Finance. It seems hard to learn. But is it really? Wall Street likes to overcomplicate everything money related, confusing a lot of people. Join us on this podcast as we help break down the world of money for you to understand from a relatable perspective. This is Finance Simplify. Hello everybody, how are you all doing today? My name is Rohan and I want to welcome you to today's episode of Finance Simplify, the official podcast for StreetFins. Today's amazing guest is Dr. John List, who is an economics professor at the University of Chicago. We'll be simplifying behavioral economics, a field in economics that has gained quite a bit of popularity in recent years. Dr. List has been a professor since 1996 and has won many prestigious awards in economics because of his work. He's been teaching at the University of Chicago, which is one of the most decorated economics departments in history since 2004. So without further ado, I want to welcome Dr. John List to the podcast. John, thanks for being here today. I'm excited to talk to you. Hi, thanks for having me. It's wonderful to be here. I guess we could just get started with kind of how you got interested in economics and how you got to where you are today, because I mean, just through the research I was doing online, you've had somewhat of an unconventional background coming into the world of academic economics. Yeah, I think that's right. So when I was your age, I had a goal of becoming a professional golfer. As a senior in high school, I was interested in going to college to play golf. No one in my family previously had gone to college, so I was a first gen. And I was recruited by a school called the University of Wisconsin at Stevens Point. It wasn't even University of Wisconsin at Madison to to play golf. So I accepted a partial scholarship there. And during my first quarter at the university, I learned two important things. The first one was I was not good enough to ever make any money in golf. I would not be a professional, but secondly, I learned that I really, really loved economics. And that love of economics had grown in part because I had become a baseball card trader. And what that basically means is when I was little, I was raised in Wisconsin. And I would shovel snow and cut grass for money. And then I would take that money to the local, I think it was called local PDQ or whatever it was called back then. And I would buy baseball cards. So I had a, I had a mast, a huge collection of baseball cards. And I was going to baseball card shows and buying, selling and trading. And it gave me a sense of that's a really interesting economics market. And I began to combine it with what I was learning at Stevens Point. And together that became a sort of research agenda for me early on when I was an undergraduate at the University of Wisconsin at Stevens Point. So that interesting experience of learning kind of as a participant in a market really with baseball cards. That was really what got you interested in economics paired with the sort of discouragement from the the golf field, right? That's exactly right there. Let's say there were two forces. One was a push. And that was the golfing community telling me I wasn't good enough. And the other one was a pull, which was this science that ended up in fact economics to me is just common sense. So it became a science that was pulling me because it just felt so obvious to me everything I learned in the classroom was just second nature to me. So I was actually thinking like an economist without actually knowing it. Yeah, right for sure. And you know, I take AP macro economics at my high school and a lot of people are saying this is one of the most sort of intuitive classes that they've taken with behavioral economics, which is something you are regarded as one of the like worlds for most academics in. There's sort of a big difference between behavioral economics and traditional economics. So what is that big difference? Yeah, I think that in the past people have marketed behavioral economics as a fundamentally different and substitute approach to traditional economics. I think that's actually wrong. Let me step back and first of all define the way I would think about behavioral economics. And that's essentially to use variance of traditional economic assumptions. And these variants are often with psychological motivation, but use those variants to explain and predict behavior. And to provide policy prescriptions. So let me give you an example, maybe this will resonate with your listeners. The way I think about behavioral economics is that it's a series of amendments to not a rejection of traditional economics. Let me consider this. Let's say that so I live here in Chicago and let's say that I have a baseball ticket to Fenway Park. So let's say my ticket is the bleachers of Fenway Park. And that's where the Boston Red Sox play. So how would this work in economies? I think standard economics will get me to Cambridge or even Boston University, which is adjacent to Fenway. But I need behavioral economics to take the final steps and to find my seat in the bleachers. And in that way, you have the traditional model augmented by the behavioral model. And together they complement themselves in a way that leads us to both understand the world better to predict behavior better and to speak to policymakers in a more informative way. So behavioral economics is this layer on top of economics where based on some of the reading I've done online about it, it's traditional economics make certain assumptions about the rationality of people. And then behavioral economics sort of says maybe people aren't as rational all the time, the super calculated, homo economicists sort of person, they make mistakes, they miscalculate, they have irrational behavior. So it's sort of that layer of accounting for irrationality on top of the traditional economics field, right? Exactly right. I want students of behavioral economics to think about this as an integrated part of classical economics. It's not a freak show that's isolated from the standard ingredients. It's actually a compliment. And one way to think about it is, you know, the standard model is a little bit like Dr. Spock. So Spock was this unswervenly rational computational genius who never made mistakes and was the perfect rational economic being. And on the other side, you have Homer Simpson. So Homer is this guy. He eats donuts and he always makes mistakes and he can never get anything right now. Depending on the situation, sometimes we're a little bit more like Homer and sometimes we're a little bit more like Dr. Spock. Now the truth usually is somewhere in between. And behavioral economics takes a standard model and gives us, let's say, particular behavioral areas where people are predictably irrational. And a behavioral economist will then think about here's a theory to explain why they're irrational in this way. And people like me who write a little bit of theory and then go out to the real world and test the theory will then explore is this new model correct. And if it's not, we augmented again, if it is, we start to build on it and try to learn even more from it. So it's really important to understand that behavioral economics is not a freak show. It's an it's an ideal where you're trying to be prescriptive and it's usually most people are in the line between Spock and Homer Simpson. And you mentioned you were trying to test out theories and one of the ways that you've done this is through field experiments. And this is sort of one of your major groundbreaking contributions to the world of behavioral economics. So could you talk a little bit about what field experiments are and how they contributed to the development of behavioral economics. So I think the first place to start is to take ourselves back to the 1990s. And in the early 1990s, there was a revolution occurring in economics.
credibility revolution. And on the one hand, this was led by people like Orléashin Felter, Alan Kruger, Steve Levitt, DeRonee Simu-Glu. And these people would use naturally occurring data. And what I mean by that is they would essentially have an idea. They would go back to their office and download mounds and mounds of secondary data to try to answer some of the most pressing questions of the day. Things like, what are the effects of minimum wages? What are the effects of various social programs? My guess is an example that a lot of your listeners know is Steve Levitt's work on how abortion laws affected crime. So Steve had mounds and mounds of data. And he used variation in state laws to learn about how those laws affected crime. Now, my contribution to the credibility revolution was instead of working with existing or secondary data, I used the world as my lab. And I generated new data from the world to test theories and estimate effects of programs. So let me give you an example. You're out in San Francisco. Right now, I'm the chief economist at left. So as a chief economist at left, I give advice to Logan Green and John Zimmer and other executives about optimal decisions that left should be making in the market. So one experiment that I might do is I might explore how different default rates in the tipping app. So essentially, what happens is, Rohan, have you taken a left or an Uber? I'm more an Uber fan myself, but I can't take a left. Okay. So as a, as the ex chief economist at Uber, I appreciate your business. So, but we can get into that later. But so at the end of your Uber trip, what you get is, you know, you leave the car and you give them a, a, a ranking rating from one to five. And then they ask you if you'd like to tip. And when they ask that question, there's a default. So typically there might be a default of like $1, $3, $5. It might be 5%, 10%, 15%. So one exploration is that you can vary those defaults and you can explore how that variation in defaults affects how much people tip. So, so my guess is, Rohan, is that you have been an experimental subject in one of my experiments. In fact, probably multiple experiments without even knowing it. Now, that's not creepy in the sense that I can't connect your name to your behavior because I don't have any IDs or names identified. But what I can do is I can say, when we give this different default string, Uber users respond in this particular way. So in that way, you can think about, well, beyond tipping, why is that important? One of the fundamental features that behaviorally economists have taught us is that defaults matter a lot. And what I mean by that is let's say that your parents have an IRA or a retirement account. It really matters a lot what the default is in that account because most people will choose the default. So that's sort of a behavioral economist trick to use defaults to guide people in the right direction with their retirement savings. For example, you can think about the same thing with donor carbs. So, not a backup. My contribution here in the early 90s on and still today is to use field experiments or to use the world to test economic theory and then to try to explain and put forward policies that can make the world a better place. Gotcha. And I feel a little bit less like a guinea pig in a live experiment now. But no, that's really cool because you were able to get so much data from their time as well previously at Uber and now at Lyft. And that would help the company make a lot of crucial decisions, not only from their app but just from their business standpoint as well. So I want to just sort of backtrack a little bit here and ask you a question about the history of behavioral economics. Could you talk about the founding figures, one of them being your colleague Dr. Thaler at the University of Chicago? Absolutely. So I think when you look at general economics and think about behavioral concepts, I think it's actually fair to say that all the way back to Adam Smith, who frequently wrote about the psychology of decision making, including the tension between a person's passions in their rational deliberations, which Smith actually refers to as the impartial spectator. All the way back then, we had these behavioral concepts being added into economic analysis. Now, really the big bang in behavioral economics was a paper on preferences over gambles that was written by two psychologists. One was named Danny Coniman and the other Amos Tversky. They published this paper on essentially how people look at gambles and how people are lost of verse over gambles, which we can come back to in a moment. But that paper was published in 1979. And in that sense, modern behavioral economics is a lot younger than the rest of the field. But people like Dick Thaler, who is my colleague here at the University of Chicago and won the Nobel Prize for his work, he ended up working very early on with Danny and Amos on issues related to loss of version with which Dick Thaler called the endowment effect, which essentially means that once you are given a good, you place a higher value on that good. And you act as if it's more valuable to you once you own it than before you own it. And that ends up having very deep implications for, let's say, financial markets for product markets. And Dick ended up working through the 80s and 90s looking at psychological insights like the endowment effect, like mental accounting, which essentially is people have different accounts, which they might put their money into. For example, if you're gambling, you place your one account is what you started with. And as you make money, you put that in a different account and say that that's money I've earned. And you might act differently over that earned money than your original dollars. These are things that people commonly do. And Dick wrote theories and did research on that. And his work really stems all the way to today. He and Cass Sunstein wrote an excellent book called Nudge, where they leverage psychological insights to in a way, try to make the world a better place. Now, where my work comes in is I'm primarily an empiricist in the sense that, you know, we have a lot of theories about behavioral economics. And a lot of those theories have been looked at in the laboratory using undergraduate students as subjects. But for me, the question was always, do those theories work in the real world? And when we move the lab from undergraduate students to real world economic actors, does the effect of things like market experience or people entering an accident do these things actually cause the behavioral insights from the lab to be more or less important in the field? So my contribution in behavioral economics has primarily been to explore using naturally occurring markets and randomization in the field experiment to explore how well those theories do in the real world. And then when they don't do well, I end up writing a, let's say, an extension or an augmented behavioral economic theory that then other people can test. And sort of going back to a concept that you said earlier, loss of version. And just a quick story about that. Yesterday was the Super Bowl. And I made some bets with the people who were at my house. I won two of those bets and I made more money than I made a profit. But what I found was that I was hesitant to bet on something else with the money that I just earned. So you mentioned that people are less likely to probably spend something that they just earned because it's almost like it's a loss for them, right? Could you kind of go into more about loss of version and then perhaps some other sort of basic theories in behavioral economics like heuristics, framing, reference dependence, and some other concepts. Yeah, absolutely.
So when you think about reference points, it's a case where if you think about what is my reference point and just for for ease of exposition, let's say that your reference point is your your current state. And what the literature has taught us is that people care in part about how their circumstances compare to reference points. So it really matters a lot whether a person is losing or gaining relative to their reference points. Now losses, so it seems from the broad literature, get far more weight than gains. And that's called loss a version. So what this essentially means is that people suffer from a loss that's about twice as much as a benefit from a gain of equal absolute magnitude. So people just don't like losses. So now you can say, what are the implications? Well, the implications are that loss of version discourages trade. Since, of course, each trade generates two losses and two gains, right, the buyer has a loss and a gain and the seller has a loss and a gain. And the losses are weighted more than the gains. So that's why it could frustrate trade and markets and as an economist, of course, what we show in our models is that trade is a good thing because trade ends up increasing the value of, you know, essentially what people can consume and what people can produce. Whenever I teach behavioral economics, I teach this part of the course by giving half the people in the room, a mug and half of them a candy bar. And then I ask each side to trade. What happens is that fewer than a quarter of the students typically trade, regardless of whether they got a mug or a candy bar, fewer than a quarter trade where economic theory would predict, of course, these two goods are roughly of equal value. In that case, economic theory would predict that half of them should trade. Students when they see that say, wow, you know, that ends up being really important because this gives us new insights from the standard economic model. And in that way, loss a version or these types of preferences can really give us a deeper understanding than just the neoclassical model alone. Right. And something that would also relate to that is the idea of risk a version in markets. The inherent fact that investors would choose probably not to invest during a time of great risk rather than taking a risk, which could obviously lead to higher awards as well. But the inherent fact that loss a version, it's prevalent very much amongst the larger group of people. It's also prevalent amongst investors too. Absolutely. So I wrote a few years back, I wrote a, that is it be called an op-ed in the New York Times on giving advice to investors to overcome loss a version in the invite, the advice was simple. It was once you invest in an asset, don't look at the returns day to day or week to week. You should not look at your investment portfolio more than once or twice per year. And the reason why is because if you look at it too much invariably, you are going to see losses, you know, every day some of your shares might have losses, some might have gains. But the losses are felt more heavily than the gains if you have loss a version and that will cause you actually to take a portfolio that ends up being too conservative because of what what I call myopic loss a version. And I was coined by actually Dick Faler and others in the literature, but I've explored myopic loss a version in markets and even traders have myopic loss a version. So myopic loss a version is something that is a feature in many, many people's preferences, but there are ways to overcome it. And I talk about that way in the New York Times op-ed about how if you just don't look or pay attention to your portfolio, you can be better off. Not just sort of obsessing with the daily volatility, the daily swings, because that can be obviously very discouraging to people who might want to be in it for the long run, but are just discouraged by short term losses. So you mentioned nudge theory based on Richard Taylor's book with a cast on steam. We also, as I mentioned before, we started recording we recently had Dr. Alvin Roth on the podcast. And as I'm sure you know, he did a lot of work with kidney donors and you have a section in your book, the y-axis, we also talk about organ donation. So just drawing kind of parallels there. How was nudging and it's sort of counter strategy, nuisances used in that organ donation study that you did. Right, absolutely. So I became interested in organ donation when my father in law was essentially on his deathbed. And he needed an organ and at the last minute, it came through for us. And I became very interested on a personal level because of my father law. But on a professional level, in part because of the seminal work of Al Roth, I became interested in whether one could use field experiments and behavioral economics to make the world a better place through organ donation. So my example was to look at cornea donation and look into cornea transplants in that particular area. And what I learned was essentially that there are millions of people who are standing ready to receive cornea that end up never receiving it because people pass along and they don't even understand that they can donate. And especially the cornea in this case. So what I did was I did a huge door to door campaign where I sent dozens and dozens of workers around Chicago to have people fill out donor cards. The element of behavioral economics that was in there is that I changed the default in terms of in the card, the default was you would donate if you didn't click a different box. And what you find there is that the default is incredibly powerful, something like we increased donation rates by five, five to 10 times what the donation rates were in the control. And then we also looked at other things like financial incentives or gift cards and explored how behavioral economics alongside elements like prices or financial incentives can work together. And what you find is that behavioral economics and standard incentives actually serve as compliments and any in many walks of life, including an energy savings. I do a lot of work on energy conservation as well, so it kind of blends itself back to the organ donation. So those are kind of ways that I've explored behavioral economics and field experiments in the area of organ donation. So I started going back to what Alvin Roth's episode was actually about, it was actually about market design and game theory. And I was hoping to ask you with game theory, there's sort of like the traditional game theory and then there's behavioral game theory. So could you also sort of make the distinction between those two? Sure. So one way to think about, for example, our payoffs. We mostly care about our own material payoffs, but we also care about the actions and tensions and payoffs of others, even people outside our family. So in the economics literature, this is called social preferences. And this comes in many systematic forms, you can think of negative reciprocity, you can think of social pressure. So what people have found is that they explore the power of social preferences. For example, you know, how much weight you put on another person's payoffs. And when you start to manipulate that aspect of economic theory and put it in a game say, say two players play in a bargaining game in economics, it's called an ultimate game. And what that means is that an anonymous sender and an anonymous recipient are paired the sender divides an endowment of $10. And they end up making that offer to the recipient. And then the recipient either accepts or rejects a division in the event of rejection. Both players go home empty handed. The recipient accepts and they go home with what the offer was. Now what that literature finds is that most senders propose a division in which a recipient receives at least $2. Because the senders anticipate that half the recipients will retaliate against an offer that is less generous and $2. So you put sort of elements like that in standard game theory and then that's called behavioral game.
And behavioral game theory essentially is adding realism to standard game theory, which people like John Nash and others pioneered. Going along this idea of taking what the traditional economic field is and its behavioral layer or counterpart, could you talk a little bit about behavioral finance, which is like kind of like a cousin of behavioral economics? Yeah, absolutely. I think where behavioral finance comes in is on the first front, a lot of the work of Dan Economan and Amos Tversky and Dick Thaler on loss of version, essentially lend themselves very well to behavioral finance. And in fact, they represent one of the core concepts in behavioral finance because what it leads to is it leads to people who are investing and trading based on their losses and gains. In a standard model, one to have that kind of prediction. So the first element where, let's say, behavioral economics enters the behavioral financial realm would be over loss of version. Now, another area would be how people think about investment over time. And in that way, you can see things like, well, people have self control problems. So what I mean by that is people plan to work hard or people plan to save for retirement or people plan to stop borrowing on their credit card. And then at the last minute, they re-nig. And in that way, if we can take care of the self control problems, we can really make people's financial well-being much better off. And a lot of these insights come from David Davidson and Matthew Rabin and Kato Donahue and others who show that we all have these kinds of self control problems. Now, in that way, that really leads to this idea that people have a really hard time trading off the present in the future. And in that way, if we could get them to make better choices in terms of investments for the future, their future selves would be a lot happier in the world to be a much better place. I think the two big things where I come in and where others have made impact has been around loss of version and around, say, way people discount the future, the way people have self control problems. Yeah, and I can attest to that idea of trading the past for the future because when you feel very full in the present, you choose not to order something in the future that will probably satisfy your hunger needs because you think that whatever is happening in the present would last into the future, right? So one thing that's super kind of been a common theme around all my episodes has been the idea of uncertainty and the idea that it plays a bigger role in our decision making than everything. So how does uncertainty play a role in behavioral economics and how does one really sort of study the effects of uncertainty and randomness and all that stuff? Yeah, that's a good question. So what I should first step back and do is define the way I think about uncertainty or ambiguity. So uncertainty or ambiguity or version was actually first first studied by a Chicago economist named Frank Knight. And he talked about ambiguity as being situations where we don't even know the probabilities that we should attach to certain events. So that's a lot different from risk. So when you think about risk, think about flipping a coin. If it's a fair coin, you would say there's a 50% chance of heads in a 50% chance of tails. So those are probabilities that we attach to each state of the world, heads or tails. And we know those probabilities in an objective sense. And we have models to look at risk aversion and expected values, etc. But with ambiguity, this is a modeling approach where you don't even know the probabilities. So you kind of attach subjective probabilities or say distributions of probabilities to try to make your decisions. Now I've been doing work on ambiguity aversion actually for roughly 10 or 15 years in the field. And what you find is that even really experienced traders are averse to ambiguity. And what I mean by that is they tend to shy away from situations that have an anordinate amount of ambiguity. But when they do have to make choices in those situations, they end up doing something that's sort of interesting. They end up putting a lot of weight on really bad outcomes. So they let's say that you could have a fair coin flip to where you said if it was heads, you lost $100. And if it was tails, you made $100, we would all attach 50% to each outcome, negative 100 and plus 100. But somebody who's ambiguity averse and doesn't know the probabilities might attach 90% to the negative 100 and only 10% to the 100. And in this way, they're shifting the subjective probability inordinately to the really negative outcome. And that causes them to look at gambles or situations in a very different way than if there were objective probabilities. So we've actually developed ways to figure out or measure people's ambiguity aversion in the field. This is work that I've done with Alex Emas and Uriganese where we have a series of field experiments and we look at people's choices and from those choices, we can back out both the risk aversion and their ambiguity aversion. And then that helps us understand why they're making the choices that they're making. Gotcha. So when reading your book, I mean, the one takeaway I got from that was that, I mean, you go to great lights in it to show that people just respond to incentives. That's kind of the basis for most of human behavior. Other those incentives are monetary or not. So my next question is, when does money really work as an incentive and when does it not? That's a really good question. And it's one that both my team and many other teams are currently exploring. But let me give you an example in each of the camps to give you and the listeners some intuition about when money might work and when it might backfire. So if I look at our data at lift and I look at when I raise prices for trips, what do you think happens when I raise the price of a trip? Do you think people consume more or less of it? We'd assume they'd consume less because it's more expensive. Exactly. So that's called the law of demand. And in economics, unlike physics, we don't have many laws. But the law of demand says as prices go off, the quantity demanded goes down. That's exactly what happens nearly every time. Likewise for drivers, if we increase their wages, what happens is they end up working more. And that's called the law of supply. So in that case, we can use money to predictably increase labor supply. And on the demand side, we can use money to predictably increase quantity demanded by lowering price. So in those types of situations, money, it works basically every time without fault. Now there are other situations where using pecuniary incentives or financial incentives, my backfire. Let's think about this story. So let's say that every morning I take out to my curb, I walk out of my front door and I have a bag of aluminum cans. And I put those cans on the curb every morning, whether it's raining, whether it's storming, whether there's snow and sleep. Every morning I put those cans out on the curb and when there's no financial incentive, my neighbors look at me and they say, wow, isn't John a great guy? He is an environmental steward who really cares about the future of the earth. He's recycling. John should be celebrated. Okay, that's great. Now let's say that we're in a world where every can I put out on the curb, I receive a dime. So now let's say I still do the same activity every morning, I take a bag of aluminum cans out to the curb.
and it's raining, it's snowing, et cetera. I still do it. Now how do my neighbors interpret my actions? What they say is, oh my God, look at that economist. He'll do anything for a dime. This guy will do cans and the winter, et cetera, et cetera. This guy is a miser. I thought he was better off than that. I didn't think he was that foolish. So now what that leads to is when we add financial incentives to an activity that I'm doing because maybe my self image or my social image, if we muddy those waters with a financial incentive, I might actually do less of it. So now that people think ill of me, maybe no longer in the morning, will I walk a bag of cans out? Because everyone thinks I'm a miser now. I'd rather help the environment in a different way rather than have people call names. So that's the trick is if we understand the underlying motivation, in that particular case, the underlying motivation might have been, I want to protect my social image or I want to feel good about myself. When we add money to those situations, if we don't add enough money, what we found is that incentives can backfire. And this goes all the way back to work on early blood donations by a psychologist named Desi in the early 70s, who found that when you add financial incentives to blood donations, there's a possibility that you can actually have less blood donated because you've added financial incentives. And I think part of the story there is exactly the story that I just told you in the listeners. Yeah, I can see how money would discourage it because it gives off a certain sense of something that money really wouldn't condone. As we near the end of our episode, I have a series of three questions that I would like to ask you. My first one is that as a professor, you talk to students at UChicago on a daily basis, what mistakes and misconceptions do you see them have about the world of economics? I think when you look at people who meet at the airport and people who just enter the University of Chicago as students, the biggest misconception is that economics is about the stock market, it is about interest rates, and GDP. That's part of economics and that's part of macroeconomics, but economics is a study of incentives and how people respond to both financial and non-financial incentives. So I think as people learn about economics here at the University of Chicago, they learn that it's a way to think about the world and that economics is involved in every facet of a person's life. And I think that the lay person and the beginning student in economics won't quite understand the importance of economics and how economic insights touch every facet of every person's life. - All right, and my final two questions, which I'll just mention to one, knowing what you know now about economics. What lessons have you given to your children about the world of money? And what advice do you have for teenagers and students in today's world and how they learn economics? - Yeah, that's a good question. So I would say that the fundamental, there are many fundamental problems that we, myself and humans more generally have, but one of the most fundamental problems that represents a thread through many of our problems in this world would be essentially that we overweight the present and underweight the future too much. So when you think about it, think about climate change. What you have to do to take care of climate change is you have to invest today, and that's a cost today and the benefits are in the future. When you think about your health, if you go to the doctor, that's sort of investing today for a good future outcome. When you think about students dropping out of high school, the easy road out is to drop out, but essentially what you need to do is invest today in the benefits are far in the future in terms of a better job or higher wages. So many of the problems that we as humans have is this problem where you need to impose a cost on yourself today in the benefits are far in the future and we tend to under invest because we put too much weight on the present compared to the future. So what I tell my kids is always make the appropriate trade-off in time and that's one of the elements that we talk a lot about in economics as well is that standard economics has discounting and how people should discount the future, but in behavior economics, what we've learned is that people make this very predictably irrational choice of putting too much weight out on the present. So I always try to get people to think more about what this leads to for their future self. And in that way, it becomes a much more, let's say, rational decision for both my kids and my students. Gotcha. And with this podcast, it's something I hope to help people in the present understand how to weigh their future in terms of their finances too. So John, I wanna thank you so much for being on the podcast today and look forward to talking to you in the future. - That sounds great. Thanks for having me and I look forward to being back on in the future. - Hey guys, I wanna thank you so much for listening to this episode of The Podcast. It truly means the world to us. Please give us your thoughts and feedback on today's episode, what you liked, disliked, and what we could do better. Thanks to Dr. John List for his insights today. I hope you understand behavior economics in a more simplified way. Once again, we are really happy that you're taking the initiative to learn finance and to better your future. If you'd like to get in touch with us, please email
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