Steal My Paper Ideas!

Since early in graduate school I’ve kept a running list of ideas for economics papers I’d like to write and publish some day. I’ve written many of the papers I planned to, and been scooped on others, but the list just keeps growing. As I begin to change my priorities post-tenure, I decided it was time to publicly share many of my ideas to see if anyone else wants to run with them. So I added an ideas page to my website:

Steal My Paper Ideas! I have more ideas than time. The real problem is that publishing papers makes the list bigger, not smaller; each paper I do gives me the idea for more than one new paper. I also don’t have my own PhD students to give them to, and don’t especially need credit for more publications. So feel free to take these and run with them, just put me in the acknowledgements, and let me know when you publish so I can take the idea off this page.

Here’s one set of example ideas:

State Health Insurance Mandates: Most of my early work was on these laws, but many questions remain unanswered. States have passed over a hundred different types of mandated benefits, but the vast majority have zero papers focused on them. Many likely effects of the laws have also never been studied for any mandate or combination of mandates. Do they actually reduce uncompensated hospital care, as Summers (1989) predicts? Do mandates cause higher deductibles and copays, less coverage of non-mandated care, or narrower networks? How do mandates affect the income and employment of relevant providers? Can mandates be used as an instrument to determine the effectiveness of a treatment? On the identification side, redoing older papers using a dataset like MEPS-IC where self-insured firms can be used as a control would be a major advance.

You can find more ideas on the full page; I plan to update to add more ideas as I have them and to remove ideas once someone writes the paper.

Thanks to a conversation with Jojo Lee for the idea of publicly posting my paper ideas. I especially encourage people to share this list with early-stage PhD students. It would also be great to see other tenured professors post the ideas they have no immediate plans to work on; I’m sure plenty of people are sitting on better ideas than mine with no plans to actually act on them.

New Textbook for Game Theory and Behavioral Economics

Game Theory and Behavior is extremely readable. Carpenter and Robbett have a great set of examples (e.g. the poison drink dilemma from The Princess Bride). I think the book has been developed from teaching a course that resonates with undergraduates today. The authors are both experimental economists, so there is natural integration with lab results from experiments with games.

Topics covered include:

Game Theory and standard definitions

Solving Games

Sequential Games

Bargaining

Markets

Social Dilemmas

Voting

Behavioral Extensions of Standard Theory

In their words:

This book provides a clear and accessible formal introduction to standard game theory, while at the same time addressing how people actually behave in these games and demonstrating how the standard theory can be expanded or updated to better predict the behavior of real people. Our objective is to simultaneously provide students with both the theoretical tools to analyze situations through the logic of game theory and the intuition and behavioral insights to apply these tools to real world situations. The book was written to serve as the primary textbook in a first course in game theory at the undergraduate level and does not assume students have any previous exposure to game theory or economics. 

Not every book on game theory would be described as extremely readable. The authors do present mathematical concepts and solutions and practice problems. I want to be clear that I’m not implying that their book is not rigorous. They present game theory as primarily an intuitive and important framework for decisions instead of as primarily a mathematical object, which should go over well with most undergraduate students.

The following are questions that occurred to me as I was writing this post, with ChatGTP replies.

Empirical Papers for Undergraduate Statistics Students

Once undergraduates have learned the basics of interpreting regression results, we would like to introduce them to the world of economics research papers. Reading these papers will help reinforce the statistical concepts, and also we want them to get access to the insights in the literature.

Many empirical papers in economics are too long or too difficult to assign to undergraduates, especially if the course is focused more on analytics than economics specifically. Here I provide materials and instructions for teaching two published econ articles to undergraduates. Assume the students have learned the basics of interpreting a regression model (perhaps from a course textbook) but have had few opportunities to apply theses skills or engage in scientific literature.

“The Effects of Attendance on Student Learning in Principles of Economics” is only 4 pages long! Students do not need to read past page 7 of “My Reference Point, Not Yours” to answer the reading guide questions. So, these readings can be assigned outside of class, but I did some of the reading during our class period.

Handing out printed copies of at least one of the papers and my guided questions can make a good classroom activity. If students do not have experience reading tables of regression results, it can be useful to do it together in person.

The questions in the reading guide help students to identify the main variables and hypotheses. Then, students are asked to pull specific results from the tables in the papers. You can customize this list of questions by deleting lines if you do not want to discuss issues like non-linear effects or the null hypothesis.

I provide links below. First is the reading guide with about 30 short-answer questions about the two articles.

  1. Link to download the reading guide that goes with both papers, starting with the shorter one.

2. This is a web link to download the Effects of Attendance paper. (4 pages long and the topic is relatable to undergraduates)

3. Two web sources for “My Reference Point, Not Yours” (15 pages in total in the JEBO manuscript, but students do not need to read past page 7 for this exercise, and they can skip the Literature Review section)

JEBO link: https://www.sciencedirect.com/science/article/abs/pii/S0167268120300299

SSRN working paper link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3434182

AI Can’t Cure a Flaccid Mind

Many of my classes consist of a large writing component. I’ve designed the courses so that most students write the best paper that they’ll ever write in their life. Recently, I had reason to believe that a student was using AI or a paid service to write their paper. I couldn’t find conclusive evidence that they didn’t write it, but it ended up not mattering much in the end.

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Message To My Students: Don’t Use AI to Cheat (at least not yet)

If you have spent any time on social media in the past week, you’ve probably noticed a lot of people using the new AI program called ChatGPT. Joy blogged about it recently too. It’s a fun thing to play with and often gives you very good (or at least interesting) responses to questions you ask. And it’s blown up on social media, probably because it’s free, responds instantly, and is easy to screenshot.

But as with all things AI, there are numerous concerns that come up, both theoretical and immediately real. One immediately real concern among academics is the possibility of cheating by students on homework, short writing assignments, or take-home exams. I don’t want to diminish these concerns, but I think for now they are overblown. Let me demonstrate by example.

This semester I am teaching an undergraduate course in Economic History. Two of the big topics we cover are the Industrial Revolution and the Great Depression. Specifically, we spend a lot of time discussing the various theories of the causes of these two events. On the exams, students are asked to, more or less, summarize these potential causes and discuss them.

How does ChatGPT do?

On the Industrial Revolution:

And on the Great Depression:

Now, it’s not that these answers are flat out wrong. The answers certainly list theories that have been discussed by at various times, including in the academic literature. But these answers just wouldn’t be very good for my class, primarily because they miss almost all of the theories that we have discussed in class as being likely causes. Moreover, the answers also list theories that we have discussed in class as probably not being correct.

These kinds of errors are especially true of the answer about the Great Depression, which reads like it was taken straight from a high school history textbook, ignoring almost everything economists have said about the topic. The answer for the Industrial Revolution doesn’t make this mistake as much as it misses most of the theories discussed by Koyama and Rubin, which was the main book we used to work through the literature. If a student gave an answer like the AI, it suggests to me that they didn’t even look at the chapter titles in K&R, which provide a roadmap of the main theories.

So, my message to students: don’t try to use this to answer questions in class, at least not right now. The program will certainly improve in the future, and perhaps it will eventually get very good at answering these kinds of academic questions.

But I also have a message to fellow academics: make sure that you are writing questions that aren’t easily answered by an AI. This can be hard to do, especially if you haven’t thought about it deeply, but ultimately thinking in this way should help you to write better exam and homework questions. This approach seems far superior to the one that the AI suggests.

The Imperfection of Subgame Perfection

I’ve written previously about Pure Strategy Nash Equilibria (PSNE). They are the set of strategies that players can adopt in equilibrium – with no incentive to change their strategy. Students have an intuition that PSNE aren’t great because some outcomes that they identify depend on players making silly decisions in the past. In jargon, we can say that some PSNE depend on players choosing irrationally in a subgame while still reaching a PSNE.

See the extensive form game (below right). There are two players, each with two strategies per information set, and player two has two information sets. All PSNE will include a strategy for each information set. We can present the same game in normal form in order to make it easier to identify the PSNE (below left).

Player 1 (P1) can choose the row (B or C) and Player 2 (P2) can choose the column. Importantly, whether P1 might want to change his mind depends on P2’s strategy at the decision node in the alternative information set. Therefore, P2 must have two strategies, one per information set.

The four PSNE strategies and payoffs are underlined in the above table and they are noted in red on the below extensive form games. Again, the logic of PSNE states that no player can improve their payoff by changing only their own strategy, given the opposing player’s strategy. After all, a player can control their own strategy, but not that of their opponent. For example, note PSNE II. In the left subgame, P2 chooses M. His payoff would be unchanged if he changed his strategy, given the strategy of P1.

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Cheers to Sumproduct!

I teach macroeconomics, finance, and other things.

Often, I use Excel to complete repetitive calculations for my students. The version that I show them is different from the version that I use. They see a lot more mathematical steps displayed in different cells, usually with a label describing what it is. But when I create an answer calculator or work on my own, I usually try to be as concise as possible, squeezing what I can into a single cell or many fewer cells. That’s what brings me to to the sumproduct excel function that I recently learned. It’s super useful I’ll illustrate it with two examples.

Example 1) NGDP

One way to calculate NGDP is to sum all of the expenditures on the different products during a time period. The expenditures on a good is simply the price of the good times the quantity that was purchased during the time period. The below image illustrates an example with the values on the left, and the equations that I used on the right. That’s the student version. There is an equation for each good which calculates the total expenditure on the individual goods. Then, there is a final equation which sums the spending to get total expenditures, or NGDP.

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6 Tips for Taming Your Inner Spock

The younger, high school and undergrad version of me was not the best person. My sense of humor was too dark and I didn’t much care about the experience of other people. When I went to grad school, I was so excited. I would finally be around other economists and I would be able to drop all of the niceties, empty social signals, and fuzziness that I thought non-economists employed. And I was oh so very wrong.

It turned out that economists are also human beings and that no amount of self-congratulatory Spock-praising would stop that from being the case. Indeed, with some candid feedback, I became convinced that I was in desperate need of the kind of prosocial norms that could help me to better produce social capital. In other words, I needed to figure out how to get along. Below is some advice that I’ve found pivotal. Maybe you can share it with another person who might be well-served by reading it too.

Below are six norms that are good to employ in order to improve social cohesion, agreeableness, and, frankly, better mental health. And these aren’t just for economists. I suspect that there are plenty of people (maybe young men) who can benefit from what took me too long to learn. So here we go!

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Are Teacher Salaries Held Back by “Bloat” in K-12 Schools?

In the past 20 years in the US, per pupil spending in K-12 schools has increased by about 20%. That’s in CPI-U inflation-adjusted dollars. What’s the cause of this increase? Higher teacher salaries? Administrative bloat? Something else?

Here’s a chart you may have seen floating around the internet. It shows the growth in the number of employees at K-12 public schools.

This looks like a lot of administrative bloat! The source of the data is the National Center for Education Statistic’s Digest of Education Statistics, Table 213.10.

But hold on, here’s another chart, showing the percent of employees in each of these same categories.

The numbers don’t add up to 100% because I’ve left off a few categories (the biggest one is “support staff,” which was 30-31% of the total throughout the time period). But overall, this chart appears to show much less bloat. Instructional staff (including aides) were by far the biggest category of employees in both categories in both time periods. Administrative staff at the district level did grow, but only by 1 percentage point of the total.

What’s the source of this data? Well, it’s a little trick I played. The source is the National Center for Education Statistic’s Digest of Education Statistics, Table 213.10. It’s the exact same data.

How is this possible?

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Business Analytics Textbook plus Discussion Book

Many undergraduates take at least one business analytics course at the 200 course level. A book that I and other professors at our business school have selected to teach business statistics is by Albright and Winston

Business Analytics: Data Analytics and Decision Making (Amazon link)

This book provides three essential ingredients to a successful course:

  1. Covering core concepts like descriptive statistics and optimization
  2. Providing relevant examples in a business context (e.g. how much inventory should a retail store order)
  3. Showing step-by-step instructions for how to do applications in a specific software which in this case is Excel

Microsoft Excel is essential for business school graduates (arguably all college graduates). No one is born knowing how to select cells or enter formulas. The book does not assume anything, so the professor does not have to require supplementary material on how to use Excel. There are lots of exercise and examples that teach proficiency in the tool while demonstrating the concepts. Analytics courses should be hands-on.

Sometimes statistics courses do not feel like they allow for critical thinking or discussions. There is only one correct formula for an average, and it is merely and exactly what the formula determines it to be. Therefore, an interesting addition to a technical class is the book by Muller

The Tyranny of Metrics (Amazon link)

Muller spends most of the book pointing out cases where measuring results backfired. He is not so much against “analytics” as he is skeptical of pay-for-performance management schemes. Many of these schemes were sold to the public as incredible technocratic improvements, such as No Child Left Behind. I do not always agree with Muller, but he gives students something to debate. Note that only select chapters should be assigned so that it does not take up too much time from the other course material.