John List – Scaling Proven Ideas for UBER, Lyft & Walmart (#260)

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John List, Scaling Proven Ideas for UBER, Lyft, & Walmart (#260)

John List is the Kenneth C. Griffin Distinguished Service Professor in Economics at the University of Chicago, the Chief Economist at Lyft, and the author of The Voltage Effect: How to Make Good Ideas Great and Great Ideas Scale. His research has led to collaborative work with several different firms, including Lyft, Uber, United Airlines, Virgin Airlines, Humana, Sears, Kmart, Facebook, Google, General Motors, Tinder, Citadel, Walmart, and several nonprofits.

With his experimental research, John has focused on issues such as market internals, the effects of various incentive schemes on market equilibria and allocations, how behavioral economics can supplement the standard economic model, early childhood education and interventions, and, most recently, the gender earnings gap in the gig economy (using evidence from rideshare drivers). John List’s research has resulted in more than 200 peer-reviewed journal papers and several books, including The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life, which he co-authored with Uri Gneezy.

In 2011, John was elected a member of the American Academy of Arts and Sciences, and in 2015, he was named a fellow of the Econometric Society. He was awarded the Kenneth Galbraith Award in 2010 and the Arrow Prize for Senior Economists in 2008 for his work in behavioral economics in the area and the Yrjö Jahnsson Lecture Prize in 2012. He is now the Journal of Political Economy’s editor.

The Importance of Field Experiments & Data

John is passionate about using field experiments to investigate economic issues. Field experiments, he believes, constitute a one-of-a-kind method of obtaining data since they compel the researcher to comprehend ordinary events. Simply recognizing the interrelationships of components in field settings is insufficient. The field experimenter must also seek to understand the processes underlying such correlations, as well as more remote phenomena with the same underlying structure. The actual benefits of field experimentation cannot be realized until these two goals are achieved.

While John List’s work in education and charity remains a major focus, the data he has gathered has provided insights into a wide range of microeconomic topics, including how behavioral economic theories apply in the real world, pricing behavior, discrimination in the marketplace, the valuation of non-marketed goods and services, public good provisioning, auction theory, and the role of the market in the development of rationality.

And now here’s John List.

Full transcript below

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Podcast with John List. Scaling Proven Ideas for UBER, Lyft, & Walmart.


economics, book, people, scale, golf, john, uber, experiment, lyft, econ, chief economist, opportunity, work, mike, chicago, learned, data, thinking, firm, quit


John List, Mike Malatesta

Mike Malatesta  00:08

Hey, Everybody, welcome back to the How’d It Happen Podcast powered by WINJECT Studios. So happy to have you here as I am with every episode, and I’ve got an amazing success story to share with you today. John List has joined me on the podcast. John, welcome to the show. Hey,

John List  02:25

thanks so much for having me, Mike.

Mike Malatesta  02:27

So I heard John on another podcast. I think it was some little podcast called Tim Ferriss, about his new book. So much about not just the book, but his life that resonated with me that I that I reached out and asked him if he would come on, and thankfully, he’s here today, and you’re going to love this. So let me tell you a little bit about John. John List is the Kenneth C. Griffin Distinguished Service Professor in Economics at the University of Chicago. He’s also the chief economist at Lyft. His new book is the Voltage Effect, How to Make Good Ideas Great and Great Ideas Scale. His research has led to collaborative work with several different firms, including Lyft, Uber, United Airlines, Virgin Airlines, Humana and a bunch of others. For decades, his field experimental research has focused on issues related to the inner workings of markets, the effects of various incentive schemes on market equilibria and allocations, how behavioral economics can augment the standard economic model, early childhood education and interventions, and most recently on the gender earnings gap in the gig economy, using evidence from rideshare drivers. So basically, he studied all sorts of behavior from an economic standpoint, and maybe a little bit more than an economic standpoint. I’m going to ask him about that. His research includes more than 200 peer-reviewed journal articles and several published books, including the bestseller he co-authored with Uri Gneezy, The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life. John was elected a member of the American Academy of Arts and Sciences in 2011 and a fellow of the Econometric Society in 2015. He received the 2010 Kenneth Galbraith Award, the 2008 Arrow Prize for Senior Economist for his research in behavioral economics in the field, and was the 2012 Yrjo Jahnsson Lecture Prize recipient. He is also the current editor of the Journal of Political Economy. You can follow John on Twitter at @Econ)4)Everyone. John, thank you so much for being here. I start every show with the same question and that is how did happen for you.

John List  04:59

So Mike, Thanks so much for that introduction, I understand that you have just learned economies, and all of our words that we make up like heteroscedasticity and all of these fun words like he kind of metrics are fun to learn, but thanks so much. You’re doing a good job.

Mike Malatesta  05:17

Thanks. I’m good. Other one wasn’t in there the header or whatever. Yeah. heteroscedasticity. Thank you for excluding that.

John List  05:26

Okay, but you’re doing a good job. Like half the battle with learning economics is learning the language is learning, which I call economies. Okay, how did it happen? For me? I would say it’s one part luck. And one part economic thinking. Okay, so let me unpack that. The family that I come from, is a is a very proud family, wonderful family. But a family that might not place as much emphasis on education is what I place on on my children. I’m a first gen college kid. And I was really, uh, first gen college kid a little bit by mistake. My dream was to be a professional golfer. And I went on a partial golf scholarship to University of Wisconsin at Stevens Point, I grew up in Sun Prairie, Wisconsin, so a little village. Outside of Madison, when I was a kid, we had about 9000 people in the city. It’s grown a lot since because Madison has grown so much, but went to Stevens Point. And I learned very quickly in that first year of golf, that I didn’t have a chance. So what I mean by that is, I wasn’t ever going to make a difference in golf, I just wasn’t good enough. And it’s a little bit lucky, on the one hand to receive a golf scholarship that allowed me to go to college. That’s the luck part. And the other side of luck is that my research agenda became important, which we’ll talk about in a little bit. But the economic thinking side was that I figured out the opportunity cost of my time. And that’s something that most people neglect. But what I mean by opportunity, cost of time, is that I figured out, if I keep spending eight hours a day in golf, that’s really what our day was eight hours a day, it would have been really hard to be a really good economics student, I was always interested in studying economics. But if you want to be a Professor in Economics, you really have to be all in. You can’t be half in and then all in in golf. So I realized that the opportunity cost of my time in golf was just too great. So my golf dream there ended I, I continued with my scholarship, and I, I played the four years. But I really spent a lot more time focusing on learning economics and studying economics at that point.

Mike Malatesta  08:18

Okay, before I ask you a question about the golf, which, which I felt like it was really interesting, a story that you told about the golf, I want to, I want to piggyback on that, I would first want to ask this question about your book time, because right off the bat, this word scale gets used all the time. And you have it in the subtitle of your book. And the last sentence of your book, I believe, this is the last sentence of your book, The only way to meaningfully change the world is at scale. And here’s the thing I that I want to ask you about is I don’t think many people know what that even means. It’s a word that gets used a lot and people associate it with growth. It’s kind of like everyone says, Well, if you can’t scale, you know, it’s not worth doing that kind of thing. But I don’t know, I want to know how you actually define it, because it’s going to be sort of the foundation of a lot of what we’re going to talk about today.

John List  09:14

Absolutely. So thanks for that. I want to first dispel the myth that if your idea can’t take over the world, you shouldn’t do it. I think that’s that’s an issue that I bring up in the epilogue of the book. And I bring it up through the lens of my family. My family is essentially one man, one truck, one good life. And there’s no need to scale more. And I’ll talk about what I mean by scaling in a moment to scale more. They’re happy with that. And that’s a great life for them. Now, when I think of skill, I want you to think about my experiences at Chicago Heights. So Chicago Heights is a community around Chicago, that I started a preschool in back in 2010. So that preschool is meant to help three-, four- and five-year-olds, I built it from soup to nuts. Now, when I think of scaling, I think of first of all, I built that preschool to help those kids in Chicago Heights. I built it to write academic papers about what have we learned on the education production function from that experiment. But I also built it because I wanted to take what worked in Chicago Heights, and I wanted to first scale it horizontally, which meant, I want a school in Minneapolis, a school in Denver, a school in LA, so does my result scale from Chicago Heights horizontally. And then I also wanted to scale it vertically. And what I mean by that is, instead of just one school, around Chicago, I want 1000. So to do that, now is a totally different proposition, then to do the horizontal scaling. And what I mean by that is, if I have to hire 30, teachers in Chicago Heights, like I did in my pilot experiment. So if I want to do that in New York, I have to hire 30. Teachers, they’re going to do it in Atlanta, 30 teachers there. Now instead that that’s okay, I can do that. But if I want to hire 30,000, teachers around Chicago, didn’t vertically scale it. That’s an entirely different proposition. So when I think of scaling, I think of scaling across markets, in within markets. And we should figure out before we invest in our idea, whether it can scale, how it can scale, and where it can scale, because we waste way too much money in throwing dollars at ideas, because we try to move fast and break things, throw spaghetti against the wall, and whatever sticks. You cook it, we have too much of that. And our federal government, our state governments can’t afford to do that anymore. Because the solutions to our major problems are not coming by way of move fast and break things not working.

Mike Malatesta  12:38

Yeah. Okay. And that. Well, thanks for clarifying that. Because that I think that something that everybody can kind of get their arms around, like, I can’t dominate a whole market, say Chicago, for example. Because there’s not enough available in a something that requires talent, you know, talent. There’s not enough talented people around in order for me to do that. But, but on the horizontal side, if I go to these different geographies, different markets, I can surely find there your 50 People who have one, what are top talent,

John List  13:11

let’s say, I love that, Mike, you’re exactly right. So in the original experiment, what we find or in the original pilot, what we find is good teachers are non-negotiables. So we find that in the experiment, that’s what we need to always do in the petri dish is figure out what are your non negotiables. And then you can scale where you can find those non negotiables, then you’re exactly right. If I try to scale too big in Chicago, good luck. I can’t find 30,000 good teachers. And but I can scale horizontally. Now that’s important to know before I spend money.

Mike Malatesta  13:50

Okay, thank you. So now, I’m gonna get back to the golfer second, because I didn’t know. And it’s been a little while since I did listen to the book, but I didn’t know it was that early, like your freshman year where you made that because I remember you talking about playing golf with it was Jerry Kelly and Steve Stricker or they were maybe weren’t playing with them, but you were playing in a tournament with them. And and I remember you, you were talking about when is you know, quitting is not bad or something like that. There’s a chapter like quitting is not bad. And you you came out of that experience with the realization as I recall that these guys were a few years ahead of you, but in age, but in you know, there were five strokes or six strokes or seven strokes ahead of you, and you’re thinking that’s just an insurmountable you know, I can’t make up that many strokes or something like that. Is that was that

John List  14:45

no, you know, 100% So I played against those guys in high school. So I was a sophomore when Jerry was a senior, and we’re in the same conference. So we played together And the difference wasn’t that great in high school. So, you know, he went to Hartford, Steve Stricker went to University of Illinois. And they came back and it was the fall of my freshman year. And they came back for some golf at Cherokee country club, which is a country club in Madison, Wisconsin. And I just happen to have that weekend off of our golf. So I went out there to practice on Friday. And on the range, I noticed that their games had markedly improved. From the last time I had seen them in mind really hadn’t improved that much. So I kind of looked at the improvement function. And then I looked at what happened that day, they’ll play the same course, didn’t go very well for me there. And then I went back, and looked and scoured data from our local library, because I wanted to make sure that what I was seeing wasn’t the bogey. And lo and behold, after you look at all the data, it wasn’t working for me. So at this point, however, you know, I was raised in Wisconsin, really under the umbrella of Vince Lombardi. And I was born in the late 60s, Vince Lombardi was winning NFL championships, and then Super Bowls in the late 60s. And Vince Lombardi taught me that winners never quit, and quitters never win. And let’s face it, society, as a whole tells us that quitting is repugnant. And if you type in quitting, and inspirational quotes, you know, you’ll find enough posters on the internet, that you’d have to cut down half of the Amazon, to print out all those posters that tell you not to quit. So I was dealing with both society telling me that you’re a loser if you quit. And also kind of the way I was brought up, you don’t quit. So I of course, I didn’t quit the team. But mentally, my dream was done. And I needed to explore and discover a new dream. And that’s what I exactly what I talked about in chapter nine, I think it’s an eight it’s called. Winners quit, because winners do quit, but they call it pivoting. And they call it call an audible. If we would just stop calling acquitting and say I’m calling an audible. We’d all be all right. Why don’t we?

Mike Malatesta  17:34

Yeah, that’s I see a new Inspirational Poster. It’s like, cool, right, or it’s not

John List  17:40

quitting. It’s calling an audible. Look what happened to Peyton Manning? Right. Are you a football fan? Mike? Yeah, of course. Yeah. man. He’s in the Hall of Fame, because he knew how to call audibles. You could throw a little bit, but he was pretty good to call it audibles.

Mike Malatesta  17:54

Yeah. Yeah. And Denver got pretty smart about picking him up, too, after his career was over, right.

John List  18:00

picked up another Super Bowl. They had a pretty good team around him. Of course, he wasn’t really that good that year that they won the Super Bowl, but

Mike Malatesta  18:06

what the heck, well, yeah, well, yeah. It doesn’t matter. Now, whether he was or not

John List  18:11

exactly. I mean, he was really good in India, of course. But yeah, he was good enough to win the Super Bowl. So so that

Mike Malatesta  18:18

the this quitting thing, and the what you were talking about earlier was like, you know, throwing spaghetti on a wall sort of approach or, you know, move fast break things that reminds me of you, you have this thing you talk about in the book, and hopefully this makes sense. You tell me if it doesn’t, but this policy-based evidence versus evidence-based policy, and when I’m looking at those two things you were talking about, I think, I thought, why I should ask because those sort of seem like and they may not? You had different examples, I think in the book, but you know, it’s like, who’s wagging? You know, what’s wagging? Is the tail wagging the dog? Is the dog wagging the tail, you know, when it comes to making decisions?

John List  18:57

So what what is,

Mike Malatesta  18:59

what is what is it with us that we believe so much in our ideas that we don’t think we need to test them? So much of your work is testing ideas that people think they know the answer to? And all of a sudden you, you say, Wow, let’s, let’s prove it. Right. You have tons of examples in the book about this. But what is it about us, John? What?

John List  19:22

Yeah, yeah, no, you? I mean, Mike, you’ve hit on some very important questions in that. So we absolutely. So let’s start with what is it about us? I think we are a bundle of psychological biases, that are just waiting to be let loose. And the particular bias that you’re bringing up that I think is important in this area is called confirmation bias. So we have an idea about something that might work. So for example, we think the Early Childhood program that I that I did in Chicago Heights, you might have a belief that, oh, that’s going to work or it’s not going to work, whatever. If you believe it’s going to work, when you when you gather new information, you tend to accentuate the new information that is consistent with your belief. And you tend to argue that, wow, these data that aren’t consistent with my belief, they’re really not true. They’re really not legitimate data, and you try to find a flaw in them. And I think in many cases, especially men who tend to be overconfident, we have a belief that’s so strong about something, that there tends to be some evidence in favor and some against in nearly every decision making that that’s important for you. And you tend to accentuate what conforms to your beliefs. So I think that’s the number one, we have confirmation bias. Now, number two, in thinking about policy-based evidence versus evidence based policy, here’s what I mean by that. Let’s, let’s start by saying, anytime we use data to make decisions, that’s a good thing. Right? So it’s the, it’s the evidence based policy revolution of the last 20 or 30 years, that’s a good thing. What’s happened in the social sciences though, is, you have an idea. You go and test it. And typically, you give your idea its best shot of working. Okay, it’s called an efficacy test. Okay? So it’s like, give your theory its best shot, or give your data or your idea, its best shot. Okay, so you run the experiment, giving your idea its best shot, it works. You write it up in an academic paper, you publish it, you forget to tell everyone, it was an efficacy test. And then you move on, and work on something new, while everyone else digests your work, and implements it. Now, that is what God has gotten us into all this trouble, because what you need to do is say, look, what are the constraints at scale? What are the constraints in the real world, and bring those constraints to your original research or to the petri dish? In SE? Does my idea work with the wards are the constraints that any idea will face when you scale it? When you do that? That’s what I call policy-based evidence, because you’re looking at the environment that you’re trying to scale into? And asking, Does my idea work in that environment? And if it does, great at the scalable idea, if it doesn’t, now we need to say, what do we need to change? To see if our idea can work in the real world? So really, it’s it’s obvious what I’m proposing, it’s obvious, in the back of your head, you’re probably thinking, of course, John’s right, we should make sure that we test our ideas, it with the same flaws and the same constraints that they’re going to face at scale. Because if we don’t, what are we doing when we scale? We’re guessing where we’re moving fast and breaking things when we know they’re not going to work. And I think that’s why we don’t have solutions to poverty, to public education to discrimination. Because we’re not serious about looking into the environments where we want to scale, bringing those to the petri dish and saying, Does my idea work in that environment? And you

Mike Malatesta  24:12

what has to be let’s take the I want to get back to the discriminate thing because you have a paper on that that I wanted to ask you about John but the this this, you know this you know what, what is it about us thing that you just answered? How what in your experience, the companies that you come into actually work with? Some of my I, I mentioned at the beginning, but what has to be going on typically inside of a company for them to be receptive to you because I, you know, you were just saying, you know, they’re probably mostly men, they probably have very strong confirmation bias about what works in their business. And they probably don’t think they need help. They probably don’t. Maybe intuitively they do but but you know, we’re gonna have the rugged individualism we’re gonna hammer through this

John List  25:00

have absolutely no, no, it’s a good question. So early on, it was companies that were in trouble. And what I mean by that is companies like Chrysler, Sears, firms that had found themselves on the difficult end of either their product space or their competition space, they were having difficulties. And then it’s let’s throw out lines. And one of them can be the economist John list, and we’ll see if he can help us. It has slowly become entrepreneurs like Travis Kalanick, or Logan green at left, or Humana or Amazon or Walmart, what have you, these firms are doing great. And in the end, they really don’t need me. But what they’re realizing is that a dash of economics and a small dosage of let’s figure out some causal relationships. And if we can generate data in an optimal way, and combine it with economics, we can make better decisions. So the firm’s that are opening up more and more, I believe, are the ones who are looking for better solutions today, looking to have an edge tomorrow. And I think that’s what economics and data generation can give them. So the things I work on in a firm, whether it’s a for profit, or nonprofit, or government group, is I work on any issue related to economics, in their firm. And since I’m a believer that economics is life, and life is economics, economics has a seat at every table within an organization.

Mike Malatesta  26:55

And you in the book, you talk about your different experiences at Uber and, and Lyft, in particular. And as I was listening to it, and now listening to us now, I was thinking, Oh, well, what John really is, is sort of a mix between an economist and sometimes an industrial psychologist or some type of psychologist too, because it’s not just about numbers, like people look at things about economics, they think, well, it’s just about numbers, the way they think that a CFO only handles the money, whereas we’re real CFO is really, and, you know, very engaged in the whole thing. Can you is it like that, John, when you go into sale?

John List  27:40

No, that’s, that’s a great analogy. I’m glad you brought that up. Early on in my career, I spent most of my time at baseball card shows, and conventions where collectors were, because that’s how I could afford to do field experiments. I funded it with my baseball card collection that I purchased in the late 70s. As, as a kid, nobody else wanted to fund my field experiments. So that’s how I did them. So early on, I thought of myself, as an economic anthropologist, I would understand the nuts and bolts of a market. And then I would bring in the discipline thinking that the economics model can provide with what I knew about the market. Now, over time, my interests evolved into not only being an economic anthropologist, but I became interested in psychology and the underpinnings of how we can use psychology to learn about economics and behavior in the field that’s become behavioral economics. I’ve also taken on interest in sociology. And that’s because the sociological aspects, the network effects that we have in our economy are super important. I wrote a paper called the social side of human capital formation, and how important neighborhoods are to teaching our young children. So I’m part sociologist, I’m also part computer scientist, you know, how am I part computer scientist? Well, we do a lot of coding. And we have mounds and mounds of data. So my team and I, my team is roughly 10 People at left, we have to do a lot of programming. And we have to do a lot of programming to make sure we’re learning about what’s happening in our mounds and mounds of data. So sort of a jack of all trades a bit, in that I try to bring in the understandings from different disciplines. Sometimes you need psychology. Sometimes you need sociology, sometimes you need anthropology, but it’s always with a dash of economics. Because I think economics ends up landing, this very disciplined approach to understanding incentives and the underpinnings of why somebody is doing something through the lens of what are the incentives that are moving these people. And once you understand that, the rest is sort of dressing around the problem and how you can get to, let’s say, first pastor the maximum.

Mike Malatesta  30:27

Okay, I was, I’m glad you, I’m glad you address that. Because I, I was, I was walking my dog, and I was listening to Adam Grant. And I’m listening to him talk, and I’m like, sounds a lot like lists, you know, I’m like, wait a second, there’s a floodgate going on here. And I remembered you have a, you do have a chapter in the book, I believe on culture. And that’s right. That’s right. I was like, when that chapter came up, I was like, What is? How it I wasn’t expecting that at all. But um, but it but it just made me think about how, you know, that people put economists in a box. And probably because a lot of them will stay in a box, they, you know, they want to give just economic forecasts and stuff and you are, like you said, you know, it’s psychologist, you know, behavioral sociologists, all of these things. It’s just, yeah, it’s kind of, I don’t know how you put all those disciplines together and make it work. But you do. It’s really cool.

John List  31:30

Thank you.

Mike Malatesta  31:31

Thank you. And speaking of culture, like you, you go to some pretty decent lengths in the book talking about the differences in your experience at Uber from the interview process all the way through, you know, the time you spent there versus Lyft, to companies that at least a port, at least, I know they have different divisions that do different stuff. But on the rideshare thing to better, you could say are commoditized as being the same. But yet you know, you have an app you get into you get into caught you call the car and the car takes you where you want to go. Usually not back to your house, which is one of the stories you tell in the book.

John List  32:18

I’m still angry about that, by the way.

Mike Malatesta  32:22

Yeah, so John, John had to go somewhere. And Uber picked him up, I believe it was an Uber that time it was Uber. And he thought he was going downtown Chicago or something. And he’s working on his presentation. And all of a sudden he looks up and he’s back at his house. Yeah, that’s, yeah, that that’s, that’s not the experience that you want to leave the client with. But anyway, can you talk a little bit more about the differences in those and how both are? Both are scaling? I think I’m right there, you know, just making tremendous bit will they’re creating a new? I don’t know, economy themselves, sort of? Oh, yeah. That’s so different. The way you you described it.

John List  33:03

Yeah, no, no, you’re right. You know, I was talking to my kids the other day about Uber and Lyft. And, and I don’t think that our kids can even understand how different travel is around cities. Just in the last 10 years, how disruptive and innovative you know, both Travis and was on the Uber side and John and Logan were on the left side, you know, used to fly into Boston Logan and stand in line for 45 minutes, waiting for a cab. And, and now it’s touch, touch, touch and half the price you’re, you’re traveling to your destination. So the one thing that the industry has, however, is a differentiation problem. And what I mean by that is when a car pulls up, you don’t know if it’s an Uber or left many of them have both stickers on Yeah, they both sticker so the person’s do a lap in. But but it’s a real issue. If you don’t even know what kind of product or service you’re purchasing, you know, I always say, at least Coke and Pepsi have different cans. And Uber and Lyft we don’t even have different cans. So So one part of that then is you have to try to differentiate on some different levels. Now you create new product or new service, but within six months, the other one copies you because it’s really hard to trademark share or black or whatever, or LX or whatever you want to call it. So it looks like from the outside these monsters or organizations are isomorphic but when you’re on the inside, very different and it’s It’s very different than the sense of we are doing this as a team. And we are doing this as an organization that is trying to change the world. Both of them have that view, both of them have the view that data is our DNA. And we are going to use data until the end to drive decision making. But at least when I was back at Uber, where the similarities ended, is more or less from the process of getting from a question to a final answer. It was a little bit like, what happens in some academic circles, where the debate can be very heavy. And the scrutiny can be very, very heavy as well. And it can be a very intense process. And it was always meant to get to the right answer and get to the right answer as quickly and efficiently as possible. So there was never any issue about some demon trying to hurt others. It wasn’t that way, it was just the process of getting to the solution is just a little bit different between the two companies, we’re at left, you can think of, you know, they started driving cars with pick mustaches on the front, right. And this is a pink mustache family. And these are family members who you’re dealing with. And that’s how you work together. The pink mustaches would still be on the cars if they hadn’t fallen off and caused some accidents, right? It still be on? But But that isn’t just for show. That’s exactly how Logan and John run the business, and exactly how they want things. Now, I have no idea how Uber is run today. You know, when when the execs left? I’m, I’m sure they had dramatic change is they rolled over everyone at the exact level. I know Dora wanted to make that a key feature of his leadership is he wanted to add much more responsibility in terms of the leadership showing respect and care for all of the workers. I think that when the engineers email went viral, in a blog post went viral about what she had experienced, I think Dora’s mission was to was to reverse course on that. And from from everything I’ve heard he’s been able to do a good job on that. So my guess is now is that Uber and Lyft are pretty similar.

Mike Malatesta  37:56

Okay. Well, it’s, you know, and I haven’t experienced the kind of growth that either one of those companies has, has experienced, but it always seemed to me that civility matters to people because the human likes predictability, they can take bad news, they can take, they can change, but they can’t take, like, one day, it’s gonna be like this. And the next day, it’s gonna be like this. It’s very nerve wracking. That’s my experience. Are you gonna watch the Showtime show on Uber was coming out?

John List  38:30

Absolutely. I’ve, I’ve urged, I’m sure I’m not going to be in there at all. But I urge them if I am. I want Matt Damon to play the chief economist. So I don’t know if you can put in a word.

Mike Malatesta  38:43

machine that okay. Yeah, I’ll do that. Yeah. Hey, I got it. I’ll text him right after this. Yeah,

John List  38:47

tax. Don’t please, please, at least they can do for me. Now. I’m sure I won’t be a part of it. But I’ll probably recognize some of the some of the features on the show, I’d suspect.

Mike Malatesta  39:00

Yeah, well, maybe though, who knows? Maybe they’ll get into the tipping thing when you help, because that’s kind of an interesting thing. Absolutely. And I do want to talk about that. But before I go there, I wanted to add one more thing to your description of yourself, as you know, like we were saying, economic anthropologist, psychologist, behavioral sociologist of computer programming, computer programming. I want to add chameleon to that, because you are one of the few people that I think that I know who, you know, have sort of blended the academic world, the corporate world and the government world. I didn’t mention that in the bio, but you were you worked in the Bush administration, as well. And so what I wanted, the first thing I want to ask you is how do you blend like just you personally? How do you fit in in all these different places? And then, where is it? Where do you feel most or least comfortable?

John List  39:55

Yeah, good question. So on the first one I think the secret sauce is, is one part. If you can explain the Principles of Economics, and apply the principles of economics to problems, those types of solutions are really ubiquitous and sense that that kind of thinking traverses every situation. So what I worked on in the federal government was the Kyoto Protocol. I worked on the clear skies act. I worked on the softwood lumber trade dispute. So these are issues that I was advising the president on environmental and Resource Economics. And day by day, as I sat through meetings, many, many of my arguments would be econ 101. And what I mean by that is applying principles to problems. I was part of the taskforce that put together the Homeland Security. And that agency, working with Colin Powell, Condi, rice, Mueller, and others, and I was just adding simple economics to those discussions. And what I look at my work within organizations, it always starts with being able to explain how economic principles can help us think through a problem. Now, in the academy, of course, it begins with first principles, but to publish papers, you have to be doing many, many more advanced things. And and those are, so to answer your second question, the academy is my true home. And I’m a scientist through and through. So I feel the most at home, in using economics in an advanced way to try to stay on the frontier, and push the frontier. So I would say, That’s my true home. And I like to apply what I learned in the ivory tower to these other settings. Because a little bit of economics can go a long way to effecting positive change in every setting.

Mike Malatesta  42:29

Okay, thank you. And you, you mentioned early on that you learned the opportunity cost of your time, early, probably earlier than most of us to and I’m wondering how you’ve applied that. I know how you’ve applied that to other folks, because you have talked about it, you describe it a lot in your book, but how do you? How do you apply that to you?

John List  42:53

Yeah. You know, when I first learned economics, I thought that it was all obvious. And I didn’t understand why people would have trouble understanding. And then when I started to teach economics, I learned why people have trouble. Because you start out you’re teaching a new language, as we talked about before, you’re teaching economies to people. You have some math, you have abstract in very critical thinking. And you have a lot of logical conclusions that you have to reach when you think like an economist. So if you don’t naturally think like an economist, it’s really hard to learn economics. I’ve just always thought like an economist. And when I learned economics, it’s just common sense to me. But it’s certainly not common sense to most people. Because in many ways, it’s a foreign way to think, for the majority of people. Okay, so how do I apply that type of thinking? When you think about why people quit jobs, you ask them and I and I’ve done this in surveys where I say, why did you quit your job? Typically, the first frontline response is my boss no longer appreciated me. Second type of responses. I didn’t receive the promotion or pay raise that I thought I deserved. Third, lighter responses. I got cross with a coworker. Okay, in each of those situations, The person’s current lot in life got soiled, and they were pushed to move. I have never quit a job, because my current lot in life was soiled. Every time I’ve quit, and I’ve had a lot of jobs, I started university Central Florida, I went to the University of Arizona, I went to the University of Maryland, came to the University of Chicago, I worked at Uber and I left. The way I think about it is, what does my opportunity set look like? And has my opportunity set gotten better? In that it draws me to join. So most of the time, people neglect their opportunity cost of time. And when you neglect your opportunity cost of time, you don’t realize that, look, I’m the chief economist that left, what opportunities Am I foregoing? As a chief economist at left? Well, for one, I can’t be the chief economist at Walmart. So if that opportunity set gets really good, how many eventually going to have to tell lift? I’m going to leave because my opportunity set has gotten better. And there’s new science, and there’s new explorations at a different firm. And I can tell you, that will probably happen sooner rather than later. Mike, I don’t want to give a drop the mic thing. But I’m

Mike Malatesta  46:27

breaking news. So hold on everybody. Breaking

John List  46:29

news. Exactly. So So today’s my last day at Lyft. And I will be joining another top firm within the next 30 days. That’s, that’s a fact. So it’s it’s natural for me to think about my opportunity set and not to neglect the opportunity cost. And I don’t think that’s natural for people. So that’s an example of just applying standard economic logic that is first principles for me, but it tends to be worked for others. Mike, how do you think about it? Do you think about your opportunity cost of time?

Mike Malatesta  47:05

I do I think about it a lot. But I still end up getting into things that I know, are not going to give me or not maximizing my opportunity cost job less now than before. Like when I first was an entrepreneur I do. I mean, I would give up opportunity costs all day long, because I always thought everything I was chasing would turn into gold. You know, it’s one of those things, who knows whether it’s gonna be good. So I have to do it. Is there like a simple matrix that people could use John to think through like a simple thinking matrix,

John List  47:40

I think at the turn in terms of query, and I do think we should periodically take a look at whether our opportunity set has gotten a lot better. And what I’m talking about here is maybe every few months, whether it’s an apartment, or a job, or what have you take a look and see, you know, is there a way or another job that will use my comparative advantage that will better leverage what I’m good at. Because a lot of times you take a job because you want to make a living. But you realize through that process that maybe this isn’t the perfect fit. And maybe they’re not leveraging my skills, as well as they could. So that’s not a good thing. So you should periodically look around, I would say, Don’t move or quit, until you know, you have a great opportunity. So I don’t want people quitting just to quit. But if you have a great opportunity, it’s a sure thing, and it’s going to take better advantage of what you’re good at. Go for it. We don’t do that enough.

Mike Malatesta  48:54

And you thank you for that. And we you know, you mentioned you talked about the quitting thing before with the golf and but but then you mentioned central central Florida, is that the first place? And if I recall, you applied to like 150 places. And 149 Central Florida said yes. As the first one that say yes out of 150. So there’s that part of not quinic Because you were at that point, I suppose you were just bought in that you were on the right path. And so you didn’t you there were no, you didn’t go to the library and look for two days. And look, that’s like you did in the golf thing, right? You You knew my exam, right or

John List  49:34

100%. Right? And that this happened sort of twice early in my career. One was applied to 150 schools, I only got one interview, and usually you’d get maybe 20 to 30 interviews. So that was a really bad sign. And the other one was nobody believed in my field experiments really. And they didn’t think that using the world is your lab was the right way to go about economic research. Now, in the first case, it really was the case that I’m, I’m really not good at anything but economics. So if I would acquit. Like, if you see a foot of work, I’m not sure what I would have done. But there really wasn’t an outside opportunity for me. What else am I going to do? If I can’t make it? So the fact that I didn’t have anything else to go to had UCF not work? I’m not really sure what I would have done in the field experiments was it was kind of clear to me that as soon as I would explain what field experiments were about, and how useful and important that can be to economics, then people did come around. So that was a process of, of educating, and teaching. But you’re right, it wasn’t the case that I was looking around right away. Because I was convinced it was my comparative advantage economics.

Mike Malatesta  50:56

Got it? Well, I’m glad you left us with that. I’m gonna get to that. Because that, you know, the, I feel like you have to say yes to a lot of things before you learn what you need to say no to be, you know, this opportunity cost is something you have to develop. And I feel like if you, you know, right off the bat, or be like, Nope, I’m not going to do this, you know, I’m only going to do this things, or I’m only going to do what I’m passionate about, or all the some of the stuff you hear on the inspirational posters we were talking about earlier, you, you really haven’t given yourself the opportunity to understand your own. What’s your opportunity cost is?

John List  51:36

I think that’s a great point. I’m so glad you made that, Mike, I think early on, youngsters don’t experiment enough. And they don’t try enough new jobs or new situations or tasks, in that they never gain a chance to figure out what they’re good at, and how they can change the world. And I think more and more as people begin to understand and appreciate their opportunity cost of time. And opportunity cost of doing a task at work means you can’t do another task. It means you can’t learn what you’re good at. And I think that is going to lead us to more and more experimentation in the workplace and more and more trial by error. I think that’s a good point, Mike.

Mike Malatesta  52:23

And last question for is it? Is it more intimidating? To write a book and see what people think about it? Or is it more intimidating to write an academic paper? And think about it?

John List  52:37

Great, great question. I think academic paper in for two reasons. One, let’s face it, that’s my real currency. My real currency as a scientist is what my colleagues and contemporaries think about my work, and how future economists use my work. So that is my true currency. The second is because a lot of our let’s say, reviews come in an anonymous way. So the way that the academy works is, you send your paper into a journal, and you tend to get maybe two, three or four anonymous reports. And those reports can be quite snarky. And they still hurt my feelings. In many cases. Most of the book reviews now there are some on Amazon that are, are snarky, and they’re anonymous, and they hurt my feelings. But in the academy tends to be really concentrated in that they’re the best other minds in the academy who are telling you that you’re dumb. And that that really hurts. I mean, it really hurts anytime. But when you have another academic saying that something you’ve worked on for a big part of your life, you’re completely wrong on that that stings, and it really does hurt. How do you handle it

Mike Malatesta  54:14

when you have the opportunity to be that reviewer? Yeah.

John List  54:20

I’m an editor. Now, as you mentioned at the beginning, and I’ve just also started a new journal called Journal of Political Economy micro. So I’m an editor of two journals now. And I try to be honest, fair, and kind. In my letters, I want my notes and reports to be if they saw me write that on my computer, that I wouldn’t be embarrassed or ashamed. And I have no problem signing my name to this and I think if we had a little bit more civility and a little bit more human Edie, in terms of, you know, think about writing this for one of your children’s essays or their reports, in which you talk in such a way to them. And if not, then you shouldn’t be writing it. Yeah, and you should be proud of what you put on paper, whether it’s anonymous or not. So that’s my view on the entire approach of anonymous reporting.

Mike Malatesta  55:27

There’s a whole skills seems to me to disagreeing with someone without being you should try to elevate your status as a result of disagreeing.

John List  55:41

That’s, that’s a great point, I think a little bit of theory of mind, will really goes a long way in these cases. And what I mean by theory of mind is the ability to put yourself in the shoes of the other person. And think about all of the work that they’ve put in, and how important that piece of research is to that person. And I think the minute you practice or have a little bit of theory of mind, then that can go a long ways and be in a kind person too.

Mike Malatesta 56:14

Well, that’s an awesome place for us to end, John. That’s that, thank you for that pick up John’s book, The Voltage Effect, believe me, you will get so much value out of it. And you will be surprised by we covered like, like this much of what’s in this book, and just all the examples, and all the theories and all the just the real stuff. It’s not like it isn’t this it’s I don’t know it to me, it felt like I was just hanging out with a with a friend. And I was just being schooled on all these different things that I may have thought a little bit about at some point. But now I think a lot more about them. So John, thank you so much for writing the book. You can you can follow John on Twitter at @Econ_4_Everyone. Is there anything else you’d like to leave us with John?

John List  57:03

No, I just want to say thanks so much for your kind words. They mean a lot and thanks for having me on. I really appreciate it Mike. My pleasure.

Mike Malatesta

Mike Malatesta

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