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Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.

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Speaker 1: So I have a funny story about my guest this week. UM,

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Speaker 1: you probably know who he is. His name is Gary Shilling.

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Speaker 1: He's an economist. He's all over television and and print

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Speaker 1: and everything. He's he's his background. He essentially built the

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Speaker 1: economics department at Merrill Lynch. He was Meryll's first chief economist. Um.

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Speaker 1: And we we get into a few stories about that,

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Speaker 1: but I have I have a really amusing story that

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Speaker 1: we just didn't get to um in our conversation. So

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Speaker 1: I have at various times spoken at different events and

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Speaker 1: and this was an event that was down in the Caribbean. Um.

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Speaker 1: And they have a lineup of different people, this economist,

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Speaker 1: that market strategist, and you sing for your supper. You

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Speaker 1: you speak for an hour or two and then you

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Speaker 1: get to play the Caribbean for a few days. So

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Speaker 1: it's a good deal for everybody. And by coincidence, I'm

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Speaker 1: on a catamaran with my wife and Gary Shilling and

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Speaker 1: Gary's wife, and uh we're going out to do a

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Speaker 1: little diving, a little snorkeling. UM. I want to say

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Speaker 1: it was Anguila or Antigua, and I never remember which

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Speaker 1: is which, but you know, at a certain point, all

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Speaker 1: those islands they're beautiful, that's sunny, the water is gorgeous,

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Speaker 1: and it's hard to tell where you are when you're

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Speaker 1: on a boat for a week or so. So we

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Speaker 1: go out to the dive location and it's a bright

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Speaker 1: sunny day and everything is marked underwater. It's twenty feet,

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Speaker 1: it's thirty feet. It's crystal clear waters. And I have

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Speaker 1: a tendency to to even win snorkeling, to like to

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Speaker 1: try and dive deep and and look at stuff. Um

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Speaker 1: and so all of a sudden storm comes in out

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Speaker 1: of nowhere. We come up from underwater and it's absolute

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Speaker 1: from bright blue size guys to totally gray. Can't see anything,

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Speaker 1: can't see more than ten ft. The boat, which was

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Speaker 1: fifty yards off in that direction, is gone. And I'm

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Speaker 1: a pretty good swimmer, and my wife is starting to panic.

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Speaker 1: What are we gonna do? We're stuck here, and I'm like, well,

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Speaker 1: we have two choices. It's the Carebbean. These storms blew

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Speaker 1: in and out in thirty seconds. We could just tread

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Speaker 1: water here and let it pass, or I'm pretty sure

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Speaker 1: the boat is that way. I have good sense. I

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Speaker 1: have a really good sense direction. And I said, um,

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Speaker 1: look see where the see where these markings are on

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Speaker 1: the floor, and where the entrance to this dive side

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Speaker 1: is straight line back that that's where the boat is.

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Speaker 1: So we could wait here for five minutes, wait for

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Speaker 1: this to pass. We could go back to the boat.

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Speaker 1: She goes, take us back to the boat. Okay, So

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Speaker 1: she grabs onto my waist ban and I swim back

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Speaker 1: to the boat um or at least where I think

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Speaker 1: the boat is, and we're swimming for about seven minutes

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Speaker 1: and lo and behold, oh look there's the outline of

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Speaker 1: a sail. Oh that's the cameraman. There's a boat. And

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Speaker 1: of course by the time we get to the camemar Ran,

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Speaker 1: the skies are clearing. But meanwhile I assumed it was

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Speaker 1: just myself and my wife swimming back to the boat.

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Speaker 1: We look back, there's a line of forty people following us,

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Speaker 1: including Gary Shilling and his wife. It was a little

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Speaker 1: nerve racking for people who either aren't good swimmers or

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Speaker 1: tends a panic a little bit. And so we all

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Speaker 1: get back on the camemar Ran and all of us

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Speaker 1: uh the cat then takes us to a cove with

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Speaker 1: the water is three ft deep, and we all get

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Speaker 1: ripped roaring lye drunk and spent a few hours stumbling

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Speaker 1: along the beach. So that was the first time I

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Speaker 1: spent any time with h Gary Shilling. We've since remained

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Speaker 1: friendly and UM, I've always enjoyed him and his wife.

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Speaker 1: They're they're fascinating, lovely people and every year he sends

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Speaker 1: a batch of honey uh to friends and family that

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Speaker 1: he raises himself. We spent a lot of time talking

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Speaker 1: about beak keeping, which is pretty hilarious conversation. Um, without

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Speaker 1: further ado, here is my chat with economist Gary Shilling.

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Speaker 1: This is Master's in Business with Barry Ridholds on Bloomberg Radio.

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Speaker 1: This week on Masters in Business on Bloomberg Radio, my

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Speaker 1: special guest is Gary Shilling, an economist and proprietor of

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Speaker 1: the a Gary Shilling Newsletter and Economic Forecast. A little

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Speaker 1: background about Gary got a degree in physics cum Laudy

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Speaker 1: Magnicum Loudy from Amherst College before getting a master's and

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Speaker 1: a pH d in economics at Stanford. Ended up on

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Speaker 1: the research staff of the Federal Reserve Bank of San Francisco,

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Speaker 1: before going on to set up the economics department at

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Speaker 1: a little shop called Merrill Lynch, where he served as

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Speaker 1: the firm's first chief economist. Wow, that's an amazing h

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Speaker 1: piece of history. Author of the book The Age of

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Speaker 1: the Leveraging twice ranked as Wall Street's top economist according

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Speaker 1: to Institutional Investor, and a legendary beekeeper, Gary, Welcome to Bloomberg.

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Speaker 1: Very glad to be with you. So Gary and I

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Speaker 1: know each other for quite a few years. We'll we'll

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Speaker 1: talk about some of our adventures together. But let's start

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Speaker 1: with the beginning. So physics, right, and I keep talking

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Speaker 1: to people on Wall Street with a physics background. How

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Speaker 1: do you go from physics? Would from that to both

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Speaker 1: a master's and a doctor in an economics at Stanford? Well,

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Speaker 1: I like the discipline of physical sciences, and uh, there

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Speaker 1: is a there is a yearning for closure own things.

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Speaker 1: You you want to fit things together. It isn't just

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Speaker 1: kind of a flash here, a flash there. You want

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Speaker 1: to see how things come out in terms of a

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Speaker 1: total and take some variables, put them into a formula.

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Speaker 1: And it's that's a little oversimplified, but but the whole

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Speaker 1: idea is that there is a there's a discipline to

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Speaker 1: any any uh natural science, physics, chemistry, math, all these things. Uh,

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Speaker 1: they don't have quite the fuzziness that economics has. Now

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Speaker 1: you get into economics, and you know, economic forecasting is

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Speaker 1: an art, it's not a science. But that discipline, I

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Speaker 1: think it's important because it kind of keeps you on

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Speaker 1: this straight and narrow But anyway, I started off there

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Speaker 1: and then my senior year I had an attack of

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Speaker 1: common sense and decided I wasn't cut out to be

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Speaker 1: a research physicist. So I had a similar epiphany in

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Speaker 1: my senior years, and so I decided to move on.

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Speaker 1: And uh, you know, it's one of these one of

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Speaker 1: these great developments where um, I was thinking about going

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Speaker 1: to graduate school in economics, and I talked to amateurs

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Speaker 1: as a small school about a thousand students at the time,

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Speaker 1: and talked to the president of the college, and he

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Speaker 1: suggested business school and a couple of other people, and

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Speaker 1: I talked to the head of the economics department. And

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Speaker 1: I had happened to have when I had an elementary

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Speaker 1: economics course and the sections were taught not by graduate

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Speaker 1: students because there were none, but by the faculty and

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Speaker 1: and uh we talked about it. He suggested a couple

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Speaker 1: of places and then he said, what's your academic record?

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Speaker 1: And I told him. He said, oh, you can get

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Speaker 1: anywhere you want to go. Where do you want to go?

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Speaker 1: And I said, well, I grew up in Ohio, I'm

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Speaker 1: here in Massachusetts. I've been an allergic sense birth. I'd

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Speaker 1: like to get into a decent climate. And he said, well,

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Speaker 1: how about Stanford? And I said the climate was fine,

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Speaker 1: how about the how about the economics department always one

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Speaker 1: of the top two or three in the country. So

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Speaker 1: he called up, set it up. I got a I

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Speaker 1: got a teaching assistant ship, a resident assistant ship. I

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Speaker 1: never filled out an application. It was one of these

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Speaker 1: things where somebody really did something for it for me.

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Speaker 1: We all have that going out and went out of

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Speaker 1: his way. And well, as I say, the rest of history,

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Speaker 1: that's fantastic. So from physics, from physics to Stanford, you

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Speaker 1: end up working in standard oil now ex on mobile correct?

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Speaker 1: How did that come about? And how did you go

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Speaker 1: from there to finance? Well it was interesting at that time. Uh,

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Speaker 1: when I came out of Stanford there, Uh, my wife

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Speaker 1: and I were would like to have stayed on the

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Speaker 1: West Coast. I met her. She was a physiology major

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Speaker 1: at Stanford and UH graduate school and uh, but there

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Speaker 1: are only three places of PhD economists could work in

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Speaker 1: the Bay Area. One was that the San Francisco Fed

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Speaker 1: and I spent a summer there and that was a

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Speaker 1: pretty laid back place. The second was Bank of America

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Speaker 1: when it was Bank of America California, UM the g

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Speaker 1: and Needy uh or origination and UH they sponsored my

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Speaker 1: my PhD research and that wasn't really quite active enough.

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Speaker 1: And the third one was Stanford Research Institute, and they

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Speaker 1: didn't pay anything. So I told my wife there are

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Speaker 1: two things I'd never never do. One is work in

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Speaker 1: New York, and he was kidding to work. Well, that

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Speaker 1: was the beginning of a great forecasting career, because I

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Speaker 1: took a job as an economist with Standard Alone New

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Speaker 1: Jersey now ax On Mobile. As you point out, Berry

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Speaker 1: and Uh, well the aggressive story as we lived in

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Speaker 1: a New York apartment for two years, moved to the suburbs,

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Speaker 1: commuter for twenty five years, but in nine nine I

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Speaker 1: moved our shop out to suburban New Jersey. And it's

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Speaker 1: a mere coincidence. It's one point four miles from our

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Speaker 1: house in Short Hills, New Jersey, just just by coincidence.

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Speaker 1: So let's talk a little bit about your time on

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Speaker 1: Wall Street. You not only were the first economist chief

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Speaker 1: economists from Merrill Lynch, you actually set up their entire economics. Yeah.

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Speaker 1: That that's an interesting story because at that point the

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Speaker 1: bond houses on Wall Street had economists. Henry Coffin was

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Speaker 1: at Solomon Brothers, al Osian Art first Boston, Lynn Santao

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Speaker 1: at Aubrey G. Lampson. Uh. But Merrill was known as

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Speaker 1: a But I was. I think I was the first

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Speaker 1: economist at a stock house Merrill Lynch, And at that

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Speaker 1: point economists were relatively new. I can remember Bill Freud,

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Speaker 1: who was the economist for New York Stock Exchange, remains

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Speaker 1: a good friend. Uh. And he would have what he

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Speaker 1: called point Freud's friends. All the economis from Wall Street

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Speaker 1: over for monthly lunches at the New York Stock Exchange,

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Speaker 1: and we all fit comfortably in one of those wonderful

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Speaker 1: ornate rooms. There couldn't have been more than twenty of us. Now,

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Speaker 1: how many dozens hundreds of economists are there in the

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Speaker 1: Wall Street makes a lot of sense. Perhaps it it

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Speaker 1: is part of the reason we obsessed so much on

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Speaker 1: the day to day economic data that seems to come out.

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Speaker 1: I recall less of an emphasis on that ten twenty

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Speaker 1: years ago then we see currently well, and of course

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Speaker 1: there's a difference to the data then. I mean, at

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Speaker 1: that point every economist would have a couple of researcher

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Speaker 1: assist since you get the data by mail, they laboriously

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Speaker 1: draw these charts. There were there were, you know, hardly

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Speaker 1: any computers. There was no there were no copy machines.

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Speaker 1: I mean, it was and of course that made you

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Speaker 1: think a lot more. You're listening to Masters in Business

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Speaker 1: on Bloomberg Radio. My guest this week is Gary Shilling,

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Speaker 1: an economist and essentially physicist who produces his own economic

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Speaker 1: research and forecasts. We were discussing earlier that you had

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Speaker 1: helped set up the research department of Merrill Lynch and

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Speaker 1: you were their chief economist. You also their first chief economists.

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Speaker 1: You also have the distinction of being the only person

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Speaker 1: to be fired not once, but twice by Donald Reagan

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Speaker 1: from Merrill Lynch. Tell us how that came about. I

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Speaker 1: went there in nineteen sixty seven and there had not

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Speaker 1: been a recession in the US really since nineteen sixty six. One.

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Speaker 1: Uh Now, I forecast recession for six seventy, which did occur.

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Speaker 1: But it was so different from Merrill Lynch because Mary

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Speaker 1: Lynch at that point it was by listed stocks only.

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Speaker 1: That was the whole rationale of the firm, and the

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Speaker 1: idea of a recession was very upsetting. So Don Reagan,

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Speaker 1: who was running the place and I had a difference

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Speaker 1: of opinion. Obviously he won. I took my entire staff left,

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Speaker 1: ended up at white Well, another Wall Street house with

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Speaker 1: no idea. In nineteen seventy eight, Mary Lynch would buy

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Speaker 1: why Well. So the story in the street, which is

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Speaker 1: literally true, was Chilling is the only guy fired twice

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Speaker 1: by Don Reagan. So we come back to you, come

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Speaker 1: back to Maryland, they buy white Well. Yea. And how

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Speaker 1: does the second firing come about? I mean, now, the

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Speaker 1: recessions that was automatic. As a matter of fact, I

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Speaker 1: found out later that that when when Reagan, the first

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Speaker 1: meeting between Don Reagan and Paul Hallingby was head of

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Speaker 1: white Well, that that Reagan said, Uh, if we get together,

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Speaker 1: I want I want to know that there's one employee

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Speaker 1: of white Weld who will not be invited to join

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Speaker 1: the combined firm. So I was out from I was

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Speaker 1: out before I got in. So anyway, that was the

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Speaker 1: inducement to do what I really had in mind, which

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Speaker 1: was set up my own firm, own firm. So before

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Speaker 1: we go to that, I want to talk about life

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Speaker 1: at a big shop in the late sixties or seventies.

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Speaker 1: What was it like as a chief economist at Merrill

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Speaker 1: Lynch back in the day. It was it was a

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Speaker 1: lot of fun in in in many ways they had

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Speaker 1: a very good UH sales staff, particularly the institutional salesman.

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Speaker 1: These guys were hungry for input. I was very willing

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Speaker 1: to travel all over the world, not only the US,

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Speaker 1: but Europe and Japan and UH. And it was it

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Speaker 1: was great working for these guys. Of course they were

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Speaker 1: they would they would really get their money's worth. I

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Speaker 1: remember one one salesman Minneapolis where this guy had scheduled

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Speaker 1: meetings with institutions every hour on the hour throughout the day.

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Speaker 1: I went to the lunch meeting, UM and I get

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Speaker 1: I get my fork ready for the first bite of lunch,

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Speaker 1: and he says, well, Gary, tell us about the economy,

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Speaker 1: and so the UH, the the entree, comes and goes,

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Speaker 1: that goes, comes and goes, and we rushed you out

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Speaker 1: there to the next one. And I say, wait a minute,

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Speaker 1: I didn't get anything. He said, don't worry. I got

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Speaker 1: a sandwich. You can eat it on the elevator on

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Speaker 1: the way down. So they kept you hopping as a

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Speaker 1: as an adjunct institutional sales. So you leave Merril almost

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Speaker 1: the second time and set up your own shop. You

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Speaker 1: have your own models and your own forecasting set up

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Speaker 1: that you put together. Let's let's talk a little bit

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Speaker 1: about the economy and economic indicators and what goes into

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Speaker 1: your process. What do you think of the most important

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Speaker 1: economic indicators, what do you follow and think has the

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Speaker 1: most resonance. Well, let me say this very just just

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Speaker 1: going into this that, as I mentioned earlier, forecasting in

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Speaker 1: my view as an artist not a science. Now, I

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Speaker 1: was trained as as econometrician. When I got to Stanford,

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Speaker 1: I had had you know, if you're a physics major,

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Speaker 1: you're a math major two whether you want to be

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Speaker 1: or not. And I was working there under kenn Arrow,

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Speaker 1: Nobel Prize winner econometrician, and and I'd had only one

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Speaker 1: undergraduate economics course. So the the math side, the econometric

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Speaker 1: side was easy. The economic stuff I had to learn.

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Speaker 1: But I have found less and less interest in these

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Speaker 1: big models. They simply do not work. They blow up,

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Speaker 1: They produced nonsensical. Are they too complex or the You know,

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Speaker 1: that's a very good question, and I don't think anybody

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Speaker 1: has really ever completely answered that. But but but they

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Speaker 1: But the problem is you have to keep going in

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Speaker 1: and plugging in and by the time you get all through,

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Speaker 1: you and do it from from from scratch. But at

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Speaker 1: that time there was this hope that somehow you could

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Speaker 1: devise a model of the economy. It would be unsolid

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Speaker 1: by human hands. You put in the inputs and outcomes

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Speaker 1: the solution and that's all you need to know. So now, forecasting,

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Speaker 1: in my view, it's a whole combination of things, and

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Speaker 1: it really can't be quantified in any precise way. It's

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Speaker 1: certainly looking at various leading indicators. What's the federals, the

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Speaker 1: Federal Reserve doing or not doing? Uh, what's the state

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Speaker 1: of consumers? Right now? We think we're in this age

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Speaker 1: of de leveraging, working off access debt from the eighties

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Speaker 1: and nineties, and that you know, I put out this

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Speaker 1: book The Age of the leveraging in and I said,

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Speaker 1: I thought we were going to have two percent real

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Speaker 1: GDP growth, And of course the FED and most people said,

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Speaker 1: oh no, it's gonna pick up. Well, where are we

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Speaker 1: two point two percent since this recovery started in the

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Speaker 1: middle of O nine. But it's it's looking at it's

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Speaker 1: looking at history. It's Kentucky winding. It's it's a whole

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Speaker 1: most of the Yeah, what is Kentucky wind. That's that's

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Speaker 1: that's a that's a Midwestern term for hunches. Okay, Kentucky wind.

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Speaker 1: I like that. Well, that's that's when you're shooting. You know,

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Speaker 1: those guys were really sharp. They were, so you have

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Speaker 1: to you have to know the wind because the wind

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Speaker 1: pushes the bullet a little bit. Oh yeah, I left.

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Speaker 1: In fact, I talked to a friend of mine who

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Speaker 1: was a trained as a sniper, and I called him

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Speaker 1: up after I've seen this movie The you know, the

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Speaker 1: American Sniper, and I asked him about that and he

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Speaker 1: explained that that shot the guy made when he took

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Speaker 1: out the bad guy, said that was impossible because the

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Speaker 1: sandstorms and with the with the winds going in and

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Speaker 1: out of the buildings, it would it would cause the

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Speaker 1: bullet to drift. And even even with all the power

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Speaker 1: of that fifty caliber, fifty caliber rifle is still going

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Speaker 1: to get I have a T shirt I have to

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Speaker 1: dig up somewhere. A buddy gave me, who was a

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Speaker 1: marine sharpshooter, their logo. Their their tagline was why run,

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Speaker 1: You'll only die tired. These guys are serious, serious shooters,

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Speaker 1: and they calculate all that stuff, everything from from curvature

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Speaker 1: of the earth to wind drift. It's all, it's all

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Speaker 1: part of it. So let's hold off discussing the economy

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Speaker 1: itself to a later segment. Let's talk a little bit

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Speaker 1: about what goes into some of the these models and

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Speaker 1: what goes into some of the forecasts. What do you

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Speaker 1: look at So you mentioned interest rates, you mentioned consumer spending.

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Speaker 1: What other factors do you think are really significant? Well,

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Speaker 1: what's what's also very import important is what is the

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Speaker 1: consensus saying. Because I in order to in order to

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Speaker 1: push back against or to see where they're wrong. Yeah,

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Speaker 1: I have two basic principles has always been Eid and me.

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Speaker 1: One is that is that human nature changes very slowly

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Speaker 1: over time. So people react to summer circumstances in Simmler

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Speaker 1: ways and others. History is relevant. Now you still have

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Speaker 1: to find the right piece of history. Mark Twain says

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Speaker 1: history doesn't repeat, but it rhymes. And the second one

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Speaker 1: is that you don't add value by rehashing the cansensus.

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Speaker 1: It doesn't mean you are contrarian, and then you bucket consensus. Regardless,

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Speaker 1: where we agree, we pass over lightly. But where we

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Speaker 1: find something that's important is h is likely to happen

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Speaker 1: because you're judged by your forecasting record, Elemanly. And third

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Speaker 1: is not yet within the purview of the consensus. That's

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Speaker 1: where we really get interested. This week on Masters in Business,

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Speaker 1: I'm speaking with economist Gary shilling uh noted author and

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Speaker 1: forecaster um and physicists for that matter, as well as

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Speaker 1: an economist. Right out of school, you spend some time

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Speaker 1: in the San Francisco Federal Reserve Office. What was that

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Speaker 1: experience like, Well, it was really at that point point

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Speaker 1: deciding that at least at that at that time, it

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Speaker 1: was a pretty sleepy operation. So I spent a lot

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Speaker 1: of time trying to figure out what indicators led the

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Speaker 1: stock market. Well, that was that was a that was

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Speaker 1: a stupid exercise because you know, you think about it.

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Speaker 1: The stock market tends to lead almost anything else. If

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Speaker 1: you could find something that consistently the stock market, hey

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Speaker 1: you'd make a fortune. So that was but that was

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Speaker 1: a learning experience. That's what happens when you're young and naive.

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Speaker 1: So let me ask you a related question. Then, what

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Speaker 1: what indicators do people tend to obsess about that really

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Speaker 1: don't matter all that Well, it changes over time, but

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Speaker 1: right now the FED is is pretty much irrelevant in

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Speaker 1: my view. I mean, you're looking at a period where

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Speaker 1: where the FED has has pushed out all this money

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Speaker 1: quantitative easing, it hasn't done much good. Why is that? Well,

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Speaker 1: it's very simple. Uh, Basically, that money got into circulation

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Speaker 1: and people use it to high assets stocks. But stocks

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Speaker 1: are owned principally by high income people who don't adjust.

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Speaker 1: They're spending much in relation to their assets. You've got

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Speaker 1: three cars in the driveway, You're not going to put

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Speaker 1: a fourth one in there. So it never got beyond that,

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Speaker 1: and it didn't do much to help the basic economy.

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Speaker 1: It's the pushing on a string, the change in liquidity trap.

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Speaker 1: You can use all the technical terms, but basically the

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Speaker 1: FED IS in my view is it is pretty much irrelevant.

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Speaker 1: And also, of course in this slow growth period um

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Speaker 1: the FED keeps pushing off the day that they're going

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Speaker 1: to raise rates. They're now a lot more concerned with

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Speaker 1: the rest of the world. Their charter is is strictly domestic,

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Speaker 1: full employment and price stability, but they obviously now are

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Speaker 1: expanding that because the rest of the world is it

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Speaker 1: is a global economy. But I think all in all,

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Speaker 1: the fet is is pretty impetent right now. It doesn't

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Speaker 1: make much difference what they do. So what has been

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Speaker 1: the impact of zero interest rate policy? What's been the

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Speaker 1: impact of of QI on the overall economy? The effect

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Speaker 1: of QUI on the overall economy has been surprisingly little.

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Speaker 1: It has pushed up asset prices, but you haven't gotten

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Speaker 1: the modiplier effect. Normally, when the FED gives the banks

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Speaker 1: a dollar in reserves by lending and re lending and

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Speaker 1: what's called a fractional reserve system, they turn it into

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Speaker 1: seventy dollars of M two money seventy this point now

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Speaker 1: it's one point four to one, so barely moving, barely moving.

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Speaker 1: Uh And so it really hasn't hasn't had much, hasn't

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Speaker 1: had much effect. Uh So so the FED, the FED

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Speaker 1: is really really I think of pretty much on the sidelines.

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Speaker 1: And and the other thing about the quantitative easing is

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Speaker 1: that the effects of this lower interest rates is created

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Speaker 1: a lot of distortions, a lot of zeal for yield.

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Speaker 1: You see the rush into leveraged loans, into emerging market

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Speaker 1: debt and equity, into UH, into commodities and hedge funds

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Speaker 1: and so on. Pension funds is still UH still cling

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Speaker 1: to the idea of eight percent returns on their portfolios.

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Speaker 1: They say, we can't get that in conventional stocks and bonds.

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Speaker 1: We're gonna get it some way. So they move out

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Speaker 1: on the risk curve, and I think a lot of

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Speaker 1: them moved a lot further out on the risker than

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Speaker 1: they realized. I still don't understand where this a percent

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Speaker 1: number has come from. It seems like they've made that

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Speaker 1: number up and that they had to. They want a

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Speaker 1: percent look in order to maintain a tax to for

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Speaker 1: its status. It's five percent is what you have to

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Speaker 1: put out. So I don't know where this number. Two.

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Speaker 1: I think maybe very was five percent plus three percent

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Speaker 1: per inflation. But but but you don't have inflation, like

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Speaker 1: you know, you haven't got any inflation. But of course

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Speaker 1: the other thing is if they start lowering that number,

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Speaker 1: then they have to lower the other side the discounting

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Speaker 1: rate for the future liabilities, the punch and payments to

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Speaker 1: bring it back to the to the present value, and

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Speaker 1: that greatly increases, you know, the lower the interest rate

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Speaker 1: you're discounting with, that greatly expands there the current value

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Speaker 1: of those liabilities. So they get hit on both sides.

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Speaker 1: So there's a great reluctance to to face the reality,

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Speaker 1: to be honest about what they should really be expecting. Correct,

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Speaker 1: that's correct, that that's quite fat sinating. So let's talk

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Speaker 1: a little bit about what should have been done following

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Speaker 1: the financial crisis. What should Congress have done? What should

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Speaker 1: the fiddle reserve have done in response to you know,

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Speaker 1: the collapse and asset prices and and GDP and jobs. Well,

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Speaker 1: bailing out Wall Street probably wasn't necessary, because we very

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Speaker 1: well could have had a full blown financial melch. What

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Speaker 1: about bailing out the bond holders? When we when we

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Speaker 1: talk about these bailouts, a lot of bad bonds were

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Speaker 1: paid out right, and I think that that really has

428
00:23:32,960 --> 00:23:35,760
Speaker 1: prolonged the agony. I think they probably went too far

429
00:23:35,840 --> 00:23:40,000
Speaker 1: on this whole and they and they really have way

430
00:23:40,040 --> 00:23:42,440
Speaker 1: overrated themselves in terms of what they can do. Listen,

431
00:23:42,480 --> 00:23:45,360
Speaker 1: look at the look at the whole affection threeon dollar damage.

432
00:23:45,400 --> 00:23:48,560
Speaker 1: It's huge quantitative easing, and what do we get? Two

433
00:23:48,560 --> 00:23:51,280
Speaker 1: percent real GDP growth? I mean, it's telling you that

434
00:23:51,320 --> 00:23:54,200
Speaker 1: these forces of the leveraging are so great they're overpowering this.

435
00:23:54,800 --> 00:23:57,680
Speaker 1: And these guys who constantly think that policy is gonna

436
00:23:57,920 --> 00:24:00,240
Speaker 1: is gonna overwhelm everything else and they're gonna get the

437
00:24:00,280 --> 00:24:02,200
Speaker 1: results they want. I think they're in a dream world.

438
00:24:02,720 --> 00:24:06,239
Speaker 1: You're listening to Masters in Business on Bloomberg Radio. My

439
00:24:06,320 --> 00:24:11,560
Speaker 1: guest today is Dr Gary Shilling. He is an economist, researcher, forecaster.

440
00:24:12,240 --> 00:24:16,959
Speaker 1: Let's talk a little bit about the present economy. Where

441
00:24:17,000 --> 00:24:21,360
Speaker 1: are we in the economic cycle. I'm not sure we're

442
00:24:21,359 --> 00:24:24,480
Speaker 1: in a conventional economic cycle, and of course everybody wishes

443
00:24:24,600 --> 00:24:27,679
Speaker 1: wishes we were. Everybody yearns for the idea of of

444
00:24:27,680 --> 00:24:30,359
Speaker 1: a very systematic cycle. And you can see where are you.

445
00:24:30,400 --> 00:24:32,600
Speaker 1: I go out and I see presentations. A lot of

446
00:24:32,600 --> 00:24:34,920
Speaker 1: the big banks have their representatives out and they say, oh,

447
00:24:34,960 --> 00:24:37,680
Speaker 1: here's a circle, and here's where we are in that. Uh.

448
00:24:38,160 --> 00:24:39,680
Speaker 1: I don't think we're in that kind of I don't

449
00:24:39,720 --> 00:24:41,520
Speaker 1: think we're in that kind of world right now. We're

450
00:24:41,520 --> 00:24:45,679
Speaker 1: going through this massive deleveraging or we're seeing slow growth,

451
00:24:45,720 --> 00:24:49,879
Speaker 1: we're seeing commadi prices decline, We're seeing the strengthen the dollar. Uh,

452
00:24:50,040 --> 00:24:53,639
Speaker 1: we're seeing competitive evaluations against the dollar. Uh. There's a

453
00:24:53,720 --> 00:24:55,520
Speaker 1: lot of things going on here that I don't think

454
00:24:55,640 --> 00:24:58,879
Speaker 1: give you a very clear idea of a cycle per se.

455
00:24:59,240 --> 00:25:01,280
Speaker 1: And one thing I think it is, you know, there's

456
00:25:01,280 --> 00:25:04,399
Speaker 1: this yearning for nostalgia. We all have that and and

457
00:25:04,480 --> 00:25:07,520
Speaker 1: forecashers are just as subject to this as anybody else.

458
00:25:07,560 --> 00:25:09,600
Speaker 1: And you always have this feeling, oh boy, if we

459
00:25:09,640 --> 00:25:11,280
Speaker 1: could get back to the days when it was a

460
00:25:11,359 --> 00:25:13,560
Speaker 1: nice cycle and I know that it's four years and

461
00:25:13,640 --> 00:25:17,639
Speaker 1: if pounds, I'd be thrilled to death. Yeah. But you know,

462
00:25:17,840 --> 00:25:20,320
Speaker 1: and equal and people talk about equal, and hey, I've

463
00:25:20,359 --> 00:25:22,320
Speaker 1: been in this business a long time, very and equal.

464
00:25:22,400 --> 00:25:25,040
Speaker 1: Everything was something you simply pass through on the way

465
00:25:25,040 --> 00:25:27,200
Speaker 1: to going to access is on the top of the bottom.

466
00:25:28,280 --> 00:25:33,280
Speaker 1: Don't value you exist at very briefly swing and in retrospect,

467
00:25:33,440 --> 00:25:36,920
Speaker 1: that's right. So along those lines, let me ask you

468
00:25:37,119 --> 00:25:40,000
Speaker 1: a um, let me ask you a related question. I

469
00:25:40,040 --> 00:25:41,840
Speaker 1: know your historian, I know you look at a lot

470
00:25:41,880 --> 00:25:45,119
Speaker 1: of economic data from days gone by. Is there any

471
00:25:45,160 --> 00:25:52,840
Speaker 1: period in history that's comparable to what we're living through now? Um,

472
00:25:52,920 --> 00:25:56,400
Speaker 1: that's a good question at times when you're working off access.

473
00:25:56,520 --> 00:25:58,440
Speaker 1: Is I suppose you could say that to a certain

474
00:25:58,480 --> 00:26:00,960
Speaker 1: extent outs what was going on in the in the

475
00:26:01,040 --> 00:26:06,879
Speaker 1: nineteen thirties, but both Great Depression or even yeah, that

476
00:26:07,000 --> 00:26:08,879
Speaker 1: was a great depression in the aftermath, but there were

477
00:26:08,920 --> 00:26:10,720
Speaker 1: a lot of other things going on. There, a complete

478
00:26:10,720 --> 00:26:14,760
Speaker 1: shifting in policy from basically a lessay fair to too

479
00:26:14,840 --> 00:26:18,280
Speaker 1: much more government involvement in the economy. Whether that helped

480
00:26:18,359 --> 00:26:22,080
Speaker 1: or hurt. You know, historians argue about that. I don't

481
00:26:22,119 --> 00:26:23,879
Speaker 1: think there is a I don't think there is a

482
00:26:23,880 --> 00:26:26,119
Speaker 1: period right now where you can you can point to

483
00:26:26,200 --> 00:26:28,560
Speaker 1: it and say, let's follow the script that does that

484
00:26:28,560 --> 00:26:31,280
Speaker 1: does happen from time to time. And I'm always looking

485
00:26:31,280 --> 00:26:33,720
Speaker 1: for those periods because but this is unique. You're saying,

486
00:26:34,119 --> 00:26:36,159
Speaker 1: I don't see I don't see the relevance of that

487
00:26:36,280 --> 00:26:39,399
Speaker 1: right now. Can you say this is unprecedented? There's nothing well,

488
00:26:39,440 --> 00:26:42,399
Speaker 1: at least, and I think in in the experience of

489
00:26:42,560 --> 00:26:47,680
Speaker 1: modern economic forecasting, it is so um, I know you're

490
00:26:47,720 --> 00:26:50,200
Speaker 1: a big bond bull and have been for a long time.

491
00:26:51,080 --> 00:26:55,960
Speaker 1: Four years thirty four year bullmarket in bonds showing no

492
00:26:56,119 --> 00:26:59,920
Speaker 1: sign of ending. Where are we in this bond? Is

493
00:27:00,040 --> 00:27:04,679
Speaker 1: the bond bull market still alive? Ye? The yield on

494
00:27:04,720 --> 00:27:07,679
Speaker 1: the third year treasure was fifteen point to one percent.

495
00:27:07,800 --> 00:27:10,680
Speaker 1: And I said in writing, we're entering the bond rally

496
00:27:10,720 --> 00:27:14,000
Speaker 1: of a lifetime because I saw inflation unwinding and with

497
00:27:14,119 --> 00:27:17,800
Speaker 1: lower inflation that would push down yields, push up bound prices.

498
00:27:18,320 --> 00:27:20,479
Speaker 1: And and I think we're still in that. I mean

499
00:27:20,560 --> 00:27:24,840
Speaker 1: yields now obviously have dropped a tremendous, tremendous amount there

500
00:27:24,840 --> 00:27:27,359
Speaker 1: more like three little over under three percent for the

501
00:27:27,400 --> 00:27:29,560
Speaker 1: third year bond. I think we're gonna go to two

502
00:27:29,560 --> 00:27:32,360
Speaker 1: percent now, somebody in the year on the three year bond.

503
00:27:32,680 --> 00:27:35,240
Speaker 1: Now somebody says, well, I mean, what's you know, what

504
00:27:35,359 --> 00:27:37,440
Speaker 1: does that do for you? And who would accept three

505
00:27:37,480 --> 00:27:40,159
Speaker 1: percent yield? I couldn't care less what the yield is.

506
00:27:40,200 --> 00:27:43,200
Speaker 1: I never have as long as it's going down, because

507
00:27:43,240 --> 00:27:44,840
Speaker 1: that means the price of the bonds is going on.

508
00:27:45,320 --> 00:27:47,960
Speaker 1: And when you look at the convexity of this whole thing,

509
00:27:48,400 --> 00:27:50,960
Speaker 1: if if I'm right. And you go from essentially three

510
00:27:51,000 --> 00:27:54,119
Speaker 1: percent to two percent on a thirty year uh coupon bond,

511
00:27:54,119 --> 00:27:56,360
Speaker 1: You make thirty percent on your money, which I think

512
00:27:56,480 --> 00:27:58,359
Speaker 1: is going to be a lot better than than whatever

513
00:27:58,480 --> 00:28:00,840
Speaker 1: is in second place, And my mortgage is going to

514
00:28:00,960 --> 00:28:04,040
Speaker 1: drop to two point nine percent. What does that do

515
00:28:04,160 --> 00:28:07,960
Speaker 1: for housing? What does that do for other items purchased

516
00:28:08,119 --> 00:28:10,879
Speaker 1: with debt? Well, of course, the question is under what

517
00:28:11,000 --> 00:28:13,600
Speaker 1: circumstance does that happen? If you're in a very low

518
00:28:13,640 --> 00:28:16,879
Speaker 1: inflationary environment, if you're in a slow growth growth, Yeah,

519
00:28:17,040 --> 00:28:19,440
Speaker 1: if you're in a slow growth environment, and it has

520
00:28:19,560 --> 00:28:23,400
Speaker 1: other characteristics. I mean, you look at housing. You mentioned housing. Housing,

521
00:28:23,440 --> 00:28:26,760
Speaker 1: This recovery has been basically a rental market. It has

522
00:28:26,800 --> 00:28:29,600
Speaker 1: not been new homeowners that normally are the basis of housing.

523
00:28:29,640 --> 00:28:32,119
Speaker 1: They're the people by the starter houses from people that

524
00:28:32,240 --> 00:28:34,440
Speaker 1: then move up the Latin X, run on the ladder

525
00:28:34,440 --> 00:28:37,760
Speaker 1: and on up and in housing not really happening because

526
00:28:37,760 --> 00:28:40,200
Speaker 1: people they don't have the incomes. Uh, they don't have

527
00:28:40,280 --> 00:28:43,600
Speaker 1: the credit scores. Uh they and and of course it's

528
00:28:43,640 --> 00:28:47,040
Speaker 1: become you know, it's it's become a virtue as as

529
00:28:47,160 --> 00:28:49,400
Speaker 1: out of necessity people. Oh, I really don't want to

530
00:28:49,480 --> 00:28:51,520
Speaker 1: house on my own. I don't want to responsibility. I'd

531
00:28:51,600 --> 00:28:54,600
Speaker 1: rather live in a more urban environment. Chicken and egg there,

532
00:28:55,080 --> 00:28:57,880
Speaker 1: Uh you know which way is a causality. But my

533
00:28:58,440 --> 00:29:02,240
Speaker 1: friend Jonathan Miller, who's been the show right well does

534
00:29:02,320 --> 00:29:05,480
Speaker 1: does a lot of interesting appraisal analysis, said that there

535
00:29:05,480 --> 00:29:09,240
Speaker 1: are so many people with either low equity, no equity,

536
00:29:09,360 --> 00:29:14,160
Speaker 1: or negative equity that a huge pool of inventory that's

537
00:29:14,160 --> 00:29:16,720
Speaker 1: normally for sale isn't on the market, and a huge

538
00:29:16,760 --> 00:29:21,040
Speaker 1: pool of potential buyers aren't participating, so you have few

539
00:29:21,080 --> 00:29:23,160
Speaker 1: buyers and even fewer houses. Yeah, and there are a

540
00:29:23,200 --> 00:29:25,040
Speaker 1: lot of people. You know, it's just like stocks, the

541
00:29:25,080 --> 00:29:27,040
Speaker 1: idea they take a beating in a stock and they say,

542
00:29:27,040 --> 00:29:28,800
Speaker 1: I won't sell it till I get out. Even it's

543
00:29:28,840 --> 00:29:31,920
Speaker 1: irrational because the market is whatever the market is today.

544
00:29:31,960 --> 00:29:34,520
Speaker 1: But I think there is that there is that pool

545
00:29:34,600 --> 00:29:38,000
Speaker 1: of of people who owned houses they bought them there underwater,

546
00:29:38,400 --> 00:29:40,360
Speaker 1: and they're basically saying, yeah, I want to shell, but

547
00:29:40,400 --> 00:29:42,000
Speaker 1: I can't get out from under it. And of course

548
00:29:42,240 --> 00:29:45,600
Speaker 1: some people they have you know, they they they're upside down.

549
00:29:45,680 --> 00:29:49,320
Speaker 1: They mortgages worth more than the house. So uh, if

550
00:29:49,320 --> 00:29:52,320
Speaker 1: they sell it, they've got they've got financial problems, to

551
00:29:52,360 --> 00:29:54,560
Speaker 1: say the least. It also depends if you're in a

552
00:29:54,600 --> 00:29:57,280
Speaker 1: recourse or a nonrecourse state, if you can walk away

553
00:29:57,360 --> 00:29:59,920
Speaker 1: or not, or if you can talk your bank into

554
00:30:00,040 --> 00:30:04,120
Speaker 1: renegotiating the total UH amounts under a number of the

555
00:30:04,160 --> 00:30:07,720
Speaker 1: hamp and tamp program, if you could do a short

556
00:30:07,760 --> 00:30:10,360
Speaker 1: sale where you basically sell the market and the lender

557
00:30:10,400 --> 00:30:12,760
Speaker 1: forgives a difference. I mean, they're all kinds of variations.

558
00:30:12,760 --> 00:30:14,600
Speaker 1: So what do you see happening in housing over the

559
00:30:14,640 --> 00:30:17,840
Speaker 1: next couple of years. Well, I think I think housing

560
00:30:17,960 --> 00:30:20,200
Speaker 1: is is probably going to limp along here, but I

561
00:30:20,400 --> 00:30:23,040
Speaker 1: don't see anything really pushing it. I mean, I mean,

562
00:30:23,080 --> 00:30:25,800
Speaker 1: we're the we're the most over housed country in the

563
00:30:25,840 --> 00:30:29,440
Speaker 1: world possible exception maybe Spain. I mean, the National Association

564
00:30:29,520 --> 00:30:32,120
Speaker 1: relators would never tell you that. But well, it's always

565
00:30:32,160 --> 00:30:34,800
Speaker 1: a good time to buy or sell a house according

566
00:30:34,800 --> 00:30:36,600
Speaker 1: to that. Yeah, I remember an ad they had, But

567
00:30:37,600 --> 00:30:39,160
Speaker 1: that's a great time to buy, it's a great time

568
00:30:39,200 --> 00:30:42,120
Speaker 1: to sell that. It's always a great always a great

569
00:30:42,160 --> 00:30:44,880
Speaker 1: time to generate a sales commission. All right, yes, you

570
00:30:45,000 --> 00:30:47,760
Speaker 1: got it, um, So let's talk about energy, because you've

571
00:30:47,800 --> 00:30:51,600
Speaker 1: sent some really interesting things about energy. Oil prices of

572
00:30:51,760 --> 00:30:55,400
Speaker 1: drop cut in half over the past year. I understand

573
00:30:55,400 --> 00:30:58,160
Speaker 1: you talked about twenty dollar a barrel oil. Yeah. Well,

574
00:30:58,160 --> 00:31:02,560
Speaker 1: here's the rationale, uh peck, is their cartel. Cartels exists

575
00:31:02,560 --> 00:31:05,720
Speaker 1: to keep prices above equilibrium. That's the whole purpose that

576
00:31:05,880 --> 00:31:10,040
Speaker 1: encourages cheating. Somebody was more than their share, either in

577
00:31:10,240 --> 00:31:15,800
Speaker 1: the cartel OPEC or outside Russia, American frackers, whoever. So

578
00:31:16,120 --> 00:31:18,840
Speaker 1: the leader of the cartel's responsibilities to cut its own

579
00:31:18,880 --> 00:31:23,080
Speaker 1: production to accommodate the cheaters to avoid a price collapse. Well,

580
00:31:23,160 --> 00:31:26,120
Speaker 1: OPEC has been doing that for years, but they're getting

581
00:31:26,120 --> 00:31:28,720
Speaker 1: tired of it. In the last ten years, OPEC production

582
00:31:28,760 --> 00:31:30,840
Speaker 1: has been flat and all the growth has come in

583
00:31:30,920 --> 00:31:34,000
Speaker 1: non OPEC sources, a lot of recently from American from

584
00:31:34,000 --> 00:31:38,480
Speaker 1: American frackers. So the Saudias and their and their colleagues

585
00:31:38,520 --> 00:31:41,920
Speaker 1: and the Persian Gulf. Back November seven, when we were

586
00:31:41,920 --> 00:31:45,160
Speaker 1: sitting down to our Thanksgiving turkeys, they decided they weren't

587
00:31:45,160 --> 00:31:47,400
Speaker 1: gonna cut They basically said, we're gonna play it. We're

588
00:31:47,440 --> 00:31:49,680
Speaker 1: gonna play in the labory game of chicken. We got

589
00:31:49,720 --> 00:31:52,800
Speaker 1: about five billion dollars in foreign currency reserves and work

590
00:31:52,840 --> 00:31:55,080
Speaker 1: and see, we're gonna see who can take lower prices.

591
00:31:55,280 --> 00:31:59,120
Speaker 1: The longest OPEC production and with thirty thirty million barrels

592
00:31:59,160 --> 00:32:01,959
Speaker 1: a day, they took off, basically took off the quotas.

593
00:32:01,960 --> 00:32:04,160
Speaker 1: It's now thirty one and a half million barrels a day.

594
00:32:04,480 --> 00:32:06,840
Speaker 1: She say, okay, now, how low the prices go before

595
00:32:06,840 --> 00:32:10,360
Speaker 1: somebody chickens out, some major producer says, I've had it,

596
00:32:10,480 --> 00:32:12,800
Speaker 1: I've got to cut back. It isn't the cost of

597
00:32:12,840 --> 00:32:17,040
Speaker 1: meeting budgets that's irrelevant here, Okay, maybe it maybe Venezuela

598
00:32:17,120 --> 00:32:20,000
Speaker 1: is fifty bucks of barrel, that's irrelevant. It isn't even

599
00:32:20,000 --> 00:32:22,720
Speaker 1: the full full cycle cost, in other words, the costs

600
00:32:22,760 --> 00:32:25,479
Speaker 1: of drilling the whole laying the pipes, the overhead. So no, no, no, no.

601
00:32:25,760 --> 00:32:28,720
Speaker 1: When you're a price war, it's the marginal cost. It's

602
00:32:28,760 --> 00:32:31,720
Speaker 1: the cost once the pipes are laid, the oil is

603
00:32:32,440 --> 00:32:34,520
Speaker 1: coming out of the ground. In other words, where is

604
00:32:34,520 --> 00:32:38,160
Speaker 1: your free cash flow disappear? And in the premium basis

605
00:32:38,160 --> 00:32:40,760
Speaker 1: in Texas and in the Persian Gulf, that's in the

606
00:32:40,800 --> 00:32:43,800
Speaker 1: ten to twenty dollar barrel range. So that's how I

607
00:32:43,840 --> 00:32:46,400
Speaker 1: get to that number. So you can actually see oil

608
00:32:46,440 --> 00:32:48,959
Speaker 1: full down to twenty five or so dollars a barrel,

609
00:32:49,240 --> 00:32:53,400
Speaker 1: and they're still making five or more dollars. That's right.

610
00:32:53,720 --> 00:32:55,920
Speaker 1: In other words, they may be losing money on a

611
00:32:55,960 --> 00:32:59,200
Speaker 1: full on the full cost basis, but in terms of

612
00:32:59,240 --> 00:33:01,440
Speaker 1: the marginal cash in other words, you know, they still

613
00:33:01,480 --> 00:33:05,360
Speaker 1: have positive cash flow on a marginal basis, so that

614
00:33:05,600 --> 00:33:08,240
Speaker 1: that's the incentive to keep producing. And now you know

615
00:33:08,320 --> 00:33:10,720
Speaker 1: price goes down, there doesn't stay there forever, but you

616
00:33:10,920 --> 00:33:12,560
Speaker 1: but you're kind to get to the point that you

617
00:33:12,640 --> 00:33:15,840
Speaker 1: have major production that disappears from the system, and we

618
00:33:15,880 --> 00:33:18,560
Speaker 1: haven't seen that. There's still the world a washing oil. Sure,

619
00:33:18,800 --> 00:33:21,240
Speaker 1: oh sure, I mean you know, you're producing about two

620
00:33:21,240 --> 00:33:24,360
Speaker 1: million barrels a day more than demand. Right now, you're

621
00:33:24,400 --> 00:33:27,040
Speaker 1: showing floating around filled with oil and no place to

622
00:33:27,120 --> 00:33:31,360
Speaker 1: drop it off. That's that's quite fascinating. So normally when

623
00:33:31,400 --> 00:33:34,360
Speaker 1: you talk about oil prices dropping from over a hundred

624
00:33:34,360 --> 00:33:39,520
Speaker 1: dollars to dollars, we would be talking about a recession.

625
00:33:40,360 --> 00:33:43,080
Speaker 1: Do you see your recession anytime in the next twelve months.

626
00:33:43,440 --> 00:33:46,240
Speaker 1: I don't see the making of a recession. Uh. You

627
00:33:46,320 --> 00:33:49,320
Speaker 1: have recession, said, at least historically for two reasons. One

628
00:33:49,360 --> 00:33:51,920
Speaker 1: is the FED raisers interest rates to choke off what

629
00:33:51,960 --> 00:33:54,920
Speaker 1: they see is an overheating economy. Now, they may have

630
00:33:54,960 --> 00:33:57,880
Speaker 1: painted themselves into a corner here. They've been yelling and

631
00:33:57,920 --> 00:34:00,960
Speaker 1: screaming about raising rates. They've cry wolf an awful lot

632
00:34:01,120 --> 00:34:03,600
Speaker 1: their credibilities at sake. They may raise rage simply to

633
00:34:03,720 --> 00:34:07,400
Speaker 1: preserve credibility. But the kind of interest rate like they

634
00:34:07,400 --> 00:34:09,319
Speaker 1: did in ninety four, where the where they want three

635
00:34:09,320 --> 00:34:12,759
Speaker 1: inter basis points on on FED funds in six months

636
00:34:12,840 --> 00:34:15,200
Speaker 1: or so, I don't see that. So the other possibility

637
00:34:15,280 --> 00:34:18,719
Speaker 1: recession is a is some kind of a shock. That's

638
00:34:18,719 --> 00:34:21,200
Speaker 1: what we had with the collapse in dot com stocks

639
00:34:21,239 --> 00:34:23,640
Speaker 1: in the late nineties. That was a housing uh in

640
00:34:23,640 --> 00:34:26,960
Speaker 1: in the in the mid two thousands, maybe China. So

641
00:34:27,000 --> 00:34:29,560
Speaker 1: in the last minute we have you you reading my mind.

642
00:34:30,040 --> 00:34:34,200
Speaker 1: What's the potential impact of China on the global economy. Well,

643
00:34:34,200 --> 00:34:37,120
Speaker 1: the reality of China is that it's nothing has really

644
00:34:37,200 --> 00:34:41,720
Speaker 1: changed their accept perceptions. China basically is not a leader.

645
00:34:41,840 --> 00:34:46,120
Speaker 1: It's not a self lead comp country. China imports raw

646
00:34:46,200 --> 00:34:49,560
Speaker 1: materials and equipment and use it to manufacture goods that

647
00:34:49,640 --> 00:34:54,200
Speaker 1: they send to North America and Europe. So their activity follows.

648
00:34:54,280 --> 00:34:56,640
Speaker 1: That's where they are depending on that. Of course they

649
00:34:56,680 --> 00:34:59,680
Speaker 1: have infrastructure spending as well. But but the point is

650
00:34:59,719 --> 00:35:03,239
Speaker 1: that it's the perception of China. With a collaption in

651
00:35:03,320 --> 00:35:06,160
Speaker 1: stock prices and the devaluation, people are suddenly saying, oh

652
00:35:06,200 --> 00:35:09,399
Speaker 1: my god, China isn't really independently growing. They haven't been

653
00:35:09,440 --> 00:35:12,239
Speaker 1: for years. But perceptions have reality, and we'll then have

654
00:35:12,360 --> 00:35:16,000
Speaker 1: enough follow on consequences with effects on commodity prices and

655
00:35:16,120 --> 00:35:20,279
Speaker 1: currencies and other developing countries. That's that's that's what's there,

656
00:35:20,320 --> 00:35:22,000
Speaker 1: and that's if there's a recession out there in the

657
00:35:22,040 --> 00:35:23,920
Speaker 1: next twelve months or so, I think that's probably where

658
00:35:23,960 --> 00:35:26,880
Speaker 1: it would would be generated. Thank you to my guest

659
00:35:26,960 --> 00:35:29,520
Speaker 1: Gary Shilling for spending so much time with us. Be

660
00:35:29,600 --> 00:35:32,560
Speaker 1: sure and check out our podcast extras where we continue

661
00:35:32,600 --> 00:35:36,359
Speaker 1: the conversation. Check out my daily column on Bloomberg View

662
00:35:36,400 --> 00:35:40,880
Speaker 1: dot com. Follow me on Twitter at Riholts. I'm Barry Ridhults.

663
00:35:40,880 --> 00:35:44,600
Speaker 1: You're listening to Masters in Business on Bloomberg Radio. Okay,

664
00:35:44,680 --> 00:35:47,240
Speaker 1: so this is the podcast portion of the show where

665
00:35:47,280 --> 00:35:49,520
Speaker 1: I stopped worrying about the time segments and we could

666
00:35:49,560 --> 00:35:53,040
Speaker 1: chat about anything before and I know I have to

667
00:35:53,040 --> 00:35:54,640
Speaker 1: get you out of here at a certain time, but

668
00:35:54,880 --> 00:35:57,920
Speaker 1: that'll be easy. Before we started ask talking about some

669
00:35:57,960 --> 00:36:01,000
Speaker 1: other the questions that we've missed and some other stuff.

670
00:36:01,680 --> 00:36:04,359
Speaker 1: These are all my questions. I have to ask you

671
00:36:05,160 --> 00:36:08,920
Speaker 1: about the bee keeping. You're you're famous on Wall Street

672
00:36:09,440 --> 00:36:13,840
Speaker 1: for for being a beekeeper and mailing out honey to

673
00:36:14,080 --> 00:36:18,239
Speaker 1: various people as as holiday presents. Yea, including myself. I

674
00:36:18,320 --> 00:36:23,240
Speaker 1: have I have a tub of honey, and I believe

675
00:36:23,719 --> 00:36:25,600
Speaker 1: and you have a different inscription every year, and the

676
00:36:25,600 --> 00:36:29,200
Speaker 1: one that stands out was the FEDS funny money can't

677
00:36:29,200 --> 00:36:32,480
Speaker 1: buy this honey. Yeah, this year as treasury bonds saw

678
00:36:32,719 --> 00:36:36,000
Speaker 1: our bees make more. There you go. We always try

679
00:36:36,000 --> 00:36:39,400
Speaker 1: to find something topical and usually related to the financial factor.

680
00:36:39,880 --> 00:36:42,200
Speaker 1: How on earth did you get into beekeeping? Well, it's

681
00:36:42,239 --> 00:36:46,120
Speaker 1: an interesting story I've got. We live in suburban New

682
00:36:46,200 --> 00:36:48,600
Speaker 1: Jersey and I have a bunch of drawer fruit trees

683
00:36:48,640 --> 00:36:51,160
Speaker 1: around our premises, and I didn't think they were getting

684
00:36:51,160 --> 00:36:54,600
Speaker 1: pollinated properly. Uh. And I had this based on what

685
00:36:54,600 --> 00:36:56,680
Speaker 1: what makes you wake up one day and say, I'm

686
00:36:56,680 --> 00:36:58,920
Speaker 1: not sure our fruit trees A bunch of blossoms are

687
00:36:58,920 --> 00:37:01,719
Speaker 1: not that much a lot of fruit? Okay, that makes sense?

688
00:37:02,000 --> 00:37:05,760
Speaker 1: Very simple road tests Anyway, I had this romantic idea

689
00:37:05,760 --> 00:37:08,400
Speaker 1: of putting in some bee hives, and my wife kept saying,

690
00:37:08,400 --> 00:37:10,319
Speaker 1: come on, this is this is this is no far

691
00:37:10,520 --> 00:37:13,600
Speaker 1: Mrs Suburbia. Well, then our third son, who was an

692
00:37:13,640 --> 00:37:17,359
Speaker 1: animal ever since birth, did his senior college thesis on bees.

693
00:37:17,440 --> 00:37:19,359
Speaker 1: And that's all it took to push me over the edge.

694
00:37:19,680 --> 00:37:22,680
Speaker 1: So in afternoon when wait, wait, wait, he does his

695
00:37:22,680 --> 00:37:31,400
Speaker 1: his college thesis prompted from you, unprovoked, totally independent, totally independent. No,

696
00:37:31,600 --> 00:37:34,840
Speaker 1: there was no leading the witness on that one. So

697
00:37:35,239 --> 00:37:39,480
Speaker 1: he's doing this and and so uh uh he and

698
00:37:39,520 --> 00:37:42,200
Speaker 1: I smuggle in a couple of highs one afternoon one.

699
00:37:43,080 --> 00:37:48,600
Speaker 1: What's how physically well the hive is the vertical essentially, Well,

700
00:37:48,600 --> 00:37:50,719
Speaker 1: you stack them up, you stack up the boxes. But

701
00:37:50,840 --> 00:37:54,160
Speaker 1: the but the box that the dimensions are are sixteen

702
00:37:54,200 --> 00:37:57,600
Speaker 1: and five inc inch wide, nineteen and seven acients long,

703
00:37:57,640 --> 00:38:00,480
Speaker 1: and they're varying depths. And I can explain to you

704
00:38:00,600 --> 00:38:03,480
Speaker 1: why they why the dimensions are Okay, this is very interesting.

705
00:38:03,920 --> 00:38:07,440
Speaker 1: Bees have have been kept since uh time in millennia.

706
00:38:08,040 --> 00:38:11,640
Speaker 1: Uh and by the way, honey never never spoiled. They've

707
00:38:11,640 --> 00:38:13,960
Speaker 1: taken it out of ancient Egyptian tombs which is just

708
00:38:14,040 --> 00:38:16,479
Speaker 1: as good as the day the bees made it. Really, Yeah,

709
00:38:16,560 --> 00:38:18,600
Speaker 1: I had no idea. I know it was good for

710
00:38:18,640 --> 00:38:20,839
Speaker 1: a long time. I don't know it was good o now.

711
00:38:21,760 --> 00:38:25,160
Speaker 1: Throughout this time though that they had bees, they were

712
00:38:25,200 --> 00:38:28,840
Speaker 1: in various cavities and so on. There's what's called the skeps,

713
00:38:29,280 --> 00:38:32,200
Speaker 1: which is a it's a series of concentric rings. Have

714
00:38:32,280 --> 00:38:35,879
Speaker 1: you ever seen a Utah road sign beehive state, that's

715
00:38:35,880 --> 00:38:39,200
Speaker 1: a skeps. You know. It's a traditional kind of round

716
00:38:39,280 --> 00:38:41,640
Speaker 1: kind of thing. And and and the bees would be

717
00:38:41,680 --> 00:38:44,960
Speaker 1: in there and they when the left of their own devices. Uh,

718
00:38:45,160 --> 00:38:48,400
Speaker 1: the bees make it has a hexonical cells, but they

719
00:38:48,440 --> 00:38:52,280
Speaker 1: look like stags being down. Well, the way they harvested

720
00:38:52,360 --> 00:38:55,719
Speaker 1: the honey was they basically killed the hive. They would

721
00:38:55,760 --> 00:38:58,560
Speaker 1: use sulfur smoke kill the hive and then crush the

722
00:38:58,600 --> 00:39:01,120
Speaker 1: combs to get the honey out. Well, that was very

723
00:39:01,120 --> 00:39:03,600
Speaker 1: inefficient because they had to have about twice as many

724
00:39:04,120 --> 00:39:07,399
Speaker 1: twice as many hives as they were going to harvest. Uh.

725
00:39:07,440 --> 00:39:11,640
Speaker 1: And also after the advent of kerosene, that's Colonel Drake

726
00:39:11,719 --> 00:39:14,480
Speaker 1: Droll as well, for lights, there was not the need

727
00:39:14,560 --> 00:39:17,879
Speaker 1: for bees wax for candles, so wax, and it takes

728
00:39:17,920 --> 00:39:20,879
Speaker 1: about ten times as much nectar to make a pound

729
00:39:20,920 --> 00:39:22,920
Speaker 1: of wax as a pound of honey, so this is

730
00:39:23,040 --> 00:39:27,239
Speaker 1: very inefficient. In eighteen fifty one eighteen fifty one. Now,

731
00:39:27,480 --> 00:39:29,520
Speaker 1: honey bees are from the old all from the old world.

732
00:39:29,560 --> 00:39:32,279
Speaker 1: They came here with the European settlers. The Indians called

733
00:39:32,320 --> 00:39:36,040
Speaker 1: them the white man's fly. But a congregational preacher in

734
00:39:36,400 --> 00:39:42,919
Speaker 1: Philadelphia named Lorenzo Langfroft, Lorenzo Langfroft made a very interesting observation.

735
00:39:43,400 --> 00:39:45,839
Speaker 1: He noticed that the v would only the bee would

736
00:39:45,840 --> 00:39:48,040
Speaker 1: only build, and the worker bees to do all this.

737
00:39:48,160 --> 00:39:50,759
Speaker 1: The drones don't do anything. She would only build her

738
00:39:51,160 --> 00:39:53,520
Speaker 1: comb within about three ace of an inch of any

739
00:39:53,560 --> 00:39:58,240
Speaker 1: other solid object, including another another comb. So he developed

740
00:39:58,239 --> 00:40:01,120
Speaker 1: from that what's called the movable frame five you might

741
00:40:01,320 --> 00:40:05,399
Speaker 1: you might our listeners may have seen those. In other words,

742
00:40:05,400 --> 00:40:09,440
Speaker 1: he put these in there, and and the bees they built,

743
00:40:09,520 --> 00:40:12,040
Speaker 1: they built out the wax coomb fill them upon. He

744
00:40:12,120 --> 00:40:14,319
Speaker 1: put a cap on there. You can take them out,

745
00:40:14,480 --> 00:40:16,680
Speaker 1: scratch off the caps, put in a central fuge, spin

746
00:40:16,719 --> 00:40:19,160
Speaker 1: them out and put them back. Okay, now coming back

747
00:40:19,200 --> 00:40:23,200
Speaker 1: to the dimensions. He's the father of modern beekeeping and

748
00:40:23,360 --> 00:40:27,920
Speaker 1: those dimensions that I mentioned sixteen and five hy those

749
00:40:27,960 --> 00:40:30,759
Speaker 1: were the dimensions of some scrap lumber he had. It

750
00:40:30,920 --> 00:40:34,120
Speaker 1: wasn't a conversion from Netrick, but he was so influential

751
00:40:34,600 --> 00:40:37,279
Speaker 1: that that became. Now it's a convenient size. But the

752
00:40:37,320 --> 00:40:39,319
Speaker 1: guy never made a dime out of this because it

753
00:40:39,360 --> 00:40:43,640
Speaker 1: was so easy to copy. But yeah, that and and

754
00:40:43,719 --> 00:40:46,400
Speaker 1: so that now and you have these These boxes are

755
00:40:46,480 --> 00:40:50,080
Speaker 1: various depths. There's usually do two boxes on the bottom

756
00:40:50,120 --> 00:40:52,080
Speaker 1: that the bees live in year round and they have

757
00:40:52,200 --> 00:40:55,759
Speaker 1: their honey to get through the winter. They have their

758
00:40:56,400 --> 00:41:00,120
Speaker 1: brewed in there, and they have um poland, which as

759
00:41:00,120 --> 00:41:02,879
Speaker 1: the nectar they feel they feed to the larva. And

760
00:41:03,160 --> 00:41:06,719
Speaker 1: those boxes nine nine and five ah deep, if they're

761
00:41:06,760 --> 00:41:09,960
Speaker 1: full of honey, they weave eighty five pounds. So the

762
00:41:09,960 --> 00:41:12,520
Speaker 1: ones you stack up on top are called supers, and

763
00:41:12,560 --> 00:41:15,040
Speaker 1: that's the honey we're gonna take off. And they're not

764
00:41:15,120 --> 00:41:17,640
Speaker 1: as deep as you can lift them, because try try

765
00:41:17,680 --> 00:41:21,640
Speaker 1: lifting eighty five pounds at at at at the shoulder height.

766
00:41:21,719 --> 00:41:25,040
Speaker 1: It's it's good for the for the stomach. Monthsls. My

767
00:41:25,120 --> 00:41:27,800
Speaker 1: dogways eighty five pound. One of my dogs eighty five pounds.

768
00:41:27,800 --> 00:41:30,719
Speaker 1: And I know when I had a carry him. I

769
00:41:30,800 --> 00:41:35,600
Speaker 1: know eighty five pounds an to lift um, so that's amazing.

770
00:41:35,680 --> 00:41:39,120
Speaker 1: So but anyway, start you've been doing decades. Yeah, we'll

771
00:41:39,120 --> 00:41:43,640
Speaker 1: start off. And anyway, this their son, Steve. He took

772
00:41:43,640 --> 00:41:46,239
Speaker 1: off for a job and the euro dollar pits in

773
00:41:46,280 --> 00:41:49,560
Speaker 1: the Chicago Murk and I and and I had been

774
00:41:49,800 --> 00:41:51,680
Speaker 1: I'd just been the flunky. He was a beekeeper. And

775
00:41:51,680 --> 00:41:54,560
Speaker 1: it was like, if you're ever driven with somebody repeatedly

776
00:41:54,600 --> 00:41:56,600
Speaker 1: to the same destination, they do the driving, you don't

777
00:41:56,600 --> 00:42:01,280
Speaker 1: pay attention. That was me. He takes off. I'm instantly

778
00:42:01,280 --> 00:42:04,120
Speaker 1: promoted a head beekeeper. So and I guess why then

779
00:42:04,160 --> 00:42:07,160
Speaker 1: we were upped about twenty hives and so how much

780
00:42:07,160 --> 00:42:10,759
Speaker 1: spaces is physically taking in the backyard. Well, I've got

781
00:42:10,800 --> 00:42:13,640
Speaker 1: fifteen of them in our residents in Short Hills, New Jersey.

782
00:42:13,680 --> 00:42:18,200
Speaker 1: And I've got about horror on the grounds underground, underground

783
00:42:18,200 --> 00:42:21,000
Speaker 1: in a corner of the property. Uh. And but I

784
00:42:21,040 --> 00:42:23,920
Speaker 1: got about a hundred hives total, and and most of

785
00:42:24,080 --> 00:42:27,799
Speaker 1: the well they're more further out Morristown, New Jersey area.

786
00:42:27,800 --> 00:42:29,359
Speaker 1: And then I've got some we have a beach house

787
00:42:29,400 --> 00:42:32,800
Speaker 1: on Fire Island some out there. But uh, but anyway,

788
00:42:32,920 --> 00:42:34,960
Speaker 1: but you know, this thing very it just keeps growing

789
00:42:35,040 --> 00:42:38,160
Speaker 1: and it's very labor intensive. But I got one. I

790
00:42:38,200 --> 00:42:39,839
Speaker 1: got a guy on my staff. We spend a lot

791
00:42:39,840 --> 00:42:41,959
Speaker 1: of time working with me on this. You're talking about

792
00:42:42,000 --> 00:42:45,840
Speaker 1: the bees labor or your labor, well and both. But

793
00:42:45,840 --> 00:42:48,880
Speaker 1: but I didn't attend the thing to grow. But the

794
00:42:48,960 --> 00:42:51,720
Speaker 1: damn thing just keeps growing. How many pounds of honey

795
00:42:51,800 --> 00:42:54,680
Speaker 1: do you generate? Well? Uh, this year, this year we

796
00:42:54,719 --> 00:42:58,839
Speaker 1: took off pounds and that's a ton of change of honey. Yeah,

797
00:42:58,880 --> 00:43:01,239
Speaker 1: and we give it all away. If I ever sold

798
00:43:01,239 --> 00:43:03,800
Speaker 1: any i'd have to keep keep keep the books. And

799
00:43:03,840 --> 00:43:06,279
Speaker 1: I don't want to make myself cry because my time

800
00:43:06,320 --> 00:43:08,720
Speaker 1: would be probably worth a quarter an hour and probably

801
00:43:08,719 --> 00:43:11,160
Speaker 1: with a minor sign in front of it. But it

802
00:43:11,520 --> 00:43:15,800
Speaker 1: very tremendously. Last year was our best year ever pounds

803
00:43:15,840 --> 00:43:17,840
Speaker 1: and we saw us three tons of hunter. Yeah, we

804
00:43:17,840 --> 00:43:21,040
Speaker 1: haven't stacked all over the office. And and my my admin,

805
00:43:21,440 --> 00:43:23,839
Speaker 1: Beth Grant, she keeps saying, come on, uh, we don't

806
00:43:23,840 --> 00:43:26,120
Speaker 1: need this much honey. I think she really hopes we

807
00:43:26,160 --> 00:43:28,200
Speaker 1: don't have a great year because trying to figure out

808
00:43:28,200 --> 00:43:30,560
Speaker 1: where we're gonna have stacked all over the place. So

809
00:43:30,600 --> 00:43:36,240
Speaker 1: what if how has these how how has these colony

810
00:43:36,360 --> 00:43:40,960
Speaker 1: collapse diseases been impacted your highs. That's probably one of

811
00:43:41,040 --> 00:43:46,080
Speaker 1: the biggest misconceptions. In two thousand seven sixty minutes, the

812
00:43:46,640 --> 00:43:51,200
Speaker 1: TV show did this segment on colony collapse disorder. Now,

813
00:43:51,200 --> 00:43:54,080
Speaker 1: what that means is the bees leave the hive and

814
00:43:54,280 --> 00:43:56,920
Speaker 1: they can't live long on their own outside. That's clear.

815
00:43:57,160 --> 00:43:59,759
Speaker 1: They don't come back. Um. And they said, this is

816
00:43:59,800 --> 00:44:02,719
Speaker 1: the the end of the world. Well, it's actually no more,

817
00:44:02,760 --> 00:44:06,480
Speaker 1: no more food pollination. About about a third of everything

818
00:44:06,520 --> 00:44:11,200
Speaker 1: we eat depends on insect pollination, andent of that is

819
00:44:11,200 --> 00:44:14,000
Speaker 1: from honey bees. In any event, they said at the

820
00:44:14,120 --> 00:44:16,040
Speaker 1: end of the world. Well, what they didn't really they

821
00:44:16,080 --> 00:44:19,960
Speaker 1: didn't do their homework, because this is a reoccurring problem. Uh,

822
00:44:20,000 --> 00:44:22,680
Speaker 1: it's about every twenty five years. The first observation of

823
00:44:22,719 --> 00:44:26,000
Speaker 1: this country was eighteen sixty nine, and it's gets on

824
00:44:26,040 --> 00:44:27,920
Speaker 1: the way. Now it's not the problem, but there are

825
00:44:28,280 --> 00:44:32,480
Speaker 1: but there are other serious problems. Uh well uh And

826
00:44:32,480 --> 00:44:33,960
Speaker 1: as a matter of fact, they just had a huge

827
00:44:33,960 --> 00:44:36,640
Speaker 1: study announced last year. All the big name U. S.

828
00:44:36,719 --> 00:44:40,280
Speaker 1: D A. Anomalogists and the guys from the big schools

829
00:44:40,280 --> 00:44:43,840
Speaker 1: where there you know, like Cornell and University of Maryland

830
00:44:43,840 --> 00:44:46,000
Speaker 1: and Penn State and U C. Davis and so on,

831
00:44:46,400 --> 00:44:49,000
Speaker 1: and they came up with three three areas, and everybody's

832
00:44:49,040 --> 00:44:51,399
Speaker 1: waiting with braided breath for what's the problem with bees?

833
00:44:51,440 --> 00:44:55,640
Speaker 1: How do we get out of this? The first one

834
00:44:53,200 --> 00:44:58,439
Speaker 1: has to be that's interesting, It isn't uh no, that's

835
00:44:58,440 --> 00:45:03,160
Speaker 1: the first guest. Pesticides. They said, maybe, but they're not

836
00:45:03,200 --> 00:45:07,239
Speaker 1: at all sure, and interestingly enough, their European counterparts were

837
00:45:07,280 --> 00:45:10,799
Speaker 1: absolutely possibly convinced it was pesticized, and two months ago

838
00:45:11,080 --> 00:45:14,399
Speaker 1: these Europeans said, we're not so sure. But that's one.

839
00:45:14,520 --> 00:45:18,719
Speaker 1: The second one is nutrition, farmers, fence, farmers, plant fence,

840
00:45:18,840 --> 00:45:21,800
Speaker 1: road defense road and there's not a lot of wildflowers

841
00:45:22,040 --> 00:45:25,200
Speaker 1: to give bees the the nectar and pollen that they need.

842
00:45:25,239 --> 00:45:27,600
Speaker 1: So what they're doing is there encurreaged road defense room,

843
00:45:27,640 --> 00:45:32,399
Speaker 1: meaning it's all cast crops, crops most of them don't

844
00:45:32,400 --> 00:45:34,759
Speaker 1: tend to have any nectar that are Pollen's interested in

845
00:45:34,800 --> 00:45:36,840
Speaker 1: the piece. But what they're doing now a lot of

846
00:45:36,880 --> 00:45:41,879
Speaker 1: cases is uh they're encouraging. They're encouraging farmers to use

847
00:45:42,200 --> 00:45:44,760
Speaker 1: marginal land to plan there. There's an outfit, for example,

848
00:45:44,840 --> 00:45:48,800
Speaker 1: called h called pheasants unlimited. Uh. They're in the Upper Midwest,

849
00:45:48,840 --> 00:45:52,480
Speaker 1: and they basically raised pheasants and quail for for hunters.

850
00:45:52,600 --> 00:45:55,280
Speaker 1: And and what they do is they provide the seed

851
00:45:55,360 --> 00:45:59,800
Speaker 1: to farmers and and uh, and the nectar and pollen

852
00:46:00,160 --> 00:46:02,280
Speaker 1: are as good for the bees, and then the seeds

853
00:46:02,320 --> 00:46:04,920
Speaker 1: that chicks the pheasants and the quail chicks eat it,

854
00:46:05,239 --> 00:46:08,120
Speaker 1: which makes them better to be harvested by the hunter.

855
00:46:08,200 --> 00:46:11,920
Speaker 1: So there, and then the third that's fascinating because there's

856
00:46:11,960 --> 00:46:14,440
Speaker 1: a farm near where I live, which is where I

857
00:46:14,480 --> 00:46:18,319
Speaker 1: get my peach raspberry pies, called Young's Farm, and I

858
00:46:18,480 --> 00:46:22,680
Speaker 1: noticed they have rows and rows of plantings. And then

859
00:46:22,719 --> 00:46:26,280
Speaker 1: along the edge which is adjacent to the street, probably

860
00:46:26,320 --> 00:46:29,759
Speaker 1: not harvestable. They have just a whole run of wildfire.

861
00:46:30,200 --> 00:46:32,360
Speaker 1: And that's that's what's being done. And that's that's helpful,

862
00:46:32,360 --> 00:46:34,760
Speaker 1: but it's you know, it's not on a big enough scale.

863
00:46:34,920 --> 00:46:37,360
Speaker 1: Then the third problem, which is probably most interesting, is

864
00:46:37,400 --> 00:46:40,080
Speaker 1: a parasitic mic called verroa v A r r O.

865
00:46:40,560 --> 00:46:44,319
Speaker 1: Read something about this. Now this is there there are

866
00:46:44,360 --> 00:46:48,400
Speaker 1: five races of honey bees. The only one that's commercially

867
00:46:49,040 --> 00:46:53,200
Speaker 1: valuable is UH. The Latin. The scientific name is APIs

868
00:46:53,239 --> 00:46:59,440
Speaker 1: malafra APIs b malafra honey. Um. Now that one orange

869
00:47:00,000 --> 00:47:02,319
Speaker 1: original bees are off from the whole, from the from

870
00:47:02,320 --> 00:47:05,800
Speaker 1: the old world. This one originated in in uh Southern

871
00:47:05,840 --> 00:47:08,799
Speaker 1: Europe and the Middle East. There's another race in the

872
00:47:08,920 --> 00:47:13,360
Speaker 1: in the Southeast Asia called APIs Serena. And this this

873
00:47:13,560 --> 00:47:17,840
Speaker 1: roa mite is indigenous indigenous on APIs Serena and APIs.

874
00:47:18,200 --> 00:47:21,080
Speaker 1: And this this roa mites hangs on the bee, sucks

875
00:47:21,120 --> 00:47:24,520
Speaker 1: out there quota or blood. APIs SaRenna recognized this as

876
00:47:24,560 --> 00:47:26,239
Speaker 1: the bad guy, and they grew them off each other.

877
00:47:26,320 --> 00:47:29,160
Speaker 1: They pull them off each other. It jumped over the

878
00:47:29,280 --> 00:47:33,320
Speaker 1: Apisa and they don't understand it's a bad guy. So

879
00:47:33,520 --> 00:47:36,120
Speaker 1: you and and so one they co evolved together, and

880
00:47:36,239 --> 00:47:39,400
Speaker 1: that's how they managed to whoever figured out you need

881
00:47:39,480 --> 00:47:42,240
Speaker 1: to take this off. Now we see their offspring around.

882
00:47:42,560 --> 00:47:44,640
Speaker 1: If you didn't co evolve, you may not have developed

883
00:47:44,680 --> 00:47:48,200
Speaker 1: that behavior. But but now they're they're they're right. Now

884
00:47:48,280 --> 00:47:52,239
Speaker 1: you've got to treat with chemicals. Um are absolutely positively

885
00:47:52,320 --> 00:47:55,200
Speaker 1: that high will be done in two years now. Yeah, yeah,

886
00:47:55,239 --> 00:47:56,800
Speaker 1: you don't treat until you take off the honey. But

887
00:47:56,800 --> 00:47:59,759
Speaker 1: we're gonna eat, of course. But they're but they're doing

888
00:47:59,840 --> 00:48:03,400
Speaker 1: some interesting things. Monshano has some interesting work where they

889
00:48:03,600 --> 00:48:06,200
Speaker 1: kill the mites believe the bees that you're trying to

890
00:48:06,280 --> 00:48:09,400
Speaker 1: kill one insect without killing another insight, and they're and

891
00:48:09,480 --> 00:48:15,120
Speaker 1: they're using some genetic uh, some some genetic modifications to

892
00:48:15,280 --> 00:48:18,560
Speaker 1: basically in effect try to disrupt the breeding cycle of

893
00:48:18,760 --> 00:48:22,080
Speaker 1: of the mice. That's a that's an experimental stage, but

894
00:48:22,239 --> 00:48:25,279
Speaker 1: that that has that's probably the greatest thing. But this

895
00:48:25,440 --> 00:48:27,600
Speaker 1: is this is a serious problem. And the thing is

896
00:48:27,680 --> 00:48:30,879
Speaker 1: he's mice mutate. I mean that the treatments that worked

897
00:48:30,920 --> 00:48:34,840
Speaker 1: just beautifully ten years ago are worth anything because they mutated,

898
00:48:34,880 --> 00:48:41,279
Speaker 1: and the ones now sounds like penicillin resistance. It's a

899
00:48:41,920 --> 00:48:44,759
Speaker 1: how did you get from? It's amazing how first of

900
00:48:44,800 --> 00:48:48,120
Speaker 1: all you you've obviously studied this in great detail, But

901
00:48:48,440 --> 00:48:52,439
Speaker 1: as an economist, I don't really think of the next

902
00:48:52,760 --> 00:48:57,520
Speaker 1: logical step as well. Of course, beekeeping should be well

903
00:48:57,560 --> 00:49:00,480
Speaker 1: that there there are, there are, there are, and treads

904
00:49:00,520 --> 00:49:04,400
Speaker 1: aybury and such as okay, well let's see. Well the

905
00:49:04,480 --> 00:49:06,480
Speaker 1: one that is not common but I like is it's

906
00:49:06,520 --> 00:49:10,000
Speaker 1: good physical exercise and particularly on a nice day, I

907
00:49:10,120 --> 00:49:12,880
Speaker 1: like to be outside. Uh. And you don't get a

908
00:49:12,920 --> 00:49:14,960
Speaker 1: lot of that when you're sitting behind your desk on

909
00:49:15,040 --> 00:49:17,560
Speaker 1: the lecture circuit or whatever. But you see the distribution

910
00:49:17,640 --> 00:49:19,719
Speaker 1: of labor amongst the hives, that's got to be an

911
00:49:19,880 --> 00:49:22,759
Speaker 1: entire Yeah. But the other interesting thing is that this

912
00:49:23,320 --> 00:49:26,239
Speaker 1: with all these diseases and pests that beset honey bees

913
00:49:26,280 --> 00:49:29,600
Speaker 1: in the last couple of decades, it is Uh, there's

914
00:49:29,680 --> 00:49:34,759
Speaker 1: a whole logic, deductive logic sequence I go through when

915
00:49:34,800 --> 00:49:36,720
Speaker 1: I open a hive. I open a hive, I'm looking,

916
00:49:36,840 --> 00:49:39,880
Speaker 1: I'm listening, I'm smelling. Is there a coin there is

917
00:49:39,960 --> 00:49:42,319
Speaker 1: she laying? If not, what do I do? I come

918
00:49:42,400 --> 00:49:44,120
Speaker 1: home from a day in the in the b yards

919
00:49:44,480 --> 00:49:46,840
Speaker 1: out with the bees, I'm rung out, not only physically

920
00:49:46,920 --> 00:49:49,640
Speaker 1: but mentally. You wouldn't think that, but it is. And

921
00:49:49,800 --> 00:49:53,239
Speaker 1: and beekeepers tend to be above average intellect. You've got

922
00:49:53,360 --> 00:49:57,160
Speaker 1: to have a natural curiosity because and another interest. Economists

923
00:49:57,280 --> 00:50:01,719
Speaker 1: just average inte life. So so bas you're saying that

924
00:50:03,120 --> 00:50:06,839
Speaker 1: the beekeeping is a greater intellectual challenge than No, I'm

925
00:50:06,880 --> 00:50:09,200
Speaker 1: not saying greater, but that's what I'm here. I'm hearing.

926
00:50:09,800 --> 00:50:12,640
Speaker 1: Anyone can be an economist to be a beekeeper. And

927
00:50:12,800 --> 00:50:15,160
Speaker 1: I know economics, it's plenty, but it's it's it's a

928
00:50:15,239 --> 00:50:17,960
Speaker 1: di virgence. It's it's it's sort of a you know,

929
00:50:18,000 --> 00:50:19,960
Speaker 1: I'm a type of guy. I always work. I just

930
00:50:20,080 --> 00:50:23,360
Speaker 1: change the venue and and and that's what it amounts to.

931
00:50:23,480 --> 00:50:26,759
Speaker 1: Where you're you're shifting, you're shifting gears to to something else,

932
00:50:26,840 --> 00:50:29,840
Speaker 1: but you're still going through that that mental process of

933
00:50:30,400 --> 00:50:32,759
Speaker 1: trying to figure out what's going on there. It's like

934
00:50:32,920 --> 00:50:35,000
Speaker 1: it's like the economy you're trying to you're trying to

935
00:50:35,080 --> 00:50:36,840
Speaker 1: put all that we talked about this earlier, trying to

936
00:50:36,880 --> 00:50:38,920
Speaker 1: put all these pieces together and see where you come out.

937
00:50:39,400 --> 00:50:42,120
Speaker 1: And uh, and you're never can be certain and and

938
00:50:42,320 --> 00:50:46,480
Speaker 1: and be keeping Hey, the visistant visistitudes the nature are tremendous.

939
00:50:46,520 --> 00:50:49,360
Speaker 1: You do everything you possibly can. It's just like a forecast.

940
00:50:49,440 --> 00:50:52,480
Speaker 1: You cover all the bases and you're you're left a

941
00:50:53,120 --> 00:50:55,640
Speaker 1: certain amount of luck some rents from then. You know.

942
00:50:55,719 --> 00:50:58,320
Speaker 1: I just I just was speaking at a conference and

943
00:50:58,440 --> 00:51:02,400
Speaker 1: the exact same convert station came up with you do

944
00:51:02,840 --> 00:51:05,040
Speaker 1: X and Y and Z. They all seem so different.

945
00:51:05,080 --> 00:51:07,440
Speaker 1: In my answer was they're really the same thing. You

946
00:51:07,719 --> 00:51:10,920
Speaker 1: look at a variety of ambiguous inputs, try and figure

947
00:51:10,920 --> 00:51:14,440
Speaker 1: out what matters and what doesn't and reach a reasonable

948
00:51:14,960 --> 00:51:19,759
Speaker 1: conclusion within the context be keeping in economics, apparently the

949
00:51:19,840 --> 00:51:23,640
Speaker 1: same same basic the process is what's so similar even

950
00:51:23,680 --> 00:51:28,640
Speaker 1: though it's totally different. Um that that that that's quite fascinating.

951
00:51:29,040 --> 00:51:32,560
Speaker 1: So earlier we were talking a little bit about, um,

952
00:51:33,760 --> 00:51:35,600
Speaker 1: what it was like when you were researcher at Mary

953
00:51:35,719 --> 00:51:38,680
Speaker 1: lynch In a researcher at the Federal Reserve. What what

954
00:51:38,800 --> 00:51:44,600
Speaker 1: are some of your commentaries or research forecasts that you're

955
00:51:44,719 --> 00:51:48,200
Speaker 1: especially proud of that really have stood the test in

956
00:51:48,280 --> 00:51:53,120
Speaker 1: time or may have been unusually contrarian. What what stands

957
00:51:53,120 --> 00:51:55,560
Speaker 1: out to you? Well? I think I think the greatest

958
00:51:55,600 --> 00:51:59,759
Speaker 1: call I made was just one. I made a bullmark

959
00:52:00,040 --> 00:52:02,040
Speaker 1: that we're entering a von Rally of a lifetime. And

960
00:52:02,520 --> 00:52:05,520
Speaker 1: was that a lonely call? Where there are peoples? Barry

961
00:52:05,680 --> 00:52:09,680
Speaker 1: was so lonely. I wrote my first book in title

962
00:52:10,080 --> 00:52:14,400
Speaker 1: The title was is inflation ending? Question mark? Are you ready?

963
00:52:14,480 --> 00:52:17,560
Speaker 1: Question Mark? My answer to the first question, yes, Yes,

964
00:52:17,680 --> 00:52:21,080
Speaker 1: inflation is ending. We're going into a period of of

965
00:52:21,719 --> 00:52:24,920
Speaker 1: lower and lower inflation because my view is at government

966
00:52:25,760 --> 00:52:28,680
Speaker 1: excess spending is the route of inflation. The FED may

967
00:52:28,719 --> 00:52:31,640
Speaker 1: be the handmaiden and implementing you. But it's the government spending.

968
00:52:32,080 --> 00:52:35,239
Speaker 1: And we saw a revolt against government, starting with Proposition

969
00:52:35,320 --> 00:52:38,600
Speaker 1: thirteen in California in nineteen seventy eight and then Reagan's

970
00:52:38,640 --> 00:52:41,960
Speaker 1: election in nine eighty. And I said from that that

971
00:52:42,080 --> 00:52:44,640
Speaker 1: inflation was on the way out, and as a result,

972
00:52:44,920 --> 00:52:47,200
Speaker 1: we were. And so the answer to the second half

973
00:52:47,200 --> 00:52:50,200
Speaker 1: of the question, are you ready, no, because everybody was

974
00:52:50,280 --> 00:52:57,080
Speaker 1: betting on inflation. They had all their tangibles and their portfolios, uh, coins, antiques, artwork, goal, etcetera.

975
00:52:57,160 --> 00:52:59,040
Speaker 1: And I said, no, no, you don't have enough stocks

976
00:52:59,200 --> 00:53:02,480
Speaker 1: or bonds because they will benefit from this. Now, that

977
00:53:02,719 --> 00:53:05,720
Speaker 1: was a very lonely call that book. Mcgrawl hill finally

978
00:53:05,880 --> 00:53:11,600
Speaker 1: got it out in nobody but inflation really peaked in

979
00:53:11,719 --> 00:53:15,040
Speaker 1: nineteen eighty, but nobody believed. The sales of the book

980
00:53:15,080 --> 00:53:17,440
Speaker 1: were an absolute disaster. As a matter of fact, McGraw

981
00:53:17,560 --> 00:53:20,560
Speaker 1: hill gave us the last couple of thousand copies. They

982
00:53:20,600 --> 00:53:24,520
Speaker 1: didn't want him. But it was but interesting in six

983
00:53:25,200 --> 00:53:28,319
Speaker 1: By then it was clear that inflation was fading. Uh.

984
00:53:28,400 --> 00:53:30,920
Speaker 1: There were two ex post reviews. One was in the

985
00:53:31,000 --> 00:53:34,120
Speaker 1: Boston Globe and the other was a Seattle Post Intelligencer

986
00:53:34,680 --> 00:53:37,440
Speaker 1: and they both you know, and both of these business

987
00:53:37,560 --> 00:53:39,440
Speaker 1: editors said, I saw this book, Oh my god, it

988
00:53:39,560 --> 00:53:42,120
Speaker 1: was happening, and they and so they wrote reviews. Well,

989
00:53:42,160 --> 00:53:43,719
Speaker 1: of course that was his hand as a pocketing your

990
00:53:43,800 --> 00:53:46,000
Speaker 1: underwear because the book was long out of print. But

991
00:53:46,160 --> 00:53:49,000
Speaker 1: it was a paric victory. But but yeah, I mean

992
00:53:49,040 --> 00:53:51,080
Speaker 1: that was that was very longly. I don't think there

993
00:53:51,120 --> 00:53:54,920
Speaker 1: was anybody else, at least notable known forecaster who was

994
00:53:54,960 --> 00:53:57,439
Speaker 1: saying anything like that. So so let me push back

995
00:53:57,480 --> 00:54:00,480
Speaker 1: about your your claim that it's the government's bending and

996
00:54:00,600 --> 00:54:04,720
Speaker 1: deficits that cause inflation. We have a nineteen trillion dollar

997
00:54:05,160 --> 00:54:09,320
Speaker 1: federal deficit and yet inflation is well non existent and

998
00:54:09,480 --> 00:54:12,320
Speaker 1: and going hard. Yeah, it's it's uh, yeah, I have

999
00:54:12,480 --> 00:54:14,400
Speaker 1: to fill that out and say, it depends on the

1000
00:54:14,480 --> 00:54:17,080
Speaker 1: rest of the economy if you have an over employed

1001
00:54:17,120 --> 00:54:19,800
Speaker 1: economy to start with, and then you put all that

1002
00:54:19,960 --> 00:54:22,359
Speaker 1: government spending on top of it. But what you see,

1003
00:54:22,400 --> 00:54:25,120
Speaker 1: that's what happened in the late sixties and seventies very

1004
00:54:25,200 --> 00:54:28,160
Speaker 1: different today. You had, Yeah, you had a huge government

1005
00:54:28,239 --> 00:54:32,800
Speaker 1: spending on war, on poverty and war in Vietnam, and

1006
00:54:32,960 --> 00:54:35,960
Speaker 1: that really strained resources on top of a twenty year

1007
00:54:36,200 --> 00:54:42,000
Speaker 1: private sector bull market generated generated all that inflation. Well,

1008
00:54:42,040 --> 00:54:45,319
Speaker 1: again you've got the reversal that starting. And so now

1009
00:54:45,400 --> 00:54:48,040
Speaker 1: we have the retiring boomers, We have a whole lot

1010
00:54:48,120 --> 00:54:51,520
Speaker 1: of underemployment. People working part time would rather work full time.

1011
00:54:52,320 --> 00:54:55,200
Speaker 1: Um what else do we have in this environment? You

1012
00:54:55,320 --> 00:54:59,719
Speaker 1: have increased global Yeah, that that's that's I think that's

1013
00:54:59,760 --> 00:55:02,600
Speaker 1: been the greatest The greatest change in the last thirty

1014
00:55:02,680 --> 00:55:05,719
Speaker 1: years is globalization. And so let's talk about globalization, but

1015
00:55:05,800 --> 00:55:09,120
Speaker 1: I also want to get to I also want to

1016
00:55:09,120 --> 00:55:13,600
Speaker 1: get to increased productivity and increased automation as other factors

1017
00:55:13,680 --> 00:55:16,120
Speaker 1: that are driving this. So what has been the impact

1018
00:55:16,200 --> 00:55:22,440
Speaker 1: of globalization on wages both here in the US and worldwide? Well,

1019
00:55:22,480 --> 00:55:26,320
Speaker 1: it's a great equalizes are of wages obviously. UM. I

1020
00:55:26,440 --> 00:55:30,160
Speaker 1: had was very interesting. This goes back years ago. Milton

1021
00:55:30,200 --> 00:55:32,080
Speaker 1: Friedman had read one of my books. He was in

1022
00:55:32,520 --> 00:55:35,000
Speaker 1: San Francisco. He invited me in. It was in an

1023
00:55:35,320 --> 00:55:39,680
Speaker 1: apartment there, uh greeting me at the door, hadn't shaved

1024
00:55:39,719 --> 00:55:42,200
Speaker 1: in three days, had a bathrobe on. We sat there

1025
00:55:42,280 --> 00:55:46,040
Speaker 1: for about three hours talking about about inflation and wages

1026
00:55:46,080 --> 00:55:48,680
Speaker 1: and of course what was this Oh gosh, this was

1027
00:55:49,280 --> 00:55:52,319
Speaker 1: this is about the mid eighties. And and his point,

1028
00:55:52,360 --> 00:55:55,320
Speaker 1: of course is that that free markets govern everything, that

1029
00:55:55,400 --> 00:55:58,880
Speaker 1: there's nothing else but and and uh and and I

1030
00:55:59,080 --> 00:56:01,839
Speaker 1: was saying, well, you know, wages, you're here, You've got

1031
00:56:03,280 --> 00:56:05,520
Speaker 1: an hour you know for the U A W I

1032
00:56:05,600 --> 00:56:08,240
Speaker 1: think in this country and two dollars an hour in Mexico.

1033
00:56:08,840 --> 00:56:11,040
Speaker 1: And I said, you know, you think it's gonna happen,

1034
00:56:11,120 --> 00:56:14,320
Speaker 1: These are gonna equate. Well, they have come a lot closer.

1035
00:56:14,480 --> 00:56:16,640
Speaker 1: And and that's what that's what's happened, is that is

1036
00:56:16,680 --> 00:56:19,200
Speaker 1: that this is globalization. And of course you had a

1037
00:56:19,280 --> 00:56:23,560
Speaker 1: lot of American labor which was enjoying, uh was enjoying

1038
00:56:23,600 --> 00:56:26,279
Speaker 1: the fruits of basically isolation. I mean, we did not

1039
00:56:26,520 --> 00:56:30,480
Speaker 1: have global competition. But that's clearly changed. Yeah, that that's

1040
00:56:30,520 --> 00:56:32,480
Speaker 1: clearly changed. And so what it means is that we

1041
00:56:32,600 --> 00:56:37,280
Speaker 1: simply can I compete in in uh, basic manufacturing or anything.

1042
00:56:37,320 --> 00:56:40,560
Speaker 1: Even services. You know, you talk about doing routine legal services.

1043
00:56:40,640 --> 00:56:42,600
Speaker 1: They do that in India, any place they speak English,

1044
00:56:42,680 --> 00:56:46,040
Speaker 1: call centers and so on. So globalization has been a

1045
00:56:46,200 --> 00:56:49,879
Speaker 1: very very important factor. And we're dealing with the we're

1046
00:56:49,920 --> 00:56:52,719
Speaker 1: dealing with the aftermath of that right now. So let's

1047
00:56:52,800 --> 00:56:56,240
Speaker 1: let's along those lines. Let's talk about demographics and retiring

1048
00:56:56,320 --> 00:56:59,440
Speaker 1: baby boomers. What does that mean for the overall economy?

1049
00:56:59,480 --> 00:57:04,359
Speaker 1: What does that mean for job possibilities and wages? Well,

1050
00:57:04,600 --> 00:57:08,520
Speaker 1: what's interesting about that is that is that people are retiring.

1051
00:57:08,560 --> 00:57:10,480
Speaker 1: As a matter of fact, the reason the unemployment rate

1052
00:57:10,480 --> 00:57:14,919
Speaker 1: has come down uh is UH is basically the people

1053
00:57:15,000 --> 00:57:17,560
Speaker 1: dropping out of the labor for what percentage of the

1054
00:57:18,000 --> 00:57:21,360
Speaker 1: fall from ten point whatever to five point one percent

1055
00:57:21,480 --> 00:57:25,440
Speaker 1: unemployment is people leaving the way little labor for well,

1056
00:57:25,520 --> 00:57:27,720
Speaker 1: let's put it this way. If you didn't have if

1057
00:57:27,800 --> 00:57:30,480
Speaker 1: you hadn't had the if you hadn't had this participation rate,

1058
00:57:30,520 --> 00:57:33,200
Speaker 1: which is anybody sixteen and over who is either at

1059
00:57:33,320 --> 00:57:35,840
Speaker 1: working or actively looking for work, if you hadn't had

1060
00:57:35,880 --> 00:57:38,680
Speaker 1: that decline from the peak in February of two thousand,

1061
00:57:38,880 --> 00:57:43,560
Speaker 1: the unemployment rate today would not not not so that

1062
00:57:43,720 --> 00:57:48,240
Speaker 1: many people have left the workforce but are still of working. Well, well, no, no, no,

1063
00:57:48,440 --> 00:57:50,640
Speaker 1: that's everybody. Now, we we've got a lot of work

1064
00:57:50,680 --> 00:57:53,439
Speaker 1: on that. About six of that are people are over

1065
00:57:53,640 --> 00:57:57,720
Speaker 1: are people retiring the post of as retiring, but are

1066
00:57:58,160 --> 00:58:01,160
Speaker 1: middle aged people who said, you know, I can't find

1067
00:58:01,200 --> 00:58:03,520
Speaker 1: a job, And of course, a lot of younger people

1068
00:58:03,560 --> 00:58:05,760
Speaker 1: who said, I'm going to stay in college, I hope

1069
00:58:05,760 --> 00:58:07,320
Speaker 1: I get a better job. Of course a lot of

1070
00:58:07,360 --> 00:58:09,880
Speaker 1: them came out with big deaths but no better job prospects.

1071
00:58:10,240 --> 00:58:12,560
Speaker 1: But what's fascinating about this With older people, and you're

1072
00:58:12,560 --> 00:58:16,280
Speaker 1: talking about retiring poster or babies, the participation rates of

1073
00:58:16,440 --> 00:58:19,600
Speaker 1: people UH sixty five to seventy four have gone up,

1074
00:58:19,720 --> 00:58:23,040
Speaker 1: still pretty good lower, they're lower than younger people, but

1075
00:58:23,120 --> 00:58:26,080
Speaker 1: they're going up and over seventy five. And why is that?

1076
00:58:26,200 --> 00:58:28,760
Speaker 1: Two reasons. One is people in better health, they're living longer,

1077
00:58:28,800 --> 00:58:30,959
Speaker 1: they want to stay actively. Also, a lot of people

1078
00:58:31,000 --> 00:58:33,680
Speaker 1: simply do not have the access to retire, So you're

1079
00:58:33,720 --> 00:58:36,960
Speaker 1: getting some very interesting diamics within that. But but the

1080
00:58:37,040 --> 00:58:39,560
Speaker 1: bottom line is there are a lot of people out

1081
00:58:39,600 --> 00:58:44,400
Speaker 1: there now training, having the skills to take jobs. That's

1082
00:58:44,400 --> 00:58:46,560
Speaker 1: another issue. But if if you assume, if you get

1083
00:58:46,640 --> 00:58:50,560
Speaker 1: people properly trained, there's there's really no shortage of labor

1084
00:58:50,560 --> 00:58:54,760
Speaker 1: in the foreseeable future, that's amazing. So let's talk along

1085
00:58:54,880 --> 00:59:01,280
Speaker 1: related lines. Let's talk about productivity gains and you directly automation.

1086
00:59:01,640 --> 00:59:04,720
Speaker 1: What is the impact of Like in my office, I know,

1087
00:59:04,920 --> 00:59:08,240
Speaker 1: we were six seven, we're now seven people were about

1088
00:59:08,240 --> 00:59:10,960
Speaker 1: to be eight people. I know that to do what

1089
00:59:11,160 --> 00:59:15,800
Speaker 1: we do thirty years ago would have taken fifty people,

1090
00:59:16,360 --> 00:59:21,120
Speaker 1: and thanks to computer technology and software, each person does.

1091
00:59:22,480 --> 00:59:25,080
Speaker 1: We don't have a bookkeeper. We outsource that to uh

1092
00:59:25,360 --> 00:59:29,120
Speaker 1: an accountant who looks at stuff quarterly, who sees everything online.

1093
00:59:29,560 --> 00:59:31,200
Speaker 1: A lot of the stuff that we used to do

1094
00:59:31,480 --> 00:59:36,040
Speaker 1: with an assistant and a secretary, we that's all automatic.

1095
00:59:36,120 --> 00:59:38,920
Speaker 1: It's all done on the on the everybody types. It's

1096
00:59:39,000 --> 00:59:42,160
Speaker 1: not like you can be an executive type. And so

1097
00:59:42,320 --> 00:59:45,440
Speaker 1: you're doing entering everything into the into the computer. And

1098
00:59:45,520 --> 00:59:49,040
Speaker 1: then when you look at different tools like like what

1099
00:59:49,320 --> 00:59:53,080
Speaker 1: we get from Salesforce as an example, as a sales

1100
00:59:53,200 --> 00:59:57,200
Speaker 1: management of CRM tool, that would have been somebody's full

1101
00:59:57,280 --> 00:59:59,360
Speaker 1: time job and now it's one piece of software for

1102
01:00:00,040 --> 01:00:04,360
Speaker 1: eight people, it's amazing how much more productive each of

1103
01:00:04,480 --> 01:00:08,640
Speaker 1: us are. What does that do to to job creation? Well, uh,

1104
01:00:10,320 --> 01:00:14,200
Speaker 1: you know, the whole the whole idea of industrialization ever

1105
01:00:14,280 --> 01:00:17,160
Speaker 1: since the industry revolution started in England and New England

1106
01:00:17,200 --> 01:00:19,960
Speaker 1: in late seventeen hundreds, was that it destroys a lot

1107
01:00:20,000 --> 01:00:22,800
Speaker 1: of jobs. You know that, you know that the origin

1108
01:00:22,880 --> 01:00:27,360
Speaker 1: of the word saboteur okay, sabbath. It comes from sabbath

1109
01:00:27,440 --> 01:00:30,920
Speaker 1: which were wooden shoes, and earlier the ductal Revolution, the

1110
01:00:31,000 --> 01:00:33,600
Speaker 1: workers wore wooden shoes, would grind him in the machines,

1111
01:00:33,640 --> 01:00:35,800
Speaker 1: direct the machines because it was putting people out of work.

1112
01:00:36,120 --> 01:00:38,160
Speaker 1: They wanted to go back to hand weavers and ah as.

1113
01:00:38,160 --> 01:00:41,880
Speaker 1: You've always had this specter of of the destruction of

1114
01:00:42,480 --> 01:00:45,360
Speaker 1: jobs by automation. But but what has happened. Of course,

1115
01:00:45,400 --> 01:00:48,800
Speaker 1: it's created more jobs, and higher level jobs and higher

1116
01:00:48,880 --> 01:00:52,080
Speaker 1: page jobs with more productivity, and that's the basis of

1117
01:00:52,160 --> 01:00:55,040
Speaker 1: living standards. We've come to a we've come to a

1118
01:00:55,080 --> 01:00:57,720
Speaker 1: bit of a gap recently with globalization. That's one of

1119
01:00:57,720 --> 01:01:00,600
Speaker 1: the reasons I think globalization is so important because it's

1120
01:01:00,640 --> 01:01:02,920
Speaker 1: given you this huge gap, in other words, more rather

1121
01:01:03,000 --> 01:01:07,240
Speaker 1: than a gradual increase in this transfer and and and

1122
01:01:07,440 --> 01:01:10,320
Speaker 1: upgrading and so on and getting rid of the secretaries

1123
01:01:10,360 --> 01:01:13,240
Speaker 1: and the in house accountants and all the stuff you mentioned. Uh,

1124
01:01:13,480 --> 01:01:16,720
Speaker 1: that's happened overnight, and it is simply left a lot

1125
01:01:16,760 --> 01:01:20,040
Speaker 1: of people in the US and other western Western economies

1126
01:01:20,760 --> 01:01:24,120
Speaker 1: who simply are are not making that transition and not

1127
01:01:24,280 --> 01:01:26,960
Speaker 1: prepared to that and it may be a generational deal,

1128
01:01:27,000 --> 01:01:28,320
Speaker 1: and I don't think it's the end of the world,

1129
01:01:28,440 --> 01:01:31,680
Speaker 1: but it is a it is almost a a quantum

1130
01:01:32,120 --> 01:01:36,040
Speaker 1: shift shift there because of globalization. So so you mentioned

1131
01:01:36,080 --> 01:01:38,720
Speaker 1: that as we've gone through the industrial era and as

1132
01:01:38,800 --> 01:01:43,840
Speaker 1: we've seen um more and more heavy manufacturing put people

1133
01:01:43,880 --> 01:01:45,920
Speaker 1: out of work, but at the same time creat other jobs.

1134
01:01:46,600 --> 01:01:53,640
Speaker 1: When we look at technology technical especially biotech, internet, computer technology,

1135
01:01:54,280 --> 01:01:59,040
Speaker 1: the amount of job loss that that's created, is that

1136
01:01:59,280 --> 01:02:02,160
Speaker 1: really going to be offset by new and related jobs

1137
01:02:02,680 --> 01:02:04,800
Speaker 1: in that space, Because that's the big concern of a

1138
01:02:04,840 --> 01:02:07,720
Speaker 1: lot of people, is that there are people who are

1139
01:02:07,800 --> 01:02:12,560
Speaker 1: creating software, creating technology that allows each person to do

1140
01:02:12,720 --> 01:02:16,800
Speaker 1: so much more. You've eliminated a huge swath of jobs.

1141
01:02:17,040 --> 01:02:19,120
Speaker 1: The jobs are being created just where that Where are

1142
01:02:19,160 --> 01:02:22,360
Speaker 1: they geographically? In other ways, are they in this country

1143
01:02:23,160 --> 01:02:26,720
Speaker 1: or are they in China? And now low end manufacturing

1144
01:02:26,800 --> 01:02:30,680
Speaker 1: moving on from China to lower cost areas Bangladesh, Vietnam,

1145
01:02:31,080 --> 01:02:33,640
Speaker 1: Pakistan and so on. Well, we see the iPhone which

1146
01:02:33,720 --> 01:02:36,240
Speaker 1: is designed in the in the United States, design in

1147
01:02:36,240 --> 01:02:41,320
Speaker 1: San Francisco, but essentially it's manufactured in China, with components

1148
01:02:41,360 --> 01:02:43,920
Speaker 1: and other parts made all of the world. But the

1149
01:02:44,040 --> 01:02:47,960
Speaker 1: bulk of which are in low cost countries. So what

1150
01:02:48,200 --> 01:02:51,480
Speaker 1: is and yet there's also an app economy where all

1151
01:02:51,520 --> 01:02:53,600
Speaker 1: these software designers and all these people are making a

1152
01:02:53,680 --> 01:02:58,320
Speaker 1: whole run of different software to put on that that

1153
01:02:58,480 --> 01:03:05,320
Speaker 1: work pretty much anywhere, but they're mostly the United States, UM, Europe, India, Japan,

1154
01:03:05,440 --> 01:03:10,000
Speaker 1: places like that. So is that technology creating more jobs?

1155
01:03:10,040 --> 01:03:13,000
Speaker 1: And it's creates creating more jobs, and of course it's

1156
01:03:13,080 --> 01:03:16,880
Speaker 1: it's adding to income polarization because those are those yeah,

1157
01:03:17,000 --> 01:03:19,360
Speaker 1: those are those are high skilled jobs, those are high

1158
01:03:19,400 --> 01:03:24,080
Speaker 1: paid jobs. But what you've eliminated are these auto factories

1159
01:03:24,080 --> 01:03:26,720
Speaker 1: in this country that employed five thousand people that that's

1160
01:03:26,760 --> 01:03:28,880
Speaker 1: out Now. One of the interesting things coming out of this,

1161
01:03:29,560 --> 01:03:31,800
Speaker 1: and particularly with what's going on right now, we've had

1162
01:03:32,240 --> 01:03:35,840
Speaker 1: eight years of basically no real income growth in the

1163
01:03:36,000 --> 01:03:40,840
Speaker 1: US and really Europe, Japan they developed world nowers adjusted

1164
01:03:40,880 --> 01:03:44,840
Speaker 1: for inflation, no no growth. People get frustrated after a

1165
01:03:44,920 --> 01:03:47,760
Speaker 1: while of that, and what's happening. We're beginning to see

1166
01:03:47,800 --> 01:03:51,920
Speaker 1: that expressed politically. For example, in France, the National Front

1167
01:03:52,360 --> 01:03:55,680
Speaker 1: headed by this woman Maria la Penn. She may be

1168
01:03:55,760 --> 01:03:58,320
Speaker 1: the next president of France. It's a very you may

1169
01:03:58,440 --> 01:04:00,680
Speaker 1: end up with Bernie Sanders or done Trump in the

1170
01:04:01,480 --> 01:04:04,920
Speaker 1: in the US, and and of course John Baynor, you know,

1171
01:04:07,120 --> 01:04:10,800
Speaker 1: and there's this reaction to politicians in the center and

1172
01:04:10,920 --> 01:04:14,200
Speaker 1: looking at the fringes UK the head of the new

1173
01:04:14,280 --> 01:04:17,120
Speaker 1: head of the Labor Party. I mean, you're getting very

1174
01:04:17,200 --> 01:04:20,200
Speaker 1: interesting expressions of this. UH. And of course you know

1175
01:04:20,320 --> 01:04:22,880
Speaker 1: we're not talking about French revolutions now where people out

1176
01:04:22,920 --> 01:04:25,160
Speaker 1: there tear it down the beast steel, but it is

1177
01:04:25,400 --> 01:04:28,120
Speaker 1: it is a similar kind of impulse and we could

1178
01:04:28,200 --> 01:04:31,920
Speaker 1: get some very interesting political ramifications. So we just saw

1179
01:04:32,000 --> 01:04:37,240
Speaker 1: that in Greece with Left coalition. Although I will tell

1180
01:04:37,320 --> 01:04:41,040
Speaker 1: you the craziest thing, so we're recording this UH in

1181
01:04:41,120 --> 01:04:44,400
Speaker 1: the beginning of fall two thousand and fifteen, so we

1182
01:04:44,480 --> 01:04:46,320
Speaker 1: don't know the outcome of the election for any of

1183
01:04:46,400 --> 01:04:48,560
Speaker 1: you in the future listening to this. We don't know

1184
01:04:48,640 --> 01:04:50,840
Speaker 1: a lot of things. But one of the things that

1185
01:04:50,920 --> 01:04:54,280
Speaker 1: I find fascinating is when you look at the shocking

1186
01:04:54,400 --> 01:04:58,760
Speaker 1: and sudden rise of Donald Trump politically, he's much more

1187
01:04:58,880 --> 01:05:03,480
Speaker 1: centrist then either the bulk of the Republicans on the

1188
01:05:03,600 --> 01:05:05,560
Speaker 1: right and the bulk of the Democrats on the left.

1189
01:05:06,720 --> 01:05:11,480
Speaker 1: I'm amazed that when you strip away the bluster. He's

1190
01:05:11,720 --> 01:05:16,320
Speaker 1: kind of a centrist, old school politician. How did who

1191
01:05:16,360 --> 01:05:18,360
Speaker 1: would have saw that coming? A few Yeah, but you know,

1192
01:05:18,440 --> 01:05:20,480
Speaker 1: it's a hell raising aspect. It's like what was that

1193
01:05:20,600 --> 01:05:23,600
Speaker 1: movie Network News where the guys because you know, I'm

1194
01:05:23,680 --> 01:05:27,400
Speaker 1: not going to take it an Yeah, absolutely, I mean

1195
01:05:27,680 --> 01:05:30,000
Speaker 1: it's it's that it's that same kind of the same

1196
01:05:30,120 --> 01:05:32,960
Speaker 1: kind of reaction, and that's what he's Bernie Sanders. I mean,

1197
01:05:33,080 --> 01:05:34,600
Speaker 1: of course he's way to the left, but it's that

1198
01:05:34,720 --> 01:05:37,720
Speaker 1: same kind of same kind of appeal. It's kind of saying,

1199
01:05:38,000 --> 01:05:41,480
Speaker 1: the centers politicians have not solved the problems. We got

1200
01:05:41,600 --> 01:05:43,840
Speaker 1: to do something else, and and there's a there's a

1201
01:05:43,880 --> 01:05:46,000
Speaker 1: big hearing for that kind of thing. So this is

1202
01:05:46,080 --> 01:05:48,440
Speaker 1: a this is a this is a kind of a

1203
01:05:48,600 --> 01:05:51,160
Speaker 1: cycle within the cycle, if you want to use cycles.

1204
01:05:51,200 --> 01:05:53,000
Speaker 1: And we talked about whether they're relevant or not. But

1205
01:05:53,120 --> 01:05:55,680
Speaker 1: you've had you've had globalization going on for you know,

1206
01:05:55,720 --> 01:05:59,240
Speaker 1: about three decades. But now in the aftermath of the

1207
01:05:59,560 --> 01:06:03,240
Speaker 1: global Great Recession oh seven oh nine, we're having this

1208
01:06:03,360 --> 01:06:05,640
Speaker 1: period of slow growth, as I called the age of

1209
01:06:05,720 --> 01:06:09,760
Speaker 1: d leveraging, no no growth and real incomes. And and

1210
01:06:09,880 --> 01:06:12,040
Speaker 1: as a result, I think the combination of these things

1211
01:06:12,160 --> 01:06:14,360
Speaker 1: is putting a lot of pressure on the political system

1212
01:06:14,400 --> 01:06:17,040
Speaker 1: and and the conventional politicians really don't know how to

1213
01:06:17,080 --> 01:06:18,760
Speaker 1: react to this. So let me ask you a question

1214
01:06:18,800 --> 01:06:21,320
Speaker 1: about that. And I'm not sure where I pulled this

1215
01:06:21,480 --> 01:06:24,440
Speaker 1: number from, but there was some news article out not

1216
01:06:24,600 --> 01:06:28,520
Speaker 1: too long ago that said, the middle class has not

1217
01:06:28,760 --> 01:06:33,560
Speaker 1: seen in real terms, um forget nominal terms, but in

1218
01:06:33,640 --> 01:06:37,400
Speaker 1: real terms, has not really seen wage gains since nineteen three.

1219
01:06:37,840 --> 01:06:40,720
Speaker 1: I think that's I think that's I think that's probably valid. Yeah,

1220
01:06:40,760 --> 01:06:44,120
Speaker 1: if you look at if you look at real wages

1221
01:06:44,360 --> 01:06:47,640
Speaker 1: and uh, you know that pretty much is that their

1222
01:06:47,640 --> 01:06:50,920
Speaker 1: insurance costs are up in the Indian real family income,

1223
01:06:51,000 --> 01:06:54,280
Speaker 1: That's that's what those statistics show you. And and you

1224
01:06:54,360 --> 01:06:56,680
Speaker 1: know the growth has has come on on the on

1225
01:06:56,800 --> 01:06:59,040
Speaker 1: the top. There's a lot of income redistribution to look

1226
01:06:59,080 --> 01:07:01,640
Speaker 1: people on the bottom. And you know, people can say, oh,

1227
01:07:01,720 --> 01:07:03,560
Speaker 1: this is this is terrible, and of course the pope

1228
01:07:03,640 --> 01:07:06,840
Speaker 1: is that was his theme as as well. But you know,

1229
01:07:06,960 --> 01:07:08,880
Speaker 1: you say, if you if you have rapid growth, if

1230
01:07:08,920 --> 01:07:11,880
Speaker 1: you have a dynamic economy, it is going to sort

1231
01:07:11,920 --> 01:07:15,480
Speaker 1: out the people who have the skills in order to participate.

1232
01:07:16,080 --> 01:07:19,760
Speaker 1: You look at China. Look how many billionaires are in China?

1233
01:07:20,040 --> 01:07:21,600
Speaker 1: And you say, well, yeah, but this is a country

1234
01:07:21,680 --> 01:07:24,080
Speaker 1: with a average income of what about a sixth of

1235
01:07:24,160 --> 01:07:28,400
Speaker 1: what we have. But yet when you see dynamics the

1236
01:07:28,520 --> 01:07:30,480
Speaker 1: people who take up, now you can say, well, that's

1237
01:07:30,560 --> 01:07:33,800
Speaker 1: not that's not equal distribution. But that's a judgment call,

1238
01:07:33,920 --> 01:07:36,160
Speaker 1: that's not a market call. So what does the United

1239
01:07:36,200 --> 01:07:39,280
Speaker 1: States need to do to sort of restart that economic

1240
01:07:39,360 --> 01:07:43,280
Speaker 1: engine and go from forget five percent, how about going

1241
01:07:43,440 --> 01:07:46,640
Speaker 1: from two percent to over three percent? Well, I think

1242
01:07:46,800 --> 01:07:48,919
Speaker 1: I think a certain extent, it's really just a matter

1243
01:07:49,080 --> 01:07:52,440
Speaker 1: of having patients and letting this whole agent be leveraging

1244
01:07:52,440 --> 01:07:54,680
Speaker 1: and run its course. Now, once people are no longer

1245
01:07:54,800 --> 01:07:57,400
Speaker 1: buried with debt they picked up in the last cycle,

1246
01:07:58,080 --> 01:08:00,520
Speaker 1: that's right activity that's after that, we are going to

1247
01:08:00,600 --> 01:08:03,280
Speaker 1: see a return to rapid growth and it will be

1248
01:08:03,480 --> 01:08:07,480
Speaker 1: led by by technology and productivity. So you're up for

1249
01:08:07,520 --> 01:08:10,600
Speaker 1: a guy who's says the bond bull market is still here.

1250
01:08:10,680 --> 01:08:13,200
Speaker 1: You're fairly optimistic. Oh, I am in the long run,

1251
01:08:13,360 --> 01:08:15,440
Speaker 1: very much so. And one of the reasons is my

1252
01:08:15,480 --> 01:08:18,799
Speaker 1: basic philosophy. You know, I mean, right now, the easy

1253
01:08:19,200 --> 01:08:23,280
Speaker 1: long term uh forecast to sell is slow growth forever.

1254
01:08:24,240 --> 01:08:26,920
Speaker 1: Because everybody looks around us. That's what I see right on, brother,

1255
01:08:27,560 --> 01:08:31,280
Speaker 1: You look at people like like Bob Gordon, Professor Northwestern.

1256
01:08:31,880 --> 01:08:35,760
Speaker 1: He's going around saying everything that is really productive, that's

1257
01:08:35,800 --> 01:08:38,680
Speaker 1: worth inventing, has been invented. Modern, by the way, we've

1258
01:08:38,760 --> 01:08:41,120
Speaker 1: heard that throughout the centuries, and it's always been wrong.

1259
01:08:41,280 --> 01:08:44,799
Speaker 1: Modern ma enthusian, and it sells very well. Neil Ferguson

1260
01:08:44,840 --> 01:08:48,719
Speaker 1: at Harvard, Uh, things are being dragged down by dragged

1261
01:08:48,760 --> 01:08:51,320
Speaker 1: down by regulation and so on. Larry Summers, you know,

1262
01:08:52,280 --> 01:08:56,000
Speaker 1: democratic fergusonsest stick to history. He's a terrible economic connentator.

1263
01:08:56,360 --> 01:08:59,240
Speaker 1: Every time he talks about economics, he manages to get something. Well,

1264
01:08:59,280 --> 01:09:03,320
Speaker 1: it's not major. But what what I'm saying, Barry, is

1265
01:09:03,400 --> 01:09:07,720
Speaker 1: that that's the easy cell. And you know, I'm always yeah,

1266
01:09:07,760 --> 01:09:10,400
Speaker 1: it's yeah, And I'm always looking for, you know, where's

1267
01:09:10,400 --> 01:09:12,760
Speaker 1: the hidden flaw that that's that's that's how I made

1268
01:09:12,800 --> 01:09:16,519
Speaker 1: my career, is looking for where's the where's the why

1269
01:09:16,640 --> 01:09:18,080
Speaker 1: is it going to go wrong? And in this case,

1270
01:09:18,720 --> 01:09:21,559
Speaker 1: you know, for example, they say that, uh, Gordon says

1271
01:09:22,200 --> 01:09:26,000
Speaker 1: that the Internet and so on is finished. Computers, it's

1272
01:09:26,040 --> 01:09:28,800
Speaker 1: all realized I think those things are more in their

1273
01:09:28,840 --> 01:09:31,760
Speaker 1: infancy than there are for I mean, just just you

1274
01:09:31,960 --> 01:09:35,960
Speaker 1: be a couple of examples. The American Industrial Revolution started

1275
01:09:35,960 --> 01:09:39,640
Speaker 1: in the late seventeen hundreds, grew like topsy, but it

1276
01:09:39,720 --> 01:09:42,559
Speaker 1: didn't get big enough to move the economy until after

1277
01:09:42,640 --> 01:09:47,840
Speaker 1: the Civil War. I mean it ter yeah, railroads again

1278
01:09:47,880 --> 01:09:50,639
Speaker 1: they started l seventeen hundreds, not until the latter half

1279
01:09:50,680 --> 01:09:53,120
Speaker 1: of the nineteenth century. I mean, it takes a long

1280
01:09:53,240 --> 01:09:56,560
Speaker 1: time for these things. And you know, you look at you,

1281
01:09:56,640 --> 01:09:58,400
Speaker 1: and I have have cell phone. I mean this has

1282
01:09:58,400 --> 01:10:01,240
Speaker 1: got more computer partner I b M three sixty this

1283
01:10:01,520 --> 01:10:04,639
Speaker 1: this little gasht in your pocket. I jokingly tell people

1284
01:10:04,800 --> 01:10:07,519
Speaker 1: there's more computing power on this than took Man to

1285
01:10:07,600 --> 01:10:10,920
Speaker 1: the moon with it really is. And and I look,

1286
01:10:10,960 --> 01:10:13,040
Speaker 1: and I was taking some pictures and here I am

1287
01:10:13,120 --> 01:10:15,400
Speaker 1: on our beach house here, you know, at home around

1288
01:10:15,880 --> 01:10:17,920
Speaker 1: I've got just where it records where it is. I mean,

1289
01:10:17,960 --> 01:10:20,280
Speaker 1: it's a big brother knows where you are. But but

1290
01:10:20,560 --> 01:10:25,360
Speaker 1: but my opinion that we are more in the infancy

1291
01:10:25,439 --> 01:10:28,760
Speaker 1: than we are finished on these new technology. Biotechnology, I

1292
01:10:28,840 --> 01:10:31,479
Speaker 1: think is is much much more in its infancy and

1293
01:10:31,960 --> 01:10:34,479
Speaker 1: what that is going to do for productivity growth in

1294
01:10:34,560 --> 01:10:36,760
Speaker 1: the future. Now again, you're gonna have people who have

1295
01:10:36,880 --> 01:10:39,360
Speaker 1: the right training. But you know, one of the problems

1296
01:10:39,640 --> 01:10:41,760
Speaker 1: we have in this country. One of the problems we

1297
01:10:41,880 --> 01:10:44,360
Speaker 1: have in this problem country. And there's a different topics,

1298
01:10:44,400 --> 01:10:47,800
Speaker 1: but I think related is the education system and and

1299
01:10:48,080 --> 01:10:51,360
Speaker 1: and you know, we have the attitude, Um, we have

1300
01:10:51,520 --> 01:10:54,240
Speaker 1: the attitude that everybody ought to go to college. And

1301
01:10:54,320 --> 01:10:57,080
Speaker 1: it is true that people with college educations make more

1302
01:10:57,160 --> 01:11:01,680
Speaker 1: than high school grads. But you can't prove causality with statistics.

1303
01:11:02,280 --> 01:11:05,439
Speaker 1: I guarantee you positively, absolutely, every time there's a total

1304
01:11:05,479 --> 01:11:07,679
Speaker 1: eclipse of the of the sun, if you go outside

1305
01:11:07,720 --> 01:11:10,880
Speaker 1: and beat a drum, it will go away hard percent correlation,

1306
01:11:11,080 --> 01:11:15,400
Speaker 1: no causality. The reality is, in my view, smart people

1307
01:11:15,479 --> 01:11:18,280
Speaker 1: go to college. But college doesn't make you smart. And

1308
01:11:18,360 --> 01:11:20,960
Speaker 1: I think we need to recognize that and say, Okay,

1309
01:11:21,000 --> 01:11:22,920
Speaker 1: there are a lot of people who can have very

1310
01:11:23,000 --> 01:11:26,400
Speaker 1: credible jobs. Hey, what's the last time you hired a

1311
01:11:26,439 --> 01:11:29,160
Speaker 1: plumber to clean out a toilet? News charge your hundred

1312
01:11:29,200 --> 01:11:31,720
Speaker 1: bucks for fifteen minutes work. I mean, you know, there

1313
01:11:31,760 --> 01:11:35,400
Speaker 1: are a lot of jobs that are not college educations,

1314
01:11:35,479 --> 01:11:39,120
Speaker 1: but they're certainly very credible. There's six estimates are the

1315
01:11:39,200 --> 01:11:42,280
Speaker 1: six hundred thousand jobs going begging now for people with

1316
01:11:42,360 --> 01:11:45,240
Speaker 1: computer skills to work in factories. And one of the

1317
01:11:45,280 --> 01:11:48,160
Speaker 1: things that's happening to solve that is the Germans. They

1318
01:11:48,200 --> 01:11:52,120
Speaker 1: have a very strong apprenticeship program history. They brought a

1319
01:11:52,200 --> 01:11:54,479
Speaker 1: lot of their plants in the southeast and this country

1320
01:11:55,479 --> 01:11:58,160
Speaker 1: and they have these apprenticeship programs combined with two year

1321
01:11:58,200 --> 01:12:01,080
Speaker 1: community college degrees, and these guys come out and they're

1322
01:12:01,200 --> 01:12:04,120
Speaker 1: very well paid. And American companies are emulating that same

1323
01:12:04,200 --> 01:12:06,160
Speaker 1: kind of thing. So I think that's one of the

1324
01:12:06,479 --> 01:12:09,479
Speaker 1: most exciting things in education that this isn't say everybody,

1325
01:12:09,600 --> 01:12:12,200
Speaker 1: and you know, we have a college for any for

1326
01:12:12,360 --> 01:12:16,200
Speaker 1: any intellectual capability in this country. Look at the poor

1327
01:12:16,280 --> 01:12:20,400
Speaker 1: profit college is absolute disaster total. They wouldn't exist without

1328
01:12:20,439 --> 01:12:22,800
Speaker 1: government subsidies and it is just a waste of moth.

1329
01:12:22,920 --> 01:12:25,120
Speaker 1: They came about on their own. Beginning, there was a

1330
01:12:25,320 --> 01:12:28,120
Speaker 1: huge movement to the private sector can do this on

1331
01:12:28,160 --> 01:12:31,000
Speaker 1: their own. And once they figured out they could suckle

1332
01:12:31,080 --> 01:12:33,920
Speaker 1: off the teat of Uncle Sam, they were all over

1333
01:12:34,600 --> 01:12:37,360
Speaker 1: and there. Sure, and you know it's an entrepreneur Okay,

1334
01:12:37,439 --> 01:12:40,840
Speaker 1: why not? You know, you know, because we know where

1335
01:12:40,840 --> 01:12:43,240
Speaker 1: it helps making the money money, the old fashioned way,

1336
01:12:43,360 --> 01:12:45,760
Speaker 1: skill luck, Clair biyance Brand's higher work, and so much

1337
01:12:45,800 --> 01:12:50,240
Speaker 1: government subsidy you can't miss until they collapse under their

1338
01:12:50,280 --> 01:12:53,760
Speaker 1: own way. So so you're really a pretty optimistic guy

1339
01:12:53,800 --> 01:12:56,200
Speaker 1: about the future of America. I am, I am, I am.

1340
01:12:56,320 --> 01:12:58,400
Speaker 1: I think we've got to get through this. This, this

1341
01:12:58,600 --> 01:13:01,680
Speaker 1: the leveraging. How long does at last? Normally? You know,

1342
01:13:01,720 --> 01:13:04,439
Speaker 1: if you look at the Ryano Rokoff data, it was

1343
01:13:04,520 --> 01:13:08,240
Speaker 1: waiting for it goes ten years. Now they are that

1344
01:13:08,560 --> 01:13:13,560
Speaker 1: data is over centuries. It's developed countries, it's banana republics.

1345
01:13:13,560 --> 01:13:17,880
Speaker 1: There's a lot of apples and oranges recently, but right now,

1346
01:13:18,360 --> 01:13:20,640
Speaker 1: right well recently, you know, if you go back to

1347
01:13:20,680 --> 01:13:23,280
Speaker 1: the thirties, it was about ten years. We're eight years

1348
01:13:23,320 --> 01:13:25,439
Speaker 1: into this now. At the rate we're going, it may

1349
01:13:25,560 --> 01:13:28,599
Speaker 1: take longer than another two years to complete, but I'm

1350
01:13:28,680 --> 01:13:32,360
Speaker 1: convinced that it will be twelve years, fifteen years maybe

1351
01:13:32,439 --> 01:13:34,559
Speaker 1: something that if you use if you use a straight line,

1352
01:13:34,600 --> 01:13:37,800
Speaker 1: the financial sector in this country has probably got another uh,

1353
01:13:38,000 --> 01:13:40,679
Speaker 1: five or six years ago. The consumer working off xces

1354
01:13:40,800 --> 01:13:44,360
Speaker 1: Stat's probably maybe a little bit longer, maybe seven eight years.

1355
01:13:44,720 --> 01:13:47,479
Speaker 1: But that's just drawing straight lines. So you're guessing we're

1356
01:13:47,560 --> 01:13:52,439
Speaker 1: halfway through. And as I mentioned earlier that one of

1357
01:13:52,520 --> 01:13:56,519
Speaker 1: the really interesting questions is is our is the electric

1358
01:13:56,640 --> 01:13:59,080
Speaker 1: going to have the patience to go through this, or

1359
01:13:59,080 --> 01:14:00,960
Speaker 1: we're gonna get a react action. We're gonna get some

1360
01:14:01,479 --> 01:14:05,840
Speaker 1: oddball uh in oddballs in Congress and administration. Are we

1361
01:14:05,920 --> 01:14:09,040
Speaker 1: going to see a big push for goverment stimulus? And

1362
01:14:09,120 --> 01:14:10,600
Speaker 1: if we do, I think it will be fiscal. It

1363
01:14:10,640 --> 01:14:13,200
Speaker 1: won't be monetary, because you know we've already I think

1364
01:14:13,240 --> 01:14:18,280
Speaker 1: we've exhausted the monetary Yeah. Well that's the traditional listen.

1365
01:14:18,439 --> 01:14:22,519
Speaker 1: Following the Great Depression, even following the two thousand recession,

1366
01:14:22,920 --> 01:14:25,840
Speaker 1: we saw a huge surge of fiscal stimulus that's been

1367
01:14:25,960 --> 01:14:29,320
Speaker 1: more or less missing this go around. What what would

1368
01:14:29,360 --> 01:14:32,360
Speaker 1: the impact of that be to the de leveraging process.

1369
01:14:32,800 --> 01:14:35,600
Speaker 1: Well it uh, I don't know that would necessary, it

1370
01:14:35,600 --> 01:14:38,760
Speaker 1: would necessarily reverse it. I mean, but it it could

1371
01:14:38,880 --> 01:14:41,439
Speaker 1: mitigate it. It could speed it up a little bit,

1372
01:14:41,560 --> 01:14:43,519
Speaker 1: speed it up a little bit. Yeah, and could speed

1373
01:14:43,600 --> 01:14:46,360
Speaker 1: it up. I just want my roads paved. You know.

1374
01:14:46,560 --> 01:14:49,040
Speaker 1: People accused me of being uh, well, well you're a

1375
01:14:49,080 --> 01:14:51,960
Speaker 1: big guy. No, No, I'm tired of replacing axles I

1376
01:14:52,080 --> 01:14:54,920
Speaker 1: want you know my run flat tires show up as

1377
01:14:54,960 --> 01:14:57,000
Speaker 1: flat because there were so many people know that. That's

1378
01:14:57,200 --> 01:15:00,519
Speaker 1: That's a big difference between monetary and fiscal policy. Monetary

1379
01:15:00,560 --> 01:15:03,479
Speaker 1: policy is a very blunt instrument. The Fed and other

1380
01:15:03,560 --> 01:15:05,720
Speaker 1: central banks you can raise and lower interest rates, can

1381
01:15:05,760 --> 01:15:08,519
Speaker 1: buy and sell securities. That's yet and beyond that, the

1382
01:15:08,560 --> 01:15:11,200
Speaker 1: ship's fallwhard and you don't really see that immediately. Yeah,

1383
01:15:11,200 --> 01:15:14,680
Speaker 1: the ships fall where they may. Fiscal policy can be pinpointed.

1384
01:15:15,080 --> 01:15:17,439
Speaker 1: If you want to improve the roads, you put money

1385
01:15:17,479 --> 01:15:20,120
Speaker 1: into road construction, if you want to help the unemployed,

1386
01:15:20,240 --> 01:15:23,640
Speaker 1: increase unemployment benefits. It can be very very specific. It

1387
01:15:23,680 --> 01:15:25,679
Speaker 1: doesn't say it's going to be efficient, doesn't say it's

1388
01:15:25,680 --> 01:15:28,639
Speaker 1: going to be I'd like our electrical grid to be upgraded.

1389
01:15:28,720 --> 01:15:32,240
Speaker 1: It's it's terrible. It'd be nice if our ports were secure.

1390
01:15:32,439 --> 01:15:36,439
Speaker 1: We know that they're still vulnerable to foreign or terrorist attacks.

1391
01:15:36,560 --> 01:15:38,360
Speaker 1: And I are on the same page here. I think

1392
01:15:38,439 --> 01:15:41,679
Speaker 1: infrastructures is really and if you go if you travel

1393
01:15:41,800 --> 01:15:45,680
Speaker 1: to Asia or Europe, our cellular system is awful, and

1394
01:15:45,800 --> 01:15:50,400
Speaker 1: our broadband, where we essentially created this technology, we're now

1395
01:15:50,560 --> 01:15:53,759
Speaker 1: the back of the but we are terrible compared forget Korea,

1396
01:15:53,840 --> 01:15:56,640
Speaker 1: who kicks our but most of Europe is three to

1397
01:15:56,720 --> 01:16:00,320
Speaker 1: five times faster than US and cheaper. Yeah, it's in credible.

1398
01:16:00,400 --> 01:16:02,760
Speaker 1: Yeah alright, so I know I only have you for

1399
01:16:02,800 --> 01:16:05,080
Speaker 1: a few more minutes. Let me go through some of

1400
01:16:05,160 --> 01:16:08,320
Speaker 1: my favorite questions to ask people and we'll get you

1401
01:16:08,439 --> 01:16:13,519
Speaker 1: out of here on time. Um. So, before before you

1402
01:16:13,560 --> 01:16:17,120
Speaker 1: came to Wall Street, you mentioned you're working for Standard Oil.

1403
01:16:17,240 --> 01:16:19,439
Speaker 1: What what did you do for them? What was your

1404
01:16:19,600 --> 01:16:23,160
Speaker 1: pre Wall Street experience? I was an economists there. They

1405
01:16:23,240 --> 01:16:25,880
Speaker 1: had what was called a general economics department. They had

1406
01:16:26,360 --> 01:16:28,880
Speaker 1: uh economists that covered various segments of the world. I

1407
01:16:28,960 --> 01:16:31,639
Speaker 1: was in charge of the US and Canada in terms

1408
01:16:31,680 --> 01:16:35,560
Speaker 1: of forecasting and analysis of the economy. And that was

1409
01:16:35,640 --> 01:16:40,760
Speaker 1: a time when the major corporations they had two things

1410
01:16:41,479 --> 01:16:43,360
Speaker 1: they knew they had to have. You couldn't go to

1411
01:16:43,520 --> 01:16:47,080
Speaker 1: lunch with your fellow CEOs and other wizards without having them.

1412
01:16:47,439 --> 01:16:49,360
Speaker 1: But they didn't know what to do with either one.

1413
01:16:49,439 --> 01:16:52,200
Speaker 1: And one was econ economists and the other was computers.

1414
01:16:53,080 --> 01:16:56,960
Speaker 1: That's fascinating. So from that you decided from that and

1415
01:16:57,080 --> 01:16:59,720
Speaker 1: from that I decided, Uh, you know, in Standard Oil

1416
01:16:59,840 --> 01:17:03,160
Speaker 1: was it is a huge company obviously well run company.

1417
01:17:03,240 --> 01:17:06,560
Speaker 1: It's going to be there forever, but it was fairly bureaucratic,

1418
01:17:06,680 --> 01:17:09,439
Speaker 1: and I wanted to imagine a little more active, and

1419
01:17:09,520 --> 01:17:12,400
Speaker 1: that's why I went left for Wall Street. So, so

1420
01:17:12,479 --> 01:17:14,160
Speaker 1: let's talk a little bit about some of your early

1421
01:17:14,240 --> 01:17:18,439
Speaker 1: mentors who really influenced your You mentioned the professor at

1422
01:17:18,439 --> 01:17:22,280
Speaker 1: Amherst who impacted your your career clearly mentor who else

1423
01:17:22,400 --> 01:17:27,040
Speaker 1: was a mentor of yours? Um, who influenced your thinking?

1424
01:17:29,680 --> 01:17:31,400
Speaker 1: I'm not sure I could name I. You know, I

1425
01:17:31,479 --> 01:17:34,240
Speaker 1: thought about that earlier. We talked about that, and I'm

1426
01:17:34,280 --> 01:17:36,400
Speaker 1: not sure I could I could mention. I mean, I

1427
01:17:36,439 --> 01:17:40,400
Speaker 1: I never, for better or worse, very I don't think

1428
01:17:40,400 --> 01:17:43,880
Speaker 1: I ever had had the mentor. So let me ask,

1429
01:17:44,000 --> 01:17:48,400
Speaker 1: let me rephrase that question slightly differently. What books throughout

1430
01:17:48,479 --> 01:17:57,400
Speaker 1: your lifetime have you found especially influential? Um. I guess

1431
01:17:57,439 --> 01:17:59,320
Speaker 1: some of the some of the basic books on the

1432
01:17:59,400 --> 01:18:03,240
Speaker 1: economy and and uh um. But I think it's been

1433
01:18:03,320 --> 01:18:09,240
Speaker 1: more the philosophical aspects and some of the some of

1434
01:18:09,280 --> 01:18:13,439
Speaker 1: the some of the great thinkers who give us some examples.

1435
01:18:13,479 --> 01:18:16,439
Speaker 1: You mentioned Milton Freedman or earlier. Yeah, certainly, I know

1436
01:18:16,560 --> 01:18:18,759
Speaker 1: you don't agree with everything. He said. You know, Kane's

1437
01:18:18,800 --> 01:18:24,080
Speaker 1: had a lot of interesting things. Um. My two thesis

1438
01:18:24,120 --> 01:18:28,559
Speaker 1: advisers of Sanford ed Shawn Jack and Jack Early. They

1439
01:18:28,600 --> 01:18:32,479
Speaker 1: came up to the idea that money pervaded in finance

1440
01:18:32,600 --> 01:18:36,439
Speaker 1: and everything had a degree of money, even insurance policies. Uh.

1441
01:18:37,040 --> 01:18:40,679
Speaker 1: But um, I can't say that I really studied under

1442
01:18:40,920 --> 01:18:45,200
Speaker 1: you know, one great mentor and U or another. So

1443
01:18:45,439 --> 01:18:52,080
Speaker 1: so let's talk about the financial industry. Obviously a lot

1444
01:18:52,240 --> 01:18:55,120
Speaker 1: has changed since you first joined Wall Street back in

1445
01:18:55,160 --> 01:18:57,200
Speaker 1: the late sixties. What do you think is the most

1446
01:18:57,280 --> 01:19:04,439
Speaker 1: significant shift we've seen you finance over the past forty years. Uh,

1447
01:19:06,360 --> 01:19:12,040
Speaker 1: it's probably the poriferation of financial instruments. When I when

1448
01:19:12,080 --> 01:19:15,400
Speaker 1: I got in, uh to Mary Lynch, and that was

1449
01:19:15,439 --> 01:19:19,439
Speaker 1: in nineteen sixty seven, you had fixed commission rates. Um,

1450
01:19:19,800 --> 01:19:24,560
Speaker 1: everything was pretty well regimented. No competition, no, yeah, no

1451
01:19:24,680 --> 01:19:28,479
Speaker 1: real competitions we know today regulation. I mean they even

1452
01:19:28,560 --> 01:19:32,760
Speaker 1: had resale holes, uh, fixed retail prices. You couldn't go

1453
01:19:32,840 --> 01:19:35,280
Speaker 1: into the store and buy you know, couldn't buy to

1454
01:19:35,479 --> 01:19:39,200
Speaker 1: a toothpaste where the price wasn't fixed in many cases. Uh.

1455
01:19:39,439 --> 01:19:44,360
Speaker 1: But I think what's happened is first First, first of all,

1456
01:19:44,439 --> 01:19:48,120
Speaker 1: you have opened things up with allowing competition starting with

1457
01:19:48,360 --> 01:19:52,760
Speaker 1: may Day and a fixed commission race in nine, and

1458
01:19:52,840 --> 01:19:57,400
Speaker 1: then also the proliferation of computers and an ability to

1459
01:19:57,479 --> 01:20:01,040
Speaker 1: trade and moving away from individuals curities. I remember Mary

1460
01:20:01,200 --> 01:20:03,880
Speaker 1: lynch Uh their trading operation that was looked like a

1461
01:20:04,000 --> 01:20:06,880
Speaker 1: race track where they had these belts that went around

1462
01:20:06,960 --> 01:20:08,639
Speaker 1: in a in a big view and a guy would

1463
01:20:09,080 --> 01:20:11,920
Speaker 1: take an order and stick it in um in this

1464
01:20:12,120 --> 01:20:13,720
Speaker 1: track and would go around with the guy on the

1465
01:20:13,800 --> 01:20:16,040
Speaker 1: other side. It would process, and I mean, you know

1466
01:20:16,479 --> 01:20:18,400
Speaker 1: it's it now. You push a button and it yeah,

1467
01:20:18,439 --> 01:20:20,560
Speaker 1: I mean, you know, music and well, and not only that,

1468
01:20:20,640 --> 01:20:22,439
Speaker 1: we're at the point now where these guys want to be.

1469
01:20:23,439 --> 01:20:25,880
Speaker 1: It's so fast that they want to be a short

1470
01:20:26,000 --> 01:20:31,799
Speaker 1: a distance physically from that hundred and eighty six thousand

1471
01:20:32,000 --> 01:20:35,280
Speaker 1: miles a second, okay, but they want to be half

1472
01:20:35,320 --> 01:20:39,840
Speaker 1: them closer. Don't travel that fast. But you know, I

1473
01:20:39,920 --> 01:20:42,840
Speaker 1: mean that that kind of thing has has really and

1474
01:20:42,920 --> 01:20:45,040
Speaker 1: if you remember the beginning of The Big Short if

1475
01:20:45,080 --> 01:20:47,439
Speaker 1: you met that book by Michael Lewis, they talked about

1476
01:20:47,520 --> 01:20:51,360
Speaker 1: all of these high frequency trading op brokerage firms that

1477
01:20:52,200 --> 01:20:55,640
Speaker 1: locate just outside of the Holland tunnel, so they're the

1478
01:20:55,840 --> 01:21:00,680
Speaker 1: closest to the feed from from all streets. And then

1479
01:21:00,800 --> 01:21:03,720
Speaker 1: these guys from Chicago laying a fiber optic cable in

1480
01:21:03,840 --> 01:21:08,320
Speaker 1: a dead straight line, didn't care what was in the way, mountains, houses,

1481
01:21:08,400 --> 01:21:10,519
Speaker 1: just buy it and blow through it. And now they're

1482
01:21:10,520 --> 01:21:14,080
Speaker 1: replacing that with you know, over the air microwave point

1483
01:21:14,160 --> 01:21:16,840
Speaker 1: to point broadcast, so you don't even have to lay

1484
01:21:16,920 --> 01:21:19,400
Speaker 1: fiber optic. You can just go. You have to have

1485
01:21:19,479 --> 01:21:21,519
Speaker 1: a series of jumps because the curvature of the earth

1486
01:21:21,600 --> 01:21:24,720
Speaker 1: gets in the way. But that's how important speed was

1487
01:21:24,880 --> 01:21:27,360
Speaker 1: to those guys. And and and the question is are

1488
01:21:27,439 --> 01:21:31,640
Speaker 1: we able to handle this uh in terms of the

1489
01:21:31,920 --> 01:21:34,400
Speaker 1: effects of this. And we've seen this with you know

1490
01:21:34,560 --> 01:21:41,880
Speaker 1: fair uh seven uh stock market nose dive one one day.

1491
01:21:41,920 --> 01:21:45,840
Speaker 1: We've seen him with flash crashes into bonds, and more

1492
01:21:45,880 --> 01:21:48,280
Speaker 1: recently we saw that with the E T F crush

1493
01:21:48,439 --> 01:21:50,720
Speaker 1: And and yeah, and and the question is are we

1494
01:21:51,240 --> 01:21:53,760
Speaker 1: are we really up to speed with with this? And

1495
01:21:54,120 --> 01:21:56,240
Speaker 1: and then you have a much better question. And this

1496
01:21:56,400 --> 01:21:58,479
Speaker 1: goes back to a lot of what we talked about

1497
01:21:58,520 --> 01:22:01,559
Speaker 1: about automation and so on. Has that made us any

1498
01:22:01,800 --> 01:22:05,800
Speaker 1: better decision makers? I'll tell you one one one one

1499
01:22:06,400 --> 01:22:08,960
Speaker 1: uh one book that I always read. It's a whole

1500
01:22:09,000 --> 01:22:11,160
Speaker 1: bunch of them. It's it's Shakespeare. I'm a great fan

1501
01:22:11,240 --> 01:22:13,800
Speaker 1: of Shakespeare. And you go back and you say, you know,

1502
01:22:13,880 --> 01:22:15,839
Speaker 1: first of all, that guy said things in an elegant

1503
01:22:15,880 --> 01:22:18,320
Speaker 1: way that none of you know, every the best line

1504
01:22:18,320 --> 01:22:21,880
Speaker 1: I've ever written is going to be big, is worse

1505
01:22:21,960 --> 01:22:24,120
Speaker 1: than the worst line he ever wrote. But you look

1506
01:22:24,160 --> 01:22:26,840
Speaker 1: at these and you say, has anything really changed? How

1507
01:22:26,880 --> 01:22:30,600
Speaker 1: are we making any better decisions with all this technology

1508
01:22:30,760 --> 01:22:32,840
Speaker 1: and speed? I'm not sure we have? And is this

1509
01:22:33,040 --> 01:22:36,360
Speaker 1: this mean that it's given us more confidence that we're

1510
01:22:36,479 --> 01:22:41,280
Speaker 1: you know, we're going bad and with more confidence than before.

1511
01:22:41,720 --> 01:22:43,439
Speaker 1: I mean because you think, well, all that data is

1512
01:22:43,439 --> 01:22:46,160
Speaker 1: available and so on, So I'm not sure that that

1513
01:22:46,320 --> 01:22:49,280
Speaker 1: we're able to synthesize that data any better. And and

1514
01:22:49,400 --> 01:22:51,519
Speaker 1: of course everybody else has the same data. And are

1515
01:22:51,560 --> 01:22:54,439
Speaker 1: you any better off really in terms of for you know,

1516
01:22:54,520 --> 01:22:57,439
Speaker 1: you're a forecaster, I'm a forecaster. Are we making better forecasting?

1517
01:22:57,479 --> 01:23:00,479
Speaker 1: We did twenty years ago? But it's feels to me

1518
01:23:00,640 --> 01:23:03,640
Speaker 1: that all this technology and all this high speed um

1519
01:23:04,600 --> 01:23:07,640
Speaker 1: not specialists, not people who have an obligation to make

1520
01:23:07,680 --> 01:23:10,920
Speaker 1: an orderly market. It makes it feel like the market

1521
01:23:11,000 --> 01:23:13,840
Speaker 1: structure is a little less stable or a lot less

1522
01:23:13,840 --> 01:23:15,720
Speaker 1: states Well, I think that I think that's true. And

1523
01:23:15,920 --> 01:23:19,360
Speaker 1: and and you really say, is that is that simply part?

1524
01:23:20,280 --> 01:23:22,120
Speaker 1: Is that part of the you know, does that go

1525
01:23:22,280 --> 01:23:25,160
Speaker 1: with the territory? And you just have to expect these

1526
01:23:25,240 --> 01:23:30,320
Speaker 1: periodic uh glicies and and and and uh, you know

1527
01:23:30,479 --> 01:23:33,400
Speaker 1: the puke point you reach me occasionally is it is

1528
01:23:33,479 --> 01:23:35,080
Speaker 1: this this part of the whole deal? And you you

1529
01:23:35,200 --> 01:23:37,120
Speaker 1: live with it? And I say, that's that's part of

1530
01:23:37,160 --> 01:23:43,240
Speaker 1: the deal. But but you know the thing about finances, finance, fundamentally,

1531
01:23:43,960 --> 01:23:47,080
Speaker 1: the justification for finance is a grease the wheels of commerce.

1532
01:23:47,800 --> 01:23:50,040
Speaker 1: It's it's if we had a barter system would be

1533
01:23:50,080 --> 01:23:52,720
Speaker 1: pretty if it would be pretty rough? Uh too much

1534
01:23:54,120 --> 01:23:57,439
Speaker 1: what finances? But I think finance, and particularly leading up

1535
01:23:57,479 --> 01:24:01,360
Speaker 1: to the collapse of nine in two thousand a, a

1536
01:24:01,439 --> 01:24:02,920
Speaker 1: lot of those guys felt they were an end of

1537
01:24:02,960 --> 01:24:06,280
Speaker 1: themselves and they're only their only job was to make money,

1538
01:24:06,800 --> 01:24:09,920
Speaker 1: and they didn't really think about are we contributing anything?

1539
01:24:09,960 --> 01:24:13,640
Speaker 1: Are we improving productivity? Are we are we making it

1540
01:24:13,840 --> 01:24:18,400
Speaker 1: possible for investments uh to get to get productive things?

1541
01:24:18,479 --> 01:24:21,360
Speaker 1: Done in the economy, and I think there's I think

1542
01:24:21,400 --> 01:24:24,320
Speaker 1: there's a lot of site and loss of of what

1543
01:24:24,439 --> 01:24:29,080
Speaker 1: the ultment game, ultiment objective of finances. I couldn't I

1544
01:24:29,120 --> 01:24:32,640
Speaker 1: couldn't agree more so that's historically looking back. Let me

1545
01:24:32,720 --> 01:24:35,960
Speaker 1: ask you, UM, next question, what do you see as

1546
01:24:36,040 --> 01:24:45,200
Speaker 1: the next important shifts in finance going forward? UM? Oh, gosh,

1547
01:24:45,280 --> 01:24:49,360
Speaker 1: it's probably gone to do with globalization. UM. So no

1548
01:24:49,479 --> 01:24:53,479
Speaker 1: more less of an impact of national borders than you have. Yeah,

1549
01:24:53,520 --> 01:24:56,519
Speaker 1: I mean, you know, you mean that the technology is there,

1550
01:24:56,560 --> 01:24:59,240
Speaker 1: and yet you do have you still have, you know,

1551
01:24:59,400 --> 01:25:03,920
Speaker 1: separate right regulations, separate exchanges. Um. There's there's a lot

1552
01:25:04,040 --> 01:25:08,799
Speaker 1: of of particularly in Europe, where they're trying to combine

1553
01:25:08,880 --> 01:25:11,800
Speaker 1: this but on a on a global basis. But you know,

1554
01:25:11,840 --> 01:25:15,519
Speaker 1: when when money can move around, move around at the

1555
01:25:15,880 --> 01:25:18,760
Speaker 1: touch of a touch of a key stroke. Um. The

1556
01:25:18,920 --> 01:25:23,080
Speaker 1: idea that you're moving into different regulatory jurisdictions because guys

1557
01:25:23,120 --> 01:25:24,960
Speaker 1: are always going to try to game system, they're going

1558
01:25:25,000 --> 01:25:28,000
Speaker 1: to look for the lowest regulatory climate. And I think

1559
01:25:28,080 --> 01:25:30,640
Speaker 1: that's probably something that's we're going to see is a

1560
01:25:30,720 --> 01:25:35,040
Speaker 1: lot more global control of of financial flows, not not

1561
01:25:35,240 --> 01:25:38,280
Speaker 1: control in the sense of big brother, but just common

1562
01:25:38,400 --> 01:25:42,680
Speaker 1: regulations so that it's it's all under the same all

1563
01:25:42,760 --> 01:25:46,720
Speaker 1: under the same regulatory framework. So so down to my

1564
01:25:46,880 --> 01:25:50,000
Speaker 1: last two favorite questions. And and let me ask you this.

1565
01:25:50,800 --> 01:25:54,439
Speaker 1: So the millennials, the people are just graduating college who

1566
01:25:54,439 --> 01:25:57,560
Speaker 1: we were discussing earlier. If one of them approached you

1567
01:25:57,720 --> 01:26:00,800
Speaker 1: and said, Gary, I'm interested in the career finance, what

1568
01:26:00,880 --> 01:26:06,360
Speaker 1: advice can you give me? What would you tell them? Uh?

1569
01:26:06,840 --> 01:26:09,640
Speaker 1: Other than other than to become a great economist, of course, Uh,

1570
01:26:11,240 --> 01:26:15,080
Speaker 1: I would. I would probably advise them to try to

1571
01:26:15,200 --> 01:26:19,680
Speaker 1: find an area where you are doing something is productive

1572
01:26:19,720 --> 01:26:25,120
Speaker 1: and you're not just glorified shuffer of paper. Uh. Trading.

1573
01:26:26,160 --> 01:26:29,960
Speaker 1: Trading is important. It lubricas the system. But but trading

1574
01:26:30,080 --> 01:26:32,519
Speaker 1: just for the sake of making money. I mean, you

1575
01:26:32,600 --> 01:26:35,439
Speaker 1: look at you look at corporate finance. Um, if you

1576
01:26:35,560 --> 01:26:38,280
Speaker 1: go back, you know, take Goldman Sacks that used to

1577
01:26:38,360 --> 01:26:42,360
Speaker 1: be an investment banking house and and their job was

1578
01:26:42,520 --> 01:26:47,160
Speaker 1: to their job was to work with clients and to

1579
01:26:47,680 --> 01:26:51,559
Speaker 1: raise money for them to do investments and productive things.

1580
01:26:52,080 --> 01:26:55,519
Speaker 1: And it was a win win situation. Uh. The client

1581
01:26:55,640 --> 01:27:01,200
Speaker 1: got the got the issue place, investors were satisfied with

1582
01:27:01,320 --> 01:27:04,759
Speaker 1: it most of the time. And and uh, the investment

1583
01:27:04,840 --> 01:27:08,840
Speaker 1: banker got a fee. Okay, now what Wall Street has

1584
01:27:08,840 --> 01:27:11,680
Speaker 1: evolved in his trading houses, and that isn't a win

1585
01:27:11,760 --> 01:27:14,639
Speaker 1: win situation. It's a zero sum game. There's a winner

1586
01:27:14,640 --> 01:27:16,760
Speaker 1: and a loser. Whether it's not like every it's not

1587
01:27:16,840 --> 01:27:19,880
Speaker 1: like the pie is getting bigger. I don't think if

1588
01:27:19,920 --> 01:27:22,200
Speaker 1: I were advising somebody, I'd say, I don't think you

1589
01:27:22,280 --> 01:27:25,240
Speaker 1: ought to be in that, uh, in that zero sum

1590
01:27:25,360 --> 01:27:29,080
Speaker 1: game business, because I somehow well, I don't think it's uh,

1591
01:27:29,800 --> 01:27:31,519
Speaker 1: you know what, whether whether it just makes a lot

1592
01:27:31,600 --> 01:27:33,800
Speaker 1: of money for you and you and you moved to

1593
01:27:33,880 --> 01:27:36,560
Speaker 1: the Hamptons and so on, but it's not fulfilling and

1594
01:27:36,640 --> 01:27:38,960
Speaker 1: it's not but I'm not sure. I'm not sure how

1595
01:27:39,040 --> 01:27:44,040
Speaker 1: sustainable that is. And then my final question, what is

1596
01:27:44,080 --> 01:27:47,960
Speaker 1: it that you know about investing and finance and economics

1597
01:27:48,080 --> 01:27:51,559
Speaker 1: today that you wish you knew when you began way

1598
01:27:51,600 --> 01:27:59,360
Speaker 1: back in the nineties sixties. Mhm Uh. It's probably a

1599
01:27:59,439 --> 01:28:05,400
Speaker 1: lot more respect for the unknowns out there and the

1600
01:28:05,560 --> 01:28:09,479
Speaker 1: vicissitudes of nature, and the realization that the best laid

1601
01:28:09,640 --> 01:28:13,080
Speaker 1: plans of mice and van gang Off the galat that

1602
01:28:13,600 --> 01:28:17,320
Speaker 1: you can that you can have a great forecast and

1603
01:28:17,720 --> 01:28:22,040
Speaker 1: all the fundamentals fall into place, and markets just simply

1604
01:28:22,120 --> 01:28:24,920
Speaker 1: do not confirm it. And the way I put it

1605
01:28:25,120 --> 01:28:28,120
Speaker 1: is marcuts can remain irrational a lot longer than we

1606
01:28:28,200 --> 01:28:31,840
Speaker 1: can remain solvent. I've heard that somewhere. Well, Gary, thank

1607
01:28:31,880 --> 01:28:34,400
Speaker 1: you so much. This has been a delight. Um. If

1608
01:28:34,479 --> 01:28:37,360
Speaker 1: people want to find your your newsletter or your research,

1609
01:28:37,439 --> 01:28:39,680
Speaker 1: how do they go about tracking you down while they

1610
01:28:39,720 --> 01:28:44,200
Speaker 1: can track us down? It's our website Www. A Gary

1611
01:28:44,400 --> 01:28:47,519
Speaker 1: Shilling dot com. And you now have a Twitter handle.

1612
01:28:47,600 --> 01:28:50,680
Speaker 1: I noticed, Oh yes, of course, and it's and it's

1613
01:28:50,720 --> 01:28:55,240
Speaker 1: the same same at A Gary Shilling. Fantastic. Well, thank

1614
01:28:55,280 --> 01:28:58,400
Speaker 1: you for spending so much time with us today. You've

1615
01:28:58,439 --> 01:29:01,720
Speaker 1: been listening to Masters in Business. If you enjoy this conversation,

1616
01:29:02,439 --> 01:29:05,360
Speaker 1: look up an Inch or down an Inch on iTunes

1617
01:29:05,400 --> 01:29:08,760
Speaker 1: and you'll see the other sixty or so podcast we've had.

1618
01:29:09,160 --> 01:29:10,640
Speaker 1: Let me make sure to say thank you to my

1619
01:29:10,720 --> 01:29:14,920
Speaker 1: head of research, Mike pat Nick and my producer Charlie Volmer.

1620
01:29:15,439 --> 01:29:18,240
Speaker 1: Be sure and check out all the rest of our

1621
01:29:18,439 --> 01:29:22,639
Speaker 1: other interviews. I'm Barry Ritults. You've been listening to Masters

1622
01:29:22,680 --> 01:29:24,599
Speaker 1: in Business on Bloomberg Radio.