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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Masters in

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Speaker 1: Business with Barry Ritholts on Bloomberg Radio.

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Speaker 2: This week on the podcast Wow. What a fascinating conversation

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Speaker 2: with a really interesting, intelligent guy. Mark Zandy has been

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Speaker 2: the chief economist of Moody's Analytics for twenty years. He

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Speaker 2: co founded a regional analytics shop in the nineties, coming

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Speaker 2: out of both Wharton and University of Pennsylvania, where he

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Speaker 2: got his undergraduate and graduate degrees in economics. He buys

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Speaker 2: economy dot com in the late nineties and builds out that.

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Speaker 2: Really a fascinating career, unique insight. You know, we live

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Speaker 2: in a highly polarized partisan world, whether it's the FED,

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Speaker 2: in flash, in labor, bls, the economy. I love speaking

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Speaker 2: to somebody who was an advisor to both the Mcking

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Speaker 2: campaign and the Obama White House. He just looks at

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Speaker 2: the world through a set of lenses that are data driven,

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Speaker 2: model driven and tries to provide the best analysis as

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Speaker 2: to what's going on, where and why. I thought this

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Speaker 2: conversation was great, and I think you will also with

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Speaker 2: no further ado. Moody Analytics Chief Economist Mark Zandy. Let's

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Speaker 2: just start with your background. You get a bachelor's from Wharton,

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Speaker 2: a doctorate in economics from the University of Pennsylvania. What

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Speaker 2: was the original career plan.

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Speaker 3: I had no career.

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Speaker 2: Plan, none, none, Never thought about going into markets economics,

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Speaker 2: like a PhD in economics. Were you thinking academia or

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Speaker 2: I definitely.

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Speaker 3: Knew not academia. My father was professor at Penn. We

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Speaker 3: all went to Penn because discounted tuition at that time,

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Speaker 3: which is a long time you're going to tell me

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Speaker 3: it was free. It was free, wow, tax free, Wow,

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Speaker 3: tax free? And you know I have four siblings. Wow.

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Speaker 3: In fact, he actually he was a pretty smart guy.

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Speaker 3: He bought a redstone at forty second in Spruce, you know,

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Speaker 3: just off campus, and we all lived in that in

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Speaker 3: that redstone.

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Speaker 2: Amazing.

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Speaker 3: Yeah, all right.

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Speaker 2: You come out of college in grad school with a

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Speaker 2: deep background in economics. What inspired you to explore a

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Speaker 2: career in economics.

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Speaker 3: Well, my work was very empirical, and my thesis advisor

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Speaker 3: was the guy named Larry Klein. He was a novel laureate. Yes,

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Speaker 3: he got it as a result of all the work

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Speaker 3: he did building macro models us macro models, and I

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Speaker 3: needed to make money when I was in school, so

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Speaker 3: I work part time. His firm is called Wharton Econometrics.

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Speaker 3: You know, after the Wharton School were called.

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Speaker 2: On a sec the school let him set up a

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Speaker 2: program called Wharton Economy at the company, a separate company

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Speaker 2: apart from the school, That's what I'm asking.

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Speaker 3: Yeah, yeah, I don't know. I'm sure there was some

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Speaker 3: kind of financial arrangement. He must have paid some kind

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Speaker 3: of royalty or something to that, but I'm not sure.

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Speaker 2: You know, but I don't think you could get away

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Speaker 2: with even paying royalties today. You couldn't set up Mit

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Speaker 2: Economics or a Stanford Econometrics.

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Speaker 3: No you don't think so. Yeah.

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Speaker 2: I mean, if you do certain research and you get

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Speaker 2: a patent, they get a piece of it. But setting

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Speaker 2: up like there is such a branding focus these days.

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Speaker 2: I can't imagine a big school would let you do.

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Speaker 3: Do that unless you played a really big royal try soon.

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Speaker 3: But yeah, But anyway, so that was a firm, a business,

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Speaker 3: economic forecasting business, and so I learned the business as

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Speaker 3: a graduate student, you know, working there to earn money.

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Speaker 3: And I also use their main at that time as

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Speaker 3: a mainframe, and everyone was on There was.

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Speaker 2: No pc is it's still the punch cards.

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Speaker 3: Punch cards for portray. Yeah. Yeah, you wanted to change

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Speaker 3: the federal funds rate by twenty five BIPs. You punch

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Speaker 3: a card, you have a act of cards. You would

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Speaker 3: take it down to some guy who put it into

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Speaker 3: the main retake twelve hours and if you messed up,

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Speaker 3: if you hit the wrong you know button, then you

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Speaker 3: had to wait another twelve hours to get the answer. Well,

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Speaker 3: how how much was a quarter point increase in the

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Speaker 3: funds rate going to do damage to the economy? That

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Speaker 3: kind of thing.

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Speaker 2: What was what was your doctoral thesis on?

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Speaker 3: It was a regional economics. Uh, it was examining a

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Speaker 3: fancy word factor flow, so labor capital and the movement

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Speaker 3: between regions and the country. And that was the basis

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Speaker 3: for the firm I started in nineteen ninety called Regional

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Speaker 3: Financial Associates because at that time, so you.

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Speaker 2: Started your own firm right pretty much right out of school.

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Speaker 3: Let's try out of school.

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Speaker 2: Wow.

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Speaker 3: Yeah, with my brother and my best friend. My best

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Speaker 3: friend was also working he was in the graduate program

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Speaker 3: at Penn and we were working at Wharton together. We

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Speaker 3: could see there was a lot of problems, you know,

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Speaker 3: with the way it was being run, and it was

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Speaker 3: mainframe oriented and PC was just coming out, so we

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Speaker 3: were able to use the PC to do the things

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Speaker 3: that we needed to do. I remember in grad school

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Speaker 3: using this poke Macclassic in nineteen eighty eight. Mac really

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Speaker 3: and the technology was just, oh look how advanced this was.

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Speaker 3: Bearskins and stone knives, That's what it reminds. Well, we

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Speaker 3: bought ibms at the time, So you launched this.

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Speaker 2: When does economy dot com come along to regional economics

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Speaker 2: almost a decade later, late nineties.

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Speaker 3: Yeah, the internet boom really took off. What ninety eight,

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Speaker 3: ninety nine, two thousand.

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Speaker 2: Yeah, like two years after the irrational of zuberant speech

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Speaker 2: is when it really became irrationally ninety six ninety six,

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Speaker 2: late ninety six Greenspan speech.

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Speaker 3: In fact, we bought the url economy dot com. This

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Speaker 3: guy from Quest, he was an executive at Request. Sure,

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Speaker 3: of course, one of the baby bells went out of

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Speaker 3: at and T a hitquarter in Denver, I believe, yeah, Colorado, Colorado, right,

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Speaker 3: and he made it. He squatted on all these names.

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Speaker 3: In fact, when we were negotiating the price for that

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Speaker 3: buying Economy dot com, he was on a yacht somewhere

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Speaker 3: in the Pacific. It made so much money on the squad.

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Speaker 2: So what did you end up paying for Economy dot

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Speaker 2: Com at the time.

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Speaker 3: It's a lot of money. Two hundred fifty k Yeah.

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Speaker 2: That is a and you one hundred exit eventually.

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Speaker 3: Yeah, it certainly was a good investment, to.

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Speaker 2: Say the very least. Yeah, I know your thesis advisor

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Speaker 2: was you mentioned Lawrence Klein and Nobel Laureate. Was he

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Speaker 2: an advisor to the firm when you were when you're

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Speaker 2: first building that out? Uh?

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Speaker 3: No, I thought that he was older at that point. Uh,

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Speaker 3: and he was. Actually we were competitor now right to Wharton.

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Speaker 3: Oh what an econometric? Yeah, I don't thought it. I

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Speaker 3: mean we weren't really you do her a bunch of

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Speaker 3: guys right right, Yeah, and we got the Economy dot com.

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Speaker 3: I'm making this up, but we might have had forty

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Speaker 3: fifty employees something like that.

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Speaker 2: Oh really, So, so what was it like building out

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Speaker 2: what essentially became a dot com in the late nineties?

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Speaker 3: Oh it was a lot. It was so much fun.

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Speaker 3: I mean I've been a startup, I've been a small

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Speaker 3: business guy, and I have been part of now obviously

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Speaker 3: part of the movie is a large multinational. So I've

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Speaker 3: seen business from a lot of different angles. And I'll

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Speaker 3: have to tell you maybe because I was just young.

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Speaker 3: I mean, I loved being a startup. It was just

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Speaker 3: it's a lot of fun, especially if it's working. Yeah,

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Speaker 3: I can imagine. And we got lucky. You know, the

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Speaker 3: interstate banking happened, so all these banks needed to think

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Speaker 3: about their footprint outside of their state, so they needed

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Speaker 3: the data and information that we were playing. So if

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Speaker 3: I were a bank in Connecticut and I was thinking

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Speaker 3: about moving into Massachusetts, I now needed to understand the

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Speaker 3: Massachusetts economy and we would help. You know, Sewman Bank

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Speaker 3: wasnt Connecticut Bank. That wasn't our first clients back.

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Speaker 2: In the day. So how you built this out in

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Speaker 2: the late nineties. You survived at dot com implosion because

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Speaker 2: although you were technically at dot com, you weren't a

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Speaker 2: frivolous clicks and eyeballs sort of company. It was a

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Speaker 2: real company with real clients and real revenue. Kind of

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Speaker 2: set you apart from pets dot com to the world.

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Speaker 3: We were an economic forecasting for masquerading as a dot

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Speaker 3: com right because we you know, as at that time,

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Speaker 3: dot com your evaluations are a lot higher. And sure,

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Speaker 3: of course it was. Practically speaking, we set up economy

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Speaker 3: dot com, right, that was our When you came to

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Speaker 3: our site, you came to economy dot com. So it

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Speaker 3: was a way to advertise where you go to get

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Speaker 3: our information.

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Speaker 2: And today you go to economy dot com and it

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Speaker 2: forwarded you to Moody's.

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Speaker 3: It does.

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Speaker 2: How did the relationship with Moodies come? About? Five six

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Speaker 2: years later?

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Speaker 3: The CEO of Moody's Analytics was this fellow Mark Almada,

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Speaker 3: great guy. He was a Philly, Philly guy, and he

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Speaker 3: and I worked together at warn't Econometrics was Philly based

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Speaker 3: because of Klein, and he was a data guy. He

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Speaker 3: was in a cube next to me. I was in

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Speaker 3: this young economists working on models and data and forecasting.

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Speaker 3: He was a data person and so we knew each

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Speaker 3: other quite well. And he went on to Moody's at

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Speaker 3: that time was the rating agency and he did extraordinarily well.

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Speaker 3: Became the CEO of Moody's Analytics when they formed the

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Speaker 3: Moody's Analytics and he just knocked on the door and said, hey,

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Speaker 3: are you interested in selling? And the answer was no,

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Speaker 3: because we had no idea what it was worth, just serendipity.

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Speaker 3: Fitch knocked on the door at roughly the same time,

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Speaker 3: within a week or two. I don't I can't connect

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Speaker 3: the dots. No, it's nothing like a bidding, Yeah, exactly.

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Speaker 3: So we were able to get a price right, and

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Speaker 3: I do remember him saying to me, Hey, Mark, what

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Speaker 3: price would it take for us to end this this

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Speaker 3: negotiation to this day, I gave. I gave him a price.

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Speaker 3: He said, he took it right away and I got.

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Speaker 2: Two years too little. Well, if you google it, it

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Speaker 2: says twenty seven million dollars. But I have no idea

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Speaker 2: how I get that. Is everything that I find through

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Speaker 2: AI and search, I always seems to have a little

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Speaker 2: asterisk with it. You know, you don't know what's especially

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Speaker 2: private stuff like that. So Moody's Analytics is a division

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Speaker 2: of Moody's, the big rating company. It's it's a group within,

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Speaker 2: is that right.

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Speaker 3: Yeah, it's there's Moody's, the rating agency, and then Moody's Analytics.

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Speaker 3: More recently they've been we've been moving together, but it's

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Speaker 3: still I'm still in the entitique Moody's Analytics.

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Speaker 2: So what was it like going from a startup to

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Speaker 2: a large multinational Entitalia.

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Speaker 3: Was great because we were allowed to remain independent in

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Speaker 3: every respect except for some of the back office kind

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Speaker 3: of things that legal age.

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Speaker 2: No one wants to do anyway.

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Speaker 3: Yeah, sales, and that's the key reason why we sold

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Speaker 3: was because we were mostly US and we were trying

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Speaker 3: to go global and that's hard. It's very expensive. We

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Speaker 3: set up an office in London and Sydney and it

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Speaker 3: was difficult. And they have a giant client base with

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Speaker 3: other everywhere clients all over the world.

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Speaker 2: That has to be a huge benefit to a small startup.

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Speaker 2: It allows you to really supersized.

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Speaker 3: In a salesforce all over the world. Right, And you

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Speaker 3: know Moody's respected institution, but overseas it's highly respected if

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Speaker 3: you go into many emerging markets, right, rating debt sovereign

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Speaker 3: debt is really really critical, and so when a Moody's

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Speaker 3: or an SMP says something, it really does move markets.

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Speaker 3: And so it helped us raise our credibilities. We had

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Speaker 3: no credibility overseas and this allowed us to gain some

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Speaker 3: credibility right away.

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Speaker 2: Speaking about gaining credibility, in two thousand and five, you

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Speaker 2: wrote a piece where are the regulators. The runaway housing

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Speaker 2: market needs tougher regulatory oversight. Very prescient analysis warning about, hey,

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Speaker 2: you can't just give mortgages to people regardless of their

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Speaker 2: ability to actually service that debt. What drove that analysis.

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Speaker 2: That was really the first time I became aware of

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Speaker 2: you as an economist.

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Speaker 3: Yeah, I remember that piece. I'm a macro guy, but

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Speaker 3: my area of expertise is housing and housing finance. I

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Speaker 3: was watching the housing and mortgage finance markets very carefully

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Speaker 3: at the time.

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Speaker 2: Which a lot of wool Street didn't really seem to

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Speaker 2: be paying much attention to. No, No, my mom was

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Speaker 2: a real estate agent. That's the only reason why I

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Speaker 2: was paying attention to this space. And that's probably how

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Speaker 2: I found you because we were having regularly so interesting

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Speaker 2: And it's a regional financial associates banks, regions, you know,

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Speaker 2: obviously it's real estate and housing are kind of top

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Speaker 2: of them, totally right. They write a lot of mortgages,

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Speaker 2: they make heelock loans and other things against it, and

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Speaker 2: they were losing market share to these unregulated non bank lenders,

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Speaker 2: a private label securities market market.

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Speaker 3: And of course, and the regulators were my clients. So

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Speaker 3: the FDI see for many, many years was my largest

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Speaker 3: client by far and away. Wow. Yeah, So I you know,

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Speaker 3: I was looking at this space from the prism of housing,

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Speaker 3: housing finance and also from a regulatory perspective, and I

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Speaker 3: could see this was, you know, problem.

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Speaker 2: Something was totally totally off foot.

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Speaker 3: I did have one, I've had. I had a number

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Speaker 3: of periods of doubt in that and that lead up

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Speaker 3: to the crisis. One was the FED under Greenspan asked

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Speaker 3: me to come in and brief them on housing because

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Speaker 3: I was a housing guy. I give this talk, uh,

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Speaker 3: and it was pretty dark and at the end of

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Speaker 3: it saying that we're gonna have a problem. I didn't

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Speaker 3: think we're gonna have a problem to the degree we

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Speaker 3: had the problem, but I knew there was a problem coming.

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Speaker 3: That was the message of the talk. And when I finished,

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Speaker 3: I didn't get a single question from one FED member,

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Speaker 3: really not one.

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Speaker 2: So there was this just a pro se discussion or silence.

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Speaker 3: I was totally confused by the whole thing. Even green

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Speaker 3: there was guy ed Gramlik, who was of course remember

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Speaker 3: him kind.

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Speaker 2: Of He was very much so he was in the

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Speaker 2: camp of, hey, you know, you have to be able

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Speaker 2: to the history of finance is not based on the

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Speaker 2: secure tire's ability to sell their product. It's based on

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Speaker 2: the barrow's ability to service the loan. If you take

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Speaker 2: that step out, you're asking for trouble.

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Speaker 3: Yeah.

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Speaker 2: So Gramlak very famously was the fly in the ointment

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Speaker 2: and also very right passed away before everything blew up.

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Speaker 3: Yeah that's right, that's but even he didn't say anything.

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Speaker 3: So I walk out that meeting and I'm going, maybe

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Speaker 3: I have this over wrong. So points in time I

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Speaker 3: had my doubt, but it became clear.

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Speaker 2: So so after the crisis in eight oh nine, or

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Speaker 2: eventually post financial crisis, you become an informal policy advisor

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Speaker 2: to the Obama administration. Tell us how that came about,

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Speaker 2: outside non partisan economic advisor.

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Speaker 3: Well, that was the time when the administration trying to

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Speaker 3: figure out how do I respond? Obama administration just the

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Speaker 3: crisis had occurred September eight, he was in office by

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Speaker 3: January of nine. They used that period to try to

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Speaker 3: figure out, how do I respond to this mess? What

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Speaker 3: do I do? You know, both from becoming a fiscal

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Speaker 3: policy perspective, from a regulatory perspective, from all angles, and

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Speaker 3: I had done a lot of work on estimating so

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Speaker 3: called multipliers of different policies. So if you do this,

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Speaker 3: you know, what is the impact on the economy. If

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Speaker 3: you do that, what is the impact on the economy.

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Speaker 3: Now that's widespread, that kind of work. Lots of people

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Speaker 3: do that work, do it much better than I do.

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Speaker 3: But at the time, there were just really wasn't anyone

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Speaker 3: looking at it that way and trying to estimate those multipliers.

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Speaker 3: So they used those multipliers and trying to design the

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Speaker 3: response the stimulus so called stimulus package that they put

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Speaker 3: in place in January twenty in two.

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Speaker 2: Thousand, arguably knowing near large enough to drive a recovery

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Speaker 2: in the economy quickly.

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Speaker 3: Well, yeah, and I think that's the lesson that the

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Speaker 3: Biden administration took coming out of the pandemic.

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Speaker 2: Right, even the Trump administration, the first CARES Act, the

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Speaker 2: first two CARES Acts were under President Trump.

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Speaker 3: Right, Biden gets into office March of twenty twenty one,

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Speaker 3: twenty twenty one, he passes the American Recovery Act two

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Speaker 3: trillion dollars, and you know, obviously it was very large.

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Speaker 3: A lot of criticism, mean, Larry Summers was all over it,

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Speaker 3: thinking it's too large. But I think the Biden administration

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Speaker 3: was looking back at the Bomb administration and saying, hey, look,

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Speaker 3: the bombministration was we will come up with this package

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Speaker 3: and if we need more, we'll get it. They never

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Speaker 3: got it. So the economy struggled for ten years after

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Speaker 3: the financial crisis, and so the bidendministration saw that and said, hey,

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Speaker 3: we probably go for a bigger bite of the apple

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Speaker 3: because we may not get another bite, and therefore let's

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Speaker 3: go for a bigger package, right, And.

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Speaker 2: That was over the next ten years, and that came

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Speaker 2: into the environment where the first Cares Act under President

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Speaker 2: Trump was the largest fiscal stimulus since World War Two,

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Speaker 2: at least as a percentage of GDP. Then there was

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Speaker 2: the Cares Act two under Trump, and then a whole bunch.

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Speaker 3: Of I think got Cares Act three, and then you

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Speaker 3: come in with Biden.

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Speaker 2: So Tears Act three was Biden, which was short term

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Speaker 2: and drop. But most of the other legislation under Biden

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Speaker 2: was was over ten the Infrastructure Bill, the Inflation Reduction Act,

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Speaker 2: those are all ten year legislation. So it feels very

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Speaker 2: much like the twenty tens was the era of monetary stimulus,

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Speaker 2: and the twenty twenties seems to be the era of

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Speaker 2: fiscal sit No.

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Speaker 3: I hadn't thought of it that way, Barry, but that's

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Speaker 3: a really good way of putting it. Yeah, exactly. I

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Speaker 3: mean the Fed had to work really hard back in

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Speaker 3: the twenty tens because they weren't getting any support from

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Speaker 3: fiscal policy. That was government shut downs, that's right, treasury

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Speaker 3: debt limit battles. Fiscal policy was contractionary, and so the

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Speaker 3: Fed had to step in and provide a lot of support. Right.

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Speaker 2: Congress did not. You know, they seem to have forgotten

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Speaker 2: everything we had learned from Keynes, and they remembered it

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Speaker 2: in twenty twenty. It's kind of amazing because I recall

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Speaker 2: being at a dinner with a number of people, including

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Speaker 2: some Nobel laureates in economics, and when I said, oh,

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Speaker 2: I think they're trying to cause a recession, Congress, they are.

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Speaker 2: They know how this works. They're just, you know, they

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Speaker 2: they want to submarine this administration. It was very much

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Speaker 2: poo pooed by the people there, and then eventually it's like, oh,

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Speaker 2: this has become much more partisan. And I wasn't making

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Speaker 2: a partisan argument. It was just an observation, Hey, we

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Speaker 2: know how this works. We've done giant fiscal stimulus, whether

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Speaker 2: it's tax cuts or spending. We know what the impact

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Speaker 2: is refusing to do it. I can't come up with

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Speaker 2: a better explanation other than we want to tank the ecounomy.

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Speaker 3: Well, they get this guy out. The explanation of face

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Speaker 3: value was, of course, step is just in debt, right,

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Speaker 3: we want to rein that in.

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Speaker 2: Right, except for giant tax cuts and big spending. Other

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Speaker 2: than that, you know, it's everybody is a deficit hawk

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Speaker 2: when they don't control the White House, and it doesn't

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Speaker 2: matter if you're Republican or a Democrat, your guy loses.

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Speaker 2: Suddenly the debt matters. And it's been going on my

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Speaker 2: entire adult life. It's so transparently political.

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Speaker 3: Or where we are on the deficit and debt.

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Speaker 2: Sure, so I want to ask about your relationship with

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Speaker 2: John McCain because I find this both fascinating and hilarious.

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Speaker 3: Yeah, well, perhaps it equally is interesting. My friend Kevin Hassett,

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Speaker 3: uh huh, asked me to come help out the McCain campaign.

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Speaker 3: You know now, Kevin is the head of the National

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Speaker 3: Economic Council and Donald Trump. He was at AI, the

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Speaker 3: American Enterprise Institute at the time.

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Speaker 2: And name consistently floated for potential figure roles.

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Speaker 3: Yeah, and this is well before Obama came on the scene.

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Speaker 3: I didn't know prison Obama at all, and I knew

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Speaker 3: McCain and I admired him mostly around foreign policy, that's

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Speaker 3: obviously where his expertise was. But I also felt like

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Speaker 3: they needed real help. The campaign needed real help on economics,

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Speaker 3: and I was the guy who took all the incoming

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Speaker 3: information about the economy and translating that into what does

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Speaker 3: it mean for the economic activity and what how should

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Speaker 3: we the campaign respond to that. Well, I wasn't paid,

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Speaker 3: I wasn't officially part of the campaign, but that's the

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Speaker 3: kind of support I provided. But you know, obviously when

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Speaker 3: the crisis hit, Senator McCain, that wasn't his strong suit.

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Speaker 3: Right again, he was foreign policy, he wasn't economics. He

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Speaker 3: kind of struggled across the finish line and never really great.

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Speaker 3: I can recall briefing the campaign saying, we got a

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Speaker 3: real problem here, this is a this is gonna be

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Speaker 3: a mess, And there was complete kind of another's not

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Speaker 3: being will be okay, And so there was a little

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Speaker 3: bit of tension at the end of that campaign.

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Speaker 2: It feels like he just encountered some unfortunate timing because

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Speaker 2: between the war in Iraq and the crisis, I think

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Speaker 2: the Bush administration had made any mainstream Republican unelectable in

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Speaker 2: two thousand and eight, and the Democrats put up a

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Speaker 2: charismatic guy. I don't think McCain would have been anything

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Speaker 2: but a really good president and in any other year,

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Speaker 2: a really strong candidate. Kind of shocking the way this

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Speaker 2: plays out. But you're often painted as this, Oh, that's

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Speaker 2: Andy is a lib like he was an advisor to

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Speaker 2: both McCain and Obama. That's more of someone trying to

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Speaker 2: serve as country, not a partisan.

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Speaker 3: I have always provided advice when asked from both sides

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Speaker 3: of the aisle, so you know, sometimes more from the

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Speaker 3: D side, at times more from the R side, but

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Speaker 3: I've done both. Clearly, the political center of gravity has

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Speaker 3: shifted here and McCain, even McCain, I'm not sure where

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Speaker 3: that kind of lines up in the political spectrum. But yeah,

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Speaker 3: I've always been nonpartisan. It tried my very best to

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Speaker 3: be non person and even now it's tough to talk

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Speaker 3: about the economy as an economist in the given all

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Speaker 3: of the things that are going on with economic policy,

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Speaker 3: tariffs and immigration and doge. Generally, when I address the group,

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Speaker 3: I start saying, you know, I know I'm going to

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Speaker 3: sound political. I don't mean to be political. I'm doing

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Speaker 3: my very best not to be political, so please forgive me.

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Speaker 3: And that generally people take that in and you know,

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Speaker 3: forgive me if I overstep in some way in their mind.

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Speaker 2: It's tough to be an honest criticizer of policy without people.

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Speaker 2: It's kind of a lazy accusation to say, Jacques ces

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Speaker 2: this is partisan. Well, no, we could. We talk about tariffs.

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Speaker 2: We tried them in nineteen thirty, didn't work out great.

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Speaker 2: Why do we think it's gonna work out well this time?

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Speaker 2: That's not partisan, that's just that's the factual situation.

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Speaker 3: Right.

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Speaker 2: If you want to make an argument for why a

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Speaker 2: consumption tax on consumers of imported goods is an efficient,

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Speaker 2: effective way to either lower the deficit or raise capital

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Speaker 2: or realign global trade, have at it. But understand there's

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Speaker 2: a body of history that informs us what happened the

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Speaker 2: last time.

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Speaker 3: Totally. It's so interesting because on almost every issue economists debate,

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Speaker 3: and the debate is reasonable, right.

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Speaker 2: Economists, reasonable people can disagree.

437
00:22:42,280 --> 00:22:45,440
Speaker 3: Yeah, And economists think about the second, third, fourth, fifth

438
00:22:45,520 --> 00:22:48,680
Speaker 3: order effects of these things and how they platter of time.

439
00:22:48,720 --> 00:22:52,800
Speaker 3: So it's very not at all unusual to have these knockout,

440
00:22:52,880 --> 00:22:57,080
Speaker 3: dragged down fights between economists over issues. But on tariffs,

441
00:22:57,240 --> 00:23:00,760
Speaker 3: broad based tariffs, it's not much of a right.

442
00:23:01,000 --> 00:23:03,720
Speaker 2: Is a pretty big consensus. Hey, the world is in

443
00:23:03,880 --> 00:23:05,560
Speaker 2: flat we chink Saturday.

444
00:23:05,960 --> 00:23:08,600
Speaker 3: So I feel like I'm on pretty sound ground when

445
00:23:08,640 --> 00:23:11,800
Speaker 3: I say I'm not a fan of these broad based turves.

446
00:23:12,040 --> 00:23:15,040
Speaker 2: The phrase that always comes up with me on these

447
00:23:15,080 --> 00:23:19,240
Speaker 2: sort of things, these accusations of partisanship, is the Overton window.

448
00:23:20,040 --> 00:23:22,159
Speaker 2: You could be middle of the road, or you know,

449
00:23:22,240 --> 00:23:25,520
Speaker 2: maybe center left or center right, but when the entire

450
00:23:25,640 --> 00:23:29,720
Speaker 2: framework shifts far to one way or another, it suddenly

451
00:23:29,720 --> 00:23:32,120
Speaker 2: looks like you're an outlier, even though you were kind

452
00:23:32,160 --> 00:23:35,840
Speaker 2: of centrist but kind of how I feel right, the

453
00:23:35,880 --> 00:23:40,680
Speaker 2: wings have expanded, and suddenly what seems like it's pretty

454
00:23:40,720 --> 00:23:44,399
Speaker 2: middle of the road isn't any any longer. Coming up,

455
00:23:44,440 --> 00:23:48,280
Speaker 2: we continue our conversation with Mark Zandy, chief economist of

456
00:23:48,320 --> 00:23:53,600
Speaker 2: Moody's Analytics, discussing what the firm is focusing on in

457
00:23:53,640 --> 00:23:57,440
Speaker 2: the twenty twenties I'm Buried Richults. You're listening to Masters

458
00:23:57,440 --> 00:24:08,400
Speaker 2: in Business on Bloomberg Radio. I'm Barry Ridults. You're listening

459
00:24:08,400 --> 00:24:11,919
Speaker 2: to Masters in Business on Bloomberg Radio. My extra special

460
00:24:11,920 --> 00:24:14,840
Speaker 2: guest this week was Mark Zandy. He's the chief economist

461
00:24:14,920 --> 00:24:19,720
Speaker 2: of Moody's Analytics. Previously, he co founded economy dot com

462
00:24:19,760 --> 00:24:23,040
Speaker 2: and hosts the Inside Economics podcast.

463
00:24:23,119 --> 00:24:24,920
Speaker 3: I bet you say that to all the economists.

464
00:24:24,960 --> 00:24:27,800
Speaker 2: Everybody is my extra special guest. I get grief about

465
00:24:27,840 --> 00:24:32,080
Speaker 2: it because once I painted myself into that corner. Hey,

466
00:24:32,200 --> 00:24:36,240
Speaker 2: my ordinary guest is this bomb. Let's talk about your

467
00:24:36,280 --> 00:24:41,359
Speaker 2: Moody's experience. We talked earlier about, you know, your warnings

468
00:24:41,400 --> 00:24:45,520
Speaker 2: on housing and home financing and what ended up happening

469
00:24:45,520 --> 00:24:51,680
Speaker 2: with subprime securitization. Moody's was one of the biggest rating agencies.

470
00:24:52,760 --> 00:24:56,760
Speaker 2: I criticized them in Bailout Nation. Tell us what it

471
00:24:56,880 --> 00:24:59,000
Speaker 2: was like when you join the firm and O five

472
00:24:59,119 --> 00:25:02,840
Speaker 2: in you're wagging a finger about these sort of things.

473
00:25:02,840 --> 00:25:04,840
Speaker 2: Did you get any sort of pushback? What what was

474
00:25:04,840 --> 00:25:10,280
Speaker 2: it like stepping into a firm that indirectly was a

475
00:25:10,280 --> 00:25:12,880
Speaker 2: focus of some of your analytical critiques.

476
00:25:12,960 --> 00:25:13,840
Speaker 3: Yeah, I got to push back.

477
00:25:13,960 --> 00:25:14,760
Speaker 2: You did I did.

478
00:25:14,880 --> 00:25:17,840
Speaker 3: Yeah, I mean I wrote a paper on the subprime

479
00:25:18,119 --> 00:25:21,880
Speaker 3: mortgage space and did everything but say, you know, these

480
00:25:21,920 --> 00:25:27,680
Speaker 3: securities should be downgraded, house price declines, credit risk defaults, foreclosure.

481
00:25:27,800 --> 00:25:29,919
Speaker 3: These are the losses. But I didn't take it with

482
00:25:29,960 --> 00:25:31,639
Speaker 3: the next step and say, okay, what does this mean

483
00:25:31,680 --> 00:25:34,880
Speaker 3: for ratings? But I wrote that paper and it went

484
00:25:34,920 --> 00:25:38,720
Speaker 3: to the CEO, a great guy in the CEO's.

485
00:25:38,400 --> 00:25:41,520
Speaker 2: CEO of analytics, or the CEO of Moody's Moodies full

486
00:25:41,680 --> 00:25:43,480
Speaker 2: and full Moodies, right, and.

487
00:25:43,440 --> 00:25:45,720
Speaker 3: This, of course I just had sold my company to them,

488
00:25:45,720 --> 00:25:48,320
Speaker 3: so this is all brand new. He didn't who is

489
00:25:48,359 --> 00:25:51,000
Speaker 3: this guy? What's what's he doing?

490
00:25:51,080 --> 00:25:53,840
Speaker 2: Sandy, Andy, that's the back of the alphabet. We never

491
00:25:53,880 --> 00:25:54,600
Speaker 2: get to this stuff.

492
00:25:55,160 --> 00:25:57,919
Speaker 3: And he goes, why is he talking about subprime mortgage?

493
00:25:57,920 --> 00:25:59,679
Speaker 3: What does that have to do about the economy? And

494
00:25:59,720 --> 00:26:02,240
Speaker 3: at the time that was a reasonable question. The best

495
00:26:02,240 --> 00:26:05,720
Speaker 3: thing that ever happened. BERNANKI gave a speech called contained

496
00:26:05,960 --> 00:26:09,280
Speaker 3: subprime Mortgage, right, and remembering that speech and he said,

497
00:26:09,320 --> 00:26:12,320
Speaker 3: don't worry, this is not a problem. But because he

498
00:26:12,400 --> 00:26:15,840
Speaker 3: wrote that speech, I could gave you. I said, look,

499
00:26:15,840 --> 00:26:17,360
Speaker 3: this is why I'm talking about it. Right.

500
00:26:17,840 --> 00:26:20,920
Speaker 2: The head of the FED is talking about it. What

501
00:26:21,080 --> 00:26:23,040
Speaker 2: was he vice chair or just a governor back then,

502
00:26:23,119 --> 00:26:24,040
Speaker 2: or was that as chairman?

503
00:26:24,160 --> 00:26:25,639
Speaker 3: He was chair? I think at the time he was,

504
00:26:25,920 --> 00:26:30,000
Speaker 3: he was definitely chair. To the CEO's credit, he said, okay,

505
00:26:30,400 --> 00:26:32,840
Speaker 3: you know, you publish it and it's the best thing

506
00:26:32,920 --> 00:26:35,040
Speaker 3: that ever happened. Well, one of the things best things

507
00:26:35,080 --> 00:26:38,360
Speaker 3: that happened to mood is because when the financial inquiry commissioned,

508
00:26:38,359 --> 00:26:39,760
Speaker 3: remember the Finish f C.

509
00:26:39,880 --> 00:26:42,560
Speaker 2: I sa absolutely they and that I have that book.

510
00:26:42,560 --> 00:26:44,040
Speaker 2: It's like this thick sitting on a show.

511
00:26:44,080 --> 00:26:47,119
Speaker 3: Oh yeah, yeah, yeah, I was. I was testified. I

512
00:26:47,200 --> 00:26:52,600
Speaker 3: was the first panel panels, and of course the CEO

513
00:26:52,800 --> 00:26:55,639
Speaker 3: was a later panel with Warren Buffett. Warren Buffett was

514
00:26:55,720 --> 00:26:57,920
Speaker 3: the is a shareholder in movies. I think he still

515
00:26:58,000 --> 00:27:01,480
Speaker 3: is a big shareholder. The law makers were questioning them,

516
00:27:01,720 --> 00:27:06,119
Speaker 3: and the CEO could say, hey, look here's here's a study.

517
00:27:06,680 --> 00:27:09,760
Speaker 2: Can I tell you something a little self awareness?

518
00:27:10,000 --> 00:27:11,879
Speaker 3: So that yeah, I've been there for twenty years. I

519
00:27:11,920 --> 00:27:16,679
Speaker 3: love Moodies. But that really helped a lot, right in

520
00:27:16,720 --> 00:27:20,920
Speaker 3: every respect. That helped my credibility, helped the companies, yeah, help.

521
00:27:20,920 --> 00:27:24,960
Speaker 3: The companies established a set of ground rules that I'm

522
00:27:24,960 --> 00:27:29,040
Speaker 3: able to write about, think about talk about anything that

523
00:27:29,080 --> 00:27:31,679
Speaker 3: I think is important about the economy. All that was

524
00:27:31,760 --> 00:27:34,119
Speaker 3: established in that point now that that's getting tested at

525
00:27:34,160 --> 00:27:36,439
Speaker 3: different points in time as we move along here. But

526
00:27:37,040 --> 00:27:39,800
Speaker 3: and we're in a trying time now. But that was very,

527
00:27:39,880 --> 00:27:43,240
Speaker 3: very important to my successful stay at Moodies for twenty years.

528
00:27:43,440 --> 00:27:47,879
Speaker 2: I wish I could remember who wrote a criticism in

529
00:27:47,960 --> 00:27:53,040
Speaker 2: response to the Bernanke speech about subprime, because the line

530
00:27:53,080 --> 00:27:56,760
Speaker 2: was subprime is contained and the response it could have

531
00:27:56,760 --> 00:27:59,600
Speaker 2: been Allen Abelson and Barons, it could have been James Grant,

532
00:28:00,119 --> 00:28:03,600
Speaker 2: could have been Josh rosin Atrailing, but it was Yes,

533
00:28:03,760 --> 00:28:06,960
Speaker 2: subprime is contained to planet Earth. The rest of the

534
00:28:07,000 --> 00:28:09,920
Speaker 2: Solar System is safe. And it was one of those

535
00:28:09,960 --> 00:28:13,800
Speaker 2: lines where damn, I wish I wrote that I might

536
00:28:13,840 --> 00:28:15,159
Speaker 2: have been able Sin or Grant.

537
00:28:15,240 --> 00:28:17,800
Speaker 3: But it sounds like a Jim Grant, right, it very

538
00:28:17,840 --> 00:28:18,320
Speaker 3: much does.

539
00:28:18,440 --> 00:28:19,680
Speaker 2: It's sort of dry.

540
00:28:19,720 --> 00:28:22,679
Speaker 3: Still writing, I think, so, yeah, you know, we'll kind

541
00:28:22,680 --> 00:28:23,320
Speaker 3: of lost track.

542
00:28:23,600 --> 00:28:26,840
Speaker 2: Yeah, it happens, especially in this era of sub stack,

543
00:28:26,920 --> 00:28:31,639
Speaker 2: where right your inbox is just overflowed with kind with stuff.

544
00:28:31,720 --> 00:28:35,199
Speaker 2: So you got some pushback, but they cleared it. I

545
00:28:35,240 --> 00:28:38,160
Speaker 2: got to ask, what was your experience. Like at Moody's

546
00:28:38,240 --> 00:28:41,720
Speaker 2: during the Great Financial Crisis, it had to be twenty

547
00:28:41,760 --> 00:28:45,800
Speaker 2: four to seven work plus terrifying everything.

548
00:28:46,280 --> 00:28:51,080
Speaker 3: Oh, it was an amazing scary I can remember a

549
00:28:51,080 --> 00:28:54,560
Speaker 3: few scary, real scary moments in my mind. You know,

550
00:28:54,680 --> 00:28:58,320
Speaker 3: when I got a call from a CEO of a

551
00:28:58,360 --> 00:29:01,280
Speaker 3: major retailer saying that, you know, if we don't do something,

552
00:29:01,440 --> 00:29:04,120
Speaker 3: he's gonna not be able to make payroll, you know,

553
00:29:04,280 --> 00:29:06,440
Speaker 3: on and I'm saying, I'm thinking to myself, he's telling

554
00:29:06,480 --> 00:29:08,920
Speaker 3: me this, we got a real problem.

555
00:29:09,120 --> 00:29:11,240
Speaker 2: Well he wants you to tell Yeah.

556
00:29:11,000 --> 00:29:13,080
Speaker 3: That's what it wants exactly what it was. That was

557
00:29:13,120 --> 00:29:15,760
Speaker 3: exactly what it was, didn't the.

558
00:29:15,720 --> 00:29:20,160
Speaker 2: Bush administration I remember, was Hank Paulsen or BERNANKI have

559
00:29:20,320 --> 00:29:25,600
Speaker 2: conversations maybe it was the CEO of Ford or GM. Hey,

560
00:29:25,840 --> 00:29:28,760
Speaker 2: we have money, but our credit facility is frozen. We

561
00:29:28,840 --> 00:29:30,800
Speaker 2: can't get our money to make payroll.

562
00:29:30,880 --> 00:29:32,840
Speaker 3: Right. Well, there was so many things going on. Remember

563
00:29:32,880 --> 00:29:36,320
Speaker 3: this commercial paper market was had frozen and yeah, completely frozen,

564
00:29:36,400 --> 00:29:39,800
Speaker 3: and of course that's key to making payroll for a

565
00:29:39,800 --> 00:29:40,560
Speaker 3: lot of these companies.

566
00:29:40,840 --> 00:29:43,720
Speaker 2: I have a buddy who was on a derivatives trading

567
00:29:43,840 --> 00:29:46,560
Speaker 2: desk and he always pushes back when I use the

568
00:29:46,600 --> 00:29:49,040
Speaker 2: word frozen. He's like, hey, I don't know what you're

569
00:29:49,040 --> 00:29:52,120
Speaker 2: talking about. We were trading billions of dollars a day

570
00:29:52,160 --> 00:29:56,520
Speaker 2: in paper. It was just discounted thirty forty, so there

571
00:29:56,600 --> 00:29:59,880
Speaker 2: was liquidity, but there was a haircut involved well, and also.

572
00:29:59,720 --> 00:30:02,000
Speaker 3: Just find out was it thirty or was it fifty

573
00:30:02,080 --> 00:30:02,720
Speaker 3: or was it seventy?

574
00:30:02,840 --> 00:30:03,320
Speaker 2: You don't know.

575
00:30:03,440 --> 00:30:04,080
Speaker 3: Yeah, you don't know.

576
00:30:04,200 --> 00:30:07,960
Speaker 2: You don't know. That. That led to the line there's

577
00:30:07,960 --> 00:30:10,840
Speaker 2: no such thing as toxic paper, only toxic price.

578
00:30:10,960 --> 00:30:11,480
Speaker 3: There you go.

579
00:30:11,760 --> 00:30:15,600
Speaker 2: So yeah, absolutely, so that experience had to be just

580
00:30:15,720 --> 00:30:16,320
Speaker 2: mind blowing.

581
00:30:16,360 --> 00:30:19,440
Speaker 3: Well also from coming just a purely academic perspective for

582
00:30:19,440 --> 00:30:22,680
Speaker 3: an economist, I mean, this was just an incredible time.

583
00:30:23,640 --> 00:30:27,240
Speaker 3: One once every century you see something like this, and

584
00:30:27,520 --> 00:30:30,880
Speaker 3: there's so much that you're learning while you're doing. And

585
00:30:31,080 --> 00:30:34,880
Speaker 3: it was not only just economics, it was also political economy.

586
00:30:34,920 --> 00:30:38,600
Speaker 3: You know, how what should lawmakers do and how should

587
00:30:38,600 --> 00:30:42,200
Speaker 3: they do it? And all the moving parts there. So

588
00:30:42,280 --> 00:30:46,040
Speaker 3: it was a very amazing time. And that's when I

589
00:30:46,040 --> 00:30:49,560
Speaker 3: wrote that first book. Was it's not a great book, Barry,

590
00:30:49,720 --> 00:30:53,240
Speaker 3: and there is. I really did write a chapter, chapter

591
00:30:53,280 --> 00:30:55,240
Speaker 3: seven on the rating agencies but I did not put

592
00:30:55,240 --> 00:30:56,880
Speaker 3: it in because I was part of the rating agency

593
00:30:56,920 --> 00:30:58,080
Speaker 3: and no one would believe me. Anyway.

594
00:30:58,760 --> 00:31:02,760
Speaker 2: Now you've been there twenty years. The financial crisis is

595
00:31:03,560 --> 00:31:07,600
Speaker 2: more than fifteen years in the rear window. Tell us

596
00:31:07,640 --> 00:31:11,200
Speaker 2: a little bit about what Moody's Analytics is doing here

597
00:31:11,240 --> 00:31:11,800
Speaker 2: and now.

598
00:31:13,040 --> 00:31:15,800
Speaker 3: We're very simple business. My part of Moody's is a

599
00:31:15,840 --> 00:31:20,160
Speaker 3: very simple business. We produce economic forecasts in scenarios.

600
00:31:20,280 --> 00:31:23,240
Speaker 2: Yeah, but that's not really a simple thing to do.

601
00:31:23,400 --> 00:31:25,840
Speaker 2: There's a lot of inputs and a lot of moving.

602
00:31:25,600 --> 00:31:31,680
Speaker 3: Parts there is, But the actual business itself is very simple.

603
00:31:32,120 --> 00:31:35,960
Speaker 3: And one of the things that has been kind of

604
00:31:35,960 --> 00:31:39,200
Speaker 3: a tailwind to our work has been the regulatory environment.

605
00:31:39,280 --> 00:31:42,400
Speaker 3: Right the financial intitutions all over the globe need to

606
00:31:42,480 --> 00:31:47,040
Speaker 3: do stress tests, kept for capital planning. It's even now

607
00:31:47,080 --> 00:31:51,520
Speaker 3: embedded in the Loan Loss provisioning of CECIL here in

608
00:31:51,560 --> 00:31:55,600
Speaker 3: the US as an accounting framework that requires forward looking projections,

609
00:31:56,800 --> 00:32:02,040
Speaker 3: IFRS nine overseas, climate stress testing, all those things require

610
00:32:02,600 --> 00:32:07,600
Speaker 3: a very disciplined, comprehensive approach to economic forecasting, and so

611
00:32:07,960 --> 00:32:10,160
Speaker 3: that's really been key to the key to the business

612
00:32:10,520 --> 00:32:12,840
Speaker 3: here over the last ten fifteen years.

613
00:32:12,960 --> 00:32:16,640
Speaker 2: So that's kind of interesting your clients. Are they necessarily

614
00:32:16,840 --> 00:32:22,480
Speaker 2: Wall Street investing firms? Are they government institutions or non

615
00:32:22,520 --> 00:32:23,760
Speaker 2: governmental agencies?

616
00:32:24,360 --> 00:32:25,440
Speaker 3: Above above?

617
00:32:25,480 --> 00:32:29,080
Speaker 2: When when I think of climate stress testing, I just

618
00:32:29,200 --> 00:32:33,440
Speaker 2: was involved in the silly debate about climate change, and

619
00:32:33,560 --> 00:32:37,400
Speaker 2: my answer is, hey, my opinion is relevant. Go talk

620
00:32:37,440 --> 00:32:40,840
Speaker 2: to an insurer if climate changes as a hoax. Great point,

621
00:32:41,000 --> 00:32:46,360
Speaker 2: and what are your experiences doing climate stress tests for you?

622
00:32:46,400 --> 00:32:48,760
Speaker 2: Look how hard it is to get insurance in places

623
00:32:48,800 --> 00:32:52,760
Speaker 2: like Florida. Like how significant is something like that to

624
00:32:52,880 --> 00:32:56,080
Speaker 2: the sort of research you would sell to a private

625
00:32:56,080 --> 00:32:57,200
Speaker 2: actity like insurance?

626
00:32:57,240 --> 00:33:01,680
Speaker 3: It's critical. So house prices go look at house prices

627
00:33:01,680 --> 00:33:04,600
Speaker 3: in Florida. We're talking about the West coast of Florida.

628
00:33:04,640 --> 00:33:08,520
Speaker 3: They're falling, and they're falling because homeowner's insurance costs are

629
00:33:08,600 --> 00:33:13,760
Speaker 3: rising because of the cost of hurricanes and other storm damage.

630
00:33:14,000 --> 00:33:17,560
Speaker 3: So the insurers take that all in they raise homeowners

631
00:33:17,600 --> 00:33:20,440
Speaker 3: insurance and that depresses demand and price, and of course

632
00:33:20,440 --> 00:33:22,720
Speaker 3: that has all kinds of implications for mortgage credit risk

633
00:33:22,920 --> 00:33:25,200
Speaker 3: if you're an mortgage insure, if you're in the mortgage

634
00:33:25,200 --> 00:33:29,320
Speaker 3: business any kind of respect. So that's a great example

635
00:33:29,400 --> 00:33:32,960
Speaker 3: of where you know, the kind of economic forecasting is

636
00:33:33,040 --> 00:33:36,320
Speaker 3: really critical to what's going on in real life, in

637
00:33:36,320 --> 00:33:40,080
Speaker 3: particular with the climate. It's real, it's happening, there's damage,

638
00:33:40,080 --> 00:33:42,600
Speaker 3: and insurers are trying to figure that out, and they're

639
00:33:42,600 --> 00:33:45,320
Speaker 3: not building that into their premiums, and it's having a

640
00:33:45,360 --> 00:33:50,160
Speaker 3: real impact. Right now, it's more concentrated in places like

641
00:33:50,200 --> 00:33:53,160
Speaker 3: Florida and Texas and California, but it's going to become

642
00:33:53,200 --> 00:33:55,760
Speaker 3: more of a problem in other parts of the country,

643
00:33:55,840 --> 00:33:56,600
Speaker 3: you know, pretty quickly.

644
00:33:56,920 --> 00:34:01,400
Speaker 2: Huh to say the very least. We've seen fires in California,

645
00:34:01,440 --> 00:34:04,400
Speaker 2: We've seen flooding in the mid Atlantic states.

646
00:34:04,480 --> 00:34:08,360
Speaker 3: Tell me get there's a good factoid for you, or

647
00:34:08,400 --> 00:34:11,000
Speaker 3: I'll ask you. I ask you guess which state has

648
00:34:11,040 --> 00:34:13,160
Speaker 3: the highest home owners insurance costs in the country.

649
00:34:13,960 --> 00:34:17,239
Speaker 2: So the two that come to mind immediately of Florida

650
00:34:17,280 --> 00:34:21,200
Speaker 2: and California. But the question makes me think it wonder,

651
00:34:21,600 --> 00:34:25,520
Speaker 2: are we talking about places like Texas or the.

652
00:34:25,480 --> 00:34:27,439
Speaker 3: Carolinas, Nebraska?

653
00:34:27,680 --> 00:34:30,080
Speaker 2: Nobrat because the tornadoes.

654
00:34:29,560 --> 00:34:34,400
Speaker 3: Well, yeah, and convection convective storms, the the the the

655
00:34:34,440 --> 00:34:37,160
Speaker 3: big thunderstorms that come along and they drop a lot

656
00:34:37,200 --> 00:34:40,320
Speaker 3: of that. Hell the hell does tremendous damage.

657
00:34:40,640 --> 00:34:43,960
Speaker 2: Yeah, yeah, you know, we just had a mild storm

658
00:34:44,640 --> 00:34:48,560
Speaker 2: and this little brand smashes the windshield of the truck

659
00:34:48,920 --> 00:34:52,640
Speaker 2: and I'm waiting three weeks to replace it. And when

660
00:34:52,680 --> 00:34:54,879
Speaker 2: I ask the we have glass coverage, and I asked

661
00:34:54,920 --> 00:34:57,440
Speaker 2: the insure about this, They're like, you have no idea

662
00:34:57,440 --> 00:35:00,840
Speaker 2: how backed up everything is. And they're a delays in

663
00:35:00,960 --> 00:35:05,840
Speaker 2: getting dumb things like windshields. So all that stuff, plus

664
00:35:06,400 --> 00:35:10,600
Speaker 2: all the pandemic shortage of automobiles and things like that,

665
00:35:10,600 --> 00:35:15,279
Speaker 2: that's driven automobile insurance up. I never would have guessed Nebraska.

666
00:35:15,320 --> 00:35:17,840
Speaker 3: That's an amazing isn't that interesting? And and and also.

667
00:35:17,680 --> 00:35:20,520
Speaker 2: Who's number two or three? I'm curious who's right behind them?

668
00:35:20,800 --> 00:35:24,279
Speaker 3: Like we're up there, they're up. They're definitely top ten. Yeah,

669
00:35:24,320 --> 00:35:27,400
Speaker 3: top ten. The state that had the lowest, and this

670
00:35:27,440 --> 00:35:28,840
Speaker 3: is I'm sure going to change when we get more

671
00:35:28,880 --> 00:35:31,520
Speaker 3: up to dated is Hawaii. But well you just had

672
00:35:31,640 --> 00:35:34,560
Speaker 3: the fires, right fire, so that's going to change. But

673
00:35:34,640 --> 00:35:37,319
Speaker 3: that that had been the case. But the other thing

674
00:35:37,440 --> 00:35:41,120
Speaker 3: is overseas climate is a real issue. Just go to Indonesia.

675
00:35:41,840 --> 00:35:44,560
Speaker 3: The Central Bank is you know, a client, and they

676
00:35:45,360 --> 00:35:49,239
Speaker 3: they're doing a lot of climate assessment because Jakarta is

677
00:35:49,280 --> 00:35:51,200
Speaker 3: increasingly underwater, right, So.

678
00:35:51,360 --> 00:35:56,200
Speaker 2: Literally not you don't mean negative cash flow, you mean.

679
00:35:55,239 --> 00:35:59,360
Speaker 3: Literally inner seawater is sea levels rising and there's there's

680
00:35:59,400 --> 00:36:01,680
Speaker 3: there's doing real damage and so you have to consider that.

681
00:36:01,760 --> 00:36:04,719
Speaker 3: So here in the US, it's an issue overseas is

682
00:36:04,760 --> 00:36:08,160
Speaker 3: becoming in some parts of the world existential, you know.

683
00:36:08,280 --> 00:36:11,120
Speaker 2: The I'm trying to remember if this was Wired or

684
00:36:11,160 --> 00:36:13,520
Speaker 2: the Atlantic, But there was a big piece a year

685
00:36:13,600 --> 00:36:18,680
Speaker 2: or two ago about Miami and the flooding risk from Miami.

686
00:36:18,960 --> 00:36:23,400
Speaker 2: And this is very surprising. It's not the seas coming

687
00:36:23,520 --> 00:36:27,400
Speaker 2: over the land. It's that so much of South Florida

688
00:36:28,000 --> 00:36:31,640
Speaker 2: is built on the sort of limestone base which is

689
00:36:31,840 --> 00:36:35,040
Speaker 2: very poorous to water. And so the flooding is not

690
00:36:35,840 --> 00:36:40,719
Speaker 2: storm surging over the coastline, it's water bubbling up from right.

691
00:36:41,000 --> 00:36:44,600
Speaker 2: It's like a crazy I never you know, there's so

692
00:36:44,680 --> 00:36:48,400
Speaker 2: many random factors that if it's not your space, Wow,

693
00:36:48,480 --> 00:36:51,040
Speaker 2: Like I never would have guessed Nebraska and I never

694
00:36:51,080 --> 00:36:52,960
Speaker 2: would have guessed southern Florida.

695
00:36:53,120 --> 00:36:55,600
Speaker 3: The sinkholes, right, that's why the sinkoles are real problem

696
00:36:55,640 --> 00:36:58,880
Speaker 3: because where in Florida, no kid, Yeah, because the bubbling

697
00:36:58,960 --> 00:37:01,240
Speaker 3: up it undermines the ground.

698
00:37:02,040 --> 00:37:05,960
Speaker 2: That's that's unbelievable. Coming up, we continue our conversation with

699
00:37:06,040 --> 00:37:11,000
Speaker 2: Mark Zandi, chief economist at Moody's, discussing the state of

700
00:37:11,040 --> 00:37:15,400
Speaker 2: the economy today. I'm Barry Hults. You're listening to Masters

701
00:37:15,520 --> 00:37:28,560
Speaker 2: Business on Bloomberg Radio. I'm Barry Ridults. You're listening to

702
00:37:28,800 --> 00:37:33,520
Speaker 2: Masters in Business on Bloomberg Radio. My better than average

703
00:37:33,560 --> 00:37:37,480
Speaker 2: guests this week is Mark Sandy. He's a chief economist

704
00:37:37,800 --> 00:37:42,360
Speaker 2: of Moody's and hosts it. Hosts My Extra Special Guests

705
00:37:42,400 --> 00:37:45,600
Speaker 2: and called me out on it. So you know Cone

706
00:37:45,640 --> 00:37:52,480
Speaker 2: O'Brien's podcast. He makes everybody say their name, and I

707
00:37:52,600 --> 00:37:57,120
Speaker 2: feel blank to be Conan O'Brien's friend, and it's kind

708
00:37:57,160 --> 00:37:59,839
Speaker 2: of a funny throw it to the guests.

709
00:37:59,640 --> 00:38:00,480
Speaker 3: To fill that in.

710
00:38:01,280 --> 00:38:04,360
Speaker 2: And I forgot her name. She was on Shrinking Jessica

711
00:38:04,400 --> 00:38:07,640
Speaker 2: and former Daily Show. She said, I feel pressured to

712
00:38:07,680 --> 00:38:11,840
Speaker 2: say anything about being cornered, so I kind of painted

713
00:38:11,880 --> 00:38:14,080
Speaker 2: myself into the corner. Maybe I'm going to have it,

714
00:38:14,239 --> 00:38:16,680
Speaker 2: get a great job getting out of it. Maybe the

715
00:38:16,840 --> 00:38:19,920
Speaker 2: guests say, what sort of a guest do you this week?

716
00:38:20,800 --> 00:38:24,280
Speaker 2: So let's talk about the state of the US economy today.

717
00:38:24,800 --> 00:38:28,359
Speaker 2: How do you assess where we are what indicators are

718
00:38:28,440 --> 00:38:32,560
Speaker 2: most concerning to you, and then we'll drill down more specifically.

719
00:38:33,040 --> 00:38:36,960
Speaker 3: The economy struggling. I think it's on the precipice of recession.

720
00:38:37,560 --> 00:38:40,480
Speaker 2: Precipice of recession. Yeah, what does that mean? Does that

721
00:38:40,560 --> 00:38:44,960
Speaker 2: mean fifty to fifty chance this year? Because we've had

722
00:38:45,000 --> 00:38:48,920
Speaker 2: economists forecasting recession pretty much since twenty twenty two.

723
00:38:48,920 --> 00:38:51,080
Speaker 3: To me, me, I haven't been.

724
00:38:51,480 --> 00:38:53,799
Speaker 2: So this is a change. You're now starting to get

725
00:38:53,880 --> 00:38:56,840
Speaker 2: more cautious as nervous I've been, and you've been robust.

726
00:38:57,480 --> 00:38:59,719
Speaker 2: You've seen this as a robust economy the past few

727
00:38:59,800 --> 00:39:04,960
Speaker 2: years I have. So the switch is significant. It is

728
00:39:05,080 --> 00:39:06,400
Speaker 2: so what what is driving?

729
00:39:07,400 --> 00:39:10,880
Speaker 3: I have to be humble because what ails the economy

730
00:39:10,920 --> 00:39:15,000
Speaker 3: is pretty obvious. It's economic policy, and it can change quickly. Therefore,

731
00:39:15,440 --> 00:39:19,160
Speaker 3: you have to be humble here because policy can change

732
00:39:19,160 --> 00:39:23,040
Speaker 3: and we may not the economy may find its footing

733
00:39:23,280 --> 00:39:25,640
Speaker 3: as a resultantly avoid recession. So there's a lot of

734
00:39:26,120 --> 00:39:27,520
Speaker 3: I hate using the word, but it's the only word

735
00:39:27,520 --> 00:39:29,560
Speaker 3: I can think of. It's uncertainty. I mean there is

736
00:39:29,600 --> 00:39:31,920
Speaker 3: a lot of that in economic pecast.

737
00:39:31,960 --> 00:39:34,960
Speaker 2: I steer clear of the U word. And and what

738
00:39:34,960 --> 00:39:38,040
Speaker 2: do you say, lack of clarity like that, because I

739
00:39:38,080 --> 00:39:41,239
Speaker 2: think it's I think it's not as pregnant as I

740
00:39:41,400 --> 00:39:44,640
Speaker 2: like that. So lack of pity, but no doubt about that.

741
00:39:44,680 --> 00:39:49,800
Speaker 2: We've seen CFOs talk about withholding capex spending and even

742
00:39:49,840 --> 00:39:54,040
Speaker 2: families postponing trips to Disneylands, and the.

743
00:39:54,080 --> 00:39:56,680
Speaker 3: Data say it so GDP growth the value of all

744
00:39:56,680 --> 00:39:59,200
Speaker 3: the things we produce that was barely one percent in

745
00:39:59,239 --> 00:40:02,720
Speaker 3: the first half of the year. Consumer spending has gone

746
00:40:02,719 --> 00:40:07,480
Speaker 3: nowhere all year long. Manufacturings in recession, constructions in recession.

747
00:40:07,600 --> 00:40:10,160
Speaker 3: Transportation distribution is in recession.

748
00:40:09,800 --> 00:40:13,400
Speaker 2: Not You're not saying this is growth rate is slowing.

749
00:40:13,480 --> 00:40:15,399
Speaker 2: You're saying this is in the red, in the red.

750
00:40:16,120 --> 00:40:20,080
Speaker 2: Manufacturing construction. Why is construction in the red. There's such

751
00:40:20,120 --> 00:40:21,200
Speaker 2: a demand for housing.

752
00:40:22,800 --> 00:40:24,840
Speaker 3: Home building is weakening very rapidly.

753
00:40:25,080 --> 00:40:29,200
Speaker 2: Really is that a function of high rates and mortgages

754
00:40:29,320 --> 00:40:31,480
Speaker 2: or is that a function of, Hey, we can't find

755
00:40:31,520 --> 00:40:34,399
Speaker 2: people to build these houses, to say nothing of we're

756
00:40:34,400 --> 00:40:37,040
Speaker 2: going to home depot and deporting the guys looking for work.

757
00:40:37,080 --> 00:40:38,719
Speaker 3: It's affordability. People can't afford the news.

758
00:40:38,880 --> 00:40:39,359
Speaker 2: That's all it is.

759
00:40:40,239 --> 00:40:44,280
Speaker 3: And the builders have done an admirable job trying with incentives,

760
00:40:44,600 --> 00:40:47,560
Speaker 3: interest rate buydowns to keep the market going and maintaining

761
00:40:47,920 --> 00:40:50,960
Speaker 3: construction levels. But that's over that. They're not able to.

762
00:40:50,880 --> 00:40:53,399
Speaker 2: Do it, no buying down.

763
00:40:53,960 --> 00:40:57,319
Speaker 3: So now we're seeing single family home building come down

764
00:40:57,360 --> 00:40:59,279
Speaker 3: for the first time. Multi family has been coming down

765
00:40:59,280 --> 00:41:02,080
Speaker 3: for for at least a year, right because it got overbuilt.

766
00:41:02,120 --> 00:41:04,280
Speaker 3: All these luxury towers going up in New York.

767
00:41:04,080 --> 00:41:05,240
Speaker 2: And tom Beach.

768
00:41:05,640 --> 00:41:09,759
Speaker 3: Vacancy rates are too high, rents are too weak. Uh.

769
00:41:09,800 --> 00:41:13,080
Speaker 3: The commercial uh, non residential site is also very weak.

770
00:41:13,200 --> 00:41:16,959
Speaker 3: The only strength is data centers. Really yeah, and that

771
00:41:16,960 --> 00:41:19,960
Speaker 3: that even with that, if you look at overall construction spending,

772
00:41:20,000 --> 00:41:22,719
Speaker 3: it's like over was it two trillion dollars? It's declining.

773
00:41:22,920 --> 00:41:28,080
Speaker 2: So I was on the impression that medical facilities, warehouses,

774
00:41:28,560 --> 00:41:31,680
Speaker 2: things like that were still fairly robust. You're telling me

775
00:41:31,719 --> 00:41:32,080
Speaker 2: that's not a.

776
00:41:34,040 --> 00:41:39,480
Speaker 3: Yeah, yeah there, you know. Healthcare is fine. Uh, data centers, booming,

777
00:41:40,239 --> 00:41:43,400
Speaker 3: offices are up way down. Multi families down. Residential uh,

778
00:41:43,640 --> 00:41:46,080
Speaker 3: single families way down. So you add it all up,

779
00:41:46,239 --> 00:41:48,719
Speaker 3: and now public construction is starting to roll over, right

780
00:41:48,719 --> 00:41:51,040
Speaker 3: because you had that big lift because of the infrastructure

781
00:41:51,160 --> 00:41:52,839
Speaker 3: legislation that was passed a few years ago.

782
00:41:53,280 --> 00:41:55,279
Speaker 2: Still, but it's still on some of it is still on.

783
00:41:55,280 --> 00:41:57,960
Speaker 3: High, but you know that the it's now rolling over.

784
00:41:58,000 --> 00:42:00,239
Speaker 3: It's a high level of spending, but you've now asked

785
00:42:00,280 --> 00:42:02,640
Speaker 3: the peak and spending it is not starting to come in,

786
00:42:02,719 --> 00:42:04,640
Speaker 3: and we're not going to see any more infrastructure spending

787
00:42:04,680 --> 00:42:07,080
Speaker 3: on the public side for quite something. Really, I don't

788
00:42:07,080 --> 00:42:07,520
Speaker 3: think I.

789
00:42:07,400 --> 00:42:09,640
Speaker 2: Thought that would continue on for a couple of years.

790
00:42:09,760 --> 00:42:10,840
Speaker 2: Wasn't that like a five or thing.

791
00:42:11,440 --> 00:42:15,799
Speaker 3: It's an elevated level. Oh and then growth is the

792
00:42:15,920 --> 00:42:19,319
Speaker 3: change in and you've passed the peak. It's coming now start.

793
00:42:19,520 --> 00:42:22,680
Speaker 2: So you've talked about everything. We haven't gotten to the job,

794
00:42:22,840 --> 00:42:25,040
Speaker 2: by the way. That's that's my next question. Tell us

795
00:42:25,080 --> 00:42:26,040
Speaker 2: about the labor market.

796
00:42:26,520 --> 00:42:30,400
Speaker 3: It's consistent with the economy is struggling. The job numbers

797
00:42:31,120 --> 00:42:33,640
Speaker 3: are showing very little job growth in recent months, and

798
00:42:33,680 --> 00:42:36,640
Speaker 3: I would not be surprised in the next few months,

799
00:42:36,640 --> 00:42:38,720
Speaker 3: assuming we get the data from the real labor statistics.

800
00:42:38,760 --> 00:42:41,440
Speaker 3: We can kind of talk about that. Assuming we actually

801
00:42:41,480 --> 00:42:44,120
Speaker 3: get the data, we could actually see some and that

802
00:42:44,239 --> 00:42:46,400
Speaker 3: would not be surprised if we saw some negative numbers,

803
00:42:46,680 --> 00:42:48,680
Speaker 3: you know, actual declines and employment.

804
00:42:48,800 --> 00:42:52,120
Speaker 2: So Jim Bianco said something the other day that really

805
00:42:52,320 --> 00:42:55,359
Speaker 2: kind of surprised me. First time in US history. We

806
00:42:55,400 --> 00:42:59,839
Speaker 2: are actually seeing negative population growth, not not caused by

807
00:42:59,880 --> 00:43:03,880
Speaker 2: a war anything, but immigrants aren't coming to the country

808
00:43:04,040 --> 00:43:07,560
Speaker 2: and people are being deported, and by the end of

809
00:43:07,560 --> 00:43:11,759
Speaker 2: twenty twenty five we may have a lower total population

810
00:43:11,920 --> 00:43:13,839
Speaker 2: number than we had at the end of twenty twenty four.

811
00:43:14,320 --> 00:43:16,080
Speaker 2: What does that mean for the labor market?

812
00:43:16,280 --> 00:43:18,640
Speaker 3: Yeah, I mean at the end of the day, if

813
00:43:18,680 --> 00:43:21,600
Speaker 3: you're a full employment and we're closed four point two

814
00:43:21,640 --> 00:43:24,320
Speaker 3: percent of employment rate, the only way you can generate

815
00:43:24,360 --> 00:43:26,760
Speaker 3: a job is if you've got someone to fill the job.

816
00:43:26,920 --> 00:43:29,080
Speaker 3: Right you need a labor you need someone who's working.

817
00:43:29,480 --> 00:43:32,759
Speaker 3: So if the labor force isn't growing and right now

818
00:43:32,760 --> 00:43:35,239
Speaker 3: it's just flat, it really has Actually if you look, well.

819
00:43:35,160 --> 00:43:39,080
Speaker 2: You could have job openings, but just they're unfilled data.

820
00:43:39,239 --> 00:43:42,239
Speaker 3: That's right, But it's not a job until you fill it.

821
00:43:42,760 --> 00:43:45,279
Speaker 3: So you could actually and right now labor force is

822
00:43:45,320 --> 00:43:49,319
Speaker 3: declining if you believe the data, believe the precision of

823
00:43:49,360 --> 00:43:52,800
Speaker 3: the data. But the level of the labor force in July,

824
00:43:53,000 --> 00:43:55,239
Speaker 3: the last STATA point is higher, is lower than it

825
00:43:55,360 --> 00:43:59,040
Speaker 3: was back in January, and so that would suggest that

826
00:43:59,120 --> 00:44:01,600
Speaker 3: it's going to be very difficul for the economy to

827
00:44:01,920 --> 00:44:05,239
Speaker 3: generate jobs, and it's very possible we start getting job

828
00:44:05,360 --> 00:44:06,800
Speaker 3: lost and just negative numbers.

829
00:44:06,880 --> 00:44:09,680
Speaker 2: So what are you What odds are you putting on

830
00:44:09,760 --> 00:44:12,320
Speaker 2: a recession? And we'll talk about inflation and tafts in

831
00:44:12,360 --> 00:44:14,640
Speaker 2: a moment, but what odds are you putting on a

832
00:44:14,680 --> 00:44:17,399
Speaker 2: recession in Q four twenty twenty five or Q one

833
00:44:17,880 --> 00:44:18,799
Speaker 2: twenty twenty six.

834
00:44:19,440 --> 00:44:24,120
Speaker 3: I think our baseline outlook, my baseline outlook has no recession,

835
00:44:24,320 --> 00:44:27,800
Speaker 3: just a weak economy. We kind of struggled the way through.

836
00:44:27,800 --> 00:44:30,520
Speaker 2: Like a sub one percent GDP and a slight.

837
00:44:30,640 --> 00:44:32,839
Speaker 3: One percent it's actually one percent on the nose year

838
00:44:32,880 --> 00:44:34,960
Speaker 3: over year through Q four of this year, Q one

839
00:44:34,960 --> 00:44:38,680
Speaker 3: of next, which is historically below the economy's potential. No

840
00:44:38,880 --> 00:44:39,960
Speaker 3: job growth.

841
00:44:39,920 --> 00:44:42,600
Speaker 2: Zero, like a zero bls print every.

842
00:44:42,719 --> 00:44:45,560
Speaker 3: I think i've average monthly job growth in sub one

843
00:44:45,680 --> 00:44:49,080
Speaker 3: hundred Oh wait, wait, like twenty five k? Really twenty

844
00:44:49,080 --> 00:44:50,880
Speaker 3: five k something like that?

845
00:44:50,880 --> 00:44:54,960
Speaker 2: That that's a you know what's shocking about this sort

846
00:44:55,000 --> 00:45:00,120
Speaker 2: of discussion is regardless of who you voted for, what

847
00:45:00,200 --> 00:45:05,920
Speaker 2: your political affiliation is, there's no debate. The first quarter

848
00:45:06,400 --> 00:45:11,360
Speaker 2: twenty twenty five was a very robust economy, with markets

849
00:45:11,440 --> 00:45:14,920
Speaker 2: hitting old time highs, and here we are eight months later.

850
00:45:15,600 --> 00:45:21,440
Speaker 2: Revenue is high, profits are high, Expectations of forward growth

851
00:45:21,480 --> 00:45:24,399
Speaker 2: in the stock market is high. I know. The old

852
00:45:24,480 --> 00:45:27,479
Speaker 2: joke is stock markets have predicted none of the last

853
00:45:27,480 --> 00:45:31,799
Speaker 2: four recessions. But what are all time highs? And this

854
00:45:32,000 --> 00:45:37,839
Speaker 2: ongoing enthusiasm for growing corporate profits. What is that saying

855
00:45:37,840 --> 00:45:38,520
Speaker 2: about the accounty?

856
00:45:38,560 --> 00:45:40,759
Speaker 3: Yeah, and that's the one reason why I don't have

857
00:45:40,800 --> 00:45:43,399
Speaker 3: a recession. In the baseline, the equity market is held up.

858
00:45:43,680 --> 00:45:46,279
Speaker 3: Although obviously a big part of what's going on the

859
00:45:46,320 --> 00:45:48,919
Speaker 3: equity market is related to AI, and that has nothing

860
00:45:48,960 --> 00:45:50,000
Speaker 3: to do with the business cycle.

861
00:45:50,280 --> 00:45:52,319
Speaker 2: It's AI, and half of the S and P five

862
00:45:52,400 --> 00:45:55,360
Speaker 2: hundred revenues are overseas, so it may not be reflected

863
00:45:55,400 --> 00:45:56,360
Speaker 2: exactly its growth.

864
00:45:56,400 --> 00:45:58,560
Speaker 3: And also, you got tax cuts, right, so if you

865
00:45:58,600 --> 00:46:02,920
Speaker 3: just assume stimulus, they have pe constant pe multiple. If

866
00:46:02,920 --> 00:46:05,160
Speaker 3: you raise after tax learnings, you should get a higher price.

867
00:46:05,600 --> 00:46:08,239
Speaker 3: So if you if you abstract from those things that

868
00:46:08,280 --> 00:46:11,520
Speaker 3: are independent of the economic cycle, the stock market at

869
00:46:11,520 --> 00:46:14,239
Speaker 3: best is flat from where it's the beginning of the year,

870
00:46:14,239 --> 00:46:16,920
Speaker 3: and that that's the economy. It's flat, it's gone nowhere.

871
00:46:17,000 --> 00:46:19,640
Speaker 2: Now the economy is flat, But I mean the stock

872
00:46:19,680 --> 00:46:23,720
Speaker 2: market can still elevate off a flat economy with tax cuts,

873
00:46:23,760 --> 00:46:25,480
Speaker 2: AI spending exactly.

874
00:46:25,080 --> 00:46:28,319
Speaker 3: Internet, And that's my sense of what's happening. So what's

875
00:46:28,320 --> 00:46:31,400
Speaker 3: going on in the equity market is actually, I think

876
00:46:32,040 --> 00:46:35,200
Speaker 3: consistent with what we're observing in the economy. Now. If

877
00:46:35,239 --> 00:46:38,440
Speaker 3: the stock market starts to head south written large, and

878
00:46:38,480 --> 00:46:41,400
Speaker 3: we see non AI part of the market starting to

879
00:46:41,400 --> 00:46:44,680
Speaker 3: go south here, I think that's the strong signal that

880
00:46:45,120 --> 00:46:48,600
Speaker 3: we're going in that we're going into it. And the

881
00:46:48,640 --> 00:46:51,640
Speaker 3: equity market is not only important as a signal, but

882
00:46:51,719 --> 00:46:56,480
Speaker 3: increasingly it drives economic activity because the bulk of spending

883
00:46:56,719 --> 00:46:59,080
Speaker 3: in the economy today is done by folks in the

884
00:46:59,080 --> 00:47:00,279
Speaker 3: top part of the income in well.

885
00:47:00,400 --> 00:47:02,760
Speaker 2: Top twenty percent is half of top spending.

886
00:47:02,840 --> 00:47:06,680
Speaker 3: By our calculations, the top ten percent account for oh

887
00:47:06,800 --> 00:47:09,000
Speaker 3: say you're right, stop twenty percent account for fifty percent

888
00:47:09,000 --> 00:47:09,640
Speaker 3: of the spell.

889
00:47:09,480 --> 00:47:12,000
Speaker 2: Right, And the top ten percent is most of that.

890
00:47:11,920 --> 00:47:13,719
Speaker 3: And most of that, and the top five percent is

891
00:47:13,800 --> 00:47:14,799
Speaker 3: most most of that.

892
00:47:15,040 --> 00:47:21,960
Speaker 2: So very not a well distributed consumer spend. It's it's

893
00:47:22,120 --> 00:47:28,239
Speaker 2: high end, high end and luxury goods, which you know,

894
00:47:28,400 --> 00:47:32,719
Speaker 2: that's top two percent like that that that Skew is

895
00:47:33,000 --> 00:47:36,239
Speaker 2: very The good news is if you go buy a

896
00:47:36,280 --> 00:47:40,520
Speaker 2: private jet, you can depreciate all of it in year one.

897
00:47:40,960 --> 00:47:46,359
Speaker 2: Of the uh's to the new tax bill, but that

898
00:47:46,560 --> 00:47:50,160
Speaker 2: sort of stuff. So I remember when Bush did his

899
00:47:50,320 --> 00:47:53,760
Speaker 2: accelerated depreciation, which I want to say it was depending

900
00:47:53,800 --> 00:47:56,120
Speaker 2: on the item, it was three to seven years instead

901
00:47:56,120 --> 00:48:00,399
Speaker 2: of ten to twenty years. Being able to depreciate these

902
00:48:00,480 --> 00:48:02,920
Speaker 2: luxury goods, maybe that's a.

903
00:48:02,880 --> 00:48:06,520
Speaker 3: Factor and end there. Yeah, and that should also help

904
00:48:06,880 --> 00:48:08,640
Speaker 3: the construction markets too, right, because.

905
00:48:08,440 --> 00:48:12,640
Speaker 2: You would think, right state, it's a little different. So

906
00:48:13,040 --> 00:48:15,000
Speaker 2: I don't know if you could depreciate all of your

907
00:48:15,000 --> 00:48:18,600
Speaker 2: build out in year one, but I'm gonna guess it's

908
00:48:18,640 --> 00:48:22,200
Speaker 2: not a twenty year depreciation schedule. You probably can do it.

909
00:48:22,960 --> 00:48:25,080
Speaker 2: I should really ask one of my tax guys what

910
00:48:25,120 --> 00:48:30,480
Speaker 2: the depreciation schedule is for new construction, because you would

911
00:48:30,480 --> 00:48:33,640
Speaker 2: think that would encourage more building, and we desperately need

912
00:48:33,760 --> 00:48:35,600
Speaker 2: more single family.

913
00:48:35,320 --> 00:48:37,920
Speaker 3: Homes and maybe the way out of recession. Not only

914
00:48:38,520 --> 00:48:42,480
Speaker 3: it's really get more fiscal support, right, and we will

915
00:48:42,560 --> 00:48:45,799
Speaker 3: likely get another reconciliation. A piece of BBB, the big

916
00:48:45,800 --> 00:48:48,760
Speaker 3: beauty Rail was reconciliation. They'll take another. They have another

917
00:48:48,800 --> 00:48:50,960
Speaker 3: shot at that on the other side of the fiscal year.

918
00:48:51,400 --> 00:48:52,000
Speaker 2: October.

919
00:48:52,560 --> 00:48:54,600
Speaker 3: Yeah, that's when the new fiscal year begins. And so

920
00:48:54,640 --> 00:48:57,640
Speaker 3: they could come up with more stimulus. Right, you've heard

921
00:48:57,640 --> 00:49:00,640
Speaker 3: talk of a stimulus check. You know, I'll pay for

922
00:49:00,719 --> 00:49:03,120
Speaker 3: the We'll take the tariff revenue, and I'll rebate some

923
00:49:03,200 --> 00:49:05,919
Speaker 3: of that back to Americans in the form of a check.

924
00:49:05,960 --> 00:49:09,280
Speaker 3: And that would that that would be stimulus for sure. Uh,

925
00:49:09,320 --> 00:49:10,000
Speaker 3: and that would.

926
00:49:10,040 --> 00:49:12,520
Speaker 2: Listen to work. The last Trump indmustration, he wrote a

927
00:49:12,600 --> 00:49:16,840
Speaker 2: check and when people were stuck at home, and you know,

928
00:49:17,560 --> 00:49:20,399
Speaker 2: I try and be nonpartisan when I look at those

929
00:49:20,440 --> 00:49:24,240
Speaker 2: sort of things. It turns out Keynes was onto something

930
00:49:24,280 --> 00:49:25,480
Speaker 2: a century ago, wasn't he.

931
00:49:25,640 --> 00:49:28,520
Speaker 3: Well, particularly if the economy's not at full employment. If

932
00:49:28,560 --> 00:49:30,440
Speaker 3: you're if you're flat on your back like you were

933
00:49:30,440 --> 00:49:33,879
Speaker 3: in the pandemic or financial crisis, you provide stimulus. Then

934
00:49:33,920 --> 00:49:35,480
Speaker 3: you don't get the crowding out, you don't get the

935
00:49:35,560 --> 00:49:37,400
Speaker 3: higher interest rates, you don't get the inflation, but you

936
00:49:37,440 --> 00:49:40,160
Speaker 3: get the growth. So we're now we're now closer to

937
00:49:40,200 --> 00:49:42,719
Speaker 3: full employment. So that's a bit of a more dangerous

938
00:49:42,760 --> 00:49:46,200
Speaker 3: game because if you overstimulate and your full employment, you're

939
00:49:46,200 --> 00:49:48,399
Speaker 3: gonna get the inflation. Already, inflation is an issue given

940
00:49:48,400 --> 00:49:49,840
Speaker 3: the tariffs and the immigration policy.

941
00:49:49,920 --> 00:49:52,520
Speaker 2: So let's talk about tariffs before we get to inflation.

942
00:49:54,000 --> 00:49:58,400
Speaker 2: What's your perspective of the impact of both the policy

943
00:49:58,480 --> 00:50:00,520
Speaker 2: and the way it's been in implemented.

944
00:50:00,840 --> 00:50:03,120
Speaker 3: Well, I'm not a fan of broad based tariffs. I mean,

945
00:50:03,160 --> 00:50:06,040
Speaker 3: strategic tariff's no problem. I can kind of get that,

946
00:50:06,760 --> 00:50:08,839
Speaker 3: but broad based tariffs. So you know, we've been there,

947
00:50:08,880 --> 00:50:11,640
Speaker 3: We've done that. You mentioned the nineteen thirties. In fact,

948
00:50:11,640 --> 00:50:14,600
Speaker 3: you can go back one hundred years before that under

949
00:50:14,680 --> 00:50:17,120
Speaker 3: Andrew Jackson, and we tried broad based traffs and it

950
00:50:17,120 --> 00:50:18,680
Speaker 3: didn't work out so well. It takes about one hundred

951
00:50:18,719 --> 00:50:21,200
Speaker 3: years for us to forget the mistake and do it again.

952
00:50:21,760 --> 00:50:24,800
Speaker 3: So I don't think this is going to end well,

953
00:50:25,960 --> 00:50:29,520
Speaker 3: it raises inflation by definition, and then we'll see more

954
00:50:29,520 --> 00:50:32,560
Speaker 3: of those past those prices pass through to consumers over

955
00:50:32,600 --> 00:50:34,800
Speaker 3: the next six to twelve months. As the time passes

956
00:50:34,840 --> 00:50:38,759
Speaker 3: here and it lowers growth, it pushes the economy towards stackflation.

957
00:50:38,840 --> 00:50:42,600
Speaker 3: And the immigration policy highly restrictive immigration policy, and I

958
00:50:42,680 --> 00:50:45,840
Speaker 3: get the need for addressing the southern border.

959
00:50:46,120 --> 00:50:49,120
Speaker 2: We're talking about legal immigration, not illegal exactly.

960
00:50:49,840 --> 00:50:54,400
Speaker 3: It's very restrictive, and that reinforces the higher inflation and

961
00:50:54,440 --> 00:50:56,640
Speaker 3: the weaker growth. So you've got two policies that are

962
00:50:57,040 --> 00:51:02,880
Speaker 3: very substantive working together to raise inflation. We can economic activity.

963
00:51:02,520 --> 00:51:06,680
Speaker 2: So reducing legal immigration contributes to higher inflation.

964
00:51:06,840 --> 00:51:09,120
Speaker 3: Explain that you're in the very go back to the

965
00:51:09,160 --> 00:51:13,880
Speaker 3: labor force, tight labor market, gotcha less bodies, highting, a

966
00:51:13,920 --> 00:51:20,160
Speaker 3: lot of businesses ag We know that restaurants, construction, leisure, hospitality,

967
00:51:20,520 --> 00:51:24,600
Speaker 3: elder care, childcare, all those things, and it will presumably

968
00:51:24,680 --> 00:51:28,439
Speaker 3: will raise costs labor costs, you'll wages rise and add

969
00:51:28,480 --> 00:51:29,640
Speaker 3: to inflationary pressures.

970
00:51:29,680 --> 00:51:33,440
Speaker 2: So we keep hearing from the FED that their data

971
00:51:33,480 --> 00:51:39,040
Speaker 2: dependent things are ambiguous. There's no clear, necessarily clear path

972
00:51:39,760 --> 00:51:44,840
Speaker 2: to a future policy. Is that a reasonable response given

973
00:51:44,920 --> 00:51:48,720
Speaker 2: everything that's been going on, Because it seems odd to say,

974
00:51:49,520 --> 00:51:51,600
Speaker 2: on the one hand, we're at risk of recession. On

975
00:51:51,640 --> 00:51:55,240
Speaker 2: the other hand, there's a chance of increased inflation. Sounds

976
00:51:55,280 --> 00:51:58,120
Speaker 2: a lot like seventies era stagflation.

977
00:51:58,360 --> 00:51:59,160
Speaker 3: It is stagflation.

978
00:51:59,480 --> 00:52:02,839
Speaker 2: What is that mean for where rates could go over

979
00:52:02,920 --> 00:52:06,920
Speaker 2: the next couple of meetings. It seems like a twenty

980
00:52:06,920 --> 00:52:10,399
Speaker 2: five bip cut is sort of locked into September, right,

981
00:52:10,440 --> 00:52:12,439
Speaker 2: and I don't know how much of that is. Hey,

982
00:52:12,520 --> 00:52:15,120
Speaker 2: let's just throw a virgin in the volcano and make

983
00:52:15,160 --> 00:52:20,400
Speaker 2: the make the president happy. But there are credible reasons

984
00:52:20,880 --> 00:52:24,200
Speaker 2: in both directions. This isn't like one sided debate.

985
00:52:24,760 --> 00:52:27,400
Speaker 3: I think their decision to stay on hold was the

986
00:52:27,440 --> 00:52:30,080
Speaker 3: right decision because they don't know what do I respond

987
00:52:30,120 --> 00:52:32,799
Speaker 3: to the inflation that I know is coming or the

988
00:52:32,800 --> 00:52:36,080
Speaker 3: weaker growth that is in train. I just and I

989
00:52:36,120 --> 00:52:38,680
Speaker 3: don't know where the policies are. I don't I have

990
00:52:38,760 --> 00:52:40,480
Speaker 3: no sense of where the tariffs are going to land

991
00:52:40,520 --> 00:52:41,879
Speaker 3: when they're going to land there. I don't know what's

992
00:52:41,880 --> 00:52:44,239
Speaker 3: going on with immigration policy. So let's just sit on

993
00:52:44,280 --> 00:52:46,680
Speaker 3: our hands and just let this thing unfold a little

994
00:52:46,680 --> 00:52:49,799
Speaker 3: bit before we can move on policy. Businesses are done

995
00:52:49,880 --> 00:52:52,120
Speaker 3: roughly the same thing. They're saying. I don't really know.

996
00:52:52,640 --> 00:52:55,480
Speaker 3: Therefore it's not I'm going to cut, but it means

997
00:52:55,480 --> 00:52:56,920
Speaker 3: I'm not going to expand I'm going to sit on

998
00:52:56,920 --> 00:52:59,200
Speaker 3: my hands, And that's why the economy has gone sideways

999
00:52:59,200 --> 00:53:01,480
Speaker 3: here since the beginning of the year. But here we

1000
00:53:01,520 --> 00:53:03,480
Speaker 3: are now, and if you're at the FED, and I

1001
00:53:03,560 --> 00:53:07,480
Speaker 3: think there are kind of their weights on their goals

1002
00:53:07,640 --> 00:53:11,000
Speaker 3: are shifting. They're putting more weight on the economy than

1003
00:53:11,040 --> 00:53:14,080
Speaker 3: on inflation. They're thinking is inflation because of the terriffs

1004
00:53:14,120 --> 00:53:16,719
Speaker 3: will be more one off. They won't be persistent, which

1005
00:53:17,239 --> 00:53:19,719
Speaker 3: I think is a reasonable thing to think. But we'll

1006
00:53:19,760 --> 00:53:22,680
Speaker 3: have to see. But we know the economy's weakening, particularly

1007
00:53:22,719 --> 00:53:25,080
Speaker 3: the job numbers, and I and I again going back

1008
00:53:25,120 --> 00:53:27,400
Speaker 3: to we're going to get some negative numbers here, and

1009
00:53:27,440 --> 00:53:29,360
Speaker 3: I think that's what they want to avoid, particularly in

1010
00:53:29,440 --> 00:53:32,000
Speaker 3: the context of the political environment, because there's a lot

1011
00:53:32,040 --> 00:53:37,200
Speaker 3: of stuff coming out of Washington about reevaluating the FEDS,

1012
00:53:37,800 --> 00:53:41,520
Speaker 3: the the Reserve active of nineteen thirteen. They're independence and

1013
00:53:41,560 --> 00:53:43,680
Speaker 3: if you're at the FED and you're seeing that, the

1014
00:53:43,800 --> 00:53:45,840
Speaker 3: last thing you want to do is go into recession

1015
00:53:45,840 --> 00:53:48,000
Speaker 3: and get blamed for the recession in the context of

1016
00:53:48,040 --> 00:53:50,400
Speaker 3: all those kind of that political overlay.

1017
00:53:50,280 --> 00:53:54,000
Speaker 2: To say the very least. So we haven't really talked

1018
00:53:54,000 --> 00:53:57,200
Speaker 2: about integrity of data, but since you alluded to it earlier,

1019
00:53:57,280 --> 00:54:00,440
Speaker 2: let's bring it up. You know, I'm a big fan

1020
00:54:00,520 --> 00:54:03,600
Speaker 2: of George Box. All models were wrong, but some are useful,

1021
00:54:04,520 --> 00:54:07,920
Speaker 2: and so my experience over the past I don't know,

1022
00:54:08,000 --> 00:54:10,960
Speaker 2: fifteen years, whenever I have a question about how something

1023
00:54:11,080 --> 00:54:15,800
Speaker 2: is put together in either a BA or BLS data point,

1024
00:54:16,280 --> 00:54:18,040
Speaker 2: I just pick up the phone and call them, and

1025
00:54:18,160 --> 00:54:21,759
Speaker 2: they eventually rout you to the person. Oh, here's the

1026
00:54:21,800 --> 00:54:25,560
Speaker 2: person who developed the birth death model, or here's the

1027
00:54:25,600 --> 00:54:32,319
Speaker 2: person in charge of survey data. They couldn't be more forthcoming, transparent,

1028
00:54:32,480 --> 00:54:36,920
Speaker 2: and helpful. And I'm kind of surprised at some of

1029
00:54:36,920 --> 00:54:40,600
Speaker 2: the crazy stuff I hear from people. I just heard

1030
00:54:40,640 --> 00:54:45,240
Speaker 2: a bunch of stuff about the MIT billion price project,

1031
00:54:45,320 --> 00:54:48,000
Speaker 2: which ended up getting picked up by somebody, and they

1032
00:54:48,000 --> 00:54:50,560
Speaker 2: were talking about how great that is, and I'm like, hey,

1033
00:54:50,600 --> 00:54:55,480
Speaker 2: when you track this against CPI, they're almost identical. So

1034
00:54:55,680 --> 00:54:59,440
Speaker 2: they're both different models. One is a little more skewed

1035
00:54:59,440 --> 00:55:02,640
Speaker 2: to the waiting of how consumers spend money, the other

1036
00:55:02,719 --> 00:55:05,400
Speaker 2: is just scraping all these data points, but they end

1037
00:55:05,480 --> 00:55:07,800
Speaker 2: up in the same place. How do you think about

1038
00:55:08,320 --> 00:55:12,560
Speaker 2: the integrity of data from the BLS right now?

1039
00:55:12,600 --> 00:55:17,200
Speaker 3: I think it's I think it's fine. There's problems, particularly

1040
00:55:17,239 --> 00:55:19,879
Speaker 3: with survey responses, but everyone but.

1041
00:55:19,840 --> 00:55:22,640
Speaker 2: That's true everywhere. Look at University of Michigan, sentiment data

1042
00:55:22,680 --> 00:55:24,839
Speaker 2: has been plumbting for ten and the answer to that

1043
00:55:24,920 --> 00:55:26,000
Speaker 2: isn't cut budgets.

1044
00:55:26,200 --> 00:55:28,960
Speaker 3: It isn't to cut staff, it is to put more

1045
00:55:29,000 --> 00:55:31,319
Speaker 3: resource into to help try to figure out how to

1046
00:55:31,360 --> 00:55:34,520
Speaker 3: improve those response rates. But even in employment data, the

1047
00:55:34,560 --> 00:55:37,040
Speaker 3: payroll employment day that we're focused on, the response rates

1048
00:55:37,080 --> 00:55:39,880
Speaker 3: by the third month is the first month of response

1049
00:55:39,960 --> 00:55:42,920
Speaker 3: rates sixty five I'm making this up, but roughly speaking, sixty.

1050
00:55:42,680 --> 00:55:45,360
Speaker 2: Five, which is below what it used to be.

1051
00:55:45,560 --> 00:55:47,520
Speaker 3: It's down from where it was. By the third it's

1052
00:55:47,600 --> 00:55:49,920
Speaker 3: ninety ninety five percent. So it's still a very very

1053
00:55:49,960 --> 00:55:54,360
Speaker 3: good survey. But we all as a result of the

1054
00:55:54,360 --> 00:55:57,520
Speaker 3: low response rates. We always get revisions to the data.

1055
00:55:58,320 --> 00:56:00,440
Speaker 3: In more typical times, when the economy moving in a

1056
00:56:00,480 --> 00:56:03,239
Speaker 3: straight line, those revisions are small. When you're at an

1057
00:56:03,280 --> 00:56:05,960
Speaker 3: inflection point or a turning point, like I've been arguing

1058
00:56:06,040 --> 00:56:08,560
Speaker 3: we are, you get these big revisions. In fact, there's

1059
00:56:08,560 --> 00:56:12,920
Speaker 3: information in the revisions. It's not a bug, it's a feature.

1060
00:56:12,960 --> 00:56:16,040
Speaker 3: It's saying, hey, the economy's weakening, and so the response

1061
00:56:16,120 --> 00:56:18,759
Speaker 3: rates the responses were getting after after the first month

1062
00:56:18,880 --> 00:56:20,600
Speaker 3: or weaker than the ones we got in the first month,

1063
00:56:20,600 --> 00:56:24,360
Speaker 3: and therefore we're revising down the data. That's signaling as

1064
00:56:24,360 --> 00:56:27,920
Speaker 3: a strong tell that the economy is struggling and potentially

1065
00:56:27,960 --> 00:56:29,200
Speaker 3: at a turning point.

1066
00:56:29,280 --> 00:56:32,360
Speaker 2: So you're saying the July non farm payroll, and I

1067
00:56:32,400 --> 00:56:34,560
Speaker 2: don't want to put words into your mouth. We had

1068
00:56:34,560 --> 00:56:37,719
Speaker 2: a July non farm payroll that was pretty punk that

1069
00:56:37,760 --> 00:56:40,279
Speaker 2: came out the first week in August, but the revisions

1070
00:56:40,280 --> 00:56:44,160
Speaker 2: were substantial for the prior two months. This isn't just

1071
00:56:44,200 --> 00:56:50,560
Speaker 2: a noisy data series or somehow partisan wrangling. This is

1072
00:56:50,600 --> 00:56:54,279
Speaker 2: a warning shot across the bow. Hey, the economy is

1073
00:56:54,320 --> 00:56:57,720
Speaker 2: starting to transition into a weaker state. Exact pay attention

1074
00:56:58,040 --> 00:56:59,080
Speaker 2: is that effects the point?

1075
00:56:59,200 --> 00:57:03,000
Speaker 3: That's the point. It's not that the data is any

1076
00:57:03,040 --> 00:57:05,239
Speaker 3: worse than it has been historically. There's anything the fary

1077
00:57:05,360 --> 00:57:08,920
Speaker 3: is going on. It's that is the nature of the data,

1078
00:57:09,120 --> 00:57:13,279
Speaker 3: and it's telling us something. There's real information there, and

1079
00:57:13,360 --> 00:57:15,359
Speaker 3: so I, you know, I do. The thing I worry

1080
00:57:15,360 --> 00:57:18,240
Speaker 3: about the most is if there's a decision to not

1081
00:57:18,360 --> 00:57:20,919
Speaker 3: release the data as timely as it's being released today.

1082
00:57:20,960 --> 00:57:23,200
Speaker 3: The employment numbers that we've been talking about are the

1083
00:57:23,240 --> 00:57:25,640
Speaker 3: most timely day to get released the Friday of the first.

1084
00:57:25,440 --> 00:57:27,840
Speaker 2: Oh the quarterly nonsense that came out, that just.

1085
00:57:27,840 --> 00:57:30,160
Speaker 3: Seems, yeah, that really makes me nervous.

1086
00:57:29,960 --> 00:57:32,560
Speaker 2: That's I think Wall Street would have a hissy fit.

1087
00:57:32,680 --> 00:57:33,680
Speaker 2: You do if that happen?

1088
00:57:33,760 --> 00:57:34,000
Speaker 3: Yeah?

1089
00:57:34,160 --> 00:57:40,120
Speaker 2: The you know what people talk about the Powell put.

1090
00:57:41,400 --> 00:57:45,720
Speaker 2: I prefer the expression the Trump collar when when the

1091
00:57:45,760 --> 00:57:48,920
Speaker 2: market's near all time highs, he's embolden and rolls out stuff.

1092
00:57:49,160 --> 00:57:52,320
Speaker 2: When the market's now fifteen to twenty percent, that's a floor.

1093
00:57:52,760 --> 00:57:56,800
Speaker 2: All right, we'll pause this for ninety days because rightly

1094
00:57:56,880 --> 00:58:00,640
Speaker 2: or wrongly, and I think there's more to this, then

1095
00:58:00,720 --> 00:58:04,240
Speaker 2: we give President Trump credit for But when the stock

1096
00:58:04,320 --> 00:58:07,200
Speaker 2: market is doing well, he takes that as his report card,

1097
00:58:07,520 --> 00:58:09,800
Speaker 2: and when the stock market is doing poorly, it makes

1098
00:58:09,880 --> 00:58:14,040
Speaker 2: him unhappy, and his bias is towards doing something anything.

1099
00:58:14,560 --> 00:58:15,920
Speaker 2: What do we have to do to get the stock

1100
00:58:15,960 --> 00:58:19,240
Speaker 2: market back on track? He doesn't care about polls. He

1101
00:58:19,320 --> 00:58:23,760
Speaker 2: cares about one poll, and that's the Dow Jones Industrial

1102
00:58:23,800 --> 00:58:25,840
Speaker 2: Average or the NASDUK or the SMP.

1103
00:58:26,440 --> 00:58:28,720
Speaker 3: Kind of focuses his attention. It's a nice way of

1104
00:58:28,720 --> 00:58:29,720
Speaker 3: putting the Trump caller.

1105
00:58:30,880 --> 00:58:33,560
Speaker 2: So I don't want to make you late for lunch.

1106
00:58:34,120 --> 00:58:36,240
Speaker 2: I have one more question before we get to our

1107
00:58:36,280 --> 00:58:41,840
Speaker 2: speed round our favorite questions, and it's a curveball question,

1108
00:58:41,920 --> 00:58:47,400
Speaker 2: which is what are investors and economists not talking about

1109
00:58:47,600 --> 00:58:49,960
Speaker 2: but perhaps they should be. What what do you think

1110
00:58:50,040 --> 00:58:53,919
Speaker 2: is an important topic? And I don't care policy assets, geographies,

1111
00:58:54,440 --> 00:58:55,680
Speaker 2: what's getting overlooked?

1112
00:58:55,680 --> 00:58:59,919
Speaker 3: But shouldn't I say, FED independence, Not that people aren't

1113
00:59:00,040 --> 00:59:02,120
Speaker 3: talking about it, but they're not focused on it like

1114
00:59:02,160 --> 00:59:03,960
Speaker 3: they should be focused on it. I think this is

1115
00:59:04,000 --> 00:59:10,920
Speaker 3: a real, potentially a real significant problem, and the independence

1116
00:59:10,960 --> 00:59:14,600
Speaker 3: of the FED is critical to a well functioning market

1117
00:59:14,640 --> 00:59:17,720
Speaker 3: economy like our own. We know that from our own history.

1118
00:59:17,920 --> 00:59:20,000
Speaker 3: You can see what happened back in the seventies and eighties,

1119
00:59:20,000 --> 00:59:24,400
Speaker 3: and or looking overseas, and we need to preserve that independence.

1120
00:59:24,440 --> 00:59:26,640
Speaker 3: And it's not only about the actual independence, it's the

1121
00:59:26,720 --> 00:59:30,920
Speaker 3: perception of independence that's really critical. And it just doesn't

1122
00:59:30,920 --> 00:59:33,080
Speaker 3: feel like to me. You follow markets more closely than

1123
00:59:33,120 --> 00:59:35,760
Speaker 3: I do, maybe have a different view, but I just

1124
00:59:35,760 --> 00:59:37,760
Speaker 3: don't get this sentence that markets are focused on this

1125
00:59:37,920 --> 00:59:40,040
Speaker 3: like they should be at this point in time. Huh.

1126
00:59:40,480 --> 00:59:44,040
Speaker 2: Pretty interesting? Take all right, let's jump to our speed round. Okay,

1127
00:59:44,080 --> 00:59:46,640
Speaker 2: feel free to bang through these as quickly as you want.

1128
00:59:46,720 --> 00:59:49,840
Speaker 2: We'll get you to lunch on time. Starting with who

1129
00:59:49,920 --> 00:59:52,200
Speaker 2: your mentors, who helped shape your career?

1130
00:59:52,640 --> 00:59:55,400
Speaker 3: Well, I mentioned doctor Klein in the Nobel Laureate. He

1131
00:59:55,680 --> 01:00:02,240
Speaker 3: clearly was a key person in my professional life. My father, uh,

1132
01:00:02,960 --> 01:00:05,480
Speaker 3: professor of engineering at Penn by the way, he will

1133
01:00:05,520 --> 01:00:08,040
Speaker 3: he'll claim he was the first to use neural nets

1134
01:00:08,080 --> 01:00:12,600
Speaker 3: back in the day for the studies he was doing.

1135
01:00:13,840 --> 01:00:16,240
Speaker 3: But I'd say those two folks are those two two

1136
01:00:16,240 --> 01:00:20,000
Speaker 3: men were the key to my to my professional development.

1137
01:00:20,240 --> 01:00:22,440
Speaker 2: Let's talk about books. What are some of your favorites?

1138
01:00:22,480 --> 01:00:25,400
Speaker 3: What are you reading? Sounds hackney now, but you know, Barry,

1139
01:00:25,440 --> 01:00:29,480
Speaker 3: I like, I just love Alexander Hamilton by Charnow. I mean,

1140
01:00:29,520 --> 01:00:31,680
Speaker 3: I that was well.

1141
01:00:31,680 --> 01:00:34,480
Speaker 2: Because the book doesn't have any wrapping in it, people

1142
01:00:34,720 --> 01:00:37,600
Speaker 2: should be aware if they go get this book, it's

1143
01:00:37,640 --> 01:00:41,520
Speaker 2: a deep historical dive. It's not an entertaining bunch of

1144
01:00:41,520 --> 01:00:42,120
Speaker 2: show tunes.

1145
01:00:42,880 --> 01:00:46,320
Speaker 3: Oh yes, that's for sure. But it's very entertaining, at

1146
01:00:46,400 --> 01:00:48,040
Speaker 3: least from a nerdy kind of perspective.

1147
01:00:48,240 --> 01:00:50,240
Speaker 2: Charn now has a new book coming out this fall,

1148
01:00:50,320 --> 01:00:51,520
Speaker 2: does any or did it come out?

1149
01:00:51,960 --> 01:00:53,840
Speaker 3: Well, I've got the I'm reading one on Washington.

1150
01:00:54,280 --> 01:00:55,000
Speaker 2: Is that is that?

1151
01:00:55,400 --> 01:00:57,400
Speaker 3: I think that's his latest? Yeah? I think so.

1152
01:00:58,240 --> 01:00:59,720
Speaker 2: He is an amazing writer.

1153
01:01:00,040 --> 01:01:03,440
Speaker 3: And uh and I like that period in economic history,

1154
01:01:05,800 --> 01:01:09,760
Speaker 3: to say the very least, and then I don't. I

1155
01:01:09,800 --> 01:01:13,040
Speaker 3: don't normally read self help books, but I like this

1156
01:01:13,040 --> 01:01:15,040
Speaker 3: book Outlive. I know everyone else has read it by

1157
01:01:15,160 --> 01:01:17,480
Speaker 3: oh sure, four years ago. So now I'm hanging.

1158
01:01:17,600 --> 01:01:20,960
Speaker 2: Is it worth reading? It's oh, Mark Twain is his name,

1159
01:01:21,080 --> 01:01:24,960
Speaker 2: Mark Twain. That's right, it's a it's a tomb. It's

1160
01:01:25,000 --> 01:01:30,200
Speaker 2: sitting on my nightstand gathering dust because it's so so intimidating,

1161
01:01:30,760 --> 01:01:33,600
Speaker 2: deep deep research. Outlive.

1162
01:01:34,160 --> 01:01:37,200
Speaker 3: Oh yeah, So it's an easy book. It's summer book

1163
01:01:37,240 --> 01:01:41,960
Speaker 3: right when you're on the beach. It's a how do

1164
01:01:42,000 --> 01:01:45,920
Speaker 3: you live your life well? Long run, and it's a

1165
01:01:45,920 --> 01:01:48,760
Speaker 3: lot of it's just intuitive. It's not non intuitive. But

1166
01:01:48,800 --> 01:01:50,800
Speaker 3: there's some things in there that I found useful in

1167
01:01:50,920 --> 01:01:52,680
Speaker 3: terms of the tests you should take. And I love

1168
01:01:52,720 --> 01:01:58,680
Speaker 3: the the hanging. You big part of of the work

1169
01:01:58,800 --> 01:02:03,240
Speaker 3: is around the strip grip strength, and so one of

1170
01:02:03,280 --> 01:02:05,480
Speaker 3: the ways you improve your grip strength is by just

1171
01:02:05,560 --> 01:02:08,960
Speaker 3: literally hanging from go try it. Okay, it's I've been

1172
01:02:09,880 --> 01:02:10,040
Speaker 3: you know.

1173
01:02:10,200 --> 01:02:12,200
Speaker 2: He says chin ups or pull ups, you just have

1174
01:02:12,280 --> 01:02:13,040
Speaker 2: to hang.

1175
01:02:13,160 --> 01:02:15,840
Speaker 3: You think this is easy, and he says, men, if

1176
01:02:15,840 --> 01:02:17,840
Speaker 3: men can do it for two minutes, that's great. Women

1177
01:02:17,920 --> 01:02:20,680
Speaker 3: one minute I'll tell you. I can't get. I literally

1178
01:02:20,760 --> 01:02:21,160
Speaker 3: can I get.

1179
01:02:21,520 --> 01:02:23,960
Speaker 2: I can't imagine. I can't. I'm not going to do

1180
01:02:24,080 --> 01:02:27,280
Speaker 2: ten pull ups, but I would be surprised if I

1181
01:02:27,280 --> 01:02:30,560
Speaker 2: couldn't hang for right for two minutes.

1182
01:02:30,600 --> 01:02:32,160
Speaker 3: But yeah, I try, try try.

1183
01:02:32,240 --> 01:02:34,520
Speaker 2: Actually, that's that's that's interesting.

1184
01:02:34,720 --> 01:02:35,040
Speaker 1: All right.

1185
01:02:35,080 --> 01:02:37,760
Speaker 2: So we're talking about books. What about streaming? What do

1186
01:02:37,800 --> 01:02:38,160
Speaker 2: you watch?

1187
01:02:39,040 --> 01:02:41,440
Speaker 3: My wife and I watch something every night, usually half

1188
01:02:41,520 --> 01:02:42,520
Speaker 3: hour to an hour.

1189
01:02:42,440 --> 01:02:46,640
Speaker 2: And we're the same. It's a post pandemic. Yeah, because

1190
01:02:46,800 --> 01:02:48,439
Speaker 2: when you were stuck at home, you couldn't go out,

1191
01:02:48,960 --> 01:02:49,640
Speaker 2: didn't we all.

1192
01:02:49,920 --> 01:02:52,920
Speaker 3: I'm annoyed with all these streaming services, like like like,

1193
01:02:53,080 --> 01:02:54,200
Speaker 3: come on, hit me a break.

1194
01:02:54,320 --> 01:02:57,240
Speaker 2: I mean, so, so what what are you streaming these days?

1195
01:02:57,360 --> 01:02:57,480
Speaker 1: Well?

1196
01:02:57,560 --> 01:02:58,960
Speaker 3: I got you? Got any suggestions?

1197
01:02:59,320 --> 01:03:01,120
Speaker 2: Yes, yes I do, I have plenty.

1198
01:03:01,320 --> 01:03:04,640
Speaker 3: I just finished disclaimer? Did you say watch one? Okay?

1199
01:03:04,680 --> 01:03:06,600
Speaker 2: I love a good suggestion disclaimer.

1200
01:03:06,720 --> 01:03:11,920
Speaker 3: Yeah, it's Kevin Klein and Cape Blanchett. Oh no kidding,

1201
01:03:12,000 --> 01:03:13,360
Speaker 3: it's short six seven.

1202
01:03:13,760 --> 01:03:16,840
Speaker 2: I love those. We watched Apartment Q, which was a

1203
01:03:16,880 --> 01:03:19,440
Speaker 2: limited series, is good, really interesting.

1204
01:03:19,840 --> 01:03:21,320
Speaker 3: Actually I watched that that was very good. This is

1205
01:03:21,360 --> 01:03:24,040
Speaker 3: one I liked a lot. It's the ending is the

1206
01:03:24,080 --> 01:03:27,160
Speaker 3: acting is great. Yeah, the ending is a little contrived.

1207
01:03:27,160 --> 01:03:29,240
Speaker 3: They need to do two more episodes or something.

1208
01:03:29,280 --> 01:03:33,240
Speaker 2: I'll give you three interesting things. We've been watching My Wife.

1209
01:03:33,360 --> 01:03:36,280
Speaker 2: My wife got me sucked into Killing Eve, which is

1210
01:03:36,320 --> 01:03:40,480
Speaker 2: an espionage thriller. We just it's four seasons. We just

1211
01:03:40,480 --> 01:03:44,080
Speaker 2: started the second season, everybody, and it is great. It's

1212
01:03:44,080 --> 01:03:46,600
Speaker 2: a little, it's a little, you know, some of it is.

1213
01:03:46,680 --> 01:03:52,400
Speaker 2: It's not terribly gory. People get killed. It's assassin and yeah,

1214
01:03:52,640 --> 01:03:57,120
Speaker 2: you know, I don't like the police procedurals where they

1215
01:03:57,200 --> 01:04:00,120
Speaker 2: show you all the when it's too realistic. Yeah, like

1216
01:04:00,160 --> 01:04:02,080
Speaker 2: we tried to watch the pit. My wife is like,

1217
01:04:02,160 --> 01:04:05,200
Speaker 2: I'm out, all right, I get that. So so Killing

1218
01:04:05,240 --> 01:04:10,680
Speaker 2: Eve has been really interesting. And you know what's fascinating

1219
01:04:10,720 --> 01:04:17,320
Speaker 2: about the Gilded Age is it's four stories old money,

1220
01:04:17,480 --> 01:04:21,920
Speaker 2: new money, the staff in both of these houses across

1221
01:04:21,960 --> 01:04:25,360
Speaker 2: the street, and then the old money secretary who is

1222
01:04:25,400 --> 01:04:30,480
Speaker 2: a black woman, and then her whole family and that storyline.

1223
01:04:30,720 --> 01:04:34,440
Speaker 2: But what's amazing is all the issues. It's one hundred

1224
01:04:34,440 --> 01:04:39,520
Speaker 2: and fifty years ago. Today it's wealth inequality, it's status,

1225
01:04:39,560 --> 01:04:45,600
Speaker 2: it's economic mobility, and it's tribal and it's so fascinating

1226
01:04:46,400 --> 01:04:50,920
Speaker 2: the guilded Age really interesting. I didn't want to watch it.

1227
01:04:50,960 --> 01:04:54,960
Speaker 2: To me, Dountain kind of looked like another soap opera,

1228
01:04:55,080 --> 01:04:58,800
Speaker 2: but amazing cast. You get sucked into it. That's on HBO,

1229
01:04:58,960 --> 01:05:05,640
Speaker 2: and so so said, so if a well department Q

1230
01:05:06,480 --> 01:05:10,360
Speaker 2: was the limited. If you like the uh, if you

1231
01:05:10,560 --> 01:05:15,840
Speaker 2: like the f spionage sort of thing, that one kind

1232
01:05:15,840 --> 01:05:22,440
Speaker 2: of unfolds really slowly and deliberately. But Killing Eve is

1233
01:05:22,520 --> 01:05:27,160
Speaker 2: much It's much faster and crazier and more interesting. And

1234
01:05:27,200 --> 01:05:30,520
Speaker 2: it it's mostly takes place in Europe, which makes it

1235
01:05:31,040 --> 01:05:35,560
Speaker 2: you know, it's I six, I won all sorts of

1236
01:05:35,560 --> 01:05:39,560
Speaker 2: awards this like I got she sort of ready, and

1237
01:05:39,600 --> 01:05:42,360
Speaker 2: when she was she I walk in and and like,

1238
01:05:42,400 --> 01:05:45,200
Speaker 2: what's this? She's like, just watch ten minutes of the

1239
01:05:45,200 --> 01:05:48,800
Speaker 2: first episode, all right, And we started watching it and

1240
01:05:49,720 --> 01:05:50,360
Speaker 2: sucked right in.

1241
01:05:50,600 --> 01:05:52,360
Speaker 3: Oh that sounds good. I definitely watch that.

1242
01:05:52,440 --> 01:05:54,800
Speaker 2: It's four seasons we need, that's right. So it gives

1243
01:05:54,880 --> 01:05:57,040
Speaker 2: you plenty and you can bang out to a night

1244
01:05:57,280 --> 01:06:01,600
Speaker 2: very very comfortably. Our final two questions, what sort of

1245
01:06:01,640 --> 01:06:05,160
Speaker 2: advice would you give a recent college grad interested in

1246
01:06:05,200 --> 01:06:07,440
Speaker 2: a career in economics and finance?

1247
01:06:08,520 --> 01:06:10,800
Speaker 3: Just show up, show up, just show up.

1248
01:06:10,840 --> 01:06:12,439
Speaker 2: Do the work, show up, show up.

1249
01:06:13,600 --> 01:06:16,480
Speaker 3: I guess the other thing I'd say is I tell

1250
01:06:16,520 --> 01:06:23,240
Speaker 3: my kids this. Every point of contact matters, every relationship,

1251
01:06:23,280 --> 01:06:29,800
Speaker 3: every phone call, every email, every team's meeting, because things

1252
01:06:29,840 --> 01:06:34,520
Speaker 3: come around. You know, you meet somebody in one way,

1253
01:06:34,600 --> 01:06:39,160
Speaker 3: they'll come back ten years from now, and if you

1254
01:06:39,400 --> 01:06:44,160
Speaker 3: did the right thing, if you were attentive to their

1255
01:06:44,280 --> 01:06:46,680
Speaker 3: needs and interests, that'll benefit you in the long run.

1256
01:06:46,720 --> 01:06:50,120
Speaker 3: It's not easy to do, it takes energy, but every

1257
01:06:50,160 --> 01:06:51,880
Speaker 3: point of contact matters. Huh.

1258
01:06:51,960 --> 01:06:54,760
Speaker 2: Really interesting And our final question, what do you know

1259
01:06:54,800 --> 01:06:57,520
Speaker 2: about the world of economics today? You wish you knew

1260
01:06:58,040 --> 01:07:01,000
Speaker 2: way back in the nineteen nineties when you first starting.

1261
01:07:00,680 --> 01:07:05,680
Speaker 3: Out, Well, I didn't. I thought everything could go back

1262
01:07:05,680 --> 01:07:08,280
Speaker 3: to your point about box and models. I thought everything

1263
01:07:08,280 --> 01:07:12,560
Speaker 3: could be solved with the model. It's like, you, guys,

1264
01:07:12,560 --> 01:07:16,360
Speaker 3: come on, this is just arithmetic, you know, mathematics. We could,

1265
01:07:16,600 --> 01:07:19,840
Speaker 3: we should be able to do this now, you know,

1266
01:07:19,880 --> 01:07:21,320
Speaker 3: the world is a very messy place.

1267
01:07:22,360 --> 01:07:24,720
Speaker 2: Really, really good stuff. Mark, Thank you for being so

1268
01:07:24,960 --> 01:07:28,840
Speaker 2: generous with your time. We have been speaking with Mark Zandy.

1269
01:07:28,960 --> 01:07:33,400
Speaker 2: He is the chief economist of Moody's Analytics. If you

1270
01:07:33,680 --> 01:07:37,160
Speaker 2: enjoyed this conversation, check out any of the five hundred

1271
01:07:37,200 --> 01:07:41,920
Speaker 2: and fifty previous discussions we've had over the past eleven years.

1272
01:07:42,400 --> 01:07:48,040
Speaker 2: You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever

1273
01:07:48,120 --> 01:07:51,560
Speaker 2: you find your favorite podcast. And be sure and check

1274
01:07:51,600 --> 01:07:55,800
Speaker 2: out my new book, How Not to Invest The ideas, numbers,

1275
01:07:55,800 --> 01:07:59,880
Speaker 2: and behaviors that destroys wealth and how to avoid them

1276
01:08:00,360 --> 01:08:04,080
Speaker 2: How Not to Invest at your favorite bookstore. Now, I

1277
01:08:04,120 --> 01:08:06,200
Speaker 2: would be remiss if I did not thank the Crack

1278
01:08:06,280 --> 01:08:10,960
Speaker 2: team that helps put these conversations together each week. Meredith

1279
01:08:11,040 --> 01:08:16,080
Speaker 2: Frank is my audio engineer. Alexis Noriega and Anna Luke

1280
01:08:16,160 --> 01:08:21,599
Speaker 2: are my producers. Sean Russo is my researcher. Sage Bauman

1281
01:08:21,840 --> 01:08:23,920
Speaker 2: is the head of podcasts at Bloomberg.

1282
01:08:24,520 --> 01:08:25,840
Speaker 3: I'm Barry Rittolfs.

1283
01:08:26,080 --> 01:08:34,480
Speaker 2: You're listening to Masters in Business on Bloomberg Radio.