← The Brainy Business | Understanding the Psychology of Why People Buy | Behavioral Economics
The Brainy Business | Understanding the Psychology of Why People Buy | Behavioral Economics
543. The Winner's Curse
00:55:59
In this episode of The Brainy Business podcast, Melina Palmer has the incredible honor of speaking with Dr. Richard Thaler and Dr. Alex Imas, co-authors of the newly reimagined edition of The Winner's Curse. This episode marks a significant milestone...
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- [00:00]
A
Welcome to episode 543 of the Brainy Business Understanding the Psychology of why People Buy. In today's episode, I'm thrilled to introduce you to Dr. Richard Thaler and Dr. Alex Emas, co authors of the Winner's Curse. Ready? Let's get started.
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B
You are listening to the Brainy Business Podcast where we dig into the psychology of why people buy and help you incorporate behavioral economics into your business business, making it more brain friendly.
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C
Now, here's your host, Melina Palmer.
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A
Hello. Hello everyone. My name is Melina Palmer and I want to welcome you to the Brainy Business Podcast. Today's episode is a bit of a dream come true and a huge milestone in my journey as a behavioral economist. This field is my life's work. I've studied it, taught it, built a business around it, and dedicated this podcast to helping others apply behavioral science in in a meaningful brain friendly way. And today I get to interview Richard Thaler. Yes, that Richard Thaler, Nobel Prize winning economist, co author of Nudge and one of the pioneers of behavioral economics and choice architecture, a concept he introduced alongside Cass Sunstein, who's also been on the show before. His work has fundamentally changed how we think about decision making, policy, leadership and business. Joining him today is Alex Emes, an accomplished behavioral economist and professor at the University of Chicago whose research focuses on attention beliefs and how people respond to uncertainty and feedback. Together they've co authored a newly reimagined version of the Winner's Curse, a title Richard first published decades ago. But this isn't just a second edition. As Alex shares in our conversation, at least 75% of the material is brand new, offering fresh insights and into how even smart, well informed people can fall into predictable decision making traps. From auction theory to sunk cost fallacies, it's a fascinating look at the real world quirks that continue to shape our choices. So here's a brainy question to keep in mind as you listen. How good are you at spotting anomalies? The little signs that something doesn't quite fit, even when the crowd seems convinced you it's right. Because often those anomalies are where innovation and transformation begin really quickly. Before we get into the conversation, I just want to be sure you know there are links in the show, notes for my top related past episodes and books, ways to get in touch, and more. It's all within the app you're listening to and@the brainybusiness.com 543. Now let's jump right in. Richard Alex, welcome to the Brainy Business Podcast thank you.
- [02:51]
B
Thank you. Happy to be here.
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A
Yeah. So excited to have you both on the show and talking about yourselves, your work, the winner's curse and everything. For everyone who doesn't yet know you, can you each share a little bit about yourselves and the work that you do?
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C
Okay. I'm Richard Thaler. I am a professor at the University of Chicago, Booth School of Business, and I've been messing with economists for 40 or 50 years or so. And this is the grand finale for which I've brought in young reinforcements, namely Alex.
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B
I am the young reinforcements. I'm not that young, but I'm a professor at the Booth School of Business as well. I'm a professor of behavioral economics. I have my PhD in economics, but half of my dissertation committee were psychologists. In undergrad, I did neuroscience, so I'm very partial to both fields. I've been interdisciplinary since the beginning, and I've fallen in love with behavioral economics since the beginning. So I've been doing behavioral economics research for more than 10 years now. I started my career at Carnegie Mellon, and I've been at the Booth School of Business for five years working with Richard Thaler.
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A
Lucky. We're all jealous and wish that we could be working with Richard. And I'm sure such an amazing team there at the Booth School of Business. And as you said there, Richard, as the kind of grand finale there, congratulations on your recently announced retirement. Retirement?
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C
Yeah. Just means I don't teach. Oh.
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B
Oh.
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C
And I don't get paid.
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B
But small detail.
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C
Otherwise it's. Otherwise it's just the thing.
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A
It's business as usual. Awesome. Well, again, thank you both so much for being here. Knowing the audience is familiar with behavioral economics, since that's pretty much all we talk about here on the show, I do think it would be great if you could each share how you define the field. Knowing Richard, you know, it also seemed very weird to be like, for people who don't know you, Richard Thaler, please introduce yourself. But like, knowing the. How much of the field is based on your work, I think your perspective on how you define and think about behavioral economics and why it's important will be really interesting for everyone. And then Alex, as you said, being as we're all kind of newer than. Than Richard in the field, but if you can share like your perspective and work in AI and all that would be interesting, I think, for everyone.
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C
So you're basically saying everyone is newer than me.
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A
I know. In the best way.
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C
I get it. I get it.
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B
That's the father of the field. It has to be true.
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C
Yeah, yeah, yeah, yeah, yeah, yeah. So look, I think behavioral economics, the original idea was to incorporate some psychology into economics. And the way economics has developed since World War II, it's gotten increasingly formal and mathematical. And because even economists have bounded rationality, making things formal kind of forced economists to create agents that are really smart because the easiest models to write down are of people optimizing. And so Adam Smith was a behavioral economist and Keynes was a behavioral economist, and the field sort of got less and less behavioral, kind of culminating with the Rational Expectations School. And that's kind of the era in which I entered the field. And I was lucky enough to meet up with Danny Kahneman and Amos Tversky as a young assistant professor and got the idea that I could use their concept of systematic bias to create another way of doing economics that would have better descriptive models. So more accurate descriptions of what people do.
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B
Yeah. And I think it's important to highlight both why behavioral economics is not psychology and how behavioral economics is not standard economics. So the way that Richard, Danny and Amos started in this process is by saying, let's take the standard model from economics, where everybody's rational, hyper smart, they know what they're doing, they never make mistakes. Let's take those axioms, those kind of principles of rationality, and systematically show how people depart from them. So loss aversion, myopia, things like that. So everything in behavioral economics is kind of defined relative to standard economics, where you have the standard model and show how there are anomalies relative to the standard model, hence the title of the book. And so that's been kind of going on for a number of decades. But where behavioral economics departs from psychology is that it's really rooted about economic questions, which are not necessarily the same questions that psychologists are interested in. So in behavioral economics, you see a lot of focus on what happens in a market, what happens when producers interact with consumers, things like that. These are not necessarily questions that psychologists would be interested in. And so therefore both there's a difference from standard economics and there's a difference from kind of behavioral science or psychology.
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A
Definitely. And being able to always kind of learn from each other and have some, you know, curious, like what's happening over here? That could be inspiring something over here. Where are they similar? Where are they different? Taking in the context of different aspects, and I think from that, I love that the initial articles that you were writing, Richard, were just these anomalies. Right. And this idea of spotting and then digging in on those anomalies to to see what, what all is there? What do you think got you interested in anomalies? And you know, do you think you're, there's a reason maybe you were uniquely suited to spot them and actually publish and put them out into, into a space?
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C
Well, you know, I, I would say my interest in the topics that were covered in those anomalies columns, I used to say it's because I was looking out the window and paying attention to what people were doing. And even when I was in grad school, I would see these models and my reaction was really, is that what people are doing? But then the origin of the original version of this book was there's this journal, the Journal of Economic Perspectives, by the way, your listeners, that's a journal that's available for free, and it's aimed to be readable to all economists, meaning non specialists. And I'd say anybody who's taken some undergrad economics classes should be able to read those articles. And when this journal was starting, they had these features every issue, which meant once a quarter. And I proposed that we have one on the topic of anomalies. And so this started in 1987, and I was recently tenured and I thought it could be useful to sort of poke every three months with a specific empirical result and say, look at this. This doesn't seem to fit the model and here's the evidence. And when I had written 14 of those that looked like a book and I more or less stapled them together, and that was the original version of the Winner's Curse, published in 1992.
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A
I love that. And it's fun, like you said. I think there's nice with that spacing, right? So it's not like constantly attacking every week with a new idea, but that like quarterly saying, well, I mean, let's look at this thing. Right? And asking that question is kind of a nice pacing to start to open it up. But I'm guessing it, you know, didn't know how big it all was going to get when you started, you know, in 1987 with those original, you know, first articles and that, that pitch for that column.
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C
Believe me, an academic article once a quarter does not seem like it's slow.
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A
Fair enough.
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B
We're at the annual pace here, right?
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A
Yes.
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C
When I would get the, the galleys of the next column, the editors were saying, okay, what's the next one going to be? So it felt like a treadmill. I mean, for somebody who's doing something weekly, this seems like a very leisurely pace. But these were Academic articles, and they had to be reviewed by the editors, who. The editor of the Journal at the time was Joe Stiglitz, who was, you know, a major figure in the field. And so there were friendly but critical eyes on each piece.
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A
Yeah, for sure. And as you say in the, you know, the intro to the book. Right. It's not like we think of an article often. People that are listening think it's like you said, an op ed, a column. Right. But it's like a couple hundred words or whatever versus many pages, as these were. So it's very different than what people might initially think of in that idea of an article. And so, as you said, the initial version, which was so well received, of course, was kind of the. All right. Like, not exactly, but kind of staple these together, and here they are in a book form. And so in this process of going to revisit the winner's curse. So there are people listening who've definitely read the. The initial. The original version, you know, why redo it? And as far as bringing in Alex for this new perspective, like, what's new and different in this new edition of.
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C
The book, Alex, why don't you take that.
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B
Richard kind of came to me, I think, in 2021, at this point, maybe even a little bit earlier, he had the opportunity to revise the book. And he said, well, you know, let's do something bigger because, you know, it's been. It's been a few decades since the original series of Anomalies columns, and he wanted to do something that looked back and also forward. Where is. Where is behavioral economics now relative to what was kind of written down in those Anomalies columns? What have we learned as a field? And two kind of, where is that field headed going forward? And so that required not just kind of like a little update that required writing essentially a new book. So we ended up with. I think our estimate is something like two thirds of the book is brand new, certainly not stapled together anymore. And, you know, each chapter essentially starts with the original Anomalies column as it was written before, with edits, obviously, you know, bringing things a bit more to speed. But then there's a. There's a significant update after each chapter looking at essentially what have we learned in the last 30 years since that column was. Was written? And the big thing that comes out and something that we really wanted to do from the beginning is, is thinking about kind of robustness. The. The. Is it. Was this a general finding? Is it something that was kind of in these little studies that were done in the 80s with human subjects at the University of British Columbia or something like that? Or is this something that's actually relevant for economics? Because that's where behavioral economics ended up going. That's why it became behavioral economics rather than a subfield documenting anomaly. It's to say, look, we've documented loss aversion. It's not just lab subjects at ubc, it's also professional golfers. It's also traders on some of the biggest exchanges in the world moving billions of dollars a day. These are things that are relevant for almost any question that economists want to ask. And that's where behavioral economics is today. And that was something that was really important for us to document and these updates as well as to include something that we also found very important, which is to show that the original findings were robust in the first place. So something that we did and include in the online appendix of the, of this book. We have a, I shouldn't even call it an appendix. It's online materials. It's going to have basically replication materials for every single main study from every chapter that was in the anomalies to basically show, look, all of this stuff replicates really well. You can do it yourself. There's no replication crisis in behavioral economics. So that's something that we really wanted to emphasize as well is that the field is built on very solid foundation.
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A
I love that and I think it is so helpful just to see this look back and like you said, the look forward and where they have the conclusion so far right of what we know, but also not just to say like well you know, this is what we did then some things are new or even to you don't have to scrap what was done before. It's amazing. So many of these anomalies have held, you know, through the decades and as you give those examples of real world application, additional academic research across, you know, countries and time and space, like all of it. So it's great to see and you can tell there's a lot that went into those, you know, new two thirds of combine combining and compiling all of that information to help it be this really balanced look at those concepts kind of one at a time as you go through. So it holds kind of that original structure but still feels so, so new and different. It's, it's really a great achievement.
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C
Probably the, maybe the most important development has been the existence of large scale data sets and meaning the possibility of replicating and elaborating on old findings with real consumers. So one example, one of my favorite Topics that I've written about over the years is mental accounting. I love mental accounting. And our friend Jesse Shapiro, now at Harvard for a while, a colleague at Booth has written a couple papers using data from a very large, large box store chain and showing. Well, the one cute result is during the financial crisis when the price of gasoline dropped by about 50%, people started buying more premium gas. So, and this is in a big recession, right? There's a financial crisis, but their gas budget has gotten looser. And so what do they do? They spend some of that money on buying pretty much a useless product which is premium gasoline. And so I love that we, we that like in one, in a capsule tells us where we've gotten in 40 years. So from, from anecdotes and experiments with survey questions to, to data with real people that's real consumers. And there are lots of others with traders and so forth.
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B
Yeah, like for example, with the endowment effect, we started with kind of pens and mugs where, you know, if you get a mug on the table, you demand almost twice as much to part with it as you do to buy it. And now we have data from the housing market where sellers who own their own house set very different prices to sell it than, you know, real estate agents sell selling similar houses because essentially sellers are endowed with their house. They set, set too high of a price and then they don't move it as fast. So there's these, this wedge that happens in a very, in a real world market, not a simulated market where there's not as much trade as you would otherwise expect to see because there's an endowment effect with housing. And you see kind of this sort of thing emerge all over.
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C
Where you see that most is people who paid a high price for a house and now prices have gone down. Those people are slower to sell because they would have to sell their house at less than what their neighbor got or perish the thought, less than what they paid. And here's some advice. If you're shopping for a house, don't bother to negotiate with somebody who paid more for it than what it's worth now. It's not worth your time.
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A
No matter how much you like that house, it's not going to be worth it.
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C
It's just. They're just never going to sell it to you.
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A
Right. Unless you want to pay exorbitantly for some other reason that doesn't really matter. Right. But that's its own anomaly for whatever that's worth. So. Well, I did have a question here that was going to Be about your. If you have a favorite chapter in the book, and I know you each kind of leaned on concepts, would you say that, like, Richard, is the mental accounting chapter your. Your favorite chapter or concept? Or do you want to talk about maybe another.
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C
Well, I, I'm particularly fond of the last chapter before the epilogue, which is a finance chapter on the law of one price.
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A
Oh, that was.
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C
Yeah, because it has a lot of very funny examples. And, you know, I like to talk about what we call smoking gun anomalies, and that chapter is full of them. So, you know, University of Chicago is the home of the efficient market hypothesis. And our colleague Gene Fama, who's a golf buddy of mine and a good friend, he invented that hypothesis. And a lot of people thought that it's not really testable. At least the part where you say that prices are correct, there's sort of two points. One is you can't beat the market. And the other is that prices are prices are right. I used to have a colleague many years ago who I would hear teaching and he would be yelling at the students the price is right. He had a big southern accent. And so how can you disprove that? Well, I may think that Tesla is priced too high, but I can't prove it. And lots of things I thought were too high have gone up by a factor of 10, like some say bitcoin. So this chapter takes the specific cases where you can test that. And here's one funny example. There's a closed end mutual fund, and I won't go into the details of that, but it's a kind of fund where the share prices are set by the market, not by the value of the stuff they own. There was one that had the ticker symbol C U B A, which of course is also the name of a country. And it was the Caribbean Basin Fund. And it, like most closed end funds, was selling for about a 10% discount, meaning you could buy $100 worth of assets for $90. Then one day it went to a 70% premium. And you know why? Well, the assets didn't go up at all. Right. So it was just everybody wanted this fund. And why? Well, it was the day that President Obama announced his intention to relax relationships with the country that has the same name as this fund, although the fund cannot invest in Cuban securities, and there aren't any Cuban securities.
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A
So.
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C
That'S amusing. And there are lots of other more recent ones. There are lots of funny stories about some of the meme stocks, including amc, the movie chain. But too long you got to read the book to get that.
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A
I love those. It did. When you were just sharing that story, it reminded me of not exactly the same thing, but. So tourism to Norway went up like over 30 plus percent when the movie Frozen came out, which is based in a mythical place. That's not.
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B
It does not exist in Norway.
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A
Yeah, it's not there. Olaf will not be there when you get there. Get there. But. And people were actually saying that was why we're taking our kids here because of the movie Frozen, which makes no sense. But, you know, they're saying, why. Why are so many people coming here? But. But it is silly. So much of it is, is silly for sure. Alex, what about you favorite chapter concept?
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B
Well, to be honest, that that's also my favorite chapter, so. But you know, it's. It's kind of a tie. So I really like that chapter. But I also like our first chapter on the Winner's Curse quite a bit because Winner's Curse is just such a, an incredibly striking phenomenon. So the difference between the Winner's Curse, which was documented in the original anomalies columns and a lot of the other anomalies columns is that it was, it started out as a phenomenon in real world data, which is that oil executives would bid on these plots of potential oil and then they would engage in an auction. And then they kept seeing that the winner of the auction would actually be losing money. Right. Over and over again, like systematically. So, so people started writing chap chapters and articles that got published in kind of specialized oil journals and things like that, saying, why is this happening? And the basic idea of the Winner's Curse is let's say there's, you know, a jar of pennies, and the jar is worth a specific amount of money, which, which is how many pennies are in the jar. You set it down for auction, and systematically, the winner of the auction will overpay for that jar. So why is that happening? Well, basically, you look, everybody kind of looks at the jar. Everybody gets kind of an idea of how much money is in there. So some people will be way too low. Let's say there's $100 in the jar. They'll say like 25. Other people will look at it, and for whatever reason, they'll say, look, it's $125. If I think there's $125, I will be the largest bid because I just think there's, there's more money in there than everybody else. So I will win, but I will also overbid relative to everybody else. So I'll end up losing money. And so this idea that bidding optimally is this very, very complicated process where you both have to take into account, look, I have a high signal, so that means I should bid high. I think there's $125 I should bid high. But also I should take into account that if I have a high signal, it's probably higher than everybody else, and therefore I might lose money. So I have to actually shade down quite a bit. But people don't do the second part systematically, right? And that's what leads to the winner's curse. You see it everywhere. And it's the, the, the wonderful part about this phenomenon is you could do it anywhere. You could, like, literally go to a bar down the street, put down a jar of pennies, and make some money because you're going to get the winner's curse, right? So I think I really love that idea. And in the updates, Richard can maybe talk about the loser's curse, which he, which he documents in. In the NFL, it kind of shows up almost everywhere. People just, like, really don't take it into account when in the, in these auctions, you have it with students, you have it with oil executives, you have it with sophisticated people, completely unsophisticated people. And it really highlights something in behavioral economics that's much more general than bidding for oil wells, which is that people are sophisticated in some ways, like, they think through the problem, but just they don't get to that final step. They're just not sophisticated enough as what's written down in our economic models. And that leads to all sorts of outcomes, like, you know, oil companies losing money.
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C
Yeah, Pick up on. I'm the designated sports analyst in this team, and I wrote a paper quite a while back with a former student, Cade Massey, who's now a professor at Wharton, on the NFL draft. And what we document is that the teams who bid for the top picks systematically pay too much for the right to pick first. And they do, because it's very hard to predict who's going to be a good player. Here's one fact from that old paper, which, incidentally, we've been in the process. Kate and I and a co author have been in the process of updating that. But suppose you take all the players at a given position, say, wide receiver, and you rank them in the order in which they were chosen. So the first one and then the second one, wherever they were picked, and you say, what's the chance the one picked earlier is better? Than the one picked next. Kate and I used to call this the better than the next guy statistic. And if teams were perfect, it would be 100% right. The players would be ranked in the order of their quality, which we can measure. And if they're flipping coins, it would be 50%. And the answer is 53%. So that means it's hard. And so you shouldn't give away the house for the right to pick the first one rather than the second one because there's only a 53% chance that he's really better than the next one.
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A
Yeah. And so many that get chosen deep in the draft, which, whether it's the psychology of like wanting to prove something, you know, because you were picked later, like what that does to someone's psyche as a player or whatnot, I think it's always fascinating. That's where, you know, fantasy football is its own.
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C
Right. The best example of this is Tom Brady considered to be the goat. The greatest of all time was taken with the 199th pick.
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A
Right. And definitely a lot of first round picks that we don't remember their names.
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C
Correct. Correct.
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A
I love it. Well, thank you for sharing those. I would say for myself and of course loved all the chapters and content. I really enjoyed the chapter on preference reversals and for me in the work that I do, it really is just in knowing for people in business, if you're looking to apply behavioral economics, like just getting started into this idea and thinking about that how you frame something will impact the choice someone is going to make. And so if you talk about it as do you want A or B versus B or A, that can determine whether or not they want A or B based on how that is presented. And people can just start to test and tweak and think about how they present that information and know that, you know, choice is relative. And that concept I think is so fundamental for people and really eye opening and helps them to say, well I can try that. Right. And go, go test and see it.
- [34:45]
C
So I'm really glad you like that chapter. And I have a fondness for that chapter for another reason, which is it was written with Amos Tversky and so the originals, many of them had co authors and Amos was the co author on that one. And as we say in the introduction, I can pick out certain phrases that I know Amos would wrote.
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A
Yeah.
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C
And if it, you know, he died so young, there are very few people left who remember him. But he, he was a genius and very meticulous thinker and, and also Funny. And so there's a chapter there with Amos. There are two chapters that were. Dania was a co author. And one of the reasons we took this weird structure of edited versions of the old stuff, plus updates, was we wanted to show how these things were presented at the time and with some of the famous early people in the field. And their words are there, and we leave their names there because they're important.
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A
Yeah. I imagine this was a very interesting process for you, to say the least, Richard, as you're reflecting on what it was like writing and thinking about those and revisiting those papers and the time that you spent in doing that and then thinking about bringing it to date and kind of this backward and forward in time processes like what's new and what's now and what was it like then? And revisiting it. So, yeah, I'm sure that was.
- [36:37]
C
Yeah, well, as Alex mentioned at the beginning, we started talking about this in 2021 or something like that. So Blue passed a lot of deadlines. We don't talk about the planners fallacy in this book, but we were certainly guilty of it, and we did now get the final, final galleys. So we think we're done.
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B
Something's coming out on October 21st.
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A
Never done.
- [37:08]
C
No, no, that's right. This is our first podcast, so.
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A
Ooh, what an honor. I'm overjoyed to be on that. So we've talked a bit about what has stayed the same and what's been reinforced there. But knowing that technology, society, it's all changed several times over, very dramatically since these were coming out in 1987 and into that early 90s. So let's shift a little bit. What do you think has changed in that time, either in your own perspective, Richard, or as you looking at what's new, what would be different for people, as we're looking kind of into the future, things to consider for the concepts and the field.
- [37:53]
C
Alex is in charge of what's new, I'm in charge of what's old.
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B
Well, I think. I think the. The really interesting part about going forward is kind of the interaction of behavioral economics as. And the percolation of AI in almost absolutely everything. You know, you're finding it in everything. You know, you're. You. You log into a website trying to buy groceries. There's like a little AI chatbot that pops up. It's going to be determining what product display placed where, what color is what. Everything is going to be kind of customized to every user. And the interesting part about that, as somebody who's kind of talked to lots of firms and managers within those firms. Behavioral economics is essentially everywhere. As far as from AB testing, which was, which has been doing, going on for decades, but now it's being done at such an incredible speed where like you log on to Amazon and your buddy logs on to Amazon next to you, they're going to be seeing a slightly different page because there's AB testing happening all the time. Where as you said before in the preference reversals section, the way that think the purchase decision or the way that products are, are placed can subtly. But you know, on the, when you have so much volume significantly affect the sort of money that you're making on a platform. And so AI could potentially kind of supercharge it to, to basically get. Use the data that it has in the, in the, in the model, plus include the data that it's collected on you over time, customize these models and essentially employ these behavioral economics concepts in a way that gets you to buy more, gets you to buy certain products over others, gets you to buy products with more margin versus less, gets you to click on the website, go through the process and then hit you with a price. At some, at some point, you know, this sunk cost fallacy that we talk about in the book, you know, you've already invested the time, you're already kind of at the end of the process, you're about to check out. Oh, all of a sudden you're hit with something else. Well, you're just going to be, you're just, you're more going to be likely to pay it because you've already invested the effort. So I think going forward, I think behavioral economics is going to be much more relevant for business than it used to be just because of the scale at which it could be deployed by firms for good and for bad. Right. So it depends on what the regulations look like. If completely unregulated, you can be really exploiting consumers to a high extent. But on the other hand, you can imagine behavioral economics used in a way that I see the products that I ultimately want to buy and it's easier for me to do that. So that is also something that can be deployed with these sorts of technologies. So I think we're kind of in unknown waters here. But my view on where we're going forward is that it's going to be very relevant.
- [40:55]
A
Yeah, absolutely agree with that. And it's been interesting to see as companies are announcing the things that they're doing as they are being praised or canceled, I guess in the, in the market of people saying, you know, where it's we're switching everything to AI or we're going to let AI do our pricing as an airline recently announced. And everybody is not happy about that. Saying like, so you're going to let AI take advantage of the highest price I'll pay for a seat compared to the person next to me. I see that though too is like you basically will be training and everyone to try to bargain and negotiate you down in a way where it doesn't end up being about like brand valuation gets to be very different in that way, in the way that you might be selling different aspects as what the AI will try to do and the deals it might make. And if you don't train it properly, I mean, there's just a lot there that I think is fascinating where those behavioral aspects are going to be really important. And COBRA effects abound.
- [42:04]
C
Yeah, I think firms have a decision to make about what kind of firm they want to be. And for sure you can steal from your customers. I mean, not literally, but you can take advantage of them and you, you can make money that way. It's not the way I would choose to run a firm. I would prefer to run a firm that people come back to because they think they can trust us. And if an airline charges its best customers higher prices because they know they're richer, that's just not going to sit well with somebody who's been spending a lot of time on airplanes. And so there's short run, long run concepts. A story we mention in the book is after hurricanes, big box stores like Home Depot will, they'll have trucks lined up in Atlanta or somewhere down there. But beyond where the hurricane is going to go, loaded up with plywood and bottled water. And they will sell the plywood at cost or below and give the water away because they want a long term relationship with the people who are going to be rebuilding those neighborhoods. Somebody else will load up a truck with bottled water and sell it off the back. And that's a good way to make some money if you get out of town before they lynch you. But it's not a good way to run a business. This is something I talk a lot about with my students or wait a minute, I used to.
- [44:20]
A
Definitely. Well, and I think with that, and I love that example, I always talk, business is a long game. Right. And we need to be thinking out into the future. And it's all about relationships. Also reciprocity, I think is the most important. Right. So giving kindness out there, it's Going to come back in all these positive ways you mentioned there. If you, if you had some students that were listening here, Richard, you know, we'll say that these are your students here. As far as advice of what you think is most important for people to be thinking about into the future for behavioral economics, the, the field, the environment, any of that that we have out there, what might you say, suggest people think about? Look to Alex, you're going to get the same question. So that's. But what do you think?
- [45:11]
C
Well, you know, I mean, Alex mentioned AI. That's obviously on everyone's mind. But you know, in terms of the big takeaways from behavioral economics, I think it's understanding the way the people you interact with think. So they're your customers, your employees, your competitors, and it's a long game with all of them. And I think that's a really important lesson. Don't try to win every exchange. Take the long. Take the long view.
- [46:04]
A
I love that. Alex, Alex, what would you say, knowing you sort of answered, but you get an opportunity to have a new answer, right?
- [46:10]
B
Yeah, I think as far as kind of like advice for people going forward, I think one of the most well documented biases is status quo bias. And it's just very, very broadly applicable. And one of the, the biggest kind of places where it shows up is what people tend to do and how do they respond to change. Right now we're in a, we're in an era where most people would agree there's a lot of change happening. And what status quo bias does is basically say, well, I will just keep doing what I've been doing before. This has worked in the past. I'm going to be doing this again. And I think one of the lessons from behavioral economics is that you should just be absorbing the information that you have and don't put any extra weight on things that you're endowed with. So if you have a certain set of skills that you kind of started on or have been using for a while, don't be afraid to say, hey, I'm actually going to take that extra class that seems important, or I'm going to use this new tool. I'll invest some time to learning it. You know, you see this with, with academics all the time. AI is coming around and, you know, I'm not going to use it. It's stupid. You know, it's. It's just a plagiarism machine. It makes mistakes, it hallucinates. This isn't going to matter. This is a bias because we know it matters. Look how much money it's generating for businesses. Look how, look at, use the frontier model for a couple hours and see, see what it's like. But people have this status quo bias for the skills that they already have and then they just, they just don't even engage with the technology and they stick to their opinions and they're going to be left behind. Those are the people who are going to be left behind. So I'm actually doing research going forward into kind of thinking about what are the sort of beliefs, what are the sort of characteristics of people who are slower to adopt new technologies versus kind of those people who just kind of jump right in and use them and potentially get ahead in the market. So to me, that's kind of one of the biggest takeaways from behavioral economics is to process information as it's coming in and to try to optimize to the best of your ability. Don't kind of rely on what you've been doing before and expect it to work again.
- [48:27]
A
Such a great point. It has been so fascinating to. I've actually seen where some people will post something that they like to write, let's say, and we'll talk about how terrible AI is and taking away from writing. So this was written by a real human, but their post is about how the AI is helping them to create the art on their own so that they don't have to hire a designer. But you know.
- [48:56]
B
Exactly.
- [48:58]
A
A little hypocritical perhaps, and we can see those opportunities there. Well, and I'm guessing knowing what I do about academic research and whatnot, potentially you're always looking for people in real businesses that might be looking to partner and open up for some of their teams that are doing some of these studies at some point. So I would say anybody who is looking for that down the line or interested or open to it, let us know, can connect you to Alex or you can of course reach out directly. But I know lots of large companies that listen that might be open to that. And getting access to real world data sets is always a nice thing to be able to have. So as we close out the show and conversation, I know you end the book with knowing you could have had many, many questions and things to think about for future research. You know, you have one sort of question that you think is a key thing for people to be considering. Do you want to share a little bit about landing on that question about what makes choices so difficult?
- [50:00]
C
Yeah, I think this is something that I've been thinking about for a long time. And we warn people that it's an interesting problem and a hard one. And the question is what makes something difficult? And it goes right to the heart of the idea of behaviorally economics. So mainstream economics is people choose by optimizing. And that's a good model for easy stuff like playing tic tac toe. And a smart first grader probably Alex's little kid can already play tic tac toe optimal. So but you know, no human plays perfect chess even though it's a deterministic game and it should be solved, but it isn't because it's too hard. So we should have different models for tic tac toe and for chess. And we don't. And it's because we don't know. We don't have a metric for what makes something hard. And we think there ought to be more research on that though we say it's a hard problem.
- [51:37]
A
Yes, it in and of itself is difficult as you look at what makes a choice difficult. But that hopefully, you know, it'll be interesting to see, you know, maybe as I'm on the edge of my own retirement in 30 years and I'm doing an interview with someone who solved that problem, it'll be fun to continue those conversations.
- [51:57]
C
I'll look forward to that.
- [51:58]
A
Ah, perfect. Wonderful. Well, I want to thank you both. I could of course talk to you all day but in being respectful of your time and for those listening, we'll go ahead and click close up here. We will of course have links in the show notes for the brand new never before seen book the Winner's Curse that happens to have a similar title to something that was out 30 years ago and links to, you know, your profiles and things. But for anyone who does want to follow you and learn more, you know, do you have best places for them to be going to do so we're.
- [52:33]
C
Both on Twitter for better or for worse, so you can find us.
- [52:38]
A
Perfect. Well, as said, we will have links in the show notes to make it easy for everyone and there's plenty out there to be able to find and research and a lot on the on the horizon. So thank you again. Hopefully the the first of I know many interviews you've done on the winner's curse. I've hopefully I've set a decent enough bar going into the future.
- [53:01]
C
Thanks a lot. It's been fun.
- [53:02]
B
Thank you.
- [53:04]
A
Thank you again to Dr. Richard Thaler and Dr. Alex Emas for joining me on the show today. What got your brain buzzing in today's conversation? For me, I'VE been thinking non stop about the importance of noticing anomalies. So often in business and life, we're trained to look for patterns, to seek consistency and focus on what's typical or expected. But sometimes the most powerful signals are the ones that don't fit neatly into the story. Those anomalies, the edge cases, the little things that, if we pause to really notice them, can completely shift how we understand the world. That mindset, being curious about the unexpected, is a thread that runs throughout the Winner's Curse, and honestly, it's one of the reasons I fell in love with behavioral economics in the first place. I encourage this mindset in everything I do with my clients, in my books, and right here on the podcast. Behavioral economics gives us the tools to see hidden patterns, ask better questions, and ultimately build systems, teams and businesses that work with human nature instead of against it. And personally, I'm just so grateful. Hosting this podcast has given me the incredible opportunity to learn from and with so many brilliant minds in behavioral science, and to be able to speak with Richard Thaler, someone whose work shaped the foundation of this entire field, and to share that conversation with you. I'm truly honored. Whether you've been listening since the beginning or this is your first episode, thank you for being part of this journey with me. As we close out the show. Here's a little something to reflect on as you go about your week. What are you overlooking because it doesn't fit the model? And what might change if you gave that anomaly a second look in your data, your decisions, your team dynamics, or even your own habits? Those quiet outliers might just hold the key to something remarkable. Whatever it is, come share it with me on social media. You'll find me as the brainy biz pretty much everywhere and as Melina Palmer on LinkedIn. There are links in the show notes to make it easy, as well as links to related past episodes and books, including the Winner's Curse, ways to get in touch, and more. It's all waiting for you in the app you're listening to and atthe brainy business.com543 and thank you again to Richard Thaler and Alex Emas for joining me on the show today. It was an absolute honor and joy to learn from you both. Join me next time for another brainy episode of the Brainy Business Podcast. It's going to be a lot of fun. You don't want to miss it. Until then, thanks again for listening and learning with me and remember to be thoughtful.
- [55:42]
B
Thank you for listening to the Brainy Business podcast, Molina offers virtual strategy sessions, workshops and other services to help businesses be more brain friendly. For more free resources, visit thebrainybusiness. Com.