I’m Chair! 😬

As of July 1st of this year, I am the Chairman of the Department of Economics at my university. It’s one of those positions that includes more work and not much compensation. Depending on who I tell, I’m given both congratulations and condolences. Generally, at my university there is an expectation that department faculty ‘take turns’ being chair. So, we’re expected to serve whether the pay is good or not. There’s a lot of informal practice around this process.

In addition, Economics Majors have been less popular at liberal arts institutions over the past several years. No one knows why and there are probably multiple reasons. At my institution, our department has healthy enrollment among the peripheral majors. So, the Economics BA and BS have lower enrollment, but the Business Economics and the Global Affairs majors are more popular than ever.

All the same, I’d like to increase the number of students who have declared majors in our department and the number of Economics graduates. How do I do that?

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RGDP Underestimates Welfare

Like many Principles of Macroeconomics courses, mine begins with an introduction to GDP. We motivate RGDP as a measure of economic activity and NGDP as an indicator of income or total expenditures. But how does more RGDP imply that we are better off, even materially? One entirely appropriate answer is that the quantities of output are greater. Given some population, greater output means more final goods and services per person. So, our real income increases.  But what else can we say?

First, after adjusting for price changes, we can say that GDP underestimates the value that people place on goods and services that are transacted in markets. Given that 1) demand slopes down and 2) transactions are consensual, it stands to reason that everyone pays no more than their maximum value for things. This implies that people’s willingness to pay for goods surpasses their actual expenditures. Therefore, RGDP is a lower bound to the economic benefits that people enjoy. Without knowing the marginal value that people place on all quantities less than those that they actually buy, we have no idea how much more value is actually provided in our economy.

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Parkinson’s Law Before Class

Parkinson’s Law, the principle that “work expands to fill the time available for its completion,” was originally intended as a satirical observation on bureaucratic inefficiencies. However, it has broader applications, especially in academic life. When preparing to teach an intermediate microeconomics class, for example, I often find that Parkinson’s Law applies: no matter how much time I dedicate, there’s always more content, illustrative examples, and analysis that could be included. The time invested in preparation creates a tradeoff between covering the broad spectrum of microeconomic theories versus delving deeply into a few core concepts. Either approach can be effective, but Parkinson’s Law reminds me that more preparation doesn’t always imply improvement.

Teaching intermediate microeconomics presents a natural tradeoff between breadth and depth. The course covers foundational concepts like consumer and producer theory, market structures, and welfare economics, and each of these areas is rich with intricate details, special cases, and real-world applications. A broader approach would expose students to more topics, providing a more comprehensive view of microeconomics. Exploring fewer topics fosters more critical thinking and analytical skills. Too much preparation on one topic can detract from time that could be spent introducing other essential concepts… Or other classes for that matter.

Let’s say I have a few hours to prepare for a Monday lecture on consumer theory. I might fall into a spiral of over-preparation: digging into endless variations of consumer surplus or finding additional applications that illustrate price elasticity. This is precisely what Parkinson’s Law warns against; if I pour time into my preparation, then the lecture becomes denser beyond the ideal for my students’ comprehension.

The extra hours may result in a more detailed presentation, but this doesn’t necessarily mean better learning outcomes. A concise, well-planned lecture is often just as effective—if not more so—than one crammed with detail. Overwhelming students with information that won’t stick is bad pedagogy.

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Update on Game Theory Teaching

I wrote at the end of the summer about some changes that I would make to my Game Theory course. You can go back and read the post. Here, I’m going to evaluate the effectiveness of the changes.

First, some history.

I’ve taught GT a total of 5 time. Below are my average student course evaluations for “I would recommend this class to others” and “I would consider this instructor excellent”. Although the general trend has been improvement, improving ratings and the course along the way, some more context would be helpful. In 2019, my expectations for math were too high. Shame on me. It was also my first time teaching GT, so I had a shaky start. In 2020, I smoothed out a lot of the wrinkles, but I hadn’t yet made it a great class. 

In 2021, I had a stellar crop of students. There was not a single student who failed to learn. The class dynamic was perfect and I administered the course even more smoothly. They were comfortable with one another, and we applied the ideas openly. In 2022, things went south. There were too many students enrolled in the section, too many students who weren’t prepared for the course, and too many students who skated by without learning the content. Finally, in 2023, the year of my changes, I had a small class with a nice symmetrical set of student abilities.  

Historically, I would often advertise this class, but after the disappointing 2022 performance, and given that I knew that I would be making changes, I didn’t advertise for the 2023 section. That part worked out perfectly. Clearly, there is a lot of random stuff that happens that I can’t control. But, my job is to get students to learn, help the capable students to excel, and to not make students *too* miserable in the process – no matter who is sitting in front of me.

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5 Game Theory Course Changes

I want to share some changes that I’ll make to my game theory course, just for the record. It’s an intense course for students. They complete homeworks, midterm exams, they present scholarly articles to the class, and they write and present a term paper that includes many parts. Students have the potential to learn a huge amount, including those more intangible communication skills for which firms pine.

There is a great deal of freedom in the course. Students model circumstances that they choose for the homeworks, and they write the paper on a topic that they choose. The 2nd half of the course is mathematically intensive. When I’ve got a great batch of students, they achieve amazing things. They build models, they ask questions, they work together. BUT, when the students are academically below average, the course much less fun (for them and me). We spend way more time on math and way less time on the theory and why the math works or on the applicable circumstances. All of that time spent and they still can’t perform on the mathematical assignments. To boot, their analytical production suffers because of all that low marginal product time invested in math. It’s a frustrating experience for them, for me, and for the students who are capable of more.

This year, I’m making a few changes that I want to share.

  1. Minimal Understanding Quizzes: All students must complete a weekly quiz for no credit and earn beyond a threshold score in order to proceed to the homework and exams. I’m hoping to stop the coasters from getting ‘too far’ in the course without getting the basics down well enough. The quizzes must strike the balance of being hard enough that students must know the content, and easy enough that they don’t resent the requirement.
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Supply & Demand, with Tables?

When I was a graduate student, I paid for my tuition by tutoring for the university athletics department. I tutored stat, math, micro, macro, excel, and finance. I tutored the same students each week, so I got to know them pretty well over the course of the semester. I also got to know their strengths and weaknesses. It was at this time that I realized most quantitative or even analytical ideas could be described in 4 potentially equivalent ways:

  1. Mathematically
  2. Using logic in English
  3. Graphically
  4. With a Table

In this post I want to share the Supply & Demand cheat-sheet that I use to help my students learn about the effects of supply and demand.

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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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In Praise of the FRED Excel Add-in

Sometimes, large entities have enough money to throw at a problem that by sheer magnitude they produce something great (albeit at too high a cost). The iPhone app from the FRED is not that thing. But the Excel add-in is something that every macroeconomics professor should consider adding to their toolkit.

Personally, I include links to FRED content in the lecture notes that I provide to students. But FRED makes it easy to do so much more. They now have an add-in that makes accessing data *much* faster. With it, professors can demonstrate in excel their transformations that students can easily replicate. The advantage is that students can learn to access and transform their own data rather than relying on links that I provide them.

The tool is easy enough to find – FRED wants you to use it. After that, the installation is largely automatic.

Installed in excel you will see the below new ribbon option. It’s very user friendly.

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Teaching Price Controls (Poorly)

Economics textbooks differ in their treatment of price controls. None of them does a great job, in my opinion. The reason is mostly due to the purpose of textbooks. Despite what you might suspect, most undergraduate textbooks are not used primarily to give students an understanding of the world. They are often used as a bound list of things to know and to create easy test questions. If a textbook has to change the assumptions of a model too much from what the balance of the chapter assumes, then the book fails to make clear what students are supposed to know for the test.

I think that this is the most charitable reason for books’ poor treatment of price controls – even graduate level books. The less charitable reasons include sloppy exposition due to author ignorance or an over-reliance on math. I honestly would have trouble believing these less charitable reasons.

I picked up 5 microeconomics text books and the below graph is typical of how they treat a price ceiling.

The books say that the price ceiling is perfectly enforced. They identify producer surplus (PS) as area C and consumer surplus (CS) as areas A & B. There are very good reasons to differ with these welfare conclusions.

Problem #1

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PSNE: No More, No Less

Today marks the 27th anniversary of John Nash winning The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for his contributions to game theory.

Opinions on game theory differ. To most of the public, it’s probably behind a shroud of mystery. To another set of the specialists, it is a natural offshoot of economics. And, finally a 3rd non-exclusive set find it silly and largely useless for real-world applications.

Regardless of the camp to which you claim membership, the Pure Strategy Nash Equilibrium (PSNE) is often misunderstood by students. In short, the PSNE is the set of all player strategy combinations that would cause no player to want to engage in a different strategy. In lay terms, it’s the list of possible choices people can make and find no benefit to changing their mind.

In class, I emphasize to my students that a Nash Equilibrium assumes that a player can control only their own actions and not those of the other players. It takes the opposing player strategies as ‘given’.

This seems simple enough. But students often implicitly suppose that a PSNE does more legwork than it can do. Below is an example of an extensive form game that illustrates a common point of student confusion. There are 2 players who play sequentially. The meaning of the letters is unimportant. If it helps, imagine that you’re playing Mortal Kombat and that Player 1 can jump or crouch. Depending on which he chooses, Player 2 will choose uppercut, block, approach, or distance. Each of the numbers that are listed at the bottom reflect the payoffs for each player that occur with each strategy combination.

Again, a PSNE is any combination of player strategies from which no player wants to deviate, given the strategies of the other players.

Students will often proceed with the following logic:

  1. Player 2 would choose B over U because 3>2.
  2. Player 2 would choose A over D because 4>1.
  3. Player 1 is faced with earning 4 if he chooses J and 3 if he chooses C. So, the PSNE is that player 1 would choose J.
  4. Therefore, the PSNE set of strategies is (J,B).

While students are entirely reasonable in their thinking, what they are doing is not finding a PSNE. First of all, (J,B) doesn’t include all of the possible strategies – it omits the entire right side of the game. How can Player 1 know whether he should change his mind if he doesn’t know what Player 2 is doing? Bottom line: A PSNE requires that *all* strategy combinations are listed.

The mistaken student says ‘Fine’ and writes that the PSNE strategies are (J, BA) and that the payoff is (4,3)*.  And it is true that they have found a PSNE. When asked why, they’ll often reiterate their logic that I enumerate above. But, their answer is woefully incomplete. In the logic above, they only identify what Player 2 would choose on the right side of the tree when Player 1 chose C. They entirely neglected whether Player 2 would be willing to choose A or D when Player 1 chooses J. Yes, it is true that neither Player 1 nor Player 2 wants to deviate from (J, BA). But it is also true that neither player wants to deviate from (J, BD). In either case the payoff is (4, 3).

This is where students get upset. “Why would Player 2 be willing to choose D?! That’s irrational. They’d never do that!” But the student is mistaken. Player 2 is willing to choose D – just not when Player 1 chooses C. In other words, Player 2 is indifferent to A or D so long as Player 1 chooses J. In order for each player to decide whether they’d want to deviate strategies given what the other player is doing, we need to identify what the other player is doing! The bottom line: A PSNE requires that neither player wants to deviate given what the other player is doing –  Not what the other player would do if one did choose to deviate.

What about when Player 1 chooses C? Then, Player 2 would choose A because 4 is a better payoff than 1. Player 2 doesn’t care whether he chooses U or B because (C, UA) and (C, BA) both provide him the same payoff of 4. We might be tempted to believe that both are PSNE. But they’re not! It’s correct that Player 2 wouldn’t deviate from (C, BA) to become better off. But we must also consider Player 1. Given (C, UA), Player 1 won’t switch to J because his payoff would be 1 rather than 3.  Given (C, BA), Player 1 would absolutely deviate from C to J in order to earn 4 rather than 3. So, (C, UA) is a PSNE and (C, BA) is not. The bottom line: Both players must have no incentive to deviate strategies in a PSNE.

There are reasons that game theory as a discipline developed beyond the idea of Nash Equilibria and Pure Strategy Nash Equilibria. Simple PSNE identify possible equilibria, but don’t narrow it down from there. PSNE are strong in that they identify the possible equilibria and firmly exclude several other possible strategy combinations and outcomes. But PSNE are weak insofar as they identify equilibria that may not be particularly likely or believable. With PSNE alone, we are left with an uneasy feeling that we are identifying too many possible strategies that we don’t quite think are relevant to real life.

These features motivated the later development of Subgame Perfect Nash Equilibria (SGPNE). Students have a good intuition that something feels not quite right about PSNE. Students anticipate SGPNE as a concept that they think is better at predicting reality. But, in so doing, they try to mistakenly attribute too much to PSNE. They want it to tell them which strategies the players would choose. They’re frustrated that it only tells them when players won’t change their mind.

Regardless of whether you get frustrated by game theory, be sure to have a drink and make toast to John Nash.

*Below is the normal form for anyone who is interested.