Welcome to the Lauder Institute at the University of Pennsylvania. I'm Jules Van Binsburgen, director of the institute and a finance professor at the Wharton School. And I'm Jonathan Burke, a finance professor at the Graduate School of Business at Stanford University. This is the All Else Equal podcast. Welcome back everybody. Today we're going to look at something that has always fascinated me, which is in a competitive market, most economists would say that the competition is so strong that if firms don't correctly optimize, they get weeded out.
And so you would expect close to optimal behavior firms. And I have to say I buy into this. But today we're going to look at a case where it's I think very clear where you have a competitive market and firms are not optimizing and that is the NFL. So before we get into it, let me first turn it over to Jules because not every listener understands football and Jules I think is one of them. >> You're so right about that Jonathan. So just for our listeners
in Europe, the NFL stands for the National Football League. And of course in the United States, football means something entirely different than it does in Europe. And so we're talking here about the sport that's called American football. And so the reason why indeed this is an interesting topic to study is that doing an an experiment in a firm where you really can observe all the possible decisions that can be made and where you have a good sense of what the competition really looks like is actually
pretty hard. And so therefore and our guest today David Romer wrote an academic paper that we are going to be discussing together. He essentially found a very nice competitive setting where we can really rationally model what a competitive player would or should do and then we can compare that with the actual behavior that we're observing and indeed for our listeners to understand what we're going to be discussing next. It is probably a good idea to lay out the basic rules of football. So let me try
to do that as in simple possible terms as they can Jonathan which is indeed not an easy feat. Now, for our listeners that are intimately familiar with football, we suggest that they skip the next 3 minutes and go straight to the 5 minute and 30 second mark. For those listeners that are not that familiar with football, I hope that the next explanation will be useful. So, you have two teams, we have a 100 yard field, and you score points by carrying or catching the ball into
what's called the end zone, which is all the way on the other side of where you start, on the opponent's side. And if you get it there, then you can score in a number of ways. One way, which is the most spectacular way, if you will, is what's called a touchdown, where you touch the ball down on the other side, which is worth six points. And then after that, you get an automatic extra point due to kicking the ball, which is so effectively you get seven
points for a touchdown. Just for our European audience, think of American football, of course, as being much closer to rugby than it is to soccer. Now, the team with the ball gets four attempts to try to progress on the field 10 yards towards the opponent. And each of those attempts are also called downs. And so, it's important that in four attempts, you make that 10 yard progress. If you keep on succeeding, then you get four new downs. And so, eventually, if you keep proceeding 10 yards
every time within your four attempts, then you reach the end zone. on the other side of the field. But if you fail and the other team takes the ball exactly where you were stopped, so the other team will take over the ball and will start from that point where you ended up in your attempts. So every possession is a sequence of I would say small bets. And the question that we're going to be really talking about is that what is the best thing to do on
the fourth attempt? So you've already failed three times to advance 10 yards. Now you're on your fourth attempt and what should you do with the last one? Okay, J, there's an important thing you left out. At any point a team can elect to kick the ball through the goalposts and if they manage to do that, they get three points. So there is a part of the field usually from the 40 yardd line onwards where teams have a chance of kicking the ball through the goalposts. And
so when the fourth down decision comes, they could go for it on fourth down and then if they don't make it, they lose the ball and the other team gets the ball or they could try to kick the ball through the goalposts and if they make it, they get three points, then the other team gets the ball. So now the crucial thing to understand is it's automatic to approximately 20 yards. If you kick it, you'll get three points for sure. But between 20 and 40 or
50 yards, it becomes less and less likely. And I would say at about 45 yards, it's impossible to get to three points. That's a crucial part this thing. And the last thing I would add for somebody who's never seen the game of football is it's very much a possession game. When one team has the ball, it is extremely hard for the other team to get the ball. So that who has possession is a big advantage. I think that's enough to understand the rules. So what our
guest David Roma did was he used a technique which is ubiquitous in optimization and economics called dynamic programming to calculate the probability from any yard line and any down of expected scoring. And the first thing that is kind of surprising about the result of that calculation is that for yard lines that are very close to your own end zone. So let's say they're one yard line. It's actually negative. The likelihood is the other team will score. And I think the reason for that is first of
all there's a concept of a safety. If they tackle you in your own end zone, the other team gets two points and the ball. But also if the other team gets the ball close to your own end zone, then the likelihood of scoring is very high. And so I think for those two reasons on the one yard line you actually have a negative expected amounts of points but of course that goes up and where you're on your own 99 yard line you have a very high
expected number of points. What David was wondering about is the decision on fourth down. So the decision on fourth down is you could go for it. If you miss the other team takes over where you are. If you make it you get four more downs. or you could try to kick the ball through the posts. And then the last point was you can also give up the ball to the other team voluntarily by what's called punting. But when you punt, you kick the ball way down
the field. And so the other team gets the ball but on their side of the field. And when you kick the ball, Jonathan, you generally kick it 30 to 40 yards or something. So you set them back by quite a bit, but definitely not all the way. Well, depending on where you are at that point in time, you don't set them all the way back to the first yard. Basically, any well-managed team is not going to find themselves inside the 20 yard line. So, they will
always take over at the 20 and usually in football somewhere between the 20 and the 40 yard line when they take over. Okay, so that's the decision people are facing. When should the team go for fourth down and when should they punt or kick a field goal? And in football, when this paper was written in the early 2000s, teams almost always either punted or kicked a field goal. What David showed was that this decision was clearly suboptimal. The paper he wrote is really an outstanding paper.
He thought about every possible reason why his result could be overturned and looked at it and did not find any good reason why the analysis wasn't correct. Now, it's complicated analysis, but there two cases where it's entirely obvious. The first case is if you've got one yard to go to get a touchdown and it's fourth down. He does a calculation and it's in expectation it's about the same. If you kick the field goal there, we'll get three for sure. If instead you go for the touchdown,
you get seven. The probability of making it is about 40% or something. Meaning in expectation, it's three points. So from an expectation standpoint, at that point, you're indifferent. But David's point is that if you fail on fourth down, the other team takes over on the one yard line. And that, as I told you, is a negative number for them. >> Yep. Whereas if you kick three points, the other team takes over on the 20, 30 or 40 yard line. And so you're indifferent about the number
of points being scored, but you certainly aren't indifferent in where they take over. And because of that, it doesn't make any sense to kick a field goal in that position. And even today, we don't see teams do that. So Jonathan, just as a clarification also for our European listeners, right, when we say 40 or 30 yard line, does that mean that from your side you've gone 30 yards or does it mean that you have 30 yards to go? >> You say you're on your own 30
yard line, it means you have 70 yards to go. If you say on your opponent's 30 yard line, then you have 30 yards to go. >> Yes. If you're all the way close to the end zone and you try to forth down and you fail, the opposing team has to essentially 100 yards to cover, which is way more than an average play than an average kickoff. And so that is a big advantage. And since you're indifferent on the number of points, that swings it that swings
it. So that means that you should always try it. When you're really close to the end, you should go for the play. You should not punt and you should not kick the field goal. >> That's one of the obvious cases. And the other obvious case is if you've got fourth down in the middle of the field. So let's say you're fourth down at the 50 yard line. It's too far to kick a field goal. But if you punt, I told you they have a kind of
an option to start on the 20 yard line. So at most you can get something like 20 or 30 yards with a punt. No. Okay. But if you make it on that fourth down, you are on the 50 yard line. And so that's another case where you should always go for it. And what happened when they wrote the paper there was no change in strategy but over the years that strategy has changed. Today in football teams generally go for it in that second situation. And so
the question on the table is why in such a competitive world with a strategy that's obviously better do teams not adopt the strategy. A number of questions come to mind immediately. The first one is when we analyze organizations the first thing that you and I always discuss and we've discussed many times on the podcast is what are the incentives of all the different players that are at stake here? And so there's a coach, the coach makes a decision, right? Is that fair? Is it to say
that the coach is really the one who makes the decision on what happens? >> Yeah. >> So therefore, obviously the incentives of the coach could matter. That's one explanation. I actually think that there's a deeper explanation and we'll see what David thinks of this. But don't you think that the reputation of the coach also depends on what the audience thinks he's supposed to be doing? And that forgoing three points for sure by doing that play and then the play fails, you look like such a fool
that you want to avoid that scenario under all costs despite the fact that in a dynamic programming sense for the team and for the winning of the team, you would do better. >> Yeah, Jules, I think that's certainly a possible explanation. It's stunning to me. The paper got a lot of press when it came out in the early 2000s and the football teams knew about the paper and they essentially ignored the paper. With the rise of analytics in general, they began to pay some attention, but
as I said, it's still not fully optimal. They still did not go enough on fourth down. I think Jules, this is the right time for us to introduce our guest today. Our guest today is David Romer. David is the Herman Royer professor of political economy at the University of California in Berkeley and the author of the standard textbook in graduate macroeconomics as well as many influential papers in the area of what's called new can economics the Nobel Prize was just given for that field. I think
that in macro David is very famous but I think that in the world David is probably the most famous for this paper. This paper that ended up changing the field of football. It took a long time but eventually I think he had major influence in this field and this was probably not a field that David expected to have a large influence in but I think it's a phenomenal study of optimal decision making under uncertainty and I think a place where we can learn a lot about
how firms operate too. David welcome to the show. >> Thank you for having me. >> It's great to have you David. So David I may be South African but I'm a somewhat of a football fan. I understand the rules of football well enough to understand the basic insights in your paper and how incontrovertible they are. When you wrote this paper, what did you think was going to happen to in football and how did you expect the NFL teams to react to your findings? I had two
predictions. Both of them were completely wrong. The first was that it would be hard to get teams to be aware of my research. it's not part of the job description and work in the National Football League to read economics journals or working papers. Within months of when my paper came out, every team knew about it. And the channel I'd missed was journalists who are always looking for something new to write about, partly, you know, to drive readership and partly out of boredom. And so they all
found my paper and talk to coaches and so on. My second prediction was once they knew about it, of course they would change their behavior because they want to win games and I thought the evidence was compelling and that did not happen. You know, this is the question that I think is the interesting question for our listeners and the decision-making podcast. You have a very competitive market. you know, a seeming incontrovertible evidence that the current strategy can be improved upon and yet in least immediately you
just saw no change in people's strategy. I think there's a prior question which is maybe more important and more interesting which was why before my paper weren't they doing this? Right? The arguments that competition, competitive pressures drive firms to efficiency, they're so powerful. They're so logical. If you're not competitive, if you're a manager of a firm doing a bad job, you'll be fired. If the firm continues to do a bad job, it'll either be outco competed or be taken over by people who can do it
better. And that wasn't happening. If I had, you know, uncovered some loophole in the rules that no one ever thought of, well, sure, that might have been something new. But you have to make a decision on fourth downs. People didn't always do exactly the same thing. There was some variation. People knew it was a decision. There have been people making this argument back. The first paper I found was from 1971. One of the authors was the backup quarterback of an NFL team. It was published in
operations research. It was written up, I think, in Sports Illustrated. So our argument is not competition leads to efficiency. If an egghehead professor points out the right strategy, our argument is supposed to be competition leads to efficiency period. And that didn't happen. That wasn't happening even before I wrote the paper. And then it sort of adds to the puzzle that you know when I wrote my paper, which got a lot of attention, I think it had stronger evidence than what came before. It did get a
lot of attention. I think that's a follow-up question. Why wasn't that enough to push it up? But I do think the prior question is the bigger one. So David, if we take a step back, how did you get the idea to write the paper? Was it already the case that you were watching games and every time you saw this happening, you were starting to get increasingly frustrated or was it that you thought let's see what comes out of this if I do the dynamic programming? Because
only after you've computed the probabilities and all the different plays can you really make the case really strongly, right? So did you already know before you started that this was pretty much going to be the outcome or was what you found quite surprising? >> It was largely what I knew. There are cases and I walk through some of them in the paper where you don't need the dynamic programming. You don't need the math. You can do fairly simple examples and it's compelling based on that. So
I was pretty sure what I would find. The one thing I didn't know, I thought that if it's very short, it was fourth and one, fourth and two, the probability of making it would be very high and fourth and 10 it would be very low. It turns out that's wrong. Fourth and one, I don't remember if it's 70% or 75 or 65, but it's not 90. And fourth and 10, it's not 5%, it's 30% or something like that. So particularly in the part of the field
where neither punting nor trying a field goal very attractive one thing that comes out is actually you should go for it with quite substantial distances to go that was unexpected to me but the overall pattern was not so David in the subsequent years and correct me if I'm wrong I think there two obvious points you can make without dynamic programming without really understanding dynamic programming one was what to do in what you call the dead zone in the middle of the field and what to do
with a fourth and one. Now, correct me if I'm wrong. The dead zone, the strategy did change, right, over the last 20 years. The strategies have changed a lot over the last 20 years. So, you just look at the fraction of times on fourth and one, fourth and two, over the whole field that teams go for it. It's much higher than before. My impression, I haven't redone the analysis, my impression is they're not as aggressive as they should be, particularly in their own territory when you
sort of, it's very palpable that if you didn't make it, the other team would be in great field position. But there's been a very big change and it's really been the last decade that that's happened. So the dual question, one is what do you think eventually caused the teams to adopt a better strategy given that they hadn't for so many years? And what about the fact that you very rarely see them going in you know forth and goal which is one of the other points of
your paper that they should go more often there. >> I think in terms of what caused the change I think three things one is the underlying forces that we sort of started with competition should produce efficiency. You wait long enough maybe you will get it without anything else. The second is the general rise of analytics. So across all sports including football it and the idea that they should look at data be analytical every team I think now has analytics not just person but staff and you
see that obviously in baseball but you see it in basketball I think you see it in soccer and you know just every sport and then the third which is kind of fun is there was a precipitating event I think which is if you look at the data from before I wrote my paper till 2017 there's essentially no change it kind of bounces around a little bit. Starting in 2018, there's a discreet step up and there's been a trend ever since then to going for it more
aggressively. The intervening event was the Super Bowl 52 in February 2018, the Eagles against the Patriots. The Eagles went for it twice on fourth downs in unconventional situations. One was a very memorable trick play on fourth and goal. And the other which I think is more important from point of view of my analysis was they were down by a little bit lateish in the game but not super late. They had fourth and one deep in their own territory. They went for it. They made it. They
drove down. They scored a touchdown. That was the margin of victory. As an aside, this led to a tweet that I just enjoyed absolutely enormously from Bill Easterly who's a very distinguished development economist. It was something like, you know, who says that economists are useless? David Ror has been arguing for years team should be more aggressive on fourth downs. Someone finally listened to him and they won the Super Bowl as a result. So, that was fun. Anyway, it got a lot of attention. It really got
noticed. I think it sort of teams woke up to the fact that gee it can make a difference and so we should question what we've been doing and think things through. So David there really in my opinion two interpretations of your paper and also to put into context what happened after I think there are two interpretations right so one is there is a lack of rationality or a lack of analytics a lack of insight people do not understand what they're supposed to be doing as the
technology progresses it's possible for them to start optimizing once the optimization becomes easier that's what they do the second interpretation is which I think is one way to read your paper is agency problem. There's the objective of winning and there is the reputation of the coach. The reputation of the coach is very much dependent on what other people think the right thing to do is regardless of whether that's right or not. And once it becomes clear that the other people understand what the right thing to
do is that allows the coach to do what the right thing to do is and therefore the agency problem if you will is resolved because the incentives are properly aligned. Should I read your paper more in the context of an agency problem that is resolved or should I read it more as a behavioral phenomenon that data analytics has resolved for us and therefore we get to more rational decisions or some combination of the two? I think my best answer is I don't know. Those are complicated
hypotheses and and it's hard to get definitive evidence on them. A very common reaction to my paper from people who were persuaded by the logic was yeah you don't want to be the coach who does this if you make an unconventional decision and it doesn't work and you know this is about you know there's an upside and downside whenever you try this you'll get pillaried and so on. It doesn't ring true to me but this is not strong evidence. It's really saying coaches knew at least
in the back of their minds what the right thing to do was and they chose not to do it. that just doesn't seem right. Particularly if you think about the people who are coaches in the NFL who have a lot of intensely smart, competitive, willing to defy things. The other thing about it is if you're coaching a bad team or you're a mid-level college coach who has ambitions of doing more, doing something that defies the conventional wisdom and works and on average, you know, it's a
good strategy that has a huge payoff. So, it's not just you did well. You did well because you were willing to buck the tide. So, I'm skeptical of the agency theory. The other reason I'm skeptical of the agency theory is the pressure to do this. It wasn't the owners telling the coaches to do this. It was internal to the workings of things. And there had been people on the outside yelling at them again, you know, for decades that they were doing the wrong thing. So it's
not like I gave them cover to do something that they knew was right. That's just not plausible. So I'm much more on the side. Again, I don't know, and I think that's very important that they're behavioral biases. They're very, very, very strong. They can block for decades these powerful competitive forces, but you know, in some cases when the evidence is clear enough, things do change. So I guess I lean toward your technology explanation, but again, I don't know. Although David, the fact is, you know, I'm
not that avid watcher of football, but I don't see them going fourth and one very often. I mean, normally they kick when it's fourth and one, right? >> So, I don't watch much football either. I think I have to put in as an aside that something makes me uncomfortable about talking about football is that it's a sport that probably shouldn't be played at all given the cost it imposes on the players. and that sort of diminished my interest. But it's certainly clear they haven't gone all
the way to the optimal strategy. I think that's pretty clear based on casual observation. I think what I don't know is whether they've sort of taken up the vast majority of the lowhanging fruit. So it's, you know, we talk about a dead weight loss from a triangle or an inefficiency from the triangle. And as you work down the bigger chunks of the triangle, even if you're not going most of the distance, you are getting most of the gains. I don't know if they've gotten a large
majority of the games or just a decent chunk of them. I think someone would need to redo my paper with modern data and modern evidence about what teams do to answer that one. If the explanation that you're providing is indeed a technology explanation, would that also mean that you think that the arrival of AI could lead to huge productivity increases? Because if this would really help people get over all their behavioral biases and they're so prevalent as your paper suggests, that must mean that introducing more
rational decision-m should make a big difference. No, >> I think for things like this, yes, but what's notable about this is it's a very well-defined decision. So that's why it was great to study and it's also a reason that finding failures of optimization there is really compelling. This is a setting where you would be particularly likely to find optimization if it were happening. Right? I mean very clear decisions. The analytics are relative to how should we position our brand in the marketplace or should we have
an assembly line or team production. This is a vastly simpler decision. I think for decisions like this AI absolutely I could imagine AI getting to the point of dear AI please improve the productivity of my firm or my team's winning performance and it comes back with your 10 things you could do the bigger picture things I don't know dear AI how should we position our brand in the global marketplace is AI really going to know that better it doesn't have a lot of data to go
on the payoffs very long term. So I think that's a hard one. >> But David, what do you think the general implications are? I mean, I would take away from your study that in a very clearcut obvious case, we observe businesses in a highly competitive market not acting optimally. I would conclude from that, well, in a case where it's not clear-cut and the competition isn't as intense, you're going to see large departures from optimality. >> To me, that makes complete sense. Yes. So that's sort of
what I was saying a moment ago. If they're not optimizing here, if they can't get this one right, there's every reason to think that they're getting other things that are harder, even more wrong. So that's one lesson. I think a second lesson is behavioral biases are really important. And if you think about it, the departures from optimality were in a particular direction. They were toward the cautious, the conservative thing to do. And if you look certainly other sports contexts, that's what we see. Teams were very
slow to figure out that three-point shots were a good thing to be doing. In baseball, teams were much too invested in scoring one run at a time rather than playing for the big rally and, you know, the three-run home run. In hockey, my understanding is teams are too slow to pull the goalie if they're behind late. So, it's behavioral, right? It's not there was randomly an error that they got wrong and then stuck with it. It's we're probably hardwired to be riskaverse because you know being
eaten by a lion is very very costly and that gets misapplied. I remember getting an email once from someone who coached high school who said he went for it a lot on fourth downs and the parents would come up and say but you know it's a life or death situation and he would say I fought in Korea I know what a life and death situation is going forward and fourth down is not a life or death situation and I shouldn't carry over the messages from Korea
to coaching this football team so behavioral biases are really big I think another message is this question of why given that the evidence was there, people were suggesting this. What is it about the organizations that made them when it was sort of presented to them for decades? Why didn't they respond? What makes an organization have the flexibility, the openness and so on to be open to the idea, gee, maybe we're making a mistake. Maybe this professor at Berkeley who's clearly never played a football game in
his life, maybe there's something there worth looking into. >> You know, David, the implication for the economy as a whole certainly must be that we're not doing a good enough job in teaching MBAs and undergraduates the importance of analytical insight, right? I mean if it is a behavioral bias where people think it's a life and death situation when it isn't the defense is an analytical approach and yet we don't see that. >> I agree. I mean I think there are couple of things that I don't
teach in the business school so I I'm not going to criticize MBA education but I think yes the value of analytics but also the value of just figuring out ways of being open to mistakes. So I'll turn it into a research question. I have the sense that there's a body of research certainly a stack of sort of top management books. I assume they're MBA classes on how to run you know a company in a way that makes it nimble that makes it respond to new ideas
makes it overcome mistakes. I would think it would be really interesting to sit down say with all those books and say what are 20 hypotheses about what makes an organization be efficient, be optimizing. Is it about analytics? Is it about the structure? Is it about the culture? Willingness to admit failure and then say how do those 20 hypotheses fit with explaining why no one did this for so long? What were the teams that picked up on it first and so on? And I'd be fascinated to
know if some of those hypotheses were like really strong successes and and others were not >> because I think that also from a cultural point of view it should not be underestimated if I look at my own kids and their generation what Moneyball also the movie what that did for the reputation of analytics within a sports context. Suddenly it's actually cool to do this and I think it was a very motivating thing for young people to find out that using these tools could actually make you
win a sports game. I don't think it had that reputation before. So I think that acceleration of that insight is good. So it may also just mean that we are still failing at marketing the tools that we teach that they're actually way more valuable than what is coming across. And it just requires Moneyball to really make that case from a marketing point of view. No, I agree. When I wrote the paper, I think I had a bunch of motivations in mind and the journal editor who
handled it really pushed me, I think completely correctly in the direction of focus on this issue of do competitive forces cause firms to optimize. The editor handled the paper was Steven Levit at the University of Chicago and his main comment was this is an intellectually serious paper. you should take out anything that seems frivolous or cute or off-topic and just focus on the query issue. And that was great advice. But one of the motivations was this is just fun. This is just shows you you can
use dynamic programming and linear algebra and things like that to get insights into a question where 99 people out of a 100red would think that's irrelevant. I recently went to my 50th high school reunion and I would say half the people there knew about my work about what I'd done on this and rather than being the boring nerd who comes back it was like oh there's this cool kid who did something on fourth down strategy so that was nice love it but you know what makes
the paper so interesting is precisely as you point out it wasn't just a seat of the pants analysis and although you in the introduction there's a lot of intuition. The really the analysis is applying dynamic programming in a very useful way. The problem with applying dynamic program in a useful way is it takes a lot of effort. It's a lot easier just to do a seat of the pants analysis, right? And so I wonder how much of the reticence is that you don't want to put
the effort in. So it's easy to say, "Ah, no, come on. That's I know the game of football. I don't need to do dynamic programming." The same as in a business. I'm an expert. I've sold shoes for 30 years. I know how to sell shoes. I don't need somebody to tell me with a computer program how to sell shoes better. >> Although that cost has come down a lot, right? Particularly now with the arrival of new technologies, the cost of doing dynamic programming has become close
to zero. >> Maybe depends if you understand it. >> I think there are two issues. I don't know which one is right. One is it's too costly and so I'll do it the old way. The other is that means that if you're the person who's made the decisions by experience, intuition, seat of the pants, and to say, well, dynamic programming might do it better is relinquishing control, right? It's saying, I'm not the expert here. And so it may be a psychological cost rather than a monetary
cost, right? The cost to a football team of hiring someone to do dynamic programming is a drop in the bucket compared to what they do. and >> agreed. >> One of the things we talked about beforehand was, you know, how did teams react? And they didn't react by adopting what I suggested. And regardless of how strong you find the evidence in my paper, the passage of time has shown that there's now a consensus that for better or worse, I was right. Seems now things have changed
dramatically without a big change in the cost and benefits of it. So the way teams reacted, I think the closest that teams got to taking it seriously would be someone to engage in the paper long enough to identify something that was left out. And then the next step was so we can ignore this. Wes, I think if you had been reading the paper and you said something was left out, the next step would be let me think about whether that thing that's left out, first of
all, which direction it goes in in. And second, could it be strong enough to overturn the results? And third, you know, how would I get evidence about that? And no team, as far as I know, got beyond the, oh, the analysis isn't perfect, therefore we can ignore it. That was the general reaction. Well, David, I have to say thank you so much for coming on. I think this is such a good example, a clear-cut example of the limits of competition that I think it's an excellent
paper. It really is. >> Thank you for having me. It's been great to talk. >> Thank you, David. >> Thanks for listening to the All Equal podcast. Please leave us a review at Apple Podcasts. We love to hear from our listeners. Also, be sure to catch our next episode by subscribing or following our show wherever you listen to your podcasts. For more information and episodes, visit all elseequalpodcast.com or follow us on LinkedIn. The All Elsequal podcast is a joint production of Stanford University's Graduate School of
Business and the Lauder Institute at the University of Pennsylvania. It is produced by University FM.