Sam Allgood: How to Design a Class Backward

Scott Wolla (VO): Welcome to Teach Economics from the St. Louis Fed, where we deliver practical advice and simple strategies to make economics click for students at every grade level. On this episode, I’m joined by Sam Allgood. Sam is the Edwin J. Faulkner Professor of Economics at the University of Nebraska-Lincoln. Sam is a leader in economics education, serving as a current member and former chair of the American Economic Association’s Committee on Economic Education.

And he’s just finishing a term as coeditor of The Journal of Economic Education. His latest project, Rethinking Economics Education: A New Framework, coauthored with KimMarie McGoldrick, was published in the fall of 2025.

Sam, what sparked your initial interest in economics?

[cut to interview]

Sam Allgood: Like a lot of people, I just fell into economics in the sense that I started out as a physics major, then realized that was not for me. But I liked the math part of it. Then I thought I was going to do political science and go to law school. But then I took an econ class, and that was it.

I took econ and ended up double-majoring in political science and economics. But if someone asked me what my major was, I would say economics. Then, I realized that I wanted to do economics and I wanted to teach. So, those two things meant that getting a Ph.D. and becoming a faculty member were the route to go.

Wolla: What was it about economics that made you say, “This is it”?

Allgood: I like math. I like current events and policy, and I like philosophy. And I can’t think of any other field that blends those three things together.

I joke with my wife; she says if I had taken philosophy before economics, I probably would have been a philosophy major. And I can’t imagine what that would have done to my brain—just all of that together.

I liked thinking the deep, big thoughts that economics addresses. I like the minutia of getting in and solving a mathematical model. I love messing with data. So, it allowed me to flex all of those different parts of my brain. And the fact that I could do all of that while addressing a lot of really important questions, it’s just hard to beat in my mind.

Wolla: So, in your academic career, it was labor economics and policy. How did you find your way into economic education?

Allgood: Like a lot of people, I didn’t realize it was a field coming out of graduate school. In fact, I was, at the time, what we call “the trailing spouse.” My wife got the job first at the University of Nebraska as a finance professor.

At that time, there was a faculty member there, Bill Walstad, and he had just gotten two large [National Science Foundation] grants, and he needed someone to come on to those grants, to help do the evaluations.

So, my first job, before I got on the faculty, was working with Bill, evaluating those grants. Then, once I did get a full-time position—  The beginning was slower getting into econ ed because to get tenure at Nebraska, I couldn’t publish in The Journal of Economic Education—that would not have gotten me tenure.

So, I did do some stuff in econ ed early on and stayed connected to it, but I had to get tenure first before I could really dive in and become more full-time economics education.

Wolla: And then eventually coeditor of The Journal of Economic Education, which is the premier outlet for economic education research. How did that come about?

Allgood: The lineage of that was—  When I first came here and got involved, Bill Becker was the journal editor, and he was a journal editor for quite some time. And then Bill Walstad became the journal editor. And he was that for about eight years as well. Then when he was ready to roll off, he came to me, and I said, “I’m willing to do this, but I don’t really want to do it alone. I don’t know that I can give it the time.” So, the idea came up to coedit with KimMarie McGoldrick. We talked about it and decided. So, that was the way it came about.

Wolla: And how many years?

Allgood: This will be the end of our eighth year.

Wolla: And, I have to believe that eight years of coediting this journal had a lot to do with writing the book.

Allgood: Yeah. KimMarie and I, from the very beginning, starting as editors, what we noticed was that the amount of research being done in economic education was declining. When we started talking about it, what we realized is that a lot of the things that people think we know, we really don’t have research on. We all have opinions about what works in teaching.

There’s maybe some correlative research out there that suggests this is associated with that. But we don’t really know nearly as much as we think we know. The economics professors lack a little metacognition in that sense. So, that got us to talking: What can we do in this space? We spent a lot of time talking about how we can get the train rolling down the track a little bit better. And that eventually led to the idea for the book.

Wolla: So, really two parts: Economic education is about the pedagogy, like how we teach, but also, as you mentioned, the research behind it. What are the biggest gaps or disconnects you see in the way we currently teach economics?

Allgood: The one thing that the research does do is a pretty good job of letting us know what people are actually doing in the classroom. There’s been a series of chalk-and-talk surveys that go back 25 years now. So, we know that for the most part, instructors still mainly lecture, and assessments still look a lot like they looked 15 or 20 years ago.

What little evidence we do have about efficacy suggests that things like active learning are more effective. That’s obviously a very broad topic, but active learning does seem to be better. So, what we advocate for is people trying out more and new active-learning methods. Then ideally, what they would do is think about that in advance and think about ways of testing whether what they’re doing is making a difference in whatever category they want to choose, because that also is a whole other topic.

When you say “making a difference” or “changing outcomes,” you have to decide what that is.

Wolla: Your book calls for a more systematic, theory-informed approach to studying economic education. It’s called “a new framework.” Why do you think the field needs a new framework now?

Allgood: I feel like when I talk to people, we’re not sure if we’re saying the same thing. If you say you want to increase engagement in your classroom, what do you mean? Do you mean engagement with the content? Instructor-student engagement? Student-to-student engagement? So, it’s helpful that when I say “endowment effect,” or some idea, that we all have the same definition. If I say “elasticity,” we all are talking the same language.

Our hope is, by using relevance, belonging and growth mindset—which we feel most of the questions that get addressed in economic education fall into one or more of these categories—we all start talking in the same language. It makes it easier for us to have conversations about what we’re doing, and maybe more importantly, why we’re doing it.

It also encourages instructors to think about: “What is it that I want to fix in my classroom? Is it that students don’t think they can learn economics?” That suggests a fixed mindset; that suggests one path of changes that you want to make. Do you feel like your students don’t think economics is relevant? That suggests a different path. So, instead of just haphazardly trying things, think about what it is you think is missing, lacking or needs to be improved in your class that, along those dimensions, will help guide you toward picking things that actually will help to solve those issues.

Wolla: You mentioned the framework: relevance, belonging, growth mindset. Could you walk us through those three in a little more detail, and talk about how they work together? Are they sequential? Are they interrelated?

Allgood: Not sequential but probably, yes, interrelated.

Relevance is kind of a broad thing. Relevance can be that either the student sees the content in their everyday life, or they see the importance of it in the world in general. So, they can connect to it on some level.

If you have students that are really into policy and stuff like that, you connect it that way. If you have students that aren’t into current events and policy, then you can connect it to their everyday life. There are a thousand examples of opportunity cost that you can use that a student in a freshman economics class is going to relate to—tying it in, and making it relevant for the students so that they can see that connection.

These three things all come out of the ed-psych motivational literature. The idea is that for students to be willing to put effort in, they have to see the material is relevant. That’s the idea of relevance.

Belonging is that sense that you are somewhere where you should be. I’ve gotten some pushback from instructors like: “I don’t do anything that would cause a student not to feel like they belong.” I don’t think we realize sometimes that students walk in not feeling like they belong. So, it’s not so much that we do something, it’s that we need to do something to help them feel like they belong.

We know that we’re a very male field. We’re lacking a minority representation—a female student walking into a classroom. In my last intermediate class of micro, a class of 45 students, I think we had eight women. So, that in and of itself can be uncomfortable and maybe make a woman ask, “Is this field really for me?”

So, I need to take actions, like the first debate topic we have: Is the gender wage gap caused by discrimination? So, make sure I’m picking out topics and stuff that make them realize that this is a field where they belong, that there are questions that they can address.

And then the growth mindset is the belief that your effort is going to pay off. Even if you don’t know it now, if you work, you will eventually reap the reward from that in terms of your learning, versus a fixed mindset of “my effort doesn’t matter.” I’ve had students say to me, “I just don’t have that kind of brain. I can’t learn this stuff.” And that’s basically saying it’s a fixed mindset. So, why would a student who has that thought process want to put effort into studying if they don’t think it’s going to pay off?

Wolla: So, this growth mindset—  I’ve heard in education circles, sometimes they talk about whether the role of that educator in the intro course, whether their role is to weed out the people who aren’t going to make it or aren’t serious, or whether the role of that person is really to nurture and invest in everyone. I imagine that has a lot of implications for this idea of growth mindset.

Allgood: Yes. The thing to keep in mind here is—  Here’s the analogy I’ll use: In my youth, I could train and train in running and I could get faster, but I would never be a fast runner. So, even with growth mindset, there are limitations, right? In other words, people do differ in their cognitive abilities.

So, what we’re trying to convey with growth mindset is not that everyone is a budding Ph.D. economist—that’s probably not realistic. But should anyone who’s gotten into college be able to pass an intro econ class? Yes. And should a C-minus student with a little effort be able to become a B-plus student or a B student? Yes.

It’s finding a way throughout the distribution; it’s not just for the students at the bottom (obviously for the A students this is a little bit less relevant) but throughout the distribution, to try to show students that with just a little more effort, they can do better.

Wolla: So, as an instructor, what’s the low hanging fruit for each of those?

Allgood: For each of these, the strategies are different. What I think about is who I’m teaching. I teach large lecture intro classes that have students from all over the university. I’m going to have political science majors, sociology majors—all of those. So, when I teach that class, there’s a little more emphasis on things like income inequality, discrimination, a little bit more talk about that aspect of what economics has to offer. I tailor what I’m going to do so that they see perhaps more relevance for what they’re doing in their other majors.

When I teach my Honors Academy students, which are all business students, I take a different tack. They’re interested in business. So, my class is more focused on that content because that’s what they think is relevant.

For belonging for all of my classes, I do a pre-semester survey, telling them in advance, “Don’t put anything on here that you don’t want to be public.” I collect a little bit of information about them and then I come back to that stuff when using examples, or I have someone share, if they have a story that I think would be relevant for what we’re talking about, or I use that to direct them early in the semester to interact with each other on some of those topics. By using what I got out of the survey, I can pair people up. That’s just a real easy way of creating a little belonging and getting people talking to each other in the classroom, making them more comfortable.

With growth mindset, it’s all about giving people safe chances to fail. So, if all they have is four exams, every time that they fail, it’s a big deal. This is again using different types of formative assessment, so they can say, “Okay, I failed this time. But it’s not that big a deal. Put some effort in. Do that again.” Now you start to do a little bit better. Safe times, safe chances to fail are really important for growth mindset.

Wolla: Do you think about these three parts of the framework differently for an intro course or principles versus a 300- or 400-level course?

Allgood: At least in theory, the students in the 300- or 400-level course have already shown an interest in the field. So, maybe there’s a little less of the relevance. I would expect students walking into maybe not intermediate but more field courses that their relevance, belonging and growth mindset are probably already a little higher to start with.

So, it might not be quite as important. But that said, if you’re teaching a class called Public Economics to college students, you’re probably going to have to find a way of making sure that they see why that’s relevant, why a college student should care about what’s going to happen in that class. But I do believe it’s probably less of an issue for those upper-level classes.

Wolla: You emphasize backward design, which is starting with what we want students to know and be able to do, and then working backward as you as a professor think about your curriculum and instruction. Why do you think that’s really important in economics? What’s your pitch there?

Allgood: I think this is true about more than just economics. When a student comes to me and says, “I’m thinking about what classes to take at the 300 or 400 level. What classes should I take?” My first question is: “What do you plan to do when you get out? I need to know where you want to be in order for us to go backward and figure out what you should be doing now.”

This would definitely fall into “do as I say, not as I do,” because as I just said, I just kind of slipped into economics without really giving it any kind of careful thought early on.

The idea is: Why did you pick that content? Why did you pick that assessment? Why did you pick that pedagogy? Just because it was given to you? Have you thought about what it is you’re trying to achieve in this class? What is it that you want the students to know and to be able to show you? Without that, the way I look at it is—  If I say to you, “I’ll meet you in Brooklyn,” that’s like saying to a student: “You need to know comparative advantage.”

“What does that mean—I need to know comparative advantage?”

“There are a hundred ways to show that you are able to use comparative advantage; I haven’t given you any indication of that.”

So, with backward design, you first decide what you want students to be able to know and how you want them to demonstrate that knowledge. That perfectly works you backward. If that’s the case, what assessment enables me to determine if they can do what I set out for them to do? What is the pedagogy and content that support that? So, again, backward design is just backward induction. We do it all the time in game theory. It just makes sure that you’re aligning and designing your class to reach the goals that you’ve set out for students.

Wolla: How does that change the approach from someone that doesn’t know anything about backward design or is not doing it right? Is it just that they grab the textbook and teach their way through the book? How is this approach different?

Allgood: For a lot of faculty, the first time they teach, maybe as a graduate student, someone gives them a syllabus and a textbook, and the syllabus has certain content on it, and it has certain types of assessments. What’s also going to play into that maybe is they had what they had.

I think that’s why we see so much lecture still. But there’s really no thought. Is that necessarily the—  I don’t want to say “the best way to do it,” because we don’t necessarily advocate for saying “best practices,” but it just means I haven’t given any thought to what they want to achieve. And if the previous instructor didn’t give any thought to what they wanted to achieve, because—let’s face it—none of us took education classes; most faculty did not. So, the person who handed them that content, that’s how they got started. So, we’re just duplicating what was done in the past without necessarily giving it any thought. That’s how most professors go.

Backward design can be very—  If KimMarie were here, she could run you through it. She has [a broad knowledge of] backward design. It can be overwhelming and daunting. It doesn’t have to be that involved. Just be a little more simple: I’m going to do this. I want to achieve this. How can I get the students to that point?

Wolla (VO): We’re going to take a short break. When we return, Sam talks about why he cuts content to focus on depth, and why economics education research still has big unanswered questions about what really works in the classroom.

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Happy teaching! Now, back to the show.

Wolla (VO): Welcome back to my conversation with professor Sam Allgood. Before the break, Sam told us how relevance, belonging and growth mindset shape his teaching philosophy and shared insights on backward design. We’ll continue with Sam’s thoughts on how to strike the right balance between depth of knowledge and the number of concepts taught in an economics course.

[cut to interview]

Allgood: I think the first thing you have to find out, if you’re teaching at the intro level or at the intermediate level, is what they need downstream. This is, again, a little bit of the backward approach. In other words, I need to give those students who are going to be taking later econ classes, I need to give them what they need in order to be successful. That’s the first thing.

Then I think about my students. I know I cover a lot fewer topics than most instructors because, the truth is, almost all the really big, interesting questions can be handled with a supply-demand curve—not all of them, but a lot of the really big questions.

So, I’m teaching my large lecture, and I look at that chapter on cost curves, and I know that’s where the click happens, and they’re gone. They can’t really do anything after that because they don’t learn those cost curves. So, why don’t I instead go to markets that talk about labor and talk about what’s happening in labor markets, instead of teaching a bunch of psych majors stuff about market structure?

I definitely condense the content. I’m much more for depth over breadth, but I think you have to weigh what’s needed downstream. Again, in our intermediate level, this goes to the quantitative nature.

We’re requiring calculus for our majors. Then I start by saying, “So, is anyone in the 300- or 400-level classes using calculus?” And they’re like, “No.” So, why are we doing calculus? Why are we putting this unnecessary hurdle? I think that is the first step. And then tailoring your class and your content, so that it’s of interest to your students. In most cases, you’ll find that’s going to be a shorter array of topics.

Wolla: That’s really interesting. In fact, almost everyone on this show has said something similar. So, maybe there’s some selection bias. The people who are on this show, almost everyone says, covering fewer topics in more depth is more meaningful and relevant to the student. It might be better for them in the long run.

Allgood: I think so. And that’s why I’m on the AP development team. When I looked at all the topics that are on that exam, I don’t know a single intro college-level class that covers every topic that they have. It’s amazing.

Wolla: It is. I agree. So, let’s talk a little bit about research. You mentioned this earlier: What are some of the most important research questions that are still unanswered, or the areas where econ ed can really do a better job?

Allgood: I don’t want to sound nihilistic here, but these questions are everything. As part of this research, I went back and looked at the first research articles published in The Journal of Econ Ed—in, like, 1970‑71—and all you had to do is change the words a little bit. There was an article about teaching economics with television. We’re basically still asking the same types of questions. It was an adaptive assessment, but it was something very similar. The truth is, the questions haven’t changed because we haven’t been able to answer them yet. We still don’t know the answer to the basic questions: What we’re teaching—does it really matter? How we’re teaching it—does it really matter?

I said “active learning.” How many types of active learning are there? Are they all equally as effective? In most cases, active learning has been tested against lecture. But is active learning A better or more effective than active learning B? We don’t have much research that compares active learning to active learning.

Again, not to sound nihilistic, but we don’t know—  This is what I was talking about with metacognition: We don’t really know that much. And in my talk later, I went to ChatGPT, and I said, “What do we know about what leads to student learning in a college classroom?” And, basically, it said we don’t really know anything.

Wolla: In fact, when you talk about active learning—just those words—it is so broad. Right? In my previous career as a high school teacher, for me, active learning was getting students out of their desks and doing a simulation or an experiment. But when I talked to a lot of professors, clickers are considered active learning, which is cognitive activity. Right? So, even those words mean just a variety of things to different people.

Allgood: Yes, that’s right. I think the broadest sense would be: Anything you have the students doing—where they’re not just a receptacle for information—is going to be considered active. And not all active is necessarily better.

What’s interesting too is, I’ve read some research that says students say they like lecture because it’s easier, because active learning requires effort. It does make the student have to think and operate in class. And when they’re in the classroom, a lot of them would just like to write down what’s going to be on the test and then take the test.

It is broad in that, in economics, I think a lot of instructors just pick the stuff that they like. My colleagues that do experiments, I think they do experiments because they like experiments. And I think that does get the students up and moving and gets them engaged with the material and each other. There’s some evidence that it leads to better student outcomes, but not real strong evidence.

So, what I find is, when it comes down to it, it’s what the instructor feels is making a difference. And at this point, that really is all we have to go on.

Wolla: It seems like—and you would know much better than I—a lot of the research that happens in econ ed is testing the things that professors are already doing in their classrooms, which means that you have a bias toward what’s already happening.

Allgood: Right. Yes. That’s generally what we find is that people do something in their classroom, and they’re like, “Huh. I wonder if it had a different—” So, they run a regression, and they’ll find a correlative result from that and come to the conclusion that that way of doing it is leading to a better outcome.

Very few people carefully design a quasi- or a controlled experiment, where there’s a true control group, and really look at efficacy. It’s hard. And so most people don’t do that.

Wolla: So, if you had a young scholar who came to you and said, “You’ve seen a lot of this research. Where should I start if I want to do research in economic education today?”

Allgood: Well, speaking of bias, the first thing I’d say is: “Read our book.”

Wolla: Right, exactly.

Allgood: Actually, I would say the first thing to do is to do some reading, so I would say our book. But there have been [Journal of Economic Literature] papers about every 15 or 20 years that give you an idea of the literature. So, you just have to read these two or three papers. Then, The Journal of Econ Ed is about to put on a symposium that will talk about research methods.

So, reading the literature and stuff will help give you an idea of the questions and help you think about where the holes are in the literature—what interests you, because, again, that has to be there. And then the symposium will talk about a lot of the methods—qualitative randomized-controlled trials, all that kind of stuff—that you would need to employ.

Then I would say to go to CTREE [Conference on Teaching and Research in Economic Education] or other teaching conferences, and meet people and talk to them and find people with like interests, because you’re going to be much better off if you can find colleagues to work with. It’ll seem much less daunting if you have people to work with instead of working in isolation.

Wolla: I’m curious; you mentioned “qualitative.” Most of my training in research was qualitative. Economic education, economics, is very quantitative. And maybe that’s the nature of the economics field. But do you see more qualitative? Do you see value in people doing more research in qualitative, using qualitative methods?

Allgood: I do think qualitative has a role. In particular, when I think about things like choice of major, there are how many different reasons that students choose the major that they do? If you try to do a statistical analysis of that, I’m not sure you’re ever going to come up with a statistical model that accurately predicts college majors. I think that’s one of those areas where talking to students and doing it more qualitatively might guide more insight into how students end up making those types of choices.

If your end goal is causation, then qualitative is not going to have a role. But qualitative in that sense then could be an important kind of observational thing that helps you to inform the causal research that you want to do. So, you can design better research by understanding the process that students are going through before you start the research.

Wolla: That’s good. When you look back at your own teaching career, what changes have you made in response to what you’ve learned in the process of doing research or reading the articles in [The Journal of Economic Education], or—?

Allgood: Some of the changes that I’ve made—  I was punitive in my early career. I would grade students on attendance—I called it preparation—and I would have them have worked a problem. Then at the beginning of the class, I would randomly call on students. They didn’t have to get it right; they just had to have demonstrated that they had made an attempt.

The way I did it is I gave them points. And then for every absence and every time they weren’t prepared, I took points away. Students much more prefer a more positive approach than that negative approach. So, I try to inform that in what I’m doing. Students like reward more than they like punishment. So, that’s one of the things.

The other thing is more fundamental to the way I teach. Like most people who get a Ph.D., I thought, as a teacher the most important thing I had was my content knowledge. So, if I can just break it down and explain it in the right way, students were going to understand.

What I’ve come to realize is that being an effective teacher—you still have to have the content knowledge—I don’t want to say cheerleader, but you are a motivator.

I did a paper early on about the idea of students’ target grading. Many students are happy with a B. If you make the class easier to learn, they’re just going to put less time in, and they’re going to get their B and they’re going to walk. So, what do I need to do as a teacher? I have to make them want to learn. This goes to that relevance and belonging and also the growth mindset. I have to help make students think that studying economics is worthwhile, and that if they study economics that they will get something out of it; they will actually be able to learn the material.

So, when it comes to what I’m doing in the classroom and assessments, I always keep that in mind.

Wolla: That’s good. For instructors who are listening to this podcast and might feel overwhelmed by the [relevance, belonging and growth mindset] framework, what’s one practical step that they could implement next semester to make a small improvement?

Allgood: They should be doing—my colleague Gail Hoyt at the University of Kentucky is also a big advocate for this—that pre-semester survey where you ask students to reveal a little bit about themselves. And what I also do on my pre-semester survey is—I know some of the questions we’re going to get into later—so, I’ll ask them their opinions on that at the beginning of the semester. Then when we get to that topic in class, I bring up that survey. After we’ve covered it, I then re-survey them after we’ve covered the topic in class. And it’s fun to put that up side by side to see how they’re thinking has evolved.

Like I said, using that pre-survey, I see things that are of interest to students. You can actually use AI now to write individual—  If you ask them about a hobby that they have—  I’ve used AI to write a supply-and-demand problem for each student that’s specific to their favorite hobby.

Again, for stuff like that, obviously it makes the grading a little bit harder. But it’s supply and demand; it’s not that much harder because it’s generally just shifting the curve. But that’s now their question for them. So, this pre-semester survey can go a long way toward helping connect the students to the content and the students to the classroom.

Wolla: That’s great. So, as an example: A student says they’re interested in skateboarding. What would the supply-and-demand question be for that student?

Allgood: Something like that could be: You were an avid skater. So, we’ve just seen that—   Well, I’m trying to think of the materials that would go into making a skateboard—wood?

Wolla: Sure. Yeah.

Allgood: Wood prices are going up, and at the same time, a new video game is making skateboarding really popular again. What would you expect to happen to the price of a new skateboard?

Wolla: Right. So, you have a supply shift and a demand shift.

Allgood: Right. So, now they have to figure it out: What’s going to happen to the price of the skateboard that they’re going to get? I’ve seen it. I had someone who was into puzzles, putting puzzles together. And I came up with a really clever idea—a much better one than I just came up with—on the fly. So, it does a really good job.

Wolla: That’s great. I think it’s really valuable to think about how AI can really be supportive of teaching. Because teaching is challenging, especially when you’re trying to customize it at the student level.

Allgood: Yes. For a lot of the things that we’ve talked about, there’s a lot of material on the web. AI will be pretty good. If you say to AI: “I’m teaching an Intro to Micro class; it’ll have these types of students; I’m aiming for this level of difficulty; just start with a particular topic; give me a set of learning outcomes on production possibility curves and comparative advantage”—you don’t have to write them all yourself. Because there’s so much material on the internet, if you know a little Bloom’s Taxonomy, you can tell it where you want to end up on the Bloom’s Taxonomy. It does a pretty good job. You’ll have to tailor it a little bit for yourself like you would any AI output, but it can save a lot of time.

Wolla: That’s great. Sam, I want to thank you for being here for this podcast. Do you have any last words of advice for economic educators?

Allgood: Yes. Be brave and experiment—and not even if it’s research. Be willing to try new stuff.

I’m the faculty director of our Teaching & Learning Center, and I talk with a colleague that I work with there all the time. We try it. If it doesn’t work, we don’t do it again.

So, be brave in the classroom and be willing to try new stuff to see whether or not it works with your students. Don’t get locked in. It’s really easy to just open that syllabus and change the date from ’25 to ’26.

Wolla: Well, Sam, thanks again for being here. This has been a great conversation. Thanks for all that you do for your students and for economic educators. I look forward to reading the book in more detail.

Allgood: Thank you. It’s been a pleasure.

Wolla (VO): I hope you enjoyed listening to my conversation with professor Sam Allgood.

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From the St. Louis Fed, I’m Scott Wolla, and you’ve been listening to Teach Economics.