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Speaker 1: This week on the podcast, I have Professor Robert Frank.

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Speaker 1: He teaches economics and management at the Graduate School up

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Speaker 1: in Cornell and is the author of a number of books. UH.

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Speaker 1: He's probably best known for The Winner Take All Society,

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Speaker 1: a very prescient book published in way ahead of a

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Speaker 1: lot of the more recent commentary on changes in society.

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Speaker 1: Most recently he's published success in Luck, Good Fortune, in

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Speaker 1: the Myth of Meritocracy. It's a fascinating conversation about how

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Speaker 1: we all tend to under emphasize and and just not

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Speaker 1: realize the impact that random fortune has in our life,

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Speaker 1: for both better and worse. He he also wrote a

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Speaker 1: textbook with some guy named bed Bernanke on economics. UH. Really,

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Speaker 1: I think you'll find this to be a fascinating conversation

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Speaker 1: if you're at all interested in how not the politics

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Speaker 1: but the economics of of income inequality and how these

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Speaker 1: things have developed and what they're subsequent impact is on

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Speaker 1: both uh, efficiency and productivity of of the economy and

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Speaker 1: what it means for society from the middle class for

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Speaker 1: changes in in corporate structures. I think you'll find this

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Speaker 1: to be an absolutely fascinating conversation. So with no further

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Speaker 1: ado my conversation with Robert Frank. This is Master's in

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Speaker 1: Business with Barry Ridholts on Bloomberg Radio. My special guest

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Speaker 1: this week is Professor Robert H. Frank. He is a

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Speaker 1: professor of management and economics at Cornell's Johnson School of Management.

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Speaker 1: That's the graduate school up at Cornell. He has won

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Speaker 1: numerous teaching awards and all sorts of other accolades. Comes

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Speaker 1: to us with a b. S. And mathematics from Georgia Tech,

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Speaker 1: has a master's in statistic and a PhD in economics

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Speaker 1: for Berkeley, and is the author of a number of books,

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Speaker 1: several of which we'll talk about later today, most recently

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Speaker 1: Success in Luck, Good Fortune, and The Myth of Meritocracy.

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Speaker 1: I would be remiss if I didn't mention the textbook

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Speaker 1: he co wrote with some gentleman named Ben Bernanke, Principles

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Speaker 1: of Economics and he He probably is best known for

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Speaker 1: a book published in The Winner Take All Society that

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Speaker 1: won all sorts of critics Choice Award Notable Book of

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Speaker 1: the Year by the New York Times Business Week's Top

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Speaker 1: ten list for Robert Frank. Welcome to Bloomberg. What a

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Speaker 1: pleasure so that that was the short version of your CV.

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Speaker 1: I could have gone on if I if I started

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Speaker 1: discussing the published papers, we would be here until next Tuesday.

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Speaker 1: But one of the things that really struck me about

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Speaker 1: your background is how long you've been studying income inequality?

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Speaker 1: How did how did you first get interested in that subject? Uh,

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Speaker 1: it's it's become quite fashionable now. I first started writing

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Speaker 1: about it, it it was very difficult to find anybody who cared.

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Speaker 1: I think my own interest in it was kindled by

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Speaker 1: my interest in biology, where where if you know an

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Speaker 1: animal's rank in whatever group, it's alpha beta, what happened, right,

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Speaker 1: that's the that's the most powerful predictor of that animal's

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Speaker 1: ability to project its stuff into the next round. So

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Speaker 1: so if if there's a famine, it's not the high

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Speaker 1: ranking animals that starve. The high rank animals typically have

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Speaker 1: much better mating opportunities. There's a whole variety of reasons

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Speaker 1: for that. But if if you don't care about where

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Speaker 1: you rank, you're probably not coming into the world very

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Speaker 1: well equipped to deal with the competitive fray that we're in.

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Speaker 1: And it is quite a competitive world, especially when it

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Speaker 1: comes to economics. On the other hand, Uh, to really

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Speaker 1: succeed in today world, it's essential to be a trusted

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Speaker 1: member of an effective team. You have to be able

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Speaker 1: to be seen by others as trustworthy and cooperative. Really

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Speaker 1: effective teams, teams with talented people have their pick. They

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Speaker 1: don't need to hire any jerks for their team if

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Speaker 1: you're If you're not a person they feel they can

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Speaker 1: rely on. When you're out of you and you have

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Speaker 1: a chance to serve your own interests at the expense

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Speaker 1: of the teams, then why should they have you on

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Speaker 1: on their team. They've got better choices. So it's a

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Speaker 1: kind of a complex balancing act. You have to be

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Speaker 1: somebody who's who's attractive to others and trustworthy in situations

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Speaker 1: where you could cheat them, but they have to feel

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Speaker 1: confident you won't. But you have to also care about

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Speaker 1: getting ahead. So it's a little bit of a balance

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Speaker 1: in society versus what we see out in the wild exactly.

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Speaker 1: Society has done an enormous amount to try to tame

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Speaker 1: the competition. We have all sorts of regulations that prevent arms,

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Speaker 1: races that get out of control and nature. But I

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Speaker 1: think you know, the income inequality problem is is maybe

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Speaker 1: one of the early signs that our attempts to keep

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Speaker 1: things in balance have been falling short. So let's talk

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Speaker 1: about income inequality a little bit. I want to mention

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Speaker 1: it's funny that you said how fashionable it is today.

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Speaker 1: I'm gonna pull a quote from either your book it was,

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Speaker 1: or it was a paper that you had written around

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Speaker 1: the same time the book had come out that I

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Speaker 1: thought was fascinating, And this is from quote. The incomes

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Speaker 1: of the top one percent have more than doubled in

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Speaker 1: real after inflation terms between nineteen seventy nine and nine

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Speaker 1: eighty nine, a period during which the meeting income was

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Speaker 1: roughly flat and which the bottom quintile the bottom twenty

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Speaker 1: of earners, so their incomes actually fall by ten percent.

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Speaker 1: Now that sounds like something that could have come out

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Speaker 1: a year or two ago, about the prior decade, and

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Speaker 1: yet this was not a big issue back I think

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Speaker 1: we were just starting to see clear evidence of those

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Speaker 1: trends that were beginning. They they began sometime in the

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Speaker 1: late sixties or early seventies. There's still some quarreling about

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Speaker 1: when the exact moment was. There probably wasn't an exact moment,

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Speaker 1: but but as it's gone on, longer, and as the

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Speaker 1: multiples have gotten bigger, more and more people have taken interest.

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Speaker 1: And you know, there's been a lot of very serious

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Speaker 1: work in recent decades on it. Well you you were

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Speaker 1: writing Picketty type stuff twenty years before Pickety was writing them. Yeah.

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Speaker 1: Well it's not always who gets there first, who wins

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Speaker 1: the prize. Yeah, Picketty has gotten a lot of very

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Speaker 1: well justified attention on these issues, and he's done the

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Speaker 1: rest of us who are in the trenches writing about

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Speaker 1: this subject and enormous service. You know, we can we

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Speaker 1: can now write a piece on on the issue and

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Speaker 1: people will pay attention to it, whereas it would have

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Speaker 1: gone lost in the shuffles. So that's that's a really

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Speaker 1: interesting point I find. First, it's amazing how similar the

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Speaker 1: data sounds twenty years ago to today. That's astonishing. But

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Speaker 1: was income inequality all that obvious back then to people

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Speaker 1: who were looking at it? Was the boom in technot

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Speaker 1: remember nineties, a huge boom in technology. The stock market

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Speaker 1: was on fire. Well, we just otherwise occupied and not

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Speaker 1: paying attention. How did this slip by relatively unnoticed right

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Speaker 1: in the middle of the nineties. Yeah, I think that's

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Speaker 1: a great question, and I don't have a compelling answer

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Speaker 1: for it. Uh. It if you take the early onset

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Speaker 1: of the date range the late sixties as the the

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Speaker 1: time when income inequality started growing rapidly, then uh, plenty

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Speaker 1: of time for a lot of people to have noticed it.

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Speaker 1: And many people did notice it. It's just that the

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Speaker 1: the subject hadn't really caught on as a as one

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Speaker 1: of general interest. I'm Barry Ridhults. You're listening to Masters

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Speaker 1: in Business on Bloomberg Radio. My special guest today is

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Speaker 1: Professor Robert Frank. He teaches up at Cornell both economics

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Speaker 1: and management. Let's talk a little bit about the winner

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Speaker 1: take all society. The book you co authored in that

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Speaker 1: seems to be quite prescient about a variety of changes

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Speaker 1: that have taken place in uh in our economy. Let

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Speaker 1: me let me start out with a quote. What do

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Speaker 1: Boris Becker, Alan Dershowitz, Diane Sawyer, Michael Jordan's, L McPherson,

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Speaker 1: and John Griffin all have in common? They are beneficiaries

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Speaker 1: of the winner take all markets. Now, what's interesting is

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Speaker 1: how memorable all those names are. And still, unless you're

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Speaker 1: a millennial, you probably know who all those names are.

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Speaker 1: Kas there was a lot of longevity to it. Explain

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Speaker 1: to us what the winner take all society is there.

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Speaker 1: There's a kind of market we've seen, uh, this market

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Speaker 1: structure going back a long long time. Actually, Uh, it

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Speaker 1: was written about in the nineteenth century in similar terms

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Speaker 1: to the ones we use to describe it. It's a

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Speaker 1: market where if you have a task that can be

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Speaker 1: done market wide by a single person, then essentially you've

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Speaker 1: got the conditions for a big tournament. Uh. It's it's

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Speaker 1: a valuable task. Typically if somebody can serve the whole market,

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Speaker 1: and if there are thousands of houses of people trying

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Speaker 1: to be anointed the person who gets to do that,

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Speaker 1: then the competition is pretty bitter and there's a lot

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Speaker 1: of bunching of talent and effort. All the people who

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Speaker 1: are finalists in that contest are going to be really,

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Speaker 1: really good, but typically one will emerge, and it will

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Speaker 1: be some one who's uh maybe a little bit better

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Speaker 1: than most of the others, but rarely the best contestant.

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Speaker 1: He's also had a lucky break or two along the way.

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Speaker 1: But when the winner emerges, there's a huge difference between

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Speaker 1: the reward that person gets and the rewards received by

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Speaker 1: others who were really so close to being as good

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Speaker 1: that no one could really tell. It was almost an

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Speaker 1: arbitrary choice to anoint the winner. And and so you

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Speaker 1: get a situation where you know, most people feel comfortable

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Speaker 1: if somebody works one percent harder than others, there is

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Speaker 1: one percent more talented, I'll fine, let and be paid

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Speaker 1: one percent more. But here, here you have some but

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Speaker 1: he emerge who's one percent more talented, And and uh,

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Speaker 1: that person might earn ten thousand times as much as

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Speaker 1: as the others who are almost as equal. So let's

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Speaker 1: let's use Michael Jordan as an example. Wins six NBA finals,

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Speaker 1: which was a huge run, but at the same time

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Speaker 1: has this amazing set of endorsement deals. He makes hundreds

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Speaker 1: of millions, literally hundreds of millions more then he's paid

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Speaker 1: as an athlete to do all his endorsements and other

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Speaker 1: business ventures. And at the time, nobody else is even

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Speaker 1: close to him. Yeah, there there would be plenty of

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Speaker 1: people who would do his job for a tiny fraction

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Speaker 1: of what he gets. You would, I'm guessing I would

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Speaker 1: have been willing. But you have more hit than me,

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Speaker 1: so you can you can do that? Well, it's not

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Speaker 1: all you need you watch you watch the highlight reel

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Speaker 1: of Michael Jordan's and you think you're seeing something in

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Speaker 1: slow motion, because it really does seem that he's hanging

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Speaker 1: in mid air for thirty five seconds, making decisions on

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Speaker 1: the fly that are not only instantaneous, but three steps

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Speaker 1: ahead of everybody else, and then executing on those decisions

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Speaker 1: while hanging in midair. So so maybe he's not the

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Speaker 1: best example of a winner who's only a little bit

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Speaker 1: better than the others. Maybe maybe give us another example

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Speaker 1: like Secretariat, he won thirty lengths. But but typically it's

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Speaker 1: not it's not that far ahead of the field. When

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Speaker 1: we see a winner emerged, you know, it could have

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Speaker 1: been any one of a number of people who emerged

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Speaker 1: that way. And and well, you mentioned Alan Dershowitz or

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Speaker 1: Al McPherson or John Grisham. There are a lot of

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Speaker 1: fantastic novelists who sell millions of books. Is that and

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Speaker 1: their books become movies? Is John Grisham a winner take all?

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Speaker 1: He's definitely an example of someone who's been a really

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Speaker 1: big winner in a winner take all market. So not

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Speaker 1: only have the books done well, but you know, a

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Speaker 1: dozen of his books have become really big movies. And

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Speaker 1: and the surest way to publish a best seller is

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Speaker 1: to have already published one. Uh, if you've published two,

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Speaker 1: then you're even more likely to have a best seller.

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Speaker 1: And and then once you've got a string of them,

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Speaker 1: the movie people start bidding against one other for the rights. Yeah,

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Speaker 1: the the rewards really do explode once you're on a

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Speaker 1: successful track. But but if you would go back early

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Speaker 1: in a person's career, it wouldn't be so clear that

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Speaker 1: that would be the person who would emerge and become

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Speaker 1: the big winner. Even in Michael Jordan's case, he was

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Speaker 1: cut from the basketball team at a couple of stages

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Speaker 1: school right, didn't do well. What about j K Rowland?

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Speaker 1: I think her book was turned down a dozen different

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Speaker 1: publishing shops and and she just on a lark published

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Speaker 1: a detective novel or who Done It under a pseudonym

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Speaker 1: after she quit the Harry Potter series, And the book

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Speaker 1: got good reviews but sold tepidly. Vantil was revealed, it

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Speaker 1: was leaked that the author really was j K. It's

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Speaker 1: shot to the top of the best seller lists. So yeah,

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Speaker 1: having been successful is the is the biggest thing that

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Speaker 1: that can assure your success in the next round. So,

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Speaker 1: so what impact does this star system have on society

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Speaker 1: and what does it mean for the long term economic

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Speaker 1: efficiency of of how things run well, It's got good

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Speaker 1: aspects to it. And also someone's that ought to concern us.

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Speaker 1: So if you think of piano manufacture in the last century,

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Speaker 1: it was a local industry. Why because it costs so

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Speaker 1: much to ship pianos that if if if you try

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Speaker 1: to sell one too far from the factory, the shipping

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Speaker 1: costs would eat you alive. And and then canals opened

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Speaker 1: up railroads, the market expanded enormously that could be served

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Speaker 1: by a single producer. So the good thing for consumers

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Speaker 1: if there really were some producers who are better than others,

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Speaker 1: now they could extend their reach, so you'd you'd be

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Speaker 1: buying a better piano than you would have had access

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Speaker 1: to before. The downside of that is that it tends

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Speaker 1: to lead to an enormous increase in the concentration of income.

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Speaker 1: The people who were thriving in local markets before now

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Speaker 1: they compete to see who's going to be the one

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Speaker 1: who dominates the broader market that's now serviceable by these firms.

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Speaker 1: Since transportation costs are low, and and the losers in

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Speaker 1: that contest, they've got to go find something else to do. Basically,

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Speaker 1: I'm Barry Ridholts. You're listening to Masters in Business on

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Speaker 1: Bloomberg Radio. My special guest today is Professor Robert Frank

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Speaker 1: of Cornell, and we were discussing earlier how the middle

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Speaker 1: class has begun to fall behind, going back as far

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Speaker 1: as the nineteen sixties or seventies, you put out a

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Speaker 1: book called falling Behind, How rising inequality harms the middle class.

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Speaker 1: And again, some of the data points in this are

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Speaker 1: just astonishing. I want to reference the toil index, uh

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Speaker 1: from a paper you put out in two thousand eleven.

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Speaker 1: Listen to this data. This is astonishing. Between nine seventy

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Speaker 1: and two thousand, the median earner would have gone from

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Speaker 1: working a little more than forty hours a week in

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Speaker 1: order to be able to afford the median priced home

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Speaker 1: to working close to seventy hours a week, almost double.

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Speaker 1: How did that happen? Yeah, it was the monthly number

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Speaker 1: of hours you had to work in order to earn

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Speaker 1: enough money to gain access to the median price house.

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Speaker 1: And and that's an interesting number because if you're in

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Speaker 1: the middle you would earn in the middle. You would

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Speaker 1: want to send your kids to a school of at

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Speaker 1: least average quality, and to do that you have to

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Speaker 1: buy the median price house because, as is true in

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Speaker 1: every country, school quality tracks house prices in the neighborhoods

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Speaker 1: very closely. So so every parent wants to do that.

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Speaker 1: Houses have gotten bigger during that time. That's partly why

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Speaker 1: families have to work more hours to be able to

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Speaker 1: afford access to the median house. And it's just that

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Speaker 1: others like them are spending a higher percentage of their

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Speaker 1: income too, so you've got to match what they do

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Speaker 1: or else you fall behind. And it's your kids who

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Speaker 1: go to schools with the metal detectors out front. What

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Speaker 1: what has the addition of a second bread winner in

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Speaker 1: a household done to this this data? Uh so, that's

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Speaker 1: a really interesting question. In the fifties we had one

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Speaker 1: earner families. Now it's much more common to have two earners.

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Speaker 1: So families should be doing much better. Well, they don't

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Speaker 1: seem to be doing much better. And and one reason

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Speaker 1: is that a lot of the extra money has gone

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Speaker 1: into a bidding war four houses in the better school districts,

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Speaker 1: so we've got more money. Now, what's what's the first

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Speaker 1: thing we want to do? Send our kids to better schools. Well,

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Speaker 1: other families want to do that too, And it's as

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Speaker 1: if everybody stands up to see better. Nobody sees any

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Speaker 1: better than before. We just bid up the prices of

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Speaker 1: the houses in the better school districts. Half of all

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Speaker 1: kids go to bottom half schools, the same as before.

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Speaker 1: There's no way around that. That math is there. That's

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Speaker 1: that's the cruel dilemma that inequality confronts people with. That

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Speaker 1: lake will be gone exists just in fiction, and all

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Speaker 1: of the children are not above average. It can't be,

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Speaker 1: cannot be. Let me let me throw another data point

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Speaker 1: out that I thought was fascinating. From UH falling behind,

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Speaker 1: the share of total income going to the top one

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Speaker 1: percent of earners was eight point nine percent in By

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Speaker 1: two thousand and seven, it had risen to twenty three

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Speaker 1: and a half percent, just about tripling. During the same period,

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Speaker 1: the average inflation adjusted hourly wage declined by more than

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Speaker 1: seven percent. So the meeting, So last time we looked

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Speaker 1: at this date, in the top one percent we're growing,

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Speaker 1: the bottom we're falling, and the median was flat. Here

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Speaker 1: we see the top one percent growing much more in

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Speaker 1: this time period, and and the average is actually falling.

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Speaker 1: So what's the drivers of this? You know, I think

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Speaker 1: it's the same technological changes that Phil Cook and I

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Speaker 1: talked about, and that indeed Alfred Marshall had talked about

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Speaker 1: in the eighteen nineties. As technology, let's the most able

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Speaker 1: performers in each domain extend their reach. Uh, there's just

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Speaker 1: gonna be a bigger slice of the market that they

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Speaker 1: can effectively serve, and then the bidding for their services

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Speaker 1: heats up. We don't need more than two or three

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Speaker 1: sopranos at this point. Uh. A hundred years ago, the

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Speaker 1: only way to listen to music was but now we

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Speaker 1: listen to music mostly in recorded form. Once the master

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Speaker 1: discs have been stamped out, they can make copies MP

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Speaker 1: three's other media or essentially zero cost to copy. And

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Speaker 1: so the real trick is to find the performer who's

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Speaker 1: better and at least in the public's eye by a

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Speaker 1: small margin, people want that performer and no other. So

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Speaker 1: this this leads to a really interesting question. You have

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Speaker 1: the current impact of technology and globalization and automation and

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Speaker 1: more and more of the winner take all society pre

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Speaker 1: nineteenth century, it was almost a feudal system where you

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Speaker 1: had the one local monarch and everybody worked for them.

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Speaker 1: That almost leads me to think that the post World

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Speaker 1: War two middle class was an aberration. That's a theme

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Speaker 1: in Thomas Picketty's book, that the period of post war

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Speaker 1: relative equality was the aberration, not the I think the

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Speaker 1: assumption along had been well, that's normal, and we're moving

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Speaker 1: away from it. I don't think, uh, that issue is

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Speaker 1: completely settled. But the technological forces that are causing incomes

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Speaker 1: to concentrate at the top, those haven't even a gun

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Speaker 1: to finish playing out. You know, Amazon is going to

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Speaker 1: continue displacing retailers until they're almost aren't any more retailers,

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Speaker 1: and we're a long way from that happening. I'm Barry

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Speaker 1: Ridhalt's you're listening to Masters in Business on Bloomberg Radio.

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Speaker 1: My special guest today is Professor Robert Frank. He is

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Speaker 1: the author of Success in Luck, good Fortune, and the

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Speaker 1: Myth of Meritocracy, as well as the Winner Take All

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Speaker 1: Society and Principles of Economics, say textbook co written with

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Speaker 1: some guy named Ben bernanke. Uh, let's jump right into

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Speaker 1: success in Law because This is a topic that I

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Speaker 1: find absolutely fascinating. Part of the reason is in this series,

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Speaker 1: in these interviews that I do, you would be amazed

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Speaker 1: at how many billionaires say and of course I got

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Speaker 1: lucky early in my career, or this happened and it

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Speaker 1: was just good fortune. And I know a lot of

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Speaker 1: people think that that's just a false humility. But I

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Speaker 1: think and have observed that folks really, especially people who

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Speaker 1: were wildly success I don't mean hey, good job, good career, whatever,

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Speaker 1: I mean wildly successful, winner, take all top of their field. Billionaires,

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Speaker 1: Many of them referenced the role of luck in their success.

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Speaker 1: Why is that? I think that's a great thing when

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Speaker 1: you see it happen, and you do see it happen.

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Speaker 1: I have no successful people who are very quick to

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Speaker 1: acknowledge that they had breaks and wouldn't be where they

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Speaker 1: are now except for them. But still there are many

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Speaker 1: who who whose position seems to be I did it

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Speaker 1: all on my own. I think think back to two

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Speaker 1: thousand and twelve when Elizabeth Warren gave her you didn't

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Speaker 1: build that speech. It was a video that went viral

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Speaker 1: and had millions of angry comments directed at her. What

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Speaker 1: did she say? She said, you built a business, it succeeded.

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Speaker 1: That's great, but just remember you shift your goods to

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Speaker 1: market on roads. The rest of has helped build you.

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Speaker 1: Hired workers the community, pay to educate. Police and firemen

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Speaker 1: that we hired helped protect you. Part of the social

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Speaker 1: contract is to pay forward, so the next group that

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Speaker 1: comes along will enjoy those same opportunities to succeed that

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Speaker 1: you did. Uh. I don't hear anything controversial in those remarks,

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Speaker 1: but people were very angered by them. And so if

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Speaker 1: you if you tell a rich person who's beginning with

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Speaker 1: the posture I did it all myself, that hey, you

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Speaker 1: were lucky also, which is almost always true. Uh, they

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Speaker 1: tend to hear you saying that, oh, you don't belong

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Speaker 1: where you were your skillful that's not the message. No,

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Speaker 1: the people who win in these markets are almost invariably

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Speaker 1: really skillful, and they work really hard. So so it's

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Speaker 1: in a way natural that when they try to explain

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Speaker 1: to themselves why do they succeed, that they focus on

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Speaker 1: their hard work and talent. That's a big pack factor

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Speaker 1: and what did bring them to the top. But they

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Speaker 1: were also very lucky. So so let's take an example

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Speaker 1: from the book that I thought was pretty fascinating. How

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Speaker 1: lucky of a guy was Bill Gates. Oh, Bill Gates, Uh,

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Speaker 1: to his everlasting credit is really quick to acknowledge how

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Speaker 1: lucky he was. He had one of the few schools

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Speaker 1: that had a computer lab in it. He was born

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Speaker 1: in nine didn't exist where if if he had been

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Speaker 1: born ten years earlier, that wouldn't have existed. If he'd

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Speaker 1: been ten years later being born, every people would have

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Speaker 1: been all over that already. He was there at the

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Speaker 1: right time. He got access to the computer labs at

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Speaker 1: the University of Washington, like an actual lab with real

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Speaker 1: time response, not the punch cards up the hill and

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Speaker 1: wait three days to see what happened. He was in

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Speaker 1: high school. That's a that's an amazing thing he had.

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Speaker 1: And he'll say there's probably probably what wasn't a group

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Speaker 1: of a dozen worldwide had opportunities like he had. But then,

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Speaker 1: even even so, you would never know who he was.

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Speaker 1: Probably belie if IBM hadn't Uh sort of in a

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Speaker 1: short sighted move giving him the license to sell the

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Speaker 1: operating system to its personal computer that was about to launch.

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Speaker 1: They didn't have high hopes for sales of that machine,

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Speaker 1: and so he ended up being the richest man on

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Speaker 1: the planet. As he's quick to concede because he got

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Speaker 1: a few really well time breaks. The technology lare is.

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Speaker 1: He goes out and purchases a version of DOS for

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Speaker 1: fifty dollars from a company who the urban legend is

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Speaker 1: that founder eventually commits suicide. Um years later when he

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Speaker 1: figures out what he does, sells this to IBM, and

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Speaker 1: IBM never says, yeah, we're gonna buy this from you.

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Speaker 1: Instead they'll say, yeah, we'll pay you for each one.

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Speaker 1: We'll pay you less, but every time we sell a machine,

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Speaker 1: we'll give you a royalty. And and that wasn't amazing.

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Speaker 1: But make no mistake, Gates is really smart. He's very talented,

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Speaker 1: very hard working. But that combination of things isn't sufficient.

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Speaker 1: So the the guys who who come in second, the

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Speaker 1: men and women who come in second, they're really smart,

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Speaker 1: they're really hard working, they're really creative and skillful and opportunistic.

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Speaker 1: But some of them just don't get a lucky break,

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Speaker 1: and they don't achieve the sort of success that we

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Speaker 1: see from the smart, hardworking, lucky ones. Brian Cranston I

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Speaker 1: had never heard of I've watched Breaking Bad. He was

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Speaker 1: unbelievably good in it. When Vince Gilligan proposed casting him

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00:26:30,520 --> 00:26:33,119
Speaker 1: in the Walter White role, which was the heart of

431
00:26:33,119 --> 00:26:37,520
Speaker 1: that series, the studio bosses said, no way. This is

432
00:26:37,560 --> 00:26:39,880
Speaker 1: a guy who's never had a leading dramatic role. He's

433
00:26:39,880 --> 00:26:43,280
Speaker 1: a middle aged sitcom guy. He was the goofy dad

434
00:26:44,040 --> 00:26:46,480
Speaker 1: in the middle, which I had never seen. But people

435
00:26:46,640 --> 00:26:48,600
Speaker 1: who saw it said, well, it was good. If you

436
00:26:48,640 --> 00:26:51,040
Speaker 1: saw it, you would have never in a million years

437
00:26:51,080 --> 00:26:55,680
Speaker 1: imagined him exactly. He was a goofball, funny, but certainly

438
00:26:55,720 --> 00:26:59,879
Speaker 1: not that intense dramatic. So so the studio people, they said, no,

439
00:27:00,320 --> 00:27:03,840
Speaker 1: we're gonna offer the part to John Cusack's totally wrong.

440
00:27:04,560 --> 00:27:08,040
Speaker 1: Cusack turned it down there all right, Matthew Broderick. Matthew

441
00:27:08,040 --> 00:27:12,320
Speaker 1: Broderick turned it down. Even then did they go to Cranston? Now,

442
00:27:12,359 --> 00:27:15,879
Speaker 1: of course Cranston is a superstar. Everybody wants him in

443
00:27:15,920 --> 00:27:18,560
Speaker 1: their picture, and he was in his mid fifties. He

444
00:27:18,680 --> 00:27:21,920
Speaker 1: was not going to become a superstar. If either Cusack

445
00:27:22,160 --> 00:27:24,639
Speaker 1: or Broderick had taken that role, that was gonna be

446
00:27:25,600 --> 00:27:28,240
Speaker 1: a fate for him. Just like thousands of other actors,

447
00:27:28,240 --> 00:27:30,920
Speaker 1: they're good enough to succeed, but they don't get their chance.

448
00:27:31,640 --> 00:27:35,480
Speaker 1: So I've noticed you've written about this, Other people have

449
00:27:35,560 --> 00:27:40,040
Speaker 1: written about this. The issue of luck versus skill seems

450
00:27:40,080 --> 00:27:44,679
Speaker 1: to divide along the political spectrum. Some people on the

451
00:27:44,760 --> 00:27:48,720
Speaker 1: left are are faster. Liberals are more quick to attribute

452
00:27:48,800 --> 00:27:52,760
Speaker 1: luck to people's success. Conservatives have a tendency to attribute

453
00:27:53,200 --> 00:27:57,679
Speaker 1: skill to me. It's luck and success. So so what

454
00:27:57,880 --> 00:28:01,800
Speaker 1: is the basis of this divide? Yeah, it's a very

455
00:28:01,840 --> 00:28:07,200
Speaker 1: interesting question. And John Hight, my friend John Hight, the psychologist,

456
00:28:07,280 --> 00:28:10,639
Speaker 1: has done some interesting work. There are temperamental differences between

457
00:28:10,680 --> 00:28:14,560
Speaker 1: liberals and conservatives. Actually, the the split between the two

458
00:28:14,600 --> 00:28:17,240
Speaker 1: groups on the role of luck is is maybe a

459
00:28:17,280 --> 00:28:21,200
Speaker 1: little more nuanced than our popular impressions make it seem.

460
00:28:21,760 --> 00:28:27,639
Speaker 1: But you know, conservatives are less likely to believe in

461
00:28:27,680 --> 00:28:30,440
Speaker 1: the challenges to the concept of free will than than

462
00:28:30,600 --> 00:28:33,680
Speaker 1: than liberals are. And so there there are some similarities

463
00:28:34,000 --> 00:28:37,680
Speaker 1: and belief patterns across the groups. But but I think

464
00:28:38,000 --> 00:28:41,920
Speaker 1: if you, if you probe a little more deeply, uh,

465
00:28:42,160 --> 00:28:45,320
Speaker 1: people from all along the political aisle, if they really

466
00:28:45,360 --> 00:28:49,120
Speaker 1: think about the examples that they know about, are are

467
00:28:49,200 --> 00:28:52,040
Speaker 1: quick to concede that. Yeah, it helps, it helps to

468
00:28:52,080 --> 00:28:56,560
Speaker 1: be lucky, being good and working hard by themselves aren't

469
00:28:56,600 --> 00:29:01,120
Speaker 1: usually enough. So we were speaking earlier about Michael Mobisan,

470
00:29:01,320 --> 00:29:05,200
Speaker 1: who is a credit Swiss and professor at Columbia who

471
00:29:05,240 --> 00:29:08,400
Speaker 1: wrote the success Equation, which looks at skill and lack

472
00:29:08,480 --> 00:29:13,400
Speaker 1: in in business, uh, sports and investing. And I said, hey,

473
00:29:13,440 --> 00:29:16,640
Speaker 1: I'm gonna be speaking to Robert Frank any questions for him?

474
00:29:16,640 --> 00:29:20,000
Speaker 1: And he said yes, absolutely. Uh. He gave me a few,

475
00:29:20,000 --> 00:29:22,680
Speaker 1: But let me give you one or two of my favorites.

476
00:29:23,200 --> 00:29:28,040
Speaker 1: How do we justify CEO pay based on skill or

477
00:29:28,120 --> 00:29:33,320
Speaker 1: are there other processes that better explain the current ratio

478
00:29:33,480 --> 00:29:39,840
Speaker 1: between CEOs and workers. That ratio, as you know, is exploded.

479
00:29:40,200 --> 00:29:43,760
Speaker 1: It used to be something like twenty times as much

480
00:29:43,800 --> 00:29:47,880
Speaker 1: as the average worker pay for the CEO in the

481
00:29:47,920 --> 00:29:52,280
Speaker 1: CEO of ratio that recently twice this week has tracked

482
00:29:52,320 --> 00:29:57,000
Speaker 1: the CEO paid average worker ratio since then, and it's

483
00:29:57,360 --> 00:29:59,600
Speaker 1: it's up depending on how large the corporation, it's up

484
00:29:59,640 --> 00:30:03,120
Speaker 1: around or hundred has has gone higher than that. It's

485
00:30:03,160 --> 00:30:06,680
Speaker 1: a huge increase. It's it's the ratio itself is exploded

486
00:30:06,720 --> 00:30:10,280
Speaker 1: by factor of ten. And there's a lot of argument

487
00:30:10,320 --> 00:30:15,080
Speaker 1: about why people talk about crony boards that are voting

488
00:30:15,120 --> 00:30:18,480
Speaker 1: favors for their pals who have installed them on the board.

489
00:30:19,600 --> 00:30:21,600
Speaker 1: You know that happened when I was a boy. We

490
00:30:21,680 --> 00:30:27,280
Speaker 1: used to hear about interlocking directorate's and but you don't ratios.

491
00:30:27,480 --> 00:30:33,480
Speaker 1: You didn't And I think, uh, there are clear examples

492
00:30:33,560 --> 00:30:37,920
Speaker 1: of waste, fraud and abuse still. But the world really

493
00:30:38,040 --> 00:30:40,520
Speaker 1: is a lot more like the NBA now than it

494
00:30:40,680 --> 00:30:47,440
Speaker 1: was when I was a kid. It's it's all it's

495
00:30:47,520 --> 00:30:50,200
Speaker 1: all competition. What have you done for me lately? If

496
00:30:50,240 --> 00:30:53,240
Speaker 1: you're not if you're not performing up to the highest standard,

497
00:30:53,400 --> 00:30:55,640
Speaker 1: if there's somebody we could replace you with who would

498
00:30:55,680 --> 00:30:58,880
Speaker 1: be even epsilon better, where you're out the door, And

499
00:30:59,320 --> 00:31:01,840
Speaker 1: I think that's you know, you don't know who's going

500
00:31:01,880 --> 00:31:04,560
Speaker 1: to be a good CEO up front. You take your chances.

501
00:31:04,680 --> 00:31:07,280
Speaker 1: But the data are pretty clear. If you hire a

502
00:31:07,320 --> 00:31:11,360
Speaker 1: CEO and the and the performance doesn't follow, then they're

503
00:31:11,400 --> 00:31:14,560
Speaker 1: on a very short leash now compared to the old days.

504
00:31:14,600 --> 00:31:16,120
Speaker 1: So but but they're on a short at least with

505
00:31:16,160 --> 00:31:20,680
Speaker 1: a very nice get a very high salary. Uh. If

506
00:31:20,760 --> 00:31:24,280
Speaker 1: they don't perform, they're out. They land whole because they

507
00:31:24,320 --> 00:31:27,600
Speaker 1: get the nice parachute but think about it, if if

508
00:31:27,600 --> 00:31:30,760
Speaker 1: you're right about the CEO, and the CEO really is

509
00:31:30,920 --> 00:31:33,760
Speaker 1: let's say three percent, five percent, if you're if you're

510
00:31:33,800 --> 00:31:37,240
Speaker 1: a ten billion dollar company annual earnings, you know that's

511
00:31:37,280 --> 00:31:41,040
Speaker 1: three million difference on your bottom line. So so having

512
00:31:41,080 --> 00:31:43,720
Speaker 1: somebody who's just a little bit better in this kind

513
00:31:43,720 --> 00:31:46,880
Speaker 1: of market really does translate into a huge difference in

514
00:31:46,920 --> 00:31:49,920
Speaker 1: the bottom line. If people want to find your work

515
00:31:50,080 --> 00:31:53,120
Speaker 1: other than Amazon, where else can they find your writings.

516
00:31:53,960 --> 00:31:57,280
Speaker 1: I have been for more than a decade a contributor

517
00:31:57,320 --> 00:31:59,880
Speaker 1: to the Economic View column in the New York Times.

518
00:32:00,280 --> 00:32:02,800
Speaker 1: Do it less frequently now, but occasionally I still write one.

519
00:32:03,880 --> 00:32:07,720
Speaker 1: Uh Mainly I'm writing books these days, so so i'd

520
00:32:07,720 --> 00:32:10,680
Speaker 1: go to the Amazon page and search out what's available.

521
00:32:10,880 --> 00:32:15,640
Speaker 1: On Twitter, I'm at econ Naturalist. Easy to find you

522
00:32:15,800 --> 00:32:19,160
Speaker 1: via Google. Be sure and check out my daily column

523
00:32:19,240 --> 00:32:22,440
Speaker 1: on Bloomberg View dot com or follow me on Twitter

524
00:32:23,040 --> 00:32:26,480
Speaker 1: at rit Halts. I'm Barry rit Halts. You're listening to

525
00:32:26,600 --> 00:32:30,760
Speaker 1: Masters in Business on Bloomberg Radio. Welcome back to the podcast.

526
00:32:30,840 --> 00:32:32,320
Speaker 1: I don't know why I do this every week, but

527
00:32:32,400 --> 00:32:34,600
Speaker 1: I do. Bob, thank you so much for doing this.

528
00:32:34,680 --> 00:32:37,719
Speaker 1: I'm I'm was really looking forward to to chatting you,

529
00:32:37,800 --> 00:32:40,360
Speaker 1: and you have not disappointed. It's been great fun to

530
00:32:40,360 --> 00:32:43,560
Speaker 1: get a chance to talk with you. So, so before

531
00:32:43,600 --> 00:32:46,800
Speaker 1: we get to some questions um that I skipped over

532
00:32:46,880 --> 00:32:50,720
Speaker 1: during the broadcast portion before I forget. So, you write

533
00:32:50,760 --> 00:32:54,760
Speaker 1: an economics the Economics View column for The Times. That's

534
00:32:54,800 --> 00:32:58,480
Speaker 1: a a monthly typically in the Sunday Business session. Is

535
00:32:58,520 --> 00:33:01,760
Speaker 1: that right? Yeah, it's It depends on how many people

536
00:33:01,800 --> 00:33:05,280
Speaker 1: are in the rotation, which is varied anywhere from five

537
00:33:05,360 --> 00:33:09,320
Speaker 1: to ten. But it's come out. But at the same time,

538
00:33:09,600 --> 00:33:13,560
Speaker 1: there is a Robert Frank who writes for The Times.

539
00:33:13,640 --> 00:33:17,000
Speaker 1: He's a reporter and he's the author of the book

540
00:33:17,080 --> 00:33:21,360
Speaker 1: Richester and a Journey through the American Wealth Boom. How

541
00:33:21,440 --> 00:33:25,240
Speaker 1: confusing is it to have to Robert Frank's both publishing

542
00:33:25,240 --> 00:33:31,400
Speaker 1: in The Times about wealth and economic inequality. Even before

543
00:33:31,440 --> 00:33:36,040
Speaker 1: he started writing for The Times, we were being confused

544
00:33:36,080 --> 00:33:38,400
Speaker 1: for one another again and again. In fact, The Times

545
00:33:38,440 --> 00:33:42,720
Speaker 1: published an article about how often people mistook one for

546
00:33:42,800 --> 00:33:45,400
Speaker 1: the other back in two thousand seven. I think it

547
00:33:45,480 --> 00:33:51,200
Speaker 1: was and probably the best story, uh, in connection with

548
00:33:52,000 --> 00:33:55,560
Speaker 1: with people mistaking us for each other is an email

549
00:33:55,600 --> 00:33:58,400
Speaker 1: I got from a friend in Houston. He had seen

550
00:33:58,440 --> 00:34:04,720
Speaker 1: an announcement for a conference catering to high net worth individuals,

551
00:34:04,880 --> 00:34:08,080
Speaker 1: and there was in the brochure for the conference a

552
00:34:08,120 --> 00:34:12,400
Speaker 1: picture of me with him, picture just of me. I

553
00:34:12,480 --> 00:34:16,440
Speaker 1: was gonna be talking about high net worth strategies or this,

554
00:34:16,440 --> 00:34:19,359
Speaker 1: this and that. That's not something he thought I would

555
00:34:19,400 --> 00:34:21,440
Speaker 1: be likely to be doing. So he wrote back and

556
00:34:21,480 --> 00:34:23,640
Speaker 1: asked me, and I said, wow, you know, I'm I'm

557
00:34:24,320 --> 00:34:26,360
Speaker 1: if I'm speaking at that conference. This is the first

558
00:34:26,400 --> 00:34:29,640
Speaker 1: I've heard about it. So I made some inquiries and

559
00:34:30,440 --> 00:34:33,920
Speaker 1: it turned out that they had tried to book the

560
00:34:33,960 --> 00:34:38,520
Speaker 1: other Robert Frank. They called the Speaker's Bureau who represents me,

561
00:34:38,800 --> 00:34:45,320
Speaker 1: and booked me instead, by mistake. The Speaker's Bureau requires

562
00:34:45,360 --> 00:34:52,480
Speaker 1: a hefty nonrefundable fee upfront deposit, and the Speaker's Bureau

563
00:34:52,680 --> 00:34:57,640
Speaker 1: refused to refund the fee to the client, even after

564
00:34:57,880 --> 00:35:00,239
Speaker 1: it became clear that they hadn't meant to engage to me.

565
00:35:00,280 --> 00:35:02,600
Speaker 1: And I said, well, he's willing to to talk to you,

566
00:35:03,840 --> 00:35:07,120
Speaker 1: We're prepared to send him. So I got a fat

567
00:35:07,200 --> 00:35:10,759
Speaker 1: check for doing nothing that time. That's great. Well, you

568
00:35:11,200 --> 00:35:13,200
Speaker 1: you did go and speak, right, did not? You did?

569
00:35:14,800 --> 00:35:19,719
Speaker 1: Now that sounds like an economic inefficiency to say the least. Um,

570
00:35:19,760 --> 00:35:21,960
Speaker 1: I want to get to a couple more questions that

571
00:35:22,040 --> 00:35:26,880
Speaker 1: we skipped earlier, some of which I find really really

572
00:35:26,920 --> 00:35:33,040
Speaker 1: intriguing on success in luck. So again another Michael Mobison question.

573
00:35:33,120 --> 00:35:36,879
Speaker 1: We tend to attribute our success to skill and our

574
00:35:37,000 --> 00:35:40,600
Speaker 1: failures to bad luck. How do we get people to

575
00:35:40,680 --> 00:35:45,560
Speaker 1: be more aware of the true role of serendipity in

576
00:35:45,600 --> 00:35:48,600
Speaker 1: their lives as opposed to merely thinking when it goes

577
00:35:48,719 --> 00:35:51,600
Speaker 1: my way, it was all me. But if something goes

578
00:35:51,680 --> 00:35:55,320
Speaker 1: along just well, you could steer people to the studies

579
00:35:55,400 --> 00:35:59,480
Speaker 1: that show that that there's that asymmetry. I suspect few

580
00:35:59,480 --> 00:36:02,800
Speaker 1: people would want to read them. Uh, And there's actually

581
00:36:02,880 --> 00:36:07,080
Speaker 1: kind of a perverse adaptive quality to the asymmetry. So,

582
00:36:07,280 --> 00:36:10,560
Speaker 1: for example, if you believe that when you succeed it's

583
00:36:10,640 --> 00:36:14,200
Speaker 1: because of your skill, not your luck, then the next

584
00:36:14,200 --> 00:36:17,840
Speaker 1: opportunity that comes along, you'll say to yourself, well, skills

585
00:36:17,880 --> 00:36:21,759
Speaker 1: a persistent trait I had skilled before I succeeded. There's

586
00:36:21,760 --> 00:36:25,439
Speaker 1: no reason not to explore this opportunity. So that's good.

587
00:36:26,000 --> 00:36:29,000
Speaker 1: You're you're you're more likely to take the action that

588
00:36:29,080 --> 00:36:31,839
Speaker 1: would lead to success. But isn't that how he ends

589
00:36:31,920 --> 00:36:35,640
Speaker 1: up with a Michael Jordan playing baseball. Yeah, well, there's

590
00:36:36,680 --> 00:36:39,400
Speaker 1: there's never a strategy that works well all the time,

591
00:36:39,520 --> 00:36:41,759
Speaker 1: you know. But with the bad luck side of that,

592
00:36:41,880 --> 00:36:45,280
Speaker 1: if you attribute your failures to bad luck, then you

593
00:36:45,280 --> 00:36:48,400
Speaker 1: you'll you'll try something you'll fail at. Oh I was unlucky.

594
00:36:48,520 --> 00:36:51,400
Speaker 1: Then another opportunity comes along, and and bad luck is

595
00:36:51,400 --> 00:36:54,040
Speaker 1: not a persistent trait, You'll say, oh, I was just

596
00:36:54,160 --> 00:36:56,480
Speaker 1: unlucky last time. I'm gonna try this time. There's no

597
00:36:56,520 --> 00:36:59,760
Speaker 1: reason to think I'll fail again. So so the person

598
00:36:59,800 --> 00:37:02,960
Speaker 1: who has that asymmetric view about good luck and bad

599
00:37:03,040 --> 00:37:06,200
Speaker 1: luck may actually do better over time than the person

600
00:37:06,239 --> 00:37:09,200
Speaker 1: who's more realistic in his beliefs. It's funny, it's it's

601
00:37:09,280 --> 00:37:12,600
Speaker 1: long been the case on Wall Street trading desks that

602
00:37:12,719 --> 00:37:17,560
Speaker 1: they recruited athletes, and a number of people have have

603
00:37:17,840 --> 00:37:21,880
Speaker 1: pondered this, and and my best explanation for that is

604
00:37:22,640 --> 00:37:25,200
Speaker 1: you can work hard all week, you can run the drills,

605
00:37:25,239 --> 00:37:29,719
Speaker 1: memorize the playbooks, and on a Saturday you get a

606
00:37:29,760 --> 00:37:32,839
Speaker 1: bad bounce or an unlucky call, you have to get

607
00:37:32,920 --> 00:37:35,439
Speaker 1: up on Monday and brush yourself off and start all over,

608
00:37:35,920 --> 00:37:39,520
Speaker 1: which pretty much describes what what happens in the random

609
00:37:39,600 --> 00:37:42,040
Speaker 1: walk on on Wall Street. You have to be able

610
00:37:42,080 --> 00:37:44,640
Speaker 1: to say that just was a bad bounce and start

611
00:37:44,640 --> 00:37:48,200
Speaker 1: all over. It seems it's a little bit of hindsight bias.

612
00:37:48,280 --> 00:37:51,759
Speaker 1: It seems to fit the existing facts and it it

613
00:37:51,880 --> 00:37:54,560
Speaker 1: sort of rationalizes it. But I have yet to find

614
00:37:54,600 --> 00:37:59,640
Speaker 1: a better explanation than that. That a symmetrical, asymmetrical way

615
00:37:59,640 --> 00:38:02,640
Speaker 1: to shake off the bad news and take credit for

616
00:38:02,680 --> 00:38:06,840
Speaker 1: the good news. One of the themes in the book

617
00:38:07,360 --> 00:38:11,960
Speaker 1: is that, uh, false belief sometimes are adaptive for you.

618
00:38:12,040 --> 00:38:15,279
Speaker 1: So when you're thinking about his luck important in your life, UH,

619
00:38:15,719 --> 00:38:20,040
Speaker 1: let me read Duncan Watts's blurb that he's a very

620
00:38:20,080 --> 00:38:24,960
Speaker 1: distinguished sociologist. If you're listeners don't know him, run out

621
00:38:25,000 --> 00:38:27,560
Speaker 1: and by his book, everything is obvious once you know

622
00:38:27,640 --> 00:38:32,760
Speaker 1: the answer. It's a terrific, terrific informative book. Uh. He writes,

623
00:38:32,880 --> 00:38:36,960
Speaker 1: building a successful life requires a deep conviction that you

624
00:38:36,960 --> 00:38:40,839
Speaker 1: are the author of your own destiny. That's absolutely right.

625
00:38:41,120 --> 00:38:42,920
Speaker 1: By the way I think, if you think, oh, I'm

626
00:38:42,920 --> 00:38:45,760
Speaker 1: a cork in the river, what was me? That's you're

627
00:38:45,760 --> 00:38:47,879
Speaker 1: not going to attack your life in a very effective way.

628
00:38:48,600 --> 00:38:53,760
Speaker 1: He continues, building a successful society requires an equally deep

629
00:38:53,840 --> 00:38:57,399
Speaker 1: conviction that no one's destiny is their own. To write

630
00:38:57,880 --> 00:39:03,720
Speaker 1: balancing these seemingly contradictory ideas maybe the most important social

631
00:39:03,800 --> 00:39:06,400
Speaker 1: challenge of our time, And then he goes on to

632
00:39:06,440 --> 00:39:09,920
Speaker 1: say nice things about the book. That's a fascinating um

633
00:39:09,960 --> 00:39:12,440
Speaker 1: way to look at it from bottoms up and top down.

634
00:39:12,520 --> 00:39:15,479
Speaker 1: Exactly what what works for an individual may not work

635
00:39:15,520 --> 00:39:18,680
Speaker 1: for a society. Yeah, what what we what we should

636
00:39:18,719 --> 00:39:22,640
Speaker 1: believe if we want to be effective psychologically confronting the

637
00:39:22,640 --> 00:39:26,399
Speaker 1: world may not be a very accurate description of how

638
00:39:26,400 --> 00:39:32,560
Speaker 1: the world works. So if inequality, as an example, is

639
00:39:32,600 --> 00:39:36,480
Speaker 1: a natural outcome of and again I'm gonna quote mobis

640
00:39:36,520 --> 00:39:42,799
Speaker 1: on a path dependent outcome luck, what if anything, should

641
00:39:42,840 --> 00:39:48,759
Speaker 1: we do about that? One of the points I try

642
00:39:48,800 --> 00:39:51,480
Speaker 1: to make in the book is that we haven't been

643
00:39:51,520 --> 00:39:55,799
Speaker 1: investing for the future. The kids who are growing up

644
00:39:55,800 --> 00:39:57,680
Speaker 1: today without a lot of money in their families are

645
00:39:57,719 --> 00:40:00,680
Speaker 1: having a hard time getting through school, that they're handicap

646
00:40:00,760 --> 00:40:03,160
Speaker 1: from a very early age in terms of training they get.

647
00:40:04,480 --> 00:40:07,319
Speaker 1: It would cost money to do something about that. But

648
00:40:07,640 --> 00:40:09,680
Speaker 1: the point I try to make in the book is

649
00:40:09,719 --> 00:40:13,080
Speaker 1: that those of us who have done well could easily

650
00:40:13,920 --> 00:40:17,040
Speaker 1: supply the resources. We need to do something about that

651
00:40:17,600 --> 00:40:21,359
Speaker 1: without making any sacrifices that would be painful at all.

652
00:40:21,680 --> 00:40:26,600
Speaker 1: And And for instance, I had a conversation with a colleague.

653
00:40:26,960 --> 00:40:29,359
Speaker 1: He was afraid about the new taxes that were coming.

654
00:40:29,400 --> 00:40:32,359
Speaker 1: I said, look, don't worry about them. People like us.

655
00:40:32,440 --> 00:40:35,200
Speaker 1: It doesn't matter. He has a successful textbook. He's not

656
00:40:35,239 --> 00:40:38,320
Speaker 1: going to spend everything. You arned, I don't spend everything.

657
00:40:38,360 --> 00:40:41,880
Speaker 1: Iron We have everything we need, right, what's an issue?

658
00:40:41,880 --> 00:40:44,520
Speaker 1: Will we still be able to get what we want

659
00:40:44,600 --> 00:40:46,440
Speaker 1: if taxes go up to Yeah, that's what he was

660
00:40:46,440 --> 00:40:48,960
Speaker 1: worried about. Well, what do people like us want? We've

661
00:40:48,960 --> 00:40:51,920
Speaker 1: got everything we need. We want something special, And you

662
00:40:51,960 --> 00:40:54,680
Speaker 1: want to be able to have a special celebration when

663
00:40:54,719 --> 00:40:57,560
Speaker 1: your daughter gets married. You want to have a house

664
00:40:57,600 --> 00:41:00,520
Speaker 1: with a sweeping view of the Lake of Choy, Slip

665
00:41:00,520 --> 00:41:03,239
Speaker 1: at the marina, whatever it might be. There aren't enough

666
00:41:03,280 --> 00:41:06,399
Speaker 1: of those things. You have to bid against other people

667
00:41:06,480 --> 00:41:10,320
Speaker 1: like us to get them. What happens if their taxes

668
00:41:10,400 --> 00:41:13,520
Speaker 1: go up and our taxes go up? Who gets those things?

669
00:41:13,600 --> 00:41:17,879
Speaker 1: The same people as before? So and he bought this, Uh,

670
00:41:17,920 --> 00:41:19,960
Speaker 1: you know, I'm not gonna say he bought it but

671
00:41:20,080 --> 00:41:23,080
Speaker 1: he seemed willing to think about it. But if if

672
00:41:23,120 --> 00:41:27,040
Speaker 1: someone were willing to think about it, it's uncontroversial. You know,

673
00:41:27,160 --> 00:41:33,359
Speaker 1: the the things that we care about are defined very

674
00:41:33,360 --> 00:41:36,320
Speaker 1: heavily in relative terms. Everybody wants to have a special

675
00:41:36,320 --> 00:41:40,680
Speaker 1: occasion for his daughter's wedding. What's special? It's a purely

676
00:41:40,680 --> 00:41:45,560
Speaker 1: relative concept. People today are spending thirty dollars on weddings

677
00:41:45,560 --> 00:41:48,759
Speaker 1: on average in New York. It's not not around here

678
00:41:49,840 --> 00:41:53,279
Speaker 1: in Manhattan. Why and it was ten thousand back in

679
00:41:54,239 --> 00:41:57,480
Speaker 1: Why have they gone up so much because other people

680
00:41:57,480 --> 00:41:59,719
Speaker 1: are spending more? And why is that? Because people at

681
00:41:59,719 --> 00:42:02,319
Speaker 1: the time opper spending more. It trickles trickles down. But

682
00:42:02,760 --> 00:42:04,880
Speaker 1: they're not bad people. They just want to have a

683
00:42:04,920 --> 00:42:08,480
Speaker 1: special occasion, and special is relative. If you spend way

684
00:42:08,560 --> 00:42:11,839
Speaker 1: less than everybody else spends, then it seems like a

685
00:42:12,000 --> 00:42:14,840
Speaker 1: kind of a two bit wedding. You use the example

686
00:42:15,000 --> 00:42:21,200
Speaker 1: that people lovers in poor countries the when dating, they

687
00:42:21,239 --> 00:42:24,160
Speaker 1: give a single rose as a gift, and it's it's

688
00:42:24,200 --> 00:42:27,520
Speaker 1: well received. But in wealthy countries, if it's not a

689
00:42:27,600 --> 00:42:31,160
Speaker 1: dozen roses, it's thought of as as you're being cheap,

690
00:42:31,200 --> 00:42:33,680
Speaker 1: and it's not the same sort of resonance. Yeah, it's

691
00:42:34,160 --> 00:42:38,600
Speaker 1: it's a familiar point. No, No one hears about examples

692
00:42:38,640 --> 00:42:40,239
Speaker 1: like that and say, oh, that's not the way the

693
00:42:40,280 --> 00:42:43,719
Speaker 1: world is. Uh, everybody knows that's the way the world works.

694
00:42:43,719 --> 00:42:48,480
Speaker 1: So it's interesting that people resist the notion that framing

695
00:42:48,520 --> 00:42:51,959
Speaker 1: effects and context matters as much as it does. So

696
00:42:52,120 --> 00:42:55,400
Speaker 1: let's let's take another example something I enjoyed from the book,

697
00:42:56,000 --> 00:42:59,080
Speaker 1: where where we were talking about how relative things are

698
00:42:59,200 --> 00:43:03,279
Speaker 1: and how when the the same tide goes up or

699
00:43:03,320 --> 00:43:07,319
Speaker 1: down it affects everybody equally, and use an example of

700
00:43:08,160 --> 00:43:12,280
Speaker 1: we have big tax cuts, which affords somebody to drive

701
00:43:12,360 --> 00:43:18,240
Speaker 1: a Ferrari, but it's over these beat up, pothole cracked roads.

702
00:43:18,480 --> 00:43:21,560
Speaker 1: Had we not had such large tax cuts, if the

703
00:43:21,560 --> 00:43:25,200
Speaker 1: tax cuts were a little smaller, society can afford to

704
00:43:25,280 --> 00:43:28,600
Speaker 1: pave everything and have nice smooth asphalt. And at that point,

705
00:43:28,640 --> 00:43:33,000
Speaker 1: you're driving a Porsche on a smooth, clean road, which

706
00:43:33,160 --> 00:43:36,560
Speaker 1: overall is the better experience for the individual, and what's

707
00:43:36,600 --> 00:43:40,440
Speaker 1: the better experience for society. And the conclusion is the

708
00:43:40,520 --> 00:43:44,120
Speaker 1: Porsche on the smooth, well paved roads is better for

709
00:43:44,160 --> 00:43:47,879
Speaker 1: everybody than a Ferrari on a horrible pothole road where

710
00:43:47,920 --> 00:43:50,520
Speaker 1: you can't get out of second gear, you know. You know, Barry,

711
00:43:50,600 --> 00:43:54,399
Speaker 1: I have yet to meet anyone who who says, oh, no,

712
00:43:54,480 --> 00:43:58,240
Speaker 1: that's not right. I'd rather drive a Ferrari on roads

713
00:43:58,320 --> 00:44:01,320
Speaker 1: riddled with footneep potholes. No, he say, Well, the pushback

714
00:44:01,360 --> 00:44:04,000
Speaker 1: would be, it's not just the Ferrari, but it's all

715
00:44:04,080 --> 00:44:07,719
Speaker 1: this across the whole board, and it's confiscatory, and we

716
00:44:07,760 --> 00:44:11,759
Speaker 1: can have high tax rates and it's a whole philosophical digression,

717
00:44:12,160 --> 00:44:16,840
Speaker 1: but I'm talking at a marginal change sufficient to I

718
00:44:16,880 --> 00:44:19,759
Speaker 1: don't know, pay for the infrastructure we all use. And

719
00:44:19,880 --> 00:44:24,520
Speaker 1: I'm a car fan. I like anything that goes fast. Um,

720
00:44:24,560 --> 00:44:26,520
Speaker 1: and I have been complaining about the roads for a

721
00:44:26,560 --> 00:44:30,920
Speaker 1: long time. We've had a gas tax that's been frozen

722
00:44:30,960 --> 00:44:35,840
Speaker 1: in place since, which leads to a question. Uh, something

723
00:44:35,880 --> 00:44:39,080
Speaker 1: else came up in one of your columns, which had

724
00:44:39,160 --> 00:44:47,160
Speaker 1: to do with the the anti government, Uh, philosophies that

725
00:44:47,320 --> 00:44:50,160
Speaker 1: say we can never raise taxes, We shouldn't be spending money.

726
00:44:50,160 --> 00:44:52,719
Speaker 1: Government should be as small as possible. And that's how

727
00:44:52,760 --> 00:44:56,000
Speaker 1: we end up painted into an a gas tax that's

728
00:44:56,080 --> 00:45:00,480
Speaker 1: unchanged for UM over twenty almost twenty five years. Yeah,

729
00:45:00,520 --> 00:45:04,480
Speaker 1: it's it's just not in the interests of anyone to

730
00:45:05,320 --> 00:45:10,720
Speaker 1: have that rigid anti tax position, and yet that's become

731
00:45:11,320 --> 00:45:14,600
Speaker 1: almost a default for half of the politician. You hear

732
00:45:14,719 --> 00:45:19,040
Speaker 1: people say without any self consciousness that taxation is theft,

733
00:45:19,200 --> 00:45:22,239
Speaker 1: and the presumption there seems to be I earned it,

734
00:45:22,239 --> 00:45:26,319
Speaker 1: it should be mine to keep. Well, every country in

735
00:45:26,360 --> 00:45:30,120
Speaker 1: the world has mandatory taxation. What what's the position here

736
00:45:30,360 --> 00:45:34,680
Speaker 1: that Samalia Smalia is your exception? Taxes should be voluntary

737
00:45:34,760 --> 00:45:36,680
Speaker 1: like there are in Smalia. Do you want to move there?

738
00:45:36,800 --> 00:45:40,399
Speaker 1: Nobody seems to be queueing enough to move there. So

739
00:45:40,400 --> 00:45:43,160
Speaker 1: so if you don't have mandatory taxes, then you don't

740
00:45:43,160 --> 00:45:44,799
Speaker 1: have a government, you don't have an army. You get

741
00:45:44,840 --> 00:45:47,239
Speaker 1: invaded by some other country that has an army, then

742
00:45:47,280 --> 00:45:50,640
Speaker 1: you pay mandatory taxes to them. So so the interesting

743
00:45:50,719 --> 00:45:53,279
Speaker 1: questions are what should we tax, how much should we

744
00:45:53,320 --> 00:45:57,399
Speaker 1: tax it? All those things are ripe for discussion, but

745
00:45:57,600 --> 00:46:00,880
Speaker 1: we don't seem to have any a bill to discuss

746
00:46:01,000 --> 00:46:03,759
Speaker 1: something that has the word tax in it. I have

747
00:46:03,960 --> 00:46:07,880
Speaker 1: a sneaking feeling that this coming election that might be

748
00:46:07,920 --> 00:46:11,200
Speaker 1: a big issue, and and the fallout after this election

749
00:46:11,920 --> 00:46:15,640
Speaker 1: might see some some interesting rethinks of of pre existing

750
00:46:16,160 --> 00:46:19,560
Speaker 1: thought processes. We'll have to see how that that plays out.

751
00:46:19,719 --> 00:46:23,400
Speaker 1: We'll watch that with great interest, won't we. So back

752
00:46:23,440 --> 00:46:26,319
Speaker 1: to um the Ferrari. You had a column in the

753
00:46:26,400 --> 00:46:30,239
Speaker 1: Times that that I when I was researching this, I

754
00:46:30,280 --> 00:46:35,200
Speaker 1: found and thought was pretty interesting, which said, conspicuous consumption

755
00:46:35,360 --> 00:46:41,480
Speaker 1: is not so crazy. You know, we we're we're creatures

756
00:46:41,840 --> 00:46:45,880
Speaker 1: of our inheritance. Uh is it cold out? Well, if

757
00:46:45,880 --> 00:46:48,839
Speaker 1: you ask somebody that in Miami, where I grew up,

758
00:46:48,880 --> 00:46:51,680
Speaker 1: on a sixty degree day in November, they're not happy.

759
00:46:51,840 --> 00:46:54,400
Speaker 1: They know it's cold out. It's a stupid question. But

760
00:46:54,440 --> 00:46:57,080
Speaker 1: if you ask somebody and I don't know Helsinki on

761
00:46:57,120 --> 00:47:00,000
Speaker 1: a sixty degree day in March, they'll think you're stupid,

762
00:47:00,000 --> 00:47:03,040
Speaker 1: would for asking, But the answers the opposite of it

763
00:47:03,120 --> 00:47:07,640
Speaker 1: was not called out. So yeah, context shapes are evaluations.

764
00:47:07,760 --> 00:47:10,120
Speaker 1: You know, I lived in a two room house with

765
00:47:10,160 --> 00:47:13,560
Speaker 1: no plumbing or electricity the two years I was Peace

766
00:47:13,560 --> 00:47:17,439
Speaker 1: Corps volunteer and rural Nepal. Not for one minute did

767
00:47:17,440 --> 00:47:21,360
Speaker 1: that house seem in any way unsatisfactory. But neither you

768
00:47:21,520 --> 00:47:23,600
Speaker 1: nor I could live in that house here in the

769
00:47:23,640 --> 00:47:28,200
Speaker 1: US without feeling ashamed from our circumstances. Your kids wouldn't

770
00:47:28,200 --> 00:47:30,719
Speaker 1: want their friends to know where you lived. So so

771
00:47:30,840 --> 00:47:35,200
Speaker 1: context is clearly important as a as a a frame

772
00:47:35,360 --> 00:47:38,400
Speaker 1: from making evaluations. How am I doing? You can't answer

773
00:47:38,440 --> 00:47:40,560
Speaker 1: the question without a frame of reference. How am I

774
00:47:40,600 --> 00:47:44,040
Speaker 1: doing relative to what? Relative to people like me? Here

775
00:47:44,040 --> 00:47:46,480
Speaker 1: and now? How am I doing? And and what is

776
00:47:46,520 --> 00:47:50,799
Speaker 1: it about some of these um luxury purchases that are

777
00:47:51,040 --> 00:47:56,319
Speaker 1: either signaling events or you know, the difference again, to

778
00:47:56,360 --> 00:47:59,120
Speaker 1: go back to the portion of Ferrari, the difference between

779
00:47:59,160 --> 00:48:02,040
Speaker 1: the portion of the Ferrari e it. At a certain

780
00:48:02,080 --> 00:48:05,920
Speaker 1: point it becomes harder and harder to justify each hundred

781
00:48:06,000 --> 00:48:09,880
Speaker 1: thousand dollar increment for the next mill you know, the

782
00:48:09,920 --> 00:48:11,799
Speaker 1: next tenth of a set. Once you're up to the

783
00:48:11,920 --> 00:48:14,240
Speaker 1: portion of nine eleven, that's a hundred and fifty thousand

784
00:48:14,280 --> 00:48:17,680
Speaker 1: dollar car, you've got virtually every design feature that affects

785
00:48:17,719 --> 00:48:22,080
Speaker 1: performance in any significant way. So if the Ferrari Berlinette

786
00:48:22,160 --> 00:48:24,959
Speaker 1: is a better car, some people will argue that it isn't.

787
00:48:25,000 --> 00:48:27,360
Speaker 1: But if it is, it's at most just a hair's

788
00:48:27,440 --> 00:48:31,840
Speaker 1: breadth better, and so you're not getting much in absolute terms.

789
00:48:31,840 --> 00:48:35,200
Speaker 1: But if you were on a planet where the Porsche

790
00:48:35,360 --> 00:48:38,360
Speaker 1: were the best car and we could hook in the

791
00:48:38,520 --> 00:48:41,360
Speaker 1: driver's brains. How happy are they about their car? They'd

792
00:48:41,360 --> 00:48:44,000
Speaker 1: be just as happy as the as the drivers on

793
00:48:44,040 --> 00:48:48,160
Speaker 1: the other world where the the Ferrari where the best car,

794
00:48:48,719 --> 00:48:52,680
Speaker 1: and and so you know, it's the it's the subjective

795
00:48:52,760 --> 00:48:55,879
Speaker 1: sense that you're driving something special that people are really

796
00:48:55,920 --> 00:48:57,520
Speaker 1: willing to pay for. You know, if you're if your

797
00:48:57,560 --> 00:49:00,799
Speaker 1: car would get to sixty miles money, it would seem

798
00:49:00,840 --> 00:49:05,240
Speaker 1: fast to you. Uh, eventually if it got that that fast,

799
00:49:05,600 --> 00:49:07,960
Speaker 1: Now it's got to get there. Now the Tesla gets

800
00:49:08,000 --> 00:49:11,680
Speaker 1: there in three point two seconds in in a ludicrous mode.

801
00:49:11,719 --> 00:49:14,960
Speaker 1: It's now under In fact, the Tesla is faster than

802
00:49:14,960 --> 00:49:17,880
Speaker 1: the portion of the Ferrari. So tho, just standards are

803
00:49:18,200 --> 00:49:22,640
Speaker 1: are very elastic. That defined special and so this is subjective,

804
00:49:23,120 --> 00:49:26,960
Speaker 1: it's relative, and the context makes a great deal of difference.

805
00:49:27,120 --> 00:49:30,759
Speaker 1: And and collectively we have some say over what the

806
00:49:30,800 --> 00:49:34,560
Speaker 1: context is, you know, meaning it's not in our interests

807
00:49:34,680 --> 00:49:40,120
Speaker 1: to keep throwing tax cuts into pockets that will result

808
00:49:40,160 --> 00:49:43,759
Speaker 1: in spending that just bids up the context. Why would

809
00:49:43,800 --> 00:49:47,560
Speaker 1: an executive be happier in a world where everyone had

810
00:49:47,600 --> 00:49:51,880
Speaker 1: at square foot mansion in that circle than in a

811
00:49:51,920 --> 00:49:55,000
Speaker 1: world where the mansions were only And you use the

812
00:49:55,040 --> 00:49:58,480
Speaker 1: example in in one of the books that if you

813
00:49:58,560 --> 00:50:01,319
Speaker 1: ask people which would they p are if everybody has

814
00:50:01,360 --> 00:50:04,320
Speaker 1: a two thousand square foot house and yours is three thousand,

815
00:50:04,880 --> 00:50:07,400
Speaker 1: or if everybody has a six thousand square foot in

816
00:50:07,400 --> 00:50:11,560
Speaker 1: your house is five thousand, and people take the bigger

817
00:50:11,600 --> 00:50:14,319
Speaker 1: small house rather than the smaller big house. Yeah, if

818
00:50:14,320 --> 00:50:17,520
Speaker 1: the small house gets small enough, they'll flip, right. But yeah,

819
00:50:17,600 --> 00:50:22,680
Speaker 1: within a reasonable range. I think people judge correctly that

820
00:50:22,719 --> 00:50:25,640
Speaker 1: they're probably going to be happier about their house if

821
00:50:25,640 --> 00:50:29,759
Speaker 1: it's not a relatively inferior one in their local context.

822
00:50:29,840 --> 00:50:36,160
Speaker 1: That that's interesting. Um, last of the mobisan questions. So

823
00:50:37,000 --> 00:50:41,279
Speaker 1: most people understand luck at a very high level. How

824
00:50:41,440 --> 00:50:46,280
Speaker 1: we capable of of pinpointing the role of luck um

825
00:50:47,320 --> 00:50:51,680
Speaker 1: in very successful outcomes? Is there a way to identify

826
00:50:51,800 --> 00:50:53,919
Speaker 1: other than Bill Gates saying, Hey, I was really lucky.

827
00:50:54,000 --> 00:50:56,440
Speaker 1: I went to this high school, I got this IBM,

828
00:50:56,480 --> 00:50:59,280
Speaker 1: made this bad deal which we took advantage of. Unless

829
00:50:59,320 --> 00:51:03,000
Speaker 1: someone's in hitting that, how could we really identify luck

830
00:51:03,120 --> 00:51:07,719
Speaker 1: versus skill? You know, it's it's interesting how you get

831
00:51:07,760 --> 00:51:10,160
Speaker 1: people to think about the role of luck in their

832
00:51:10,200 --> 00:51:14,720
Speaker 1: lives and uh, there was a article on Mother Jones

833
00:51:14,840 --> 00:51:19,000
Speaker 1: by Kevin Drum last Uh. He had seen a piece

834
00:51:19,160 --> 00:51:23,360
Speaker 1: that was excerpted from my book on vox vox dot com,

835
00:51:23,400 --> 00:51:29,920
Speaker 1: and he was quick to identify all the lucky things

836
00:51:29,920 --> 00:51:33,680
Speaker 1: that had benefited him in his life. But he was

837
00:51:33,760 --> 00:51:37,239
Speaker 1: skeptical about my claim that telling rich people they'd been

838
00:51:37,320 --> 00:51:40,600
Speaker 1: lucky would make them more willing to pay taxes. Uh.

839
00:51:40,880 --> 00:51:43,200
Speaker 1: The claim in the book is that if you're more

840
00:51:43,200 --> 00:51:46,400
Speaker 1: cognizant of having been lucky, then you are more generous

841
00:51:46,400 --> 00:51:49,400
Speaker 1: to the next generation. And I wrote him back and

842
00:51:49,400 --> 00:51:52,480
Speaker 1: I said, well, I agree. Just telling them that they're

843
00:51:52,560 --> 00:51:57,120
Speaker 1: lucky will elicit a reaction of anger and defensiveness, much

844
00:51:57,120 --> 00:51:59,600
Speaker 1: as that you didn't build that speech to you're telling

845
00:51:59,600 --> 00:52:03,120
Speaker 1: people you don't belong where you are. Uh. But there's

846
00:52:03,400 --> 00:52:07,759
Speaker 1: an interesting twist. If you'll ask a successful person, can

847
00:52:07,800 --> 00:52:10,799
Speaker 1: you think of any examples of breaks eve enjoyed along

848
00:52:10,840 --> 00:52:15,840
Speaker 1: the way that completely disarms the anger and the defensiveness.

849
00:52:15,840 --> 00:52:19,400
Speaker 1: People seem to immediately light up. They think about what

850
00:52:19,640 --> 00:52:21,560
Speaker 1: you know they're they're past. If they think of an

851
00:52:21,600 --> 00:52:23,600
Speaker 1: example of a break they had, they want to tell

852
00:52:23,640 --> 00:52:26,000
Speaker 1: you about it right away. The more examples they can

853
00:52:26,040 --> 00:52:29,120
Speaker 1: think of the happier they seem to get. It's just

854
00:52:29,640 --> 00:52:34,960
Speaker 1: a complete jiu jitsu maneuver. It has a dramatically different

855
00:52:34,960 --> 00:52:39,600
Speaker 1: effect on how they react to the idea that luck

856
00:52:39,640 --> 00:52:42,080
Speaker 1: may have mattered in their their lives. And so I

857
00:52:42,800 --> 00:52:46,680
Speaker 1: wrote that up into a piece uh with the title

858
00:52:46,680 --> 00:52:49,080
Speaker 1: I like best of any piece I ever wrote. The

859
00:52:49,120 --> 00:52:55,120
Speaker 1: title is ask Comma, don't tell ask people about their

860
00:52:55,200 --> 00:52:59,880
Speaker 1: their like. Um, that's a variation on a Ben Franklin issue.

861
00:53:00,239 --> 00:53:03,239
Speaker 1: Instead of debating with people, he would agree with them

862
00:53:03,280 --> 00:53:06,480
Speaker 1: and ask them as to you know, my position is

863
00:53:06,520 --> 00:53:09,319
Speaker 1: wrong and I can't figure out and he would have

864
00:53:09,360 --> 00:53:11,200
Speaker 1: listened their help, and by the time they were done,

865
00:53:11,640 --> 00:53:14,279
Speaker 1: they had convinced him that his position was was right.

866
00:53:14,640 --> 00:53:20,120
Speaker 1: But there's a certain fact to having people volunteered themselves

867
00:53:20,280 --> 00:53:23,160
Speaker 1: rather than you know, the Socratic method has been around

868
00:53:23,160 --> 00:53:26,200
Speaker 1: for a few thousand years, not for no reason. So

869
00:53:26,360 --> 00:53:30,040
Speaker 1: let me jump to some of my favorite questions. UM,

870
00:53:30,080 --> 00:53:32,160
Speaker 1: I was gonna ask you about your background, but pretty

871
00:53:32,239 --> 00:53:35,000
Speaker 1: much out of the PhD talk math. And then you

872
00:53:35,120 --> 00:53:37,640
Speaker 1: ended up at Cornell twenty years ago or so. How

873
00:53:37,640 --> 00:53:39,200
Speaker 1: long have you been there for I've been at Cornell

874
00:53:39,280 --> 00:53:44,200
Speaker 1: since nine, right out of graduate school, UH and started

875
00:53:44,200 --> 00:53:46,279
Speaker 1: my teaching career at Cornell, and I've been there ever

876
00:53:46,320 --> 00:53:49,600
Speaker 1: since except for various sabbatical leaves. Like so, who are

877
00:53:49,640 --> 00:53:53,120
Speaker 1: some of your mentors? There's one I have to ask

878
00:53:53,160 --> 00:53:56,239
Speaker 1: because I'm a fan of his work, But I would

879
00:53:56,320 --> 00:53:59,880
Speaker 1: say that the two economists who have shaped my thinking

880
00:54:00,120 --> 00:54:04,720
Speaker 1: personally the most by a wide margin, even one would

881
00:54:04,719 --> 00:54:12,440
Speaker 1: be Tom Shelling, Nobel laureate, a long time Harvard Public

882
00:54:12,480 --> 00:54:20,919
Speaker 1: Policy School professor. I think he, more than anyone, had

883
00:54:21,000 --> 00:54:25,839
Speaker 1: written clearly about why what it makes sense for us

884
00:54:25,920 --> 00:54:29,840
Speaker 1: individually to do may not make sense for us to

885
00:54:30,000 --> 00:54:32,600
Speaker 1: do when we think about it from the perspective of

886
00:54:32,680 --> 00:54:36,719
Speaker 1: the groups we belong to, so all standing to get

887
00:54:36,719 --> 00:54:40,680
Speaker 1: a better view, no one sees better than if everybody

888
00:54:40,719 --> 00:54:44,200
Speaker 1: remained comfortably seated. That's kind of a trivial example of

889
00:54:44,239 --> 00:54:46,799
Speaker 1: that sort, but that's been a big theme in my

890
00:54:46,880 --> 00:54:54,160
Speaker 1: own thinking about behavior and social organization. The other economists

891
00:54:54,160 --> 00:54:57,600
Speaker 1: who's had the most influence on me is Ronald Co's,

892
00:54:58,400 --> 00:55:03,920
Speaker 1: who U also also no. He was University of Chicago.

893
00:55:04,239 --> 00:55:09,600
Speaker 1: He was also a Nobel laureate. UH and UH wrote

894
00:55:10,239 --> 00:55:15,360
Speaker 1: very little, actually, just a handful of articles, but one

895
00:55:15,680 --> 00:55:18,960
Speaker 1: I think is the most widely quoted and cited article

896
00:55:19,280 --> 00:55:22,360
Speaker 1: of all time and economics, the problem of social cost

897
00:55:22,560 --> 00:55:26,240
Speaker 1: and it's it's it's a way of thinking more clearly

898
00:55:26,280 --> 00:55:31,479
Speaker 1: about what happens when somebody does something that has either

899
00:55:31,560 --> 00:55:35,440
Speaker 1: negative or positive spillover effects on others. You make noise

900
00:55:35,480 --> 00:55:38,719
Speaker 1: that disturbed the neighbors, You drive a heavy car, you

901
00:55:38,760 --> 00:55:41,719
Speaker 1: put others at greater risk of injury and death. Uh.

902
00:55:42,080 --> 00:55:45,880
Speaker 1: It used to be that people thought about those kinds

903
00:55:45,880 --> 00:55:49,440
Speaker 1: of issues in terms of perpetrators and victims. You know,

904
00:55:49,440 --> 00:55:52,480
Speaker 1: there were good guys and bad guys, and and his

905
00:55:52,560 --> 00:55:57,239
Speaker 1: insight was that, no, these are people whose interests, both legitimate,

906
00:55:57,600 --> 00:56:01,320
Speaker 1: are just in conflict with one another. Their shared interest

907
00:56:01,440 --> 00:56:03,920
Speaker 1: is to figure out the most efficient way of resolving

908
00:56:03,960 --> 00:56:09,000
Speaker 1: their conflict, and that sometimes leads to very counterintuitive conclusions

909
00:56:09,000 --> 00:56:11,200
Speaker 1: about what ought to be done. So let me ask

910
00:56:11,239 --> 00:56:14,600
Speaker 1: you about two other people who were at Cornell. One

911
00:56:14,880 --> 00:56:18,719
Speaker 1: as someone you referenced in the book, Ed Gramleck was

912
00:56:19,120 --> 00:56:22,040
Speaker 1: on the Federal Federal Reserve. He was a member of

913
00:56:22,040 --> 00:56:25,879
Speaker 1: the Board of Governors of the FED. Very insightful way

914
00:56:25,920 --> 00:56:30,560
Speaker 1: ahead of the curve, criticizing subprime lending, predatory lending, and

915
00:56:30,640 --> 00:56:34,680
Speaker 1: a whole slew of different things that uh he brought

916
00:56:34,880 --> 00:56:38,840
Speaker 1: Alan Greenspan's attention, and Greenspan said, don't worry, the marketplace

917
00:56:38,840 --> 00:56:41,200
Speaker 1: will take care of it. And actually Greenspan was right.

918
00:56:41,480 --> 00:56:44,799
Speaker 1: Eventually the marketplace did take care of it. Jeter, we

919
00:56:44,840 --> 00:56:46,800
Speaker 1: went through the Ringer right, just just not quite the

920
00:56:46,840 --> 00:56:49,480
Speaker 1: way I think he anticipated. But you tell a wonderful

921
00:56:49,520 --> 00:56:52,520
Speaker 1: story in the book about Graham Lock and you on

922
00:56:52,600 --> 00:56:56,080
Speaker 1: a ski lift. Yeah. He he came as a visitor

923
00:56:56,200 --> 00:56:58,279
Speaker 1: my my fourth year when I was at Cornell, I

924
00:56:58,280 --> 00:57:05,239
Speaker 1: had written very little. I had various UH issues had

925
00:57:05,680 --> 00:57:07,960
Speaker 1: sort of kept me from putting as much time and

926
00:57:08,040 --> 00:57:10,520
Speaker 1: energy into my writing. So I was, you know today

927
00:57:10,560 --> 00:57:14,040
Speaker 1: they would fire somebody like me in year three. Then

928
00:57:14,120 --> 00:57:15,839
Speaker 1: they kept me on just because I was a good

929
00:57:15,880 --> 00:57:19,240
Speaker 1: teacher in the a big class. It was hard to staff.

930
00:57:19,360 --> 00:57:23,080
Speaker 1: But they would have fired me at next opportunity, I'm

931
00:57:23,160 --> 00:57:27,160
Speaker 1: quite sure. But but but Ned took an interest in

932
00:57:27,280 --> 00:57:33,240
Speaker 1: my work. We became friends. He offered to publish a

933
00:57:33,280 --> 00:57:35,320
Speaker 1: paper if I would write it for a volume he

934
00:57:35,400 --> 00:57:39,360
Speaker 1: was editing, uh and and nobody else had shown any

935
00:57:39,400 --> 00:57:41,600
Speaker 1: interest in what I was doing up until and so

936
00:57:41,680 --> 00:57:46,240
Speaker 1: I happily agreed and wrote the paper, I was pretty

937
00:57:46,240 --> 00:57:48,400
Speaker 1: pleased about it. I gave it to him, and then

938
00:57:49,160 --> 00:57:51,320
Speaker 1: a day or two later he came to my office

939
00:57:51,360 --> 00:57:55,960
Speaker 1: with a hangdog expression, saying that the sponsor of the

940
00:57:56,120 --> 00:58:00,480
Speaker 1: volume that the paper was to have appeared in had

941
00:58:00,520 --> 00:58:03,360
Speaker 1: called him to say the volume had been canceled, and

942
00:58:04,480 --> 00:58:07,120
Speaker 1: it seemed like bad luck to me. I sent the

943
00:58:07,120 --> 00:58:09,920
Speaker 1: paper out to a very selective journal just on lark,

944
00:58:09,960 --> 00:58:13,000
Speaker 1: and it got accepted for publication, which was for me

945
00:58:13,600 --> 00:58:17,600
Speaker 1: a way better outcome. And if it had gone into

946
00:58:17,680 --> 00:58:22,000
Speaker 1: a an edited volume, which hardly anyone reads, and you know,

947
00:58:22,080 --> 00:58:24,840
Speaker 1: isn't isn't really a good career move. But yeah, I

948
00:58:24,920 --> 00:58:28,840
Speaker 1: was incredibly lucky to get that paper accepted where it were,

949
00:58:28,880 --> 00:58:31,680
Speaker 1: And and I had a string of papers that got

950
00:58:31,720 --> 00:58:35,760
Speaker 1: accepted in quick succession with almost no delay. That's never

951
00:58:35,840 --> 00:58:39,880
Speaker 1: happened to me since then. The later papers I've written,

952
00:58:39,920 --> 00:58:42,120
Speaker 1: I'm sure we're at least as good as those early ones.

953
00:58:42,280 --> 00:58:46,120
Speaker 1: But if if I'd had the usual editorial delays even

954
00:58:46,160 --> 00:58:49,840
Speaker 1: with them, I would have been fired the next opportunity.

955
00:58:50,000 --> 00:58:53,320
Speaker 1: So the lucky break that the editor journal is canceled.

956
00:58:53,360 --> 00:58:57,440
Speaker 1: What was it Econometrica that so Econometrica accepted my paper,

957
00:58:57,680 --> 00:59:00,400
Speaker 1: did that success be get the other substit well, then

958
00:59:00,440 --> 00:59:03,840
Speaker 1: I had There was a quick extension of the econometric

959
00:59:03,880 --> 00:59:05,919
Speaker 1: of paper that I thought to write. I sent it out,

960
00:59:05,960 --> 00:59:09,720
Speaker 1: It got accepted quickly. I wrote three more papers the

961
00:59:09,760 --> 00:59:12,919
Speaker 1: next summer. I sent them out for review. They got

962
00:59:12,920 --> 00:59:16,720
Speaker 1: accepted in quick succession by three of the top journals

963
00:59:16,760 --> 00:59:20,520
Speaker 1: and economics. That never happens. You know, all my other

964
00:59:20,560 --> 00:59:23,880
Speaker 1: papers since then have gotten rejected at least once, many

965
00:59:23,840 --> 00:59:27,240
Speaker 1: of them four times, and when they accepted it's after

966
00:59:27,320 --> 00:59:31,160
Speaker 1: a year's delay or three rounds of revisions. So so,

967
00:59:31,200 --> 00:59:32,880
Speaker 1: if he didn't ask you to do this paper, you

968
00:59:32,880 --> 00:59:35,600
Speaker 1: wouldn't have written it. If it wasn't canceled, you wouldn't

969
00:59:35,640 --> 00:59:38,240
Speaker 1: have submitted it. And if none of these sort of

970
00:59:38,400 --> 00:59:42,240
Speaker 1: random things in the car that really ended up getting

971
00:59:42,240 --> 00:59:46,800
Speaker 1: you tenure at Cornell, Yeah, which was so far and

972
00:59:46,880 --> 00:59:50,800
Speaker 1: away a better outcome for me professionally than what would

973
00:59:50,840 --> 00:59:53,560
Speaker 1: have happened, which I also know a little bit about.

974
00:59:54,560 --> 00:59:58,480
Speaker 1: I would have had a very different life except for

975
00:59:58,560 --> 01:00:02,280
Speaker 1: that string of fortunate events. So so the other person

976
01:00:02,400 --> 01:00:06,120
Speaker 1: outside of um Gramleck is a person who wrote a

977
01:00:06,120 --> 01:00:10,920
Speaker 1: book that started me down a path into behavioral economics,

978
01:00:11,000 --> 01:00:14,680
Speaker 1: which is Tom Gilgovich who wrote How We Know It

979
01:00:14,720 --> 01:00:17,960
Speaker 1: Isn't So, which I I found. I don't even remember

980
01:00:18,000 --> 01:00:20,800
Speaker 1: how I found it. Maybe a friend gave it to

981
01:00:20,880 --> 01:00:24,240
Speaker 1: me way back when. And it's it's not a lay

982
01:00:24,240 --> 01:00:27,720
Speaker 1: person book. It's a it's really a little more detailed

983
01:00:27,920 --> 01:00:31,640
Speaker 1: academic book. But it makes clear that the way we

984
01:00:31,800 --> 01:00:35,880
Speaker 1: perceive our own cognition is wildly wrong, and that we're

985
01:00:35,920 --> 01:00:39,280
Speaker 1: really just a series of errors waiting to happen. Um.

986
01:00:39,320 --> 01:00:41,920
Speaker 1: And you've you, I believe in. I don't remember which

987
01:00:41,960 --> 01:00:44,920
Speaker 1: book it was you referenced some of Yeah. Tom Gilovich

988
01:00:45,000 --> 01:00:47,680
Speaker 1: is in fact a very close friend. We've been collaborators

989
01:00:47,720 --> 01:00:51,960
Speaker 1: for decades. Uh. He saved my life once. Uh really

990
01:00:52,040 --> 01:00:55,560
Speaker 1: there was literally literally Yeah. No, he and I played

991
01:00:55,560 --> 01:00:59,680
Speaker 1: tennis regularly. Oh, you mentioned we were playing tennis one

992
01:00:59,680 --> 01:01:04,320
Speaker 1: sat morning. In the second set, we were seated on

993
01:01:04,360 --> 01:01:07,480
Speaker 1: the bench during a changeover. He tells me this, I

994
01:01:07,480 --> 01:01:10,000
Speaker 1: don't have any recollection, he says. The next scene, knows

995
01:01:10,120 --> 01:01:13,880
Speaker 1: I'm lying motionless on the court, no breath, no pulse.

996
01:01:15,000 --> 01:01:19,680
Speaker 1: He kneels to investigate, realizes this looks uh not quite right,

997
01:01:20,360 --> 01:01:23,120
Speaker 1: and he yells out for somebody to call nine one one,

998
01:01:23,240 --> 01:01:25,640
Speaker 1: and then he flips me over onto my back and

999
01:01:25,680 --> 01:01:28,040
Speaker 1: starts pounding on my chest. You know, you've seen that

1000
01:01:28,960 --> 01:01:31,320
Speaker 1: many times in movies, so have I. So had He'd

1001
01:01:31,400 --> 01:01:33,480
Speaker 1: never been trained to do it, but just started pounding

1002
01:01:33,480 --> 01:01:37,040
Speaker 1: on your chest. He said. Uh. One of his Israeli

1003
01:01:37,120 --> 01:01:40,400
Speaker 1: graduate students who had been in the military had told

1004
01:01:40,440 --> 01:01:43,680
Speaker 1: him once that if you don't break the victim's breastbone,

1005
01:01:43,760 --> 01:01:47,480
Speaker 1: you weren't trying hard enough. So he he No, he

1006
01:01:47,520 --> 01:01:50,840
Speaker 1: didn't break break my breastbone. I don't think they never

1007
01:01:50,880 --> 01:01:53,560
Speaker 1: told me if he did. But he got a cough

1008
01:01:53,600 --> 01:01:56,360
Speaker 1: out of me after what seemed like forever, but then

1009
01:01:57,000 --> 01:02:00,520
Speaker 1: I went dead again, and he was about to give

1010
01:02:00,600 --> 01:02:03,560
Speaker 1: up hope when in through the doors of the tennis

1011
01:02:03,600 --> 01:02:07,160
Speaker 1: facility comes in the MT team. They cut my shirt off,

1012
01:02:07,200 --> 01:02:10,360
Speaker 1: they put the paddles on me, They rushed me to

1013
01:02:10,440 --> 01:02:12,960
Speaker 1: the hospital. They put me on a helicopter and fly

1014
01:02:13,120 --> 01:02:16,120
Speaker 1: me to a bigger hospital in Pennsylvania. They put me

1015
01:02:16,160 --> 01:02:21,040
Speaker 1: on ice overnight. Three days later, I'm beginning to uh

1016
01:02:21,320 --> 01:02:24,080
Speaker 1: come out of the fog, and I'm told by the

1017
01:02:24,560 --> 01:02:28,720
Speaker 1: medical people in Pennsylvania that I suffered sudden cardiac death

1018
01:02:29,280 --> 01:02:32,880
Speaker 1: just like that, not a heart attack. I died on

1019
01:02:32,920 --> 01:02:37,120
Speaker 1: the tennis court. Of the people who who don't get

1020
01:02:37,120 --> 01:02:42,480
Speaker 1: im media attention never revive the two percent, they told me,

1021
01:02:42,640 --> 01:02:44,640
Speaker 1: the two percent who do make it, you don't want

1022
01:02:44,640 --> 01:02:47,560
Speaker 1: to see them. They're they're all kind of messed up,

1023
01:02:48,000 --> 01:02:54,840
Speaker 1: typically long standing. But if you're without that, lots lots

1024
01:02:54,880 --> 01:02:59,200
Speaker 1: of problems for you. And and uh, for some reason,

1025
01:02:59,440 --> 01:03:02,760
Speaker 1: I escaped all that. And the reason had to have

1026
01:03:02,840 --> 01:03:04,960
Speaker 1: been that the ambulance came as quickly as it did.

1027
01:03:05,320 --> 01:03:07,640
Speaker 1: But that was the mystery. How did an ambulance come

1028
01:03:08,560 --> 01:03:10,880
Speaker 1: so fast when we were six miles out of town

1029
01:03:10,960 --> 01:03:13,640
Speaker 1: and the ambulances are dispatched away from the other side

1030
01:03:13,640 --> 01:03:17,080
Speaker 1: of Itha. And what I learned was that there had

1031
01:03:17,120 --> 01:03:20,480
Speaker 1: been two auto accidents close to the tennis center that

1032
01:03:20,520 --> 01:03:23,680
Speaker 1: had occurred before I collapsed. Two ambulances are well on

1033
01:03:23,720 --> 01:03:27,040
Speaker 1: their way to those accidents. One of them. The injuries

1034
01:03:27,080 --> 01:03:29,240
Speaker 1: aren't serious, so when the call comes to that one,

1035
01:03:29,480 --> 01:03:32,240
Speaker 1: they say, divert to the tennis center. We got something

1036
01:03:32,280 --> 01:03:34,680
Speaker 1: more important for you. And they were there. And except

1037
01:03:34,720 --> 01:03:38,200
Speaker 1: for that, I'm I'm a dead man. So not a coincidence.

1038
01:03:38,240 --> 01:03:41,280
Speaker 1: You you write a book on the road right about

1039
01:03:41,320 --> 01:03:44,200
Speaker 1: what you know that's what they tell authors, And I

1040
01:03:44,240 --> 01:03:47,000
Speaker 1: tell people I'm probably the luckiest person they know. Maybe

1041
01:03:47,000 --> 01:03:49,680
Speaker 1: that's not true, but I'm certainly one of the luckiest.

1042
01:03:49,720 --> 01:03:53,680
Speaker 1: That's pretty fascinating. Um, so let's talk about other books.

1043
01:03:53,680 --> 01:03:56,800
Speaker 1: What what are some of your favorite books that perhaps

1044
01:03:56,840 --> 01:04:01,480
Speaker 1: you haven't written, you have not written. Uh. Tom Shelling's

1045
01:04:01,520 --> 01:04:04,360
Speaker 1: book US, in which I didn't mention the title of

1046
01:04:05,200 --> 01:04:11,440
Speaker 1: is Micromotives and macro Behavior. Absolutely wonderful book. If you

1047
01:04:11,520 --> 01:04:16,600
Speaker 1: liked grow Behavior all right, if you liked Tom Gilovich's book,

1048
01:04:16,720 --> 01:04:19,880
Speaker 1: it's it's sort of aimed at that same slice of

1049
01:04:19,880 --> 01:04:24,840
Speaker 1: the market for the intelligent, curious person. I mentioned Duncan

1050
01:04:24,880 --> 01:04:28,200
Speaker 1: Watts's book. I think I actually have that at home.

1051
01:04:28,320 --> 01:04:31,960
Speaker 1: That is a fabulous book. Is the Mona Lisa famous

1052
01:04:32,040 --> 01:04:36,240
Speaker 1: because it's a great painting, No, says Duncan. He says

1053
01:04:36,480 --> 01:04:39,960
Speaker 1: it's famous because it's famous. It's famous because it was stolen.

1054
01:04:40,120 --> 01:04:42,760
Speaker 1: Prior to that, nobody really gave a damn about it

1055
01:04:42,880 --> 01:04:45,840
Speaker 1: until nineteen eleven. Then it was stolen from the Louver.

1056
01:04:46,960 --> 01:04:48,880
Speaker 1: Not a big picture, by the way, everybody thinks it's

1057
01:04:48,960 --> 01:04:50,800
Speaker 1: John It's no big deal when you see it. At

1058
01:04:50,840 --> 01:04:53,640
Speaker 1: least that was my my reaction and his two. And

1059
01:04:53,680 --> 01:04:59,080
Speaker 1: so he saw that there were two Leonardo canvases in

1060
01:04:59,120 --> 01:05:02,800
Speaker 1: the very next gal Nobody seemed to be crowding around

1061
01:05:03,040 --> 01:05:05,640
Speaker 1: to look at them, but there were three people elbowing

1062
01:05:05,680 --> 01:05:07,720
Speaker 1: one the other side to see the Mona Lisa. And

1063
01:05:07,800 --> 01:05:09,400
Speaker 1: so he did a little digging and he found that

1064
01:05:09,840 --> 01:05:13,240
Speaker 1: until nineteen eleven, nobody cared about the Mona Lisa. Then

1065
01:05:13,240 --> 01:05:15,920
Speaker 1: it got stolen. Took two years for them to resolve

1066
01:05:15,960 --> 01:05:20,640
Speaker 1: the crime. They arrested the Italian custodian who stole it.

1067
01:05:20,760 --> 01:05:25,320
Speaker 1: Then again, the paintings splashed across the newspapers all around

1068
01:05:25,360 --> 01:05:27,640
Speaker 1: the world, first time that had ever happened. And so

1069
01:05:27,680 --> 01:05:32,320
Speaker 1: now it's a symbol of Western culture, quite quite amazing,

1070
01:05:32,480 --> 01:05:34,840
Speaker 1: pure chance that it got to be that. Uh and

1071
01:05:34,920 --> 01:05:38,960
Speaker 1: what was the name of Duncan's book? Everything is obvious

1072
01:05:39,040 --> 01:05:43,240
Speaker 1: and then there's an asterisk, and in parenthesis beneath its asterisk.

1073
01:05:43,520 --> 01:05:47,320
Speaker 1: Once you know the answer, I'm gonna have to take

1074
01:05:47,320 --> 01:05:49,520
Speaker 1: a look. I'm pretty sure that's sitting in my queue

1075
01:05:50,320 --> 01:05:52,880
Speaker 1: waiting to be to be read. So so let me

1076
01:05:52,920 --> 01:05:56,000
Speaker 1: get to my last two favorite questions I asked all

1077
01:05:56,080 --> 01:06:00,360
Speaker 1: my guests. So a millennial or a recent college ad

1078
01:06:00,400 --> 01:06:02,480
Speaker 1: comes up to you and says, I'm interested in a

1079
01:06:02,640 --> 01:06:07,960
Speaker 1: career in economics. What sort of advice do you give them?

1080
01:06:08,080 --> 01:06:11,800
Speaker 1: I tell people to try to think of a time

1081
01:06:11,960 --> 01:06:16,520
Speaker 1: when they felt completely immersed in some activity, that the

1082
01:06:16,560 --> 01:06:20,720
Speaker 1: hours went by without them being conscious of time flying

1083
01:06:21,400 --> 01:06:27,120
Speaker 1: by it all, and to try and find a career

1084
01:06:27,120 --> 01:06:30,240
Speaker 1: where you would be doing that activity much of the time.

1085
01:06:31,280 --> 01:06:34,920
Speaker 1: If you if you can find something that you can

1086
01:06:34,960 --> 01:06:40,000
Speaker 1: engage with at that level, you will become an expert

1087
01:06:40,040 --> 01:06:42,880
Speaker 1: at it because you'll care so much about it. Won't

1088
01:06:42,880 --> 01:06:45,360
Speaker 1: seem like you're working hard to become an expert. It'll

1089
01:06:45,400 --> 01:06:49,920
Speaker 1: just be an organic process. And if you want to

1090
01:06:50,480 --> 01:06:56,000
Speaker 1: be a success, I think becoming developing deep expertise at

1091
01:06:56,120 --> 01:07:00,720
Speaker 1: something is the route to take In today's climate. We

1092
01:07:00,720 --> 01:07:03,720
Speaker 1: were talking about winner take all markets. You know, being

1093
01:07:04,360 --> 01:07:08,240
Speaker 1: the third best person that something isn't gonna do much

1094
01:07:08,320 --> 01:07:10,800
Speaker 1: for you. If you're the best at something, though, even

1095
01:07:10,880 --> 01:07:13,760
Speaker 1: it's if it's something that not that many people care about,

1096
01:07:13,760 --> 01:07:17,240
Speaker 1: there's often a lucrative niche for you. There's very least

1097
01:07:17,320 --> 01:07:19,440
Speaker 1: you're gonna be doing something you like that. There's a

1098
01:07:19,480 --> 01:07:23,960
Speaker 1: number of studies that talk about having an expertise, having

1099
01:07:24,000 --> 01:07:27,640
Speaker 1: a sense of control and actually being able to affect

1100
01:07:27,680 --> 01:07:32,120
Speaker 1: the outcome that that leads to workers satisfaction and and

1101
01:07:32,200 --> 01:07:37,760
Speaker 1: so you're giving that exact advice um to millennials, exact advice,

1102
01:07:37,880 --> 01:07:43,840
Speaker 1: you know. Charlie mungerh Warren, Buffett's second in command, said

1103
01:07:43,880 --> 01:07:46,280
Speaker 1: that if if you want to get what you want,

1104
01:07:46,560 --> 01:07:49,360
Speaker 1: a good strategy is to try to deserve what you want.

1105
01:07:49,960 --> 01:07:52,960
Speaker 1: Makes sense, and and getting really good at something that's

1106
01:07:53,040 --> 01:07:55,520
Speaker 1: that's how you most likely to get what you want.

1107
01:07:55,680 --> 01:07:59,560
Speaker 1: My final question, what do you know today about skill

1108
01:07:59,680 --> 01:08:04,160
Speaker 1: and about income inequality, about economics that you wish you

1109
01:08:04,320 --> 01:08:07,959
Speaker 1: understood better in the beginning of your career twenty plus

1110
01:08:08,040 --> 01:08:13,280
Speaker 1: years ago. You know, most people, as I say in

1111
01:08:13,320 --> 01:08:16,360
Speaker 1: the book, tend to overlook the role of luck in

1112
01:08:16,400 --> 01:08:21,720
Speaker 1: their lives. That hasn't been true of me. Not so

1113
01:08:21,800 --> 01:08:26,080
Speaker 1: much because I think I'm more observant or or perspicacious

1114
01:08:26,160 --> 01:08:28,360
Speaker 1: than the typical person. I think luck has had a

1115
01:08:28,439 --> 01:08:31,880
Speaker 1: much more obvious effect in my life. I would not

1116
01:08:32,040 --> 01:08:35,880
Speaker 1: advise anybody to organize his life the way I've done.

1117
01:08:35,920 --> 01:08:39,599
Speaker 1: You know, I think I've stumbled into a career that's

1118
01:08:39,600 --> 01:08:44,040
Speaker 1: been in so many ways just the right career for myself.

1119
01:08:44,600 --> 01:08:49,840
Speaker 1: I think if if you're more systematic about it and

1120
01:08:49,840 --> 01:08:53,240
Speaker 1: and today, I probably wouldn't have succeeded. I think the

1121
01:08:53,280 --> 01:08:55,920
Speaker 1: doors start closing at younger ages. Now you have to

1122
01:08:55,960 --> 01:09:00,160
Speaker 1: be I have credentials, solid line even to get into

1123
01:09:00,200 --> 01:09:02,519
Speaker 1: a good school. Now. It wasn't so much true when

1124
01:09:02,560 --> 01:09:05,559
Speaker 1: I was. But I think, you know, finding something that

1125
01:09:05,600 --> 01:09:09,559
Speaker 1: you you like and you can get lost in would

1126
01:09:09,600 --> 01:09:12,800
Speaker 1: be the same advice I'd give to somebody almost at

1127
01:09:12,840 --> 01:09:14,800
Speaker 1: any age. So if you're if you're a parent, you've

1128
01:09:14,800 --> 01:09:18,160
Speaker 1: got kids, uh, you know, kids don't like everything that

1129
01:09:18,240 --> 01:09:24,080
Speaker 1: they do, uh, and their reactions to the various activities

1130
01:09:24,080 --> 01:09:27,559
Speaker 1: that you urge them to try or instructive, So pay attention.

1131
01:09:28,200 --> 01:09:31,240
Speaker 1: Do they love something? You know, open some doors and

1132
01:09:31,280 --> 01:09:33,800
Speaker 1: see if you can get them more deeply involved in

1133
01:09:33,840 --> 01:09:36,880
Speaker 1: that thing that they love. Thanks Bob, this has been

1134
01:09:37,240 --> 01:09:40,720
Speaker 1: absolutely fascinating, and thank you for being so generous with

1135
01:09:40,840 --> 01:09:43,680
Speaker 1: your time. Thank you Berry. It was just an absolute

1136
01:09:43,720 --> 01:09:46,200
Speaker 1: pleasure for me to get to come down. If you've

1137
01:09:46,320 --> 01:09:49,000
Speaker 1: enjoyed this conversation, be sure and look up an inch

1138
01:09:49,080 --> 01:09:51,479
Speaker 1: or down an inch on Apple iTunes and you can

1139
01:09:51,560 --> 01:09:55,960
Speaker 1: see the other ninety or so such chats that we've had.

1140
01:09:56,920 --> 01:09:59,920
Speaker 1: I would be remiss if I omitted Taylor Rigs for

1141
01:10:00,120 --> 01:10:05,040
Speaker 1: helping to organize each of these conversations, and Charlie Vollmer,

1142
01:10:05,080 --> 01:10:09,479
Speaker 1: who is our chief engineer here. Uh, you've been listening

1143
01:10:09,520 --> 01:10:12,080
Speaker 1: to Masters in Business on Bloomberg Radio