even though the dictator seems to be at an advantage in a non-transparent environment, the dictator still might choose a transparency policy if it affects which workers select into the team.

View and download your article*   This hyperlink is good for a limited number of free downloads of my paper with Demiral and Saglam, says Springer the publisher. Please don’t waste it, but if you want the article I might as well put it out there. I posted this on 11/2/2024, so there is no guarantee that the link will work for you.

Cite our article: Buchanan, J., Demiral, E.E. & Sağlam, Ü. Effort transparency and fairness. Public Choice (2024). https://doi.org/10.1007/s11127-024-01230-9

Can researchers recruit human subjects online to take surveys anymore?

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The experimental economics world is currently still doing data collection in traditional physical labs with human subjects who show up in person. This is still the gold standard, but it is expensive per observation. Many researchers, including myself, also do projects with subjects that are recruited online because the cost per observation is much lower.

As I remember it, the first platform that got widely used was Mechanical Turk. Prior to 2022, the attitude toward MTurk changed. It became known in the behavioral research community that MTurk had too many bots and bad actors. MTurk had not been designed for researchers, so maybe it’s not surprising that it did not serve our purposes.

The Prolific platform has had a good reputation for a few years. You have to pay to use Prolific but the cost per observation is still much lower than what it costs to use a traditional physical laboratory or to pay Americans to show up for an appointment. Prolific is especially attractive if the experiment is short and does not require a long span of attention from human subjects.

Here is a new paper on whether supposedly human subjects are going to be reliably human in the future: Detecting the corruption of online questionnaires by artificial intelligence   

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Physics Highlights from What is Real

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Some highlights from reading the book What is Real? The Unfinished Quest for the Meaning of Quantum Physics* 

Page 9 “The godfather of quantum physics, Niels Bohr, talked about a division between the world of big objects, where classical Newtonian physics rules, and small objects, where quantum physics reigned.”

The book has some drama, much centered around Einstein’s rejection of the Copenhagen interpretation.

The title of Chapter 2 is so excellent: “Chap 2: Something Rotten in the Eigenstate of Denmark”

Pg 37 “But Max Born had discovered a piece of the puzzle that summer. He found that a particle’s wave function in a location yields the probability of measuring the particle in that location – and that the wave function collapses once measurement happens… The measurement problem had arrived.”

Pg 56 “Einstein rejected any violation of locality, calling it “spooky action at a distance” in a letter to Max Born.”

Pg 79 “By the end of the war, the Manhattan Project had cost the nation nearly $25 billion, employing 125,000 people at thirty-one different locations across the United States and Canada. Hundreds of physicists were called away from their everyday laboratory work … After the war ended, physics research in the United States never returned to what it was… Damned by their success … military research dollars poured into physics.”

Pg 82 “Research into the meaning of quantum physics was one of the casualties of the war. With all these new students crowding classrooms around the country, professors found it impossible to teach the philosophical questions at the foundation of quantum physics.”

Joy: The politics of physics in academia was interesting to me. I recommend this book to university economists on that merit alone.

Page 100 “the photons are deliberately messing with you”

Experimentalists take note, page 104 “The story that comes along with a scientific theory influences the experiments that scientists choose to perform”

Joy: Having no internet greatly slowed down the spread of the correct ideas. However, eventually, over the course of a few decades and with a few career casualties, the more correct information did seem to influence the consensus.

Joy: I’m used to economists having very basic and sometimes heated disagreements. One might say that issues in economics are a bit more subjective than a topic in the physical sciences. However, with quantum physics turning out to be so weird, there are also heated disagreements among the physicists.

An equivalent book for economics might be Grand Pursuit by Sylvia Nasar.

Pg 108: “Bohm’s theory had also appeared during the height of Zhdanovism, an ideological campaign by Stalin’s USSR to stamp out any work that had even the faintest whiff of a conflict with the ideals of Soviet communism.”

Pg 124: “This universal wave function, according to Everett, obeyed the Schrödinger equation at all times, never collapsing, but splitting instead. Each experiment, each quantum event… creating a multitude of universes…”

*Thanks to Josh Reeves and Samford University for buying me the book.

Related previous posts: Is the Universe Legible to Intelligence?

Oppenheimer Film Thoughts

Literature Review is a Difficult Intellectual Task

Literature Review is a Difficult Intellectual Task

Joy Buchanan4 Comments

As I was reading through What is Real?, it occurred to me that I’d like a review on an issue. I thought, “Experimental physics is like experimental economics. You can sometimes predict what groups or “markets” will do. However, it’s hard to predict exactly what an individual human will do.” I would like to know who has written a little article on this topic.

I decided to feed the following prompt into several LLMs: “What economist has written about the following issue: Economics is like physics in the sense that predictions about large groups are easier to make than predictions about the smallest, atomic if you will, components of the whole.”

First, ChatGPT (free version) (I think I’m at “GPT-4o mini (July 18, 2024)”):

I get the sense from my experience that ChatGPT often references Keynes. Based on my research, I think that’s because there are a lot of mentions of Keynes books in the model training data. (See “”ChatGPT Hallucinates Nonexistent Citations: Evidence from Economics“) 

Next, I asked ChatGPT, “What is the best article for me to read to learn more?” It gave me 5 items. Item 2 was “Foundations of Economic Analysis” by Paul Samuelson, which likely would be helpful but it’s from 1947. I’d like something more recent to address the rise of empirical and experimental economics.

Item 5 was: “”Physics Envy in Economics” (various authors): You can search for articles or papers on this topic, which often discuss the parallels between economic modeling and physics.” Interestingly, ChatGPT is telling me to Google my question. That’s not bad advice, but I find it funny given the new competition between LLMs and “classic” search engines.

When I pressed it further for a current article, ChatGPT gave me a link to an NBER paper that was not very relevant. I could have tried harder to refine my prompts, but I was not immediately impressed. It seems like ChatGPT had a heavy bias toward starting with famous books and papers as opposed to finding something for me to read that would answer my specific question.

I gave Claude (paid) a try. Claude recommended, “If you’re interested in exploring this idea further, you might want to look into Hayek’s works, particularly “The Use of Knowledge in Society” (1945) and “The Pretense of Knowledge” (1974), his Nobel Prize lecture.” Again, I might have been able to get a better response if I kept refining my prompt, but Claude also seemed to initially respond by tossing out famous old books.

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Writing with ChatGPT Buchanan Seminar on YouTube

Joy Buchanan3 Comments

I was pleased to be a (virtual) guest speaker for Plateau State University in Nigeria. My host was (Emergent Ventures winner) Nnaemeka Emmanuel Nnadi. The talk is up on Youtube with the following timestamp breakdown:

During the first ten minutes of the video, Ashen Ruth Musa gives an overview called “The Bace People: Location, Culture, Tourist Attraction.”

Then I introduce LLMs and my topic.

Minute 19:00 – 29:00 is a presentation of the paper “ChatGPT Hallucinates Nonexistent Citations: Evidence from Economics“

Minute 23:30 – 34 is summary of my paper “Do People Trust Humans More Than ChatGPT?”

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Probability Theory for the Minecraft Generation

Joy Buchanan1 Comment

If you are teaching statistics to 20-year-olds (or maybe even if you are not), you might be interested in ways to make probability theory more engaging. I watched a students eyes light up when I showed this in class, so that makes it feel worth sharing.

The Law of Large Numbers is a standard part of statistics or business analytics classes. Something that goes along with it conceptually is “The Law of Truly Large Numbers,” sometimes also called The Infinite Monkey Theorem. The idea is that if you put monkeys in front of typewriters, perhaps infinite monkeys with infinite typewriters and with infinite time, they will eventually write a Shakespeare play.

To illustrate this feature of probability theory for the video gamers, a fun and well-produced video is
“Can Mobs Beat Minecraft?” by Wifies

There is nothing inappropriate for students. The video is 13 minutes, which is too long to show during a class session. I recommend watching the first minute and a half and then explaining that the middle is a lot of gaming details to prove that it is technically possible that a randomly acting “mob” could eventually beat the entire Minecraft game, given enough time.

At the 10-minute mark, the math begins. You could watch about one more minute and a half to see how he tries to calculate the infinitesimally-small-and-yet-positive probability that this could happen. Given enough time, just about anything that is possible will happen.

Another possibility for a teacher is not to show the video in class but to offer it as an optional or extra credit assignment, so that a student who loves Minecraft could really have fun with it and other students can skip.

For me, this pairs with Chapter 5 on Probability for the textbook Applied Statistics in Business and Economics.

Another teaching tip. If you ever need to print out paper rulers, you might be Googling “printable rulers” and you’ll see a bunch of scams as the top results. THIS link works: https://www.brightonk12.com/cms/lib/MI02209968/Centricity/Domain/517/Ruler_6-inch_by_16.pdf

Paper on Finance and Economics Women Club

Joy Buchanan1 Comment

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.

Notes from Greg Mankiw podcast

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Good job to Jon Hartley to get the conversation going. All indented quotes are from Mankiw in the podcast.

Some history for those of us who write about sticky wages and prices.

But it was that idea that real wages weren’t countercyclical, that said, you have to start thinking about not only sticky wages, I have to start thinking about sticky prices.

And if I’m gonna start thinking about sticky prices, you have to have firms that are not competitive, that are price setters, not price takers. Because if you’re going to think about the incentives that firms have to adjust prices, you can’t have them being price takers. And it was that that got me to write my small menu cost paper…

There is a lot more on that topic in the transcript, for those who are interested.

How do we feel about big models?

I think people were getting a little tired of these big models because they were large, non intuitive. They seemed very black boxy, so you didn’t really know what was happening in them.

Haha. Here comes ChatGPT. ‘Leeroy Jenkins’ and all that.

One thing I’ll say about being Chair of the Council, which I did from 2003 to 2005. And I worked harder those two years than any two years of my life, by far, because the days are long. In the Bush administration, every day started with the 7:30 AM staff meeting in the Roosevelt room, which is the conference room right next to the Oval office.

In all my years at Harvard, I’ve been in Harvard almost 40 years, nobody’s ever called a 07:30 AM meeting. While I was at the White House, every day it was at 7:30 AM meeting. It’s not like you take off early at the end of the day, you work long hours at the end of the day too.

So they’re are very, very long days. I left my family behind in Boston, my wife was a saint and took care of my three small kids. And I basically moved into a hotel just a few blocks from the White House…

Note the saints lurking behind the intellectual contributions. With falling fertility all over the world, it raises the question of who watches the three small kids? Something I am pondering this week is that I’m glad I didn’t try to homeschool my kids this semester. I support others who make that choice, but it wouldn’t have been good for us.

Rote Education has a Purpose

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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.