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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.

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Speaker 2: Hello and welcome to another episode of the Audlots Podcast.

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Speaker 2: I'm Tracy Alloway.

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Speaker 3: And I'm Joe. Why isn't Joe?

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Speaker 2: This is very special. This is actually this must be

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Speaker 2: our fastest turnaround time on an episode ever.

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Speaker 3: Well, it is election day.

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Speaker 4: Yes, I think we had technically a faster turnaround day

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Speaker 4: on the day of the Baltimore Bridge collapse.

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Speaker 2: Okay, fine, fine, but this was like four hours of

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Speaker 2: content that we are squeezing into a very timely episode.

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Speaker 2: So what you are about to hear is a live

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Speaker 2: recording of the Audlots Podcast, multiple panels, multiple conversations, that

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Speaker 2: took place on November fourth, at a recording in front

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Speaker 2: of a live audio in New York.

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Speaker 5: That's right.

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Speaker 4: So today is an election day. Last night was election Eve.

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Speaker 4: We figured a bunch of people, if they have preferences

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Speaker 4: in this election, we're probably anxious looking for something to

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Speaker 4: do other than just sort of refresh the Internet and

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Speaker 4: refresh Twitter all night. So I figure, why not get

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Speaker 4: some of our favorite guests over the years from the

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Speaker 4: podcast and get our fans who we always love seeing

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Speaker 4: our listeners and hang out and talk politics and policy

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Speaker 4: for a little while. And I didn't drink, actually, but

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Speaker 4: some people drank.

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Speaker 2: I stress drink.

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Speaker 6: I did it.

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Speaker 3: Yeah I didn't.

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Speaker 2: But what better way to spend election day than listening

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Speaker 2: to some live recordings of the au Thoughts podcast. So

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Speaker 2: what you are about to hear is a selection of

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Speaker 2: the conversations. We had some amazing guests. So we started

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Speaker 2: with Zoe lu She is of course a senior fellow

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Speaker 2: for China Studies at the Council on Foreign Relations, and

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Speaker 2: we had her with Jordan Schneider of the China Talk podcast.

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Speaker 2: We've spoken to both of them before, but we had

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Speaker 2: a great conversation about what's going on in China right

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Speaker 2: now and what could possibly happen with US China trade.

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Speaker 4: Right and then where this particular episode will pick up.

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Speaker 4: Then we had a conversation with Neil Dutta of Renaissance

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Speaker 4: Macro Research, Sconda Amernath, executive director at Employee America. And

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Speaker 4: we had a special guest that we kind of have

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Speaker 4: to explain here for a second, because otherwise some of

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Speaker 4: the conversation might not make any sense. We had zvie Maashwitz,

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Speaker 4: and he is a prediction market's better.

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Speaker 3: He's a writer.

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Speaker 4: He's a legendary designer of Magic the Gathering Decks. He's

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Speaker 4: an advisor to Polymarket. He used to be a Jane

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Speaker 4: Street trader. We're gonna have to have him on some time.

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Speaker 4: Tracy just yeah, it's totally separated.

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Speaker 6: He was great.

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Speaker 2: I just want to talk to him about deck construction, deck.

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Speaker 4: Construction in Jane Street. Let's do like that episode.

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Speaker 2: Okay, But Zphie, in addition to all those things, set

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Speaker 2: up a betting pool on Manifold for which podcast he

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Speaker 2: would actually appear on in twenty twenty four, and one

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Speaker 2: of those options was blocks, right.

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Speaker 4: He set it up at the beginning of the year,

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Speaker 4: and so there's all these different possibilities which podcast will

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Speaker 4: appear on. And just again to sort of set the stage,

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Speaker 4: we never announced the t V is going to be

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Speaker 4: part of this. He is our mystery guest. But we

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Speaker 4: flashed the market onto the screen behind us while we

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Speaker 4: were at caveat the place where we recorded the episode,

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Speaker 4: and then during the conversation we watched as the market

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Speaker 4: slowly repriced.

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Speaker 2: It's very priced up and down.

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Speaker 3: It was very strange.

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Speaker 4: My belief in efficient markets has been completely debunked.

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Speaker 2: No, you know what, it was this is actually really interesting.

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Speaker 2: There was someone in the audience who was using free

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Speaker 2: manifold tokens to bring the probability down even as V

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Speaker 2: was actually on stage. So a live experiment in how

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Speaker 2: prediction markets work.

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Speaker 4: How they actually work right. Well, Actually, one of the

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Speaker 4: things you'll hear is V talks a lot about one

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Speaker 4: of the constraints and prediction markets being a capital constraints

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Speaker 4: among traders. Yeah, so here's a guy who currently had

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Speaker 4: no capital construction because he had free tooken, and you

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Speaker 4: see how much that destroys that. So we started off

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Speaker 4: that conversation to about all things markets, finance, what to

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Speaker 4: watch it polling, what to watch for in tonight's selection yep.

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Speaker 2: And then our headliner of the evening was Brad Setzer.

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Speaker 2: He is, of course a senior fellow at the Council

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Speaker 2: on Foreign Relations, one of our favorite guests. We've had

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Speaker 2: him on I can't even remember how many times.

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Speaker 3: Nine times now probably Yeah.

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Speaker 2: He was also a trade advisor to USTR's Catherine Tie

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Speaker 2: under the Biden administration, So someone who definitely knows what's

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Speaker 2: up when it comes to, I guess, the sausage making

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Speaker 2: of trade policy. So a fantastic group, a great evening.

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Speaker 2: Big thanks to everyone who came, and if you weren't

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Speaker 2: able to make it in person, we hope you enjoy

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Speaker 2: this version.

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Speaker 4: Right so start off check out our first our conversation

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Speaker 4: with Skanda, Neil and Zvie. We have some great guests

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Speaker 4: coming up and.

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Speaker 2: Bowser chance to money.

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Speaker 3: Now's your chance you could play.

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Speaker 4: We have a one of the people I'm not gonna

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Speaker 4: say who it is, but one of the people that

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Speaker 4: we will be having on the show is an avid

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Speaker 4: prediction markets trader expert in this area, and I'm not gonna.

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Speaker 2: Say who it is, but it's a mystery mystery guest.

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Speaker 4: So let's bring to the stage, in no particular order,

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Speaker 4: we have a Neil Dutta of Renaissance Macro Research, frequent

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Speaker 4: odd Lots guests, and we have Skanda Amernath of Employee America,

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Speaker 4: another frequent odd Lots guest. And we have Zvimashewitz. He's

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Speaker 4: a writer, trader into prediction markets and stuff and currently

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Speaker 4: on Manifold Markets. There's a twenty percent chance that he

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Speaker 4: appears on odd Lots in the year twenty twenty four,

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Speaker 4: so we're doing a little test of prediction markets or sorry,

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Speaker 4: efficient markets right here live on stage, so.

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Speaker 3: Thank you so much. He's ready to insider trade.

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Speaker 4: He hasn't insider traded on his own market yet, but

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Speaker 4: it's just sitting there.

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Speaker 3: We'll see, we'll see if the odds move. We'll see.

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Speaker 2: If the odds move, they should be at one hundred percent.

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Speaker 4: So yeah, I guess prediction markets are debunked if they

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Speaker 4: don't immediately move to one hundred percent.

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Speaker 3: Actually, V, let's start with you.

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Speaker 4: When you look at any prediction markets and you're also

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Speaker 4: advisor to polymarket.

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Speaker 6: Yes, I'm advised it's your trader prediction market guy.

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Speaker 3: Oh there it is. It moved up to forty four percent,

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Speaker 3: still works, It's still.

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Speaker 6: Not high enough, Like it's still I'm not sure.

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Speaker 3: It's literally on stage, is literally on stage right now?

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Speaker 6: Like how do you note that? Yes, but you don't

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Speaker 6: think you should take it farther?

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Speaker 4: Yeah, it's something for okay whatever, maybe if someone, oh

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Speaker 4: there it is, someone tweet this out. There's still fourteen

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Speaker 4: percent gains to be made. The IRR of fourteen percent

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Speaker 4: in like thirty seconds of increduble anyway, when we see

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Speaker 4: these odds, not for this market, apparently, but when we

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Speaker 4: see these poly market and kelshy odds, et cetera. They say, whatever,

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Speaker 4: how seriously should we take them?

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Speaker 6: I take them at least as seriously as any other

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Speaker 6: data point or source of information that we have available.

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Speaker 6: They are the best thing we have.

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Speaker 4: It's up to there's still a chance that you're not

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Speaker 4: appearing on this stage right now.

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Speaker 2: Yeah, wait, why do you they're the best thing we have? Like,

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Speaker 2: please explain in the context of this still being stuck

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Speaker 2: at ninety four percent.

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Speaker 6: Well, if you're on the internet, what other source do

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Speaker 6: you have other than the actual broadcast? Like obviously, if

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Speaker 6: you're looking at the poll not just the polls, but

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Speaker 6: like the actual ballots and you're like, oh, I guess

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Speaker 6: we know who won, then that's better than a prediction market.

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Speaker 6: But anything short of that that we have is going

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Speaker 6: to be incorporated into the prediction market, right, So, like

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Speaker 6: the polls, the aggrogations, the projections, all of that gets

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Speaker 6: worked into how we trade the prediction markets. So for

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Speaker 6: the prediction markets to be wrong, there has to be

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Speaker 6: is thematic mistake. And those mistakes do happen, and you

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Speaker 6: can in fact profit from them, but it cannot to

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Speaker 6: be very large.

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Speaker 4: Neil, what about real markets, and you know, you're always

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Speaker 4: watching what's happened what I said, real markets, the ticker DJT,

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Speaker 4: what's happening in rates, maybe regional banks. What are you

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Speaker 4: like seeing over the last few days or what are

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Speaker 4: you going to be sort of watching in terms of

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Speaker 4: the real markets and how they trade.

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Speaker 7: Well, I I mean, my work suggests that the sort

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Speaker 7: of Trump trade, particularly with respective fixed income markets, wasn't

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Speaker 7: so much Trump, I mean, as it was just stronger

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Speaker 7: economic news. I mean, you have to remember that the increasing

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Speaker 7: probability at least up until recently, that you know, Trump

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Speaker 7: would you know, sweep into the White House. That was

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Speaker 7: coinciding at a time of you know, meaningful data surprises

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Speaker 7: to the upside, we had a strong job's number of

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Speaker 7: strong retail sales. Jobless claims have been low. So I

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Speaker 7: think it's less about politics and a lot more just

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Speaker 7: about the data as it's been coming out. I mean,

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Speaker 7: in terms of what I'm going to be watching in particular,

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Speaker 7: my sense is that people will just replay the twenty

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Speaker 7: sixteen playbook if if that's what happens, and if you

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Speaker 7: get the alternative, in which case I think it's likely

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Speaker 7: that you know a Vice President Harris Wins. You probably

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Speaker 7: get a Republican center. You probably see, you know, a

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Speaker 7: rally and fixed income.

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Speaker 2: Scanda. What are you watching? Because with poles, so obviously

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Speaker 2: there's a lot of you know, people have strong opinions

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Speaker 2: about the usefulness of poles. I kind of think, like

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Speaker 2: who is answering the phone anymore? If someone an unidentified

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Speaker 2: number is calling them, it feels like there's a bias

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Speaker 2: to towards a certain demographic that's actually picking up the phone.

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Speaker 6: But what are you watching?

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Speaker 8: Yeah, I mean I think there's a clear limit on

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Speaker 8: what poles are going to be able to tell you

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Speaker 8: be on a certain point. I think that itself just

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Speaker 8: kind of tells you it's close.

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Speaker 5: It's probably fifty to fifty.

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Speaker 8: Your ability to discern whether it's fifty fifty or sixty

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Speaker 8: forty is pretty limited, even like you could make a

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Speaker 8: case for sixty forty for either side. But beyond this, like,

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Speaker 8: we don't have a lot of information that polls tell

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Speaker 8: us poles are scammier.

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Speaker 3: Now what do you mean by that?

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Speaker 8: There are some establishments that seem a little less scrupulous

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Speaker 8: that do a good job of gaming the rating systems.

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Speaker 8: So I guess like to give the finance analogy, so

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Speaker 8: passive versus active, like the idea of just like, okay,

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Speaker 8: just trust the aggregation more so than in visual polls.

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Speaker 8: But now we have like a weird set of partisan

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Speaker 8: or quasi partisan polsters that come in less transparent methodologies

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Speaker 8: and the attempts to make process to better understand who's

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Speaker 8: better who's worse.

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Speaker 5: That's not great.

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Speaker 8: So we actually have like aggregators that I don't pay

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Speaker 8: as much attention to relative to. Just like, Okay, if

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Speaker 8: there's a good poll from a whether it's a republican

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Speaker 8: establishment or democratic establishment, there are some good ones on

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Speaker 8: either side, I think that's got more information in it.

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Speaker 8: But even then it's like very limited, there's a ceiling.

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Speaker 8: I mean, I'd be more curious to see about the

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Speaker 8: geographic distribution. So obviously the Sphing states come out seven

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Speaker 8: pm onwards. We get some early states I report early

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Speaker 8: but are read. Just seeing the geographic distribution is gonna

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Speaker 8: be kind of interesting because that's actually the polarizing thing

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Speaker 8: I see, which is urban like urban versus more democratic

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Speaker 8: trending suburban versus rural, And it's like ultimately about the

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Speaker 8: margins and how those shift relatives of twenty twenty. That's like,

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Speaker 8: still not really clear about how many new Trump voters

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Speaker 8: can come out of the would work there were a

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Speaker 8: lot in twenty twenty and how much will a lot

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Speaker 8: of those suburbs swing further to the left. Yeah, these

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Speaker 8: are all kind of open questions, and I don't think

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Speaker 8: we have great ways of betchmarking probability be on a

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Speaker 8: certain point.

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Speaker 4: Zv Anskanda, maybe can you explain the hurting controversy. I've

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Speaker 4: been seeing a lot of tweets like upholsters are hurting

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Speaker 4: and what's that? And then I don't know, how do

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Speaker 4: you heard exactly? Like what is that all about?

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Speaker 3: Like doing?

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Speaker 6: So? The idea is, if you have a poll and

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Speaker 6: you come up with the same results as every other pollster,

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Speaker 6: and so everyone is saying Harris plus one or Trump

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Speaker 6: plus one, you come out with Harris plus one or

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Speaker 6: Trump plus one or zero, then no matter what happens

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Speaker 6: in the election, this is not your fault, right, you

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Speaker 6: didn't screw up. But if you were to say Harris

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Speaker 6: plus four and then Trump wins that state, then suddenly

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Speaker 6: everyone looks at you and goes, you're terrible, your career

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Speaker 6: is over, You're an idiot, and to lesser extent if

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Speaker 6: it's Trump plus four. So what a lot of these

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Speaker 6: pollsters are very cretively doing batistical analysis for the polls

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Speaker 6: is they are cooking their books, putting their fingers on

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Speaker 6: the scale to make sure that their number comes back

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Speaker 6: very close to what everyone else is saying. And there

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Speaker 6: are only a few, like New York Times Morning consults

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Speaker 6: that are clearly not doing that. And often they'll also

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Speaker 6: do this thing where they'll take a poll and they'll

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Speaker 6: see the result is like way off, and then maybe

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Speaker 6: they just won't release it, or they'll find a way

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Speaker 6: to adjust it or whatever they have to do. And

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Speaker 6: Nate Silver recently posted recently on Twitter the chance of

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Speaker 6: all these polls coming in this close even if the

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Speaker 6: race was actually tied on the order of one in

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Speaker 6: nine trillions. So it's clearly just not a coincidence.

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Speaker 2: So what actually happens on prediction markets on election night?

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Speaker 2: I imagine like things are going to be moving quite a bit.

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Speaker 2: But also when does the actual payout occur for Trump

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Speaker 2: versus Harris?

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Speaker 6: So the payout depends on the exact terms of the contract.

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Speaker 6: So four years ago, we had a lot of very

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Speaker 6: interesting discussions going on behind the scenes, and a lot

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Speaker 6: of very public yelling as different sites proposed to pay

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Speaker 6: out based on the fact that Biden had actually won

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Speaker 6: the election, and other people very much disputing that Biden

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Speaker 6: hadn't won the election, and in fact buying Trump long

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Speaker 6: after Biden had won the election. Yeah, I made some

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Speaker 6: money on that. That was kind of awesome. And so

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Speaker 6: I mean, like the bets before election day, they did Okay,

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Speaker 6: I won them, but I should have held my money.

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Speaker 6: The bets afterwards so much better. But the way it

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Speaker 6: works is there's a technical rule for when the bet

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Speaker 6: pays out, and this convey based on where you bet.

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Speaker 6: So what are the ways to do it? Did you say, Okay,

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Speaker 6: if the networks call the election, then that counts because

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Speaker 6: they're being very conservative these days. And then we pay

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Speaker 6: out immediately no matter what happens. And that way you

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Speaker 6: don't have to hold it for weeks and weeks, including

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Speaker 6: if there's another dispute, which you know, we all hope

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Speaker 6: there isn't, but you never know that.

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Speaker 4: The way happened, it occurred to me, so you're now

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Speaker 4: at ninety six percent chance of appearing on odd lats.

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Speaker 4: It occurred to me there may be some ambiguity of

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Speaker 4: the rules because this this audio could I don't want

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Speaker 4: to jinx it, but maybe it never comes to see

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Speaker 4: the light of day. And so maybe just the same

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Speaker 4: way people are wondering the technical rules of your contract

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Speaker 4: here and whether interviewing you on the stage is the

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Speaker 4: same as appearing on the podcast. Let's get to a

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Speaker 4: little macro neil monetary policy. Have you been contacted about

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Speaker 4: being either the next fed share or being on the

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Speaker 4: FOMC in the event of.

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Speaker 3: A Trump victory.

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Speaker 7: What are you trying to say?

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Speaker 3: I am not saying anything.

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Speaker 4: I'm simply asking whether the transition team has reached out

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Speaker 4: not a role.

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Speaker 7: I've not been contacted, and I wouldn't expect you, though

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Speaker 7: I know people that are that traffic in those circles.

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Speaker 4: Okay, do you what do you like when you think

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Speaker 4: about the medium term trajectory of monetary policy under a

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Speaker 4: theoretical Trump administration or a Harris administration. Does tomorrow night

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Speaker 4: sort of change your outlook on that type of policy?

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Speaker 7: Not really? I mean I think in terms of what

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Speaker 7: I typically do, as you know, I don't let political

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Speaker 7: outcomes really affect my kind of near term decision making

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Speaker 7: in terms of what my monetary policy call is going

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Speaker 7: to be. I think the next few rate cuts are

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Speaker 7: really just baked, I mean, regardless of who wins. And

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Speaker 7: that's because I think the underlying dynamics in the economy

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Speaker 7: are still kind of pointing to slower growth, benign inflation,

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Speaker 7: and probably ongoing monetary policy recalibration. So I don't think

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Speaker 7: that's going to change, you know, before the first quarter

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Speaker 7: of next year. So I think they'll they'll keep cutting.

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Speaker 7: It's really just about how much they will gone to.

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Speaker 2: I'd be curious to get your take on this as well,

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Speaker 2: like what kind of economy or how would you characterize

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Speaker 2: the economy that either Harris or Trump will inherit.

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Speaker 8: So, I mean, all things considered, like employment's still very high,

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Speaker 8: inflation is generally falling. I mean, each month is their bumps.

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Speaker 8: That's not a bad hand to be given. Productivity growth

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Speaker 8: looks like it's picking up a gear at least for

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Speaker 8: the time being. All these things are pretty good at

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Speaker 8: the same time. To Neil's point, there are gonna be

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Speaker 8: some foreseeing signs that growth will be slower in Q

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Speaker 8: four and probably Q one, and for that reason, like

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Speaker 8: we're kind of see some some bumps in the road.

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Speaker 8: I don't think that policy is going to be changing

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Speaker 8: on a dime, even if like Trump goes for really

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Speaker 8: aggressive tariffs. These are not things that will be done overnight.

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Speaker 8: And so that's like the kind of friction in the system.

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Speaker 8: Everyone likes to talk about politics and how it's relevant

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Speaker 8: to markets, and there will be some election reaction, but

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Speaker 8: it's like as twenty sixteen kind of told you, right,

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Speaker 8: whatever correlation structure was their pre election, doesn't it to

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Speaker 8: be their pro selection. And I do think that's like

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Speaker 8: something is to be mindful of. As far as like

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Speaker 8: policy will take more time to change, I think it's

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Speaker 8: pretty clear that if it's a Harris administration, it's probably

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Speaker 8: with the Republican Senate, there's like some compromise on tax policy.

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Speaker 5: You're not going to get big things done.

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Speaker 8: But I don't think there's even like a huge appetite

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Speaker 8: within the Democratic Party to do big things. That's a

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Speaker 8: little different in terms of like like they've already passed

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Speaker 8: all legislation, right, but in terms of Republicans they actually

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Speaker 8: have a.

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Speaker 5: Good shot at trifect though.

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Speaker 8: Right if that happens, then the box opens up. They

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Speaker 8: might cut corporate taxes more, but there's also more discretion

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Speaker 8: on like trade and immigration that Trump could wield.

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Speaker 7: Well, I was just gonna say, I mean, if you

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Speaker 7: go back to twenty seventeen, remember that discussion around monetary offset.

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Speaker 7: We were all talking about monetary offset because the idea was, well,

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Speaker 7: you know, Trump is going to be this sort of

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Speaker 7: inflationary demon, and you know the Fed has to do

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Speaker 7: all this sort of rate hikes to offset. And in hindsight,

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Speaker 7: there wasn't really a monetary offset. They ended up doing

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Speaker 7: more or less what they were planning to do. So,

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Speaker 7: you know, I just think it's it's important to kind

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Speaker 7: of try to separate these things out and just sort

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Speaker 7: of take the world as it comes to you. I

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Speaker 7: think that's as opposed to trying to forecast in front

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Speaker 7: run sort of potential fiscal outcomes.

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Speaker 3: I mean, if you're the.

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Speaker 4: FITZV, do you see anyone, Well, you're back down to

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Speaker 4: fifty percent.

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Speaker 6: How did that happen?

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Speaker 3: We've fallen.

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Speaker 4: Someone hit the cell and apparently the order book must

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Speaker 4: not be They're like, all right, I'm going to take

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Speaker 4: my profits at ninety six percent. And I guess the

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Speaker 4: order book was pretty thin because whoever just sold you like,

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Speaker 4: really got a bad price on that, So you shouldn't

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Speaker 4: have sold whoever that was.

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Speaker 3: Oh okay, there you go. Yeah, it gotta get we

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Speaker 3: gotta get some liquidity.

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Speaker 4: Here is anyone doing, like, do you see people in

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Speaker 4: your world trading cross between the prediction markets and the

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Speaker 4: real the real markets, I don't know what to call them,

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Speaker 4: oh market, you know. Do you see much of that

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Speaker 4: where it is like, you know, this should this level

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Speaker 4: of confidence in Trump is not consistent with this thing

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Speaker 4: we're seeing in I don't know, bitcoin or something like that.

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Speaker 3: Are you seeing much of that?

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Speaker 6: So you earlier asked what happens on election night, and

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Speaker 6: what happens on election night is that the odds will

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Speaker 6: move dramatically and they will respond very quickly to every

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Speaker 6: piece of news. And there's both the reaction that happens

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Speaker 6: when the news is available to those who are paying attention.

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Speaker 6: So like if the counties file their numbers online, there's

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Speaker 6: some people who are downloading the information from the counties

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Speaker 6: and they have their spreadsheets ready and they're analyzing all

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Speaker 6: the details and they're trying to stay ahead of the game.

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Speaker 6: And then there are the people who are watching the

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Speaker 6: news and they're like, oh, they've network called Wisconsin and

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Speaker 6: then they suddenly you know, the money comes in.

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Speaker 4: But of course it's kind of embarrassing, isn't it, Like

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Speaker 4: I remember that last time, Like the people always following

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Speaker 4: on Twitter clearly new stuff before the official calls, and

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Speaker 4: yet the market seem to react to the calls in

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Speaker 4: many cases.

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Speaker 6: That's right, So if if you know what the calls

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Speaker 6: are going to be, you can clearly make some money

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Speaker 6: by doing something before the market moves. But this is

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Speaker 6: often true of that there's there's one set of people

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Speaker 6: who have one set of information and those lot of

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Speaker 6: people who have a different set of information, which is

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Speaker 6: coming to them slower. Right, they're more square action, they're

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Speaker 6: more less sophisticated, and they still help make the market

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Speaker 6: more accurate in general, but they're often predictable somewhat in advance.

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Speaker 6: But they're all transaction cost about Neil, I know, people

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Speaker 6: only have so much capital, Like all the major players

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Speaker 6: on election night are going to be somewhat capital constrained

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Speaker 6: in the prediction markets because they're often going to see

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Speaker 6: there's some sort of systematic miss pricing, there's some sort

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Speaker 6: of opportunity and they're going to have to watch their

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Speaker 6: bankrolls and make sure they don't spend too much. Right,

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Speaker 6: So in a situation where everyone's looking for these big

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Speaker 6: miss pricings, but then like you have these different waves

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Speaker 6: and then one of the things that you notice is

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Speaker 6: the early movement on the prediction markets is often actually

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Speaker 6: ahead of the financial market movements and things like currency

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Speaker 6: things that are open and you can in fact make

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Speaker 6: money for real if you are watching about this, because

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Speaker 6: the beta thing is real. Right, so like you go

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Speaker 6: touch not you say, okay, what is going to be

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Speaker 6: the trump you know beta for everything in the world, right,

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Speaker 6: every currency exchange, every index that's still trading, whatever you

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Speaker 6: can get and if it was going on during market hours,

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Speaker 6: it would be so much more fun.

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Speaker 2: Wait, who's actually trading on the prediction markets? Like walk

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Speaker 2: us through the typical person who's doing this and whether

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Speaker 2: or not that introduces some bias into the probabilities because

441
00:21:25,119 --> 00:21:28,320
Speaker 2: I imagine, you know, for something like poly market, you

442
00:21:28,359 --> 00:21:30,359
Speaker 2: have to have a VPN, you have to be somewhat

443
00:21:30,640 --> 00:21:35,399
Speaker 2: crypto literate. L Yeah, so like does that influence some

444
00:21:35,440 --> 00:21:36,600
Speaker 2: of the numbers that we're seeing.

445
00:21:36,800 --> 00:21:40,560
Speaker 6: So you could be a French multi millionaire. You could

446
00:21:40,600 --> 00:21:43,639
Speaker 6: be a Scottish teen is the other traditional joke. But

447
00:21:43,880 --> 00:21:46,240
Speaker 6: the answer is, you know, all types of people around

448
00:21:46,280 --> 00:21:48,760
Speaker 6: the world are getting into it, but yes, because it's

449
00:21:48,800 --> 00:21:52,880
Speaker 6: poly market. You see a difference between poly market and say,

450
00:21:53,000 --> 00:21:55,879
Speaker 6: you know Calshi or you know these other sources predict

451
00:21:55,880 --> 00:21:59,120
Speaker 6: it that are allowing Americans in and that aren't crypto,

452
00:21:59,280 --> 00:22:04,280
Speaker 6: because there's absolutely a bias in who has easier access

453
00:22:04,440 --> 00:22:07,359
Speaker 6: to polymarket, who wants to get involved in poly market,

454
00:22:07,359 --> 00:22:10,159
Speaker 6: who's eager to do that, and that bias is favoring

455
00:22:10,200 --> 00:22:12,119
Speaker 6: Trump this year, Trump is much more for a crypto.

456
00:22:12,560 --> 00:22:15,720
Speaker 6: You see these associations in various different ways. So polymarket

457
00:22:15,760 --> 00:22:19,320
Speaker 6: has been several points stronger for Trump than other similar

458
00:22:19,359 --> 00:22:22,359
Speaker 6: prediction markets. And you could also of course argue that like, no,

459
00:22:22,400 --> 00:22:24,600
Speaker 6: it's polymarket, that's fine, and then everyone else is biased

460
00:22:24,680 --> 00:22:26,400
Speaker 6: and like you know, who is really to say?

461
00:22:26,760 --> 00:22:28,120
Speaker 3: You're up to ninety eight point six.

462
00:22:28,160 --> 00:22:32,399
Speaker 4: Now, Scanna, tell us more about what specifically you're going

463
00:22:32,480 --> 00:22:35,439
Speaker 4: to be watching. You mentioned the rural urban splits that

464
00:22:35,600 --> 00:22:39,080
Speaker 4: even in the red areas we may get signal from

465
00:22:39,240 --> 00:22:42,359
Speaker 4: some of these things. Are there bell weather counties that

466
00:22:42,440 --> 00:22:45,680
Speaker 4: are useful to watch Wakeosha County, Wisconsin is like a

467
00:22:46,400 --> 00:22:49,560
Speaker 4: crucial Waukeasha County. Now you're done to fifty percent? Uh?

468
00:22:49,680 --> 00:22:51,520
Speaker 4: Is there anything like that? Like what a what are

469
00:22:51,600 --> 00:22:53,320
Speaker 4: talk more about? How you're going to be consuming the

470
00:22:53,359 --> 00:22:54,160
Speaker 4: information to man?

471
00:22:54,359 --> 00:22:54,679
Speaker 3: Yeah?

472
00:22:54,800 --> 00:22:59,320
Speaker 8: Bell Weather counties are basically fake, right, So like what matters?

473
00:22:59,720 --> 00:23:02,080
Speaker 8: Like you can have We've had a twenty twenty twenty

474
00:23:02,080 --> 00:23:04,679
Speaker 8: sixteen where the p packing, isn't it.

475
00:23:04,640 --> 00:23:08,800
Speaker 4: Because you can always find some county that always vote

476
00:23:08,800 --> 00:23:10,760
Speaker 4: for the winner but doesn't necessarily manage.

477
00:23:11,040 --> 00:23:13,600
Speaker 8: I mean we have every county is moving somewhere at

478
00:23:13,640 --> 00:23:16,120
Speaker 8: the margin, right, and every marginal vote counts. So if

479
00:23:16,240 --> 00:23:19,480
Speaker 8: like let's say Harris is really well at just trimming

480
00:23:19,520 --> 00:23:21,960
Speaker 8: Trump's margins and rural counties, that's like a big deal.

481
00:23:22,119 --> 00:23:24,440
Speaker 8: In the same way that Trump's ability to amplify them

482
00:23:24,680 --> 00:23:27,840
Speaker 8: in twenty twenty was very underrated by the polls, by

483
00:23:28,200 --> 00:23:31,440
Speaker 8: general expectations among forecasters that he was able to scale

484
00:23:31,520 --> 00:23:34,960
Speaker 8: rural turnout even the percent margins, which people obsess about.

485
00:23:35,280 --> 00:23:38,880
Speaker 8: Percentage margins in a lot of deep red counties did

486
00:23:39,040 --> 00:23:42,359
Speaker 8: narrow in twenty twenty, but just because turnout was ramped

487
00:23:42,440 --> 00:23:45,560
Speaker 8: up even further, Trump got more margin and so a

488
00:23:45,560 --> 00:23:47,240
Speaker 8: lot of states were a lot closer than what the

489
00:23:47,240 --> 00:23:49,880
Speaker 8: polls predicted. You find your ways to cluster the counties,

490
00:23:50,119 --> 00:23:53,560
Speaker 8: whether it's an urban, suburban, ext urban, rural, whatever way

491
00:23:53,600 --> 00:23:58,040
Speaker 8: you want to swing it, that cluster every single one matters, right,

492
00:23:58,080 --> 00:23:59,639
Speaker 8: every part of it. Like there's going to be some

493
00:23:59,680 --> 00:24:04,040
Speaker 8: movement among the urban counties those that among that are

494
00:24:04,080 --> 00:24:07,479
Speaker 8: trending blue, and every vote counts on either on all

495
00:24:07,480 --> 00:24:09,199
Speaker 8: of them. So it doesn't really make a lot of

496
00:24:09,200 --> 00:24:13,040
Speaker 8: sense to like obsess about a particular county where if

497
00:24:13,040 --> 00:24:15,080
Speaker 8: it slips from red to blue, that can happen at

498
00:24:15,119 --> 00:24:17,720
Speaker 8: the exact same time a bunch of red counties that

499
00:24:17,760 --> 00:24:19,199
Speaker 8: are deep red become even redder.

500
00:24:19,400 --> 00:24:20,960
Speaker 5: And that's like what happened in Florida for example.

501
00:24:21,000 --> 00:24:23,880
Speaker 8: Right, So we had a like Pinelli's County was highlighted

502
00:24:23,880 --> 00:24:26,320
Speaker 8: as that chooses the winner. It wasn't in twenty sixteen.

503
00:24:26,320 --> 00:24:29,160
Speaker 8: It was Hillsborough County and that wasn't right. So these

504
00:24:29,240 --> 00:24:31,560
Speaker 8: these flip blue and it didn't really matter. And it's

505
00:24:31,600 --> 00:24:33,359
Speaker 8: just that's a good warning for a lot of this

506
00:24:33,400 --> 00:24:34,400
Speaker 8: election I coverage.

507
00:24:34,880 --> 00:24:35,160
Speaker 9: Neil.

508
00:24:35,240 --> 00:24:37,840
Speaker 2: I know one of your favorite things to do is

509
00:24:37,880 --> 00:24:42,080
Speaker 2: to tear apart the ism Manufacturing survey. What happened to

510
00:24:42,440 --> 00:24:48,199
Speaker 2: the vibes like the soft data post the election, and

511
00:24:48,200 --> 00:24:51,320
Speaker 2: how should we measure it? I guess not the ism clearly.

512
00:24:52,119 --> 00:24:54,280
Speaker 7: Well, I mean you mean when right.

513
00:24:54,160 --> 00:24:56,639
Speaker 2: Now, no, after the election, next week?

514
00:24:57,960 --> 00:25:00,440
Speaker 7: I mean I think you would. I would expect to

515
00:25:00,480 --> 00:25:03,720
Speaker 7: see a pretty meaningful increase in consumer confidence and small

516
00:25:03,760 --> 00:25:07,119
Speaker 7: business sentiment, primarily because you know, small business sentiment. I

517
00:25:07,119 --> 00:25:10,720
Speaker 7: mean that survey really skews you know, I mean, think

518
00:25:10,720 --> 00:25:12,719
Speaker 7: about who's putting it out. It's the NFIB. What do

519
00:25:12,760 --> 00:25:15,000
Speaker 7: they do. They're a lobbying an organization on behalf of

520
00:25:15,520 --> 00:25:18,920
Speaker 7: you know, sort of right wing causes. So my sense

521
00:25:19,000 --> 00:25:21,280
Speaker 7: is that the small business sentiment number would go up

522
00:25:21,320 --> 00:25:23,920
Speaker 7: a lot, consumer confidence would probably go up a lot too.

523
00:25:24,400 --> 00:25:27,520
Speaker 7: Whether that actually translates into real consumer spending, I have

524
00:25:27,640 --> 00:25:29,800
Speaker 7: my doubts, but that's kind of what you saw after

525
00:25:29,880 --> 00:25:33,879
Speaker 7: the twenty sixteen period, right And similarly, you saw a

526
00:25:33,880 --> 00:25:37,440
Speaker 7: big decline in sentiment after you know, after the twenty

527
00:25:37,480 --> 00:25:41,600
Speaker 7: twenty election, but again that didn't really translate into what

528
00:25:41,720 --> 00:25:45,080
Speaker 7: people were actually doing. So, you know, I think twenty

529
00:25:45,080 --> 00:25:48,040
Speaker 7: sixteen was an interesting case because things like the ism

530
00:25:48,040 --> 00:25:51,040
Speaker 7: which you mentioned, I mean Trump was coming into office

531
00:25:51,080 --> 00:25:53,320
Speaker 7: at that time at the front edge of sort of

532
00:25:53,359 --> 00:25:57,520
Speaker 7: a global manufacturing recovery. So this is, you know, the

533
00:25:57,560 --> 00:25:59,480
Speaker 7: so called sort of Trump boom. I mean that was

534
00:26:00,640 --> 00:26:02,680
Speaker 7: it was an Abe boom, and it was a you're

535
00:26:02,760 --> 00:26:04,520
Speaker 7: you know, you saw that in a Macron boom. I

536
00:26:04,520 --> 00:26:06,320
Speaker 7: mean it was everyone was kind of feeling it at

537
00:26:06,400 --> 00:26:09,320
Speaker 7: at the time, so it wasn't just us specific.

538
00:26:09,280 --> 00:26:10,000
Speaker 3: This time around.

539
00:26:10,040 --> 00:26:13,199
Speaker 7: I mean, manufacturing frankly looks a little sluggish. I mean

540
00:26:13,240 --> 00:26:15,400
Speaker 7: there there hasn't really been much. There's been a lot

541
00:26:15,400 --> 00:26:20,480
Speaker 7: of construction of manufacturing facilities, and I know Scan's Scanda

542
00:26:20,480 --> 00:26:22,879
Speaker 7: has been pointing that out quite a bit, but but

543
00:26:22,920 --> 00:26:25,879
Speaker 7: if you look at actual manufacturing production, you know, it

544
00:26:25,880 --> 00:26:27,399
Speaker 7: hasn't really been great shakes.

545
00:26:28,040 --> 00:26:31,280
Speaker 4: Is election uncertainty and you see this like in the

546
00:26:31,359 --> 00:26:34,560
Speaker 4: anecdotal comments on some of these surveys, whether it's the

547
00:26:34,600 --> 00:26:37,400
Speaker 4: is M or the Dallas FED, which always has very

548
00:26:37,400 --> 00:26:43,080
Speaker 4: colorful anecdotal aspects. Is election uncertainty real or is that

549
00:26:43,520 --> 00:26:47,359
Speaker 4: just a code word for people who preferred Trump hoping

550
00:26:47,400 --> 00:26:49,520
Speaker 4: that that's the outcome and then that maybe changing their

551
00:26:49,520 --> 00:26:50,679
Speaker 4: outcome out their outlook.

552
00:26:51,359 --> 00:26:53,560
Speaker 5: I'm sure it's probably both. I think there's like something.

553
00:26:53,480 --> 00:26:55,879
Speaker 3: I really deals not happening. He's like, I don't, we

554
00:26:55,920 --> 00:26:56,159
Speaker 3: don't know.

555
00:26:56,800 --> 00:26:58,439
Speaker 8: I think, like, I'm serious, but we'll think about all

556
00:26:58,440 --> 00:27:00,639
Speaker 8: the enacted legislation. Right, So, if you say there's like,

557
00:27:00,920 --> 00:27:03,960
Speaker 8: if let's say Ira, maybe parts of chips that have

558
00:27:04,040 --> 00:27:07,240
Speaker 8: come up under scrutiny or parts of the infrastructure wal

559
00:27:07,359 --> 00:27:09,720
Speaker 8: if these are all things that are cast as these

560
00:27:09,720 --> 00:27:13,200
Speaker 8: were all left wing items that Biden passed, and if

561
00:27:13,200 --> 00:27:14,800
Speaker 8: it's like depends on whether Trump's going to be an

562
00:27:14,840 --> 00:27:16,719
Speaker 8: office or not. If you perceive it as like, well

563
00:27:16,760 --> 00:27:19,240
Speaker 8: it's a fifty fifty proposition. If Harris is in place,

564
00:27:19,520 --> 00:27:21,400
Speaker 8: then it's goin to stick. If Trump's in.

565
00:27:21,320 --> 00:27:22,800
Speaker 5: Place, it may or may not stick.

566
00:27:23,200 --> 00:27:24,919
Speaker 8: Then I can actually see like a case for like,

567
00:27:25,000 --> 00:27:27,560
Speaker 8: if you have any business attached to a government contract

568
00:27:27,640 --> 00:27:29,960
Speaker 8: or a government subsidy that might actually be genuine.

569
00:27:30,240 --> 00:27:32,320
Speaker 5: I think that I think there's also some partisanship.

570
00:27:33,640 --> 00:27:35,760
Speaker 7: I think generally speaking in my career, I mean, you

571
00:27:36,160 --> 00:27:39,679
Speaker 7: talk about these sort of formal measures of policy uncertainty,

572
00:27:39,720 --> 00:27:43,000
Speaker 7: like the one from Nicholas Bloom that's widely cited. My

573
00:27:43,359 --> 00:27:46,159
Speaker 7: experience is that when that index is high, it's usually

574
00:27:46,200 --> 00:27:48,679
Speaker 7: a time to go long equities right when so, so

575
00:27:48,720 --> 00:27:51,840
Speaker 7: when policy uncertainty is high, it's usually a time to

576
00:27:51,840 --> 00:27:54,080
Speaker 7: dip your toe into the market. It's a buying opportunity

577
00:27:54,119 --> 00:27:55,560
Speaker 7: for stock historic.

578
00:28:12,040 --> 00:28:13,720
Speaker 2: Can we go out in the line and talk about

579
00:28:13,720 --> 00:28:16,640
Speaker 2: like what everyone's day is actually going to look like tomorrow?

580
00:28:16,720 --> 00:28:20,240
Speaker 2: Like how are you spending the election? Let's start with Neil.

581
00:28:21,240 --> 00:28:23,679
Speaker 7: So, like I said, I mean, the election is actually

582
00:28:23,680 --> 00:28:25,720
Speaker 7: a very small part of what I try to do

583
00:28:25,760 --> 00:28:28,480
Speaker 7: on a day to day basis. I'll probably i mean

584
00:28:28,600 --> 00:28:30,679
Speaker 7: just a front run aer. I'll probably be spending some

585
00:28:30,720 --> 00:28:32,639
Speaker 7: of my spare hours working on this piece that I

586
00:28:32,680 --> 00:28:33,560
Speaker 7: was talking to you about.

587
00:28:33,800 --> 00:28:36,399
Speaker 4: You we have a new daily odd Latch newsletter, and

588
00:28:36,440 --> 00:28:38,560
Speaker 4: Neil has promised to be one of the contributors, and

589
00:28:38,600 --> 00:28:39,880
Speaker 4: so we have a piece coming from him.

590
00:28:39,960 --> 00:28:42,280
Speaker 7: So it just sort of gives me an opportunity to

591
00:28:42,400 --> 00:28:44,160
Speaker 7: kind of take a step back because I have no edge.

592
00:28:44,160 --> 00:28:46,080
Speaker 7: I don't try to pretend to have an edge on

593
00:28:46,280 --> 00:28:50,000
Speaker 7: political stuff. And you know, one of the things I've

594
00:28:50,000 --> 00:28:52,760
Speaker 7: been thinking about is just the sort of you know,

595
00:28:52,800 --> 00:28:55,400
Speaker 7: this neutral interest rate. I mean, you know, FET's talking

596
00:28:55,440 --> 00:28:58,840
Speaker 7: about it all the time and just exploring the ideas.

597
00:28:58,880 --> 00:29:01,600
Speaker 7: They're like a dual neutral rate. I mean, for example,

598
00:29:01,680 --> 00:29:06,240
Speaker 7: the neutral rate for housing, I mean whatever it is

599
00:29:06,280 --> 00:29:08,320
Speaker 7: that it's not working. I mean, housing is not working

600
00:29:08,360 --> 00:29:10,680
Speaker 7: with mortgage rates here, So the neutral rate for housing

601
00:29:10,720 --> 00:29:13,800
Speaker 7: is clearly a lot lower than maybe it is for

602
00:29:13,920 --> 00:29:17,160
Speaker 7: say the housing I mean the labor market.

603
00:29:17,160 --> 00:29:17,560
Speaker 6: I don't know.

604
00:29:17,600 --> 00:29:20,080
Speaker 7: I mean so did and so if if if you

605
00:29:20,120 --> 00:29:21,880
Speaker 7: sort of buy into that, I mean, it would imply

606
00:29:22,000 --> 00:29:24,840
Speaker 7: that the FED needs to do a bit more to

607
00:29:24,960 --> 00:29:27,480
Speaker 7: get you know, certain areas of the economy going. And

608
00:29:27,520 --> 00:29:30,560
Speaker 7: if the Fed's lost the ability to stimulate housing, you know,

609
00:29:30,600 --> 00:29:32,680
Speaker 7: I think that that's a that's a potential problem. So

610
00:29:32,720 --> 00:29:35,160
Speaker 7: I'll probably be focusing more of my time on that

611
00:29:35,360 --> 00:29:39,120
Speaker 7: as opposed to checking out the returns in I don't

612
00:29:39,160 --> 00:29:40,960
Speaker 7: know what is it, Cuyahoga County or something.

613
00:29:44,160 --> 00:29:47,600
Speaker 8: I too am working on a piece for thover that

614
00:29:47,600 --> 00:29:51,000
Speaker 8: that that that sir forthcoming as well on productivity. But

615
00:29:52,160 --> 00:29:56,240
Speaker 8: I look, elections are people like numbers changing and like

616
00:29:56,280 --> 00:29:58,640
Speaker 8: following them, which is probably most of you, I'm gonna

617
00:29:58,640 --> 00:30:03,160
Speaker 8: guess on some level. If you're interested in finance and markets, Yeah,

618
00:30:03,200 --> 00:30:05,680
Speaker 8: it's just a fun exercise of like seeing.

619
00:30:05,400 --> 00:30:06,560
Speaker 5: How margins shift.

620
00:30:07,000 --> 00:30:09,400
Speaker 8: I have some spreadsheets prepared for myself just to kind

621
00:30:09,400 --> 00:30:11,840
Speaker 8: of track things if the New York Times needle isn't

622
00:30:11,880 --> 00:30:14,240
Speaker 8: up and running, and yeah, I'll probably take it easy

623
00:30:14,280 --> 00:30:15,960
Speaker 8: in the day, but I'll maybe I'll catch a nap

624
00:30:15,960 --> 00:30:16,360
Speaker 8: and then.

625
00:30:16,200 --> 00:30:18,920
Speaker 5: I will probably be up till at least three am.

626
00:30:19,080 --> 00:30:22,800
Speaker 6: So as a writer, I want people to read what

627
00:30:22,920 --> 00:30:24,360
Speaker 6: I'm writing, and I want them to think about it

628
00:30:24,400 --> 00:30:26,200
Speaker 6: and pay attention to it and learn from it, and

629
00:30:26,240 --> 00:30:29,840
Speaker 6: I want to influence them. So this past week has

630
00:30:29,920 --> 00:30:32,719
Speaker 6: been a case of if I write about something, no

631
00:30:32,720 --> 00:30:34,680
Speaker 6: one's going to pay much attention to it because they're

632
00:30:34,720 --> 00:30:37,680
Speaker 6: going to be focused on the election. And so I

633
00:30:37,960 --> 00:30:42,000
Speaker 6: kind of take this time off because I'm not going

634
00:30:42,080 --> 00:30:44,000
Speaker 6: to try and put anything up except for my weekly

635
00:30:44,080 --> 00:30:47,960
Speaker 6: update until after the election is settled. So instead I've

636
00:30:48,000 --> 00:30:49,920
Speaker 6: had a chance to like program some tools that are

637
00:30:49,920 --> 00:30:51,800
Speaker 6: going to help me write over the long term. I

638
00:30:51,880 --> 00:30:54,440
Speaker 6: might go see a movie, have a nice long lunch,

639
00:30:54,880 --> 00:30:57,280
Speaker 6: you know, relax, and then of course in the evening

640
00:30:57,360 --> 00:30:59,600
Speaker 6: I'm going to absolutely be following. I'll have the prediction

641
00:30:59,720 --> 00:31:02,160
Speaker 6: markets up in various windows and various devices.

642
00:31:02,240 --> 00:31:03,400
Speaker 3: How many screens do you have?

643
00:31:04,280 --> 00:31:06,320
Speaker 6: I have three thirty inch screens, so I have I

644
00:31:06,360 --> 00:31:09,680
Speaker 6: have one horizontal and two vertical on the two sides. Yeah,

645
00:31:10,560 --> 00:31:12,520
Speaker 6: the trader you have six. But now that I'm trying

646
00:31:12,560 --> 00:31:14,560
Speaker 6: to stay away from that, like I think that three

647
00:31:14,600 --> 00:31:16,680
Speaker 6: is about right. And so you know, about one of

648
00:31:16,720 --> 00:31:19,800
Speaker 6: them will probably be various prediction markets, especially Polymarket, and

649
00:31:19,960 --> 00:31:21,719
Speaker 6: various different markets within them, So you need a lot

650
00:31:21,720 --> 00:31:24,000
Speaker 6: of space. And then you know, you're watching the television

651
00:31:24,040 --> 00:31:27,000
Speaker 6: like everybody else, and you're watching Twitter, and you know

652
00:31:27,160 --> 00:31:30,040
Speaker 6: you're just trying to get through it and process it

653
00:31:30,080 --> 00:31:31,680
Speaker 6: because you know that, like even if you don't really

654
00:31:31,720 --> 00:31:34,200
Speaker 6: want to pay quose attention, Like, what else are you

655
00:31:34,240 --> 00:31:34,920
Speaker 6: going to do tonight?

656
00:31:34,960 --> 00:31:36,800
Speaker 3: Sorry? What else is anyone going to be doing?

657
00:31:37,600 --> 00:31:37,880
Speaker 5: Wait?

658
00:31:37,920 --> 00:31:41,360
Speaker 4: Real quickly, why is there not Why has the spread

659
00:31:41,400 --> 00:31:43,680
Speaker 4: on some of these markets between the say Kelsey and

660
00:31:43,920 --> 00:31:45,280
Speaker 4: Polymarket not been harbed away.

661
00:31:45,960 --> 00:31:48,200
Speaker 3: What is the constraint to free money?

662
00:31:48,520 --> 00:31:51,320
Speaker 6: The constraints is liquidity and access to the market, and

663
00:31:51,360 --> 00:31:54,040
Speaker 6: the capital costs of committing the capitol to multiple places

664
00:31:54,040 --> 00:31:56,680
Speaker 6: moving the money in and out. You know, everyone's kind

665
00:31:56,680 --> 00:31:58,640
Speaker 6: of a little bit terrified every time they initiate any

666
00:31:58,640 --> 00:32:00,400
Speaker 6: crypto transaction that somehow they don't and it's going to

667
00:32:00,440 --> 00:32:02,520
Speaker 6: finish or something wrong is going to happen. I mean,

668
00:32:02,600 --> 00:32:05,600
Speaker 6: it's it's very very unlikely in any given transaction it's

669
00:32:05,600 --> 00:32:09,320
Speaker 6: going to happen. But you know, I definitely have an opinion.

670
00:32:09,400 --> 00:32:10,600
Speaker 6: By the way, I want to be clear, like when

671
00:32:10,600 --> 00:32:12,760
Speaker 6: I say, like who knows which one is wrong? I

672
00:32:13,200 --> 00:32:17,400
Speaker 6: very strongly believe that the poly market line is the

673
00:32:17,400 --> 00:32:19,600
Speaker 6: one that is biased in the situation due to the

674
00:32:19,720 --> 00:32:22,760
Speaker 6: access issues, Whereas I think that the line at the

675
00:32:22,800 --> 00:32:26,040
Speaker 6: other markets is much more effective of what the line

676
00:32:26,120 --> 00:32:27,240
Speaker 6: kind of showed in some air quotes.

677
00:32:27,280 --> 00:32:32,640
Speaker 4: Sense be actually real quickly, Skanda, Since you mentioned productivity

678
00:32:33,040 --> 00:32:35,520
Speaker 4: and I know you have some thoughts on productivities via

679
00:32:35,560 --> 00:32:38,000
Speaker 4: In fact, you just mentioned coding up some tools to

680
00:32:38,000 --> 00:32:40,840
Speaker 4: make your life as a writing easier, I think you

681
00:32:40,920 --> 00:32:43,080
Speaker 4: both have some different You think we're going to have

682
00:32:43,160 --> 00:32:45,920
Speaker 4: like fifty percent GDP growth in the coming year on

683
00:32:46,000 --> 00:32:47,640
Speaker 4: year because of AI or something like that.

684
00:32:48,600 --> 00:32:50,960
Speaker 6: No, not fifty percent this year.

685
00:32:51,200 --> 00:32:54,880
Speaker 4: No, but no, like you give us the give us

686
00:32:54,920 --> 00:32:57,240
Speaker 4: the short the short synopsis of what you think is

687
00:32:57,280 --> 00:32:58,680
Speaker 4: coming for productivity growth.

688
00:32:59,240 --> 00:33:02,920
Speaker 6: I think that the the skeptical line on productivity growth

689
00:33:03,240 --> 00:33:06,440
Speaker 6: is we're talking about you know, percents per year every

690
00:33:06,520 --> 00:33:08,760
Speaker 6: year on the course of ten to twenty years. And

691
00:33:08,800 --> 00:33:11,320
Speaker 6: I think that's sort of the the ultimate barecase for AI.

692
00:33:11,400 --> 00:33:13,240
Speaker 6: It doesn't do what we want it or expect it

693
00:33:13,320 --> 00:33:17,560
Speaker 6: or hope it would do. And the bual case singularity

694
00:33:17,880 --> 00:33:20,320
Speaker 6: super intelligence, we're all completely transformed.

695
00:33:20,600 --> 00:33:23,400
Speaker 4: Great, Uh, it's Kanda, what's your what's the gist of

696
00:33:23,440 --> 00:33:26,400
Speaker 4: the productivity? And then also Neil, but what's the gist

697
00:33:26,400 --> 00:33:28,840
Speaker 4: of your productivity piece that you have coming for the

698
00:33:28,840 --> 00:33:30,200
Speaker 4: odd lasted daily newsletter.

699
00:33:30,400 --> 00:33:32,600
Speaker 8: Yes, so just speaking in terms of the realized data,

700
00:33:32,640 --> 00:33:34,880
Speaker 8: and I try to start from how the data measured,

701
00:33:35,160 --> 00:33:37,680
Speaker 8: what what are we actually capturing which may not be

702
00:33:37,760 --> 00:33:40,720
Speaker 8: indicative of sort of conceptually what we assay say the

703
00:33:40,720 --> 00:33:44,880
Speaker 8: productive productivity, but proctivity growth is actually outperformed post pandemic

704
00:33:45,000 --> 00:33:47,920
Speaker 8: in a pretty meaningful sense relative to what we were

705
00:33:47,920 --> 00:33:50,640
Speaker 8: seeing pre pandemics or pre pandemic was roughly one zero

706
00:33:50,680 --> 00:33:53,240
Speaker 8: point four percent. If it takes sort of longer look

707
00:33:53,280 --> 00:33:56,240
Speaker 8: backs and we've been done put post pandemic period something

708
00:33:56,280 --> 00:33:58,400
Speaker 8: like two percent. Maybe it's one point nine, maybe it's two.

709
00:33:58,800 --> 00:34:02,440
Speaker 8: But that's like on an anualize basis, that's pretty meaningful deviation.

710
00:34:03,120 --> 00:34:05,400
Speaker 8: And there are like a lot of reasons why but

711
00:34:05,480 --> 00:34:07,360
Speaker 8: I think that it all kind of has to come

712
00:34:07,400 --> 00:34:11,960
Speaker 8: back to, like the measured set of transactions inflation adjusted

713
00:34:12,320 --> 00:34:15,759
Speaker 8: divided by total hours worked. That is basically our most

714
00:34:15,760 --> 00:34:19,200
Speaker 8: measurable version of productivity. It comes with lots of flaws.

715
00:34:19,360 --> 00:34:23,040
Speaker 8: For example, Google maps that everyone uses on a day

716
00:34:23,040 --> 00:34:25,680
Speaker 8: to day basis, right, it's ads supported, Right, it's not

717
00:34:25,680 --> 00:34:29,240
Speaker 8: supported by a final expenditure. It should filter in somehow

718
00:34:29,280 --> 00:34:31,719
Speaker 8: into our productivity statistics, but we don't have a great

719
00:34:31,760 --> 00:34:33,720
Speaker 8: way of saying now and estimating.

720
00:34:33,760 --> 00:34:34,600
Speaker 5: That's actually really hard.

721
00:34:34,800 --> 00:34:36,440
Speaker 8: So for example, there's a lot of things that AI can

722
00:34:36,440 --> 00:34:37,920
Speaker 8: make our lives very efficient and the same way the

723
00:34:37,920 --> 00:34:41,240
Speaker 8: Internet's made our lives very efficient, but it didn't necessarily

724
00:34:41,280 --> 00:34:42,480
Speaker 8: lead to a lot of transactions.

725
00:34:42,800 --> 00:34:44,000
Speaker 5: And that's kind of the open question.

726
00:34:44,080 --> 00:34:47,520
Speaker 8: That's like, for a lot of AI breakthroughs, how that

727
00:34:47,640 --> 00:34:50,040
Speaker 8: leads to it may improve a lot of welfare, But

728
00:34:50,120 --> 00:34:52,520
Speaker 8: the actual nuts and bolts of how it leads to

729
00:34:52,600 --> 00:34:55,880
Speaker 8: more people spending in ways that are reflecting real things

730
00:34:55,920 --> 00:34:58,680
Speaker 8: and not price increases, that is like actually a big

731
00:34:58,719 --> 00:34:59,520
Speaker 8: part of the ballgame.

732
00:35:00,400 --> 00:35:05,439
Speaker 3: Neil An, your thoughts of productivity.

733
00:35:03,440 --> 00:35:05,319
Speaker 7: I mean, I agree with Scanda. The measure data is

734
00:35:05,320 --> 00:35:07,600
Speaker 7: what the measured data is or the data are I

735
00:35:07,640 --> 00:35:10,280
Speaker 7: mean's over it's you know, two percent, that's very strong.

736
00:35:10,400 --> 00:35:14,440
Speaker 7: I think for what that means for me is that basically,

737
00:35:15,120 --> 00:35:18,440
Speaker 7: this is one reason why we should not worry about inflation, okay,

738
00:35:18,520 --> 00:35:21,360
Speaker 7: and and that and that should give the FED, you know,

739
00:35:21,440 --> 00:35:24,040
Speaker 7: plenty of cover, right being, And this is something we

740
00:35:24,080 --> 00:35:26,680
Speaker 7: talked about earlier in the year, right is that it's

741
00:35:26,719 --> 00:35:28,680
Speaker 7: one thing to just see the inflation data it's going

742
00:35:28,760 --> 00:35:31,279
Speaker 7: up without having like a rational framework for why it's

743
00:35:31,280 --> 00:35:33,879
Speaker 7: going to keep doing that. And you know, the fact

744
00:35:33,920 --> 00:35:37,959
Speaker 7: that productivity has been fairly robust over the last year,

745
00:35:38,560 --> 00:35:41,160
Speaker 7: I think it means a couple things. Number One, we

746
00:35:41,160 --> 00:35:43,480
Speaker 7: should sort of resist the temptation to kind of buy

747
00:35:43,520 --> 00:35:46,520
Speaker 7: into the stagflation store. You can't really have stagflation of

748
00:35:46,600 --> 00:35:49,600
Speaker 7: productivity is doing what it's doing. But it also makes

749
00:35:49,960 --> 00:35:54,040
Speaker 7: the likelihood of like some inflation reacceleration highly unlikely as well,

750
00:35:54,080 --> 00:35:56,200
Speaker 7: like where is it coming from? Unit labor cost growth

751
00:35:56,600 --> 00:36:00,279
Speaker 7: over the last year is basically zero, So, you know,

752
00:36:00,320 --> 00:36:03,360
Speaker 7: for a FED that has a very labor market centric

753
00:36:03,480 --> 00:36:07,959
Speaker 7: view of how the inflationary process works, the robust growth

754
00:36:08,000 --> 00:36:10,440
Speaker 7: and productivity that we've seen, I think is an important

755
00:36:10,560 --> 00:36:15,359
Speaker 7: kind of you know story in terms of mitigating inflation risk.

756
00:36:16,600 --> 00:36:18,560
Speaker 2: If you had to choose, what would you say is

757
00:36:18,560 --> 00:36:22,600
Speaker 2: the biggest constraint for Trump and Harris both?

758
00:36:22,800 --> 00:36:22,880
Speaker 6: Like?

759
00:36:23,320 --> 00:36:26,680
Speaker 2: Is it political? You know, maybe like Harris gets in

760
00:36:26,719 --> 00:36:29,920
Speaker 2: and doesn't have a trifecta like maybe the Republicans would have.

761
00:36:30,000 --> 00:36:34,480
Speaker 2: Is it something like the deficit? Choose one for each.

762
00:36:34,560 --> 00:36:36,520
Speaker 7: Well, I mean, personally, I think that it's going to be.

763
00:36:37,320 --> 00:36:38,960
Speaker 7: I mean, the markets have been sort of like, oh,

764
00:36:39,000 --> 00:36:42,719
Speaker 7: the unified GOP. But I mean even if Trump, even

765
00:36:42,760 --> 00:36:44,640
Speaker 7: if it was to be a unified GOP government, the

766
00:36:44,680 --> 00:36:46,839
Speaker 7: margins in the House would still be very very thin.

767
00:36:46,920 --> 00:36:49,239
Speaker 7: It's not like they can just steamroll whatever the hell

768
00:36:49,239 --> 00:36:51,560
Speaker 7: he wants, you know, next year. But I would I

769
00:36:51,560 --> 00:36:53,839
Speaker 7: would probably say the bond markets the constrain. I mean,

770
00:36:53,880 --> 00:36:56,240
Speaker 7: you have to be worried about how what's the appetite

771
00:36:56,280 --> 00:36:58,200
Speaker 7: going to be in the fixed income market to fund

772
00:36:59,200 --> 00:37:03,440
Speaker 7: a huge sort of deficit, you know, spending plan.

773
00:37:04,800 --> 00:37:05,240
Speaker 2: Skanda.

774
00:37:05,960 --> 00:37:07,360
Speaker 5: I go back to the politics.

775
00:37:07,400 --> 00:37:10,640
Speaker 8: I think like American government makes it very hard to

776
00:37:10,680 --> 00:37:14,919
Speaker 8: pass things in general, and the wisdom of that where

777
00:37:14,920 --> 00:37:18,240
Speaker 8: everyone wants a debate. It's just even under a unified government.

778
00:37:18,280 --> 00:37:20,880
Speaker 8: To Neil's point, like Lisa Murkowski still has a lot

779
00:37:20,920 --> 00:37:23,279
Speaker 8: of leverage, Susan Collins has a lot of leverage.

780
00:37:23,480 --> 00:37:24,880
Speaker 5: They probably will pass some things.

781
00:37:24,960 --> 00:37:27,439
Speaker 8: It's easier to pass things under unified government than under

782
00:37:27,480 --> 00:37:31,960
Speaker 8: divide government. But that's probably still binding constraint. It was

783
00:37:32,000 --> 00:37:36,479
Speaker 8: the constraint on Biden in one twenty twenty two. I mean,

784
00:37:36,640 --> 00:37:38,520
Speaker 8: even though interest rates are going up, the real question

785
00:37:38,600 --> 00:37:40,920
Speaker 8: was was Joe Manchin willing to say yes to? And

786
00:37:41,000 --> 00:37:44,560
Speaker 8: so even if like we can debate how much, what's

787
00:37:44,600 --> 00:37:47,239
Speaker 8: the nature of public finance constraints? Oftentimes they are re

788
00:37:47,400 --> 00:37:50,840
Speaker 8: used ultimately to like the hardball legislative politics.

789
00:37:50,920 --> 00:37:52,960
Speaker 4: I've alluded to this before, and I don't want to

790
00:37:53,080 --> 00:37:55,319
Speaker 4: like let it shade my view, but I would like

791
00:37:55,360 --> 00:37:57,760
Speaker 4: mortgage rates to come down in the next two years.

792
00:37:58,560 --> 00:38:00,759
Speaker 4: Do we need to get do we need to like

793
00:38:00,880 --> 00:38:02,840
Speaker 4: do we need a spending crackdown? Do we need to

794
00:38:02,840 --> 00:38:06,440
Speaker 4: go into austerity mode to get mortgage rates back to

795
00:38:06,560 --> 00:38:09,560
Speaker 4: roughly somewhere on the ballpark of the twenty tens.

796
00:38:10,160 --> 00:38:11,520
Speaker 8: I mean, I would say, to the extent you can

797
00:38:11,560 --> 00:38:14,560
Speaker 8: free of real resources, right, yeah, I mean to the

798
00:38:14,560 --> 00:38:17,520
Speaker 8: extent that you're actually reducing inflation or getting the FED

799
00:38:17,520 --> 00:38:20,359
Speaker 8: to be more confident about the willingness to lower interest rates.

800
00:38:20,400 --> 00:38:21,960
Speaker 5: That would probably be the main methods.

801
00:38:21,960 --> 00:38:26,400
Speaker 4: I won't let my mortgage affect how I assess the economy.

802
00:38:26,400 --> 00:38:30,920
Speaker 8: But I'm just saying, yeah, but I think that's like

803
00:38:31,320 --> 00:38:33,240
Speaker 8: a tricky thing. You can do a lot of deficit

804
00:38:33,320 --> 00:38:35,440
Speaker 8: reduction that doesn't necessarily move the needle on inflation or

805
00:38:35,440 --> 00:38:38,839
Speaker 8: the fence reaction function. But like health care costs for example, right,

806
00:38:38,840 --> 00:38:40,400
Speaker 8: health care costs in general need.

807
00:38:40,280 --> 00:38:42,759
Speaker 5: To be constrained. They do have a pretty direct role

808
00:38:42,760 --> 00:38:43,840
Speaker 5: in inflation outcomes.

809
00:38:44,280 --> 00:38:46,480
Speaker 8: And because of those two things, that's a pretty strong

810
00:38:46,560 --> 00:38:49,799
Speaker 8: nexus for if we could reduce health care inflation by

811
00:38:50,360 --> 00:38:52,640
Speaker 8: half a percentage point each year, that would be a

812
00:38:52,719 --> 00:38:55,280
Speaker 8: very big deal for what the FED will We'll probably

813
00:38:55,280 --> 00:38:57,120
Speaker 8: get to the last mile of whatever the Fed's trying

814
00:38:57,120 --> 00:38:58,560
Speaker 8: to achieve. V.

815
00:38:59,560 --> 00:39:01,239
Speaker 4: Can you say a little bit more like about the

816
00:39:01,280 --> 00:39:05,600
Speaker 4: spreadsheets set up that and you scotn do you mentioned

817
00:39:05,600 --> 00:39:08,560
Speaker 4: your spreadsheets too? As that data is coming in tomorrow,

818
00:39:08,560 --> 00:39:10,000
Speaker 4: I mean, this is what we really care about, right,

819
00:39:10,040 --> 00:39:12,200
Speaker 4: Like the numbers start to come in, they get posted

820
00:39:12,239 --> 00:39:15,359
Speaker 4: on what secondary of state websites, et cetera. Like how

821
00:39:15,400 --> 00:39:20,120
Speaker 4: are the traders ingesting that in that process to be

822
00:39:20,200 --> 00:39:23,080
Speaker 4: ahead of like when the network's the cold Wisconsin.

823
00:39:23,600 --> 00:39:26,520
Speaker 6: So it's gonna vary a lot from trader to trader,

824
00:39:26,560 --> 00:39:29,840
Speaker 6: from house to house, and you know, a remarkably large

825
00:39:29,920 --> 00:39:32,799
Speaker 6: number of people just don't do this. And that's clear

826
00:39:32,880 --> 00:39:34,799
Speaker 6: by because you look at the financial markets over time,

827
00:39:34,840 --> 00:39:37,040
Speaker 6: like I haven't followed the most recent was like twenty

828
00:39:37,040 --> 00:39:39,600
Speaker 6: twenty two that carefully in terms of the reactions, but

829
00:39:39,840 --> 00:39:42,239
Speaker 6: you definitely see these delays, and like if there was

830
00:39:42,280 --> 00:39:44,280
Speaker 6: a lot of participants in the market who were keeping

831
00:39:44,400 --> 00:39:47,560
Speaker 6: close eyes and incorporating that money that information instantly, that

832
00:39:47,600 --> 00:39:51,240
Speaker 6: wouldn't happen. So the right ways to do it involve

833
00:39:51,320 --> 00:39:54,799
Speaker 6: things like setting up automatic interfaces with these websites to

834
00:39:54,920 --> 00:39:57,000
Speaker 6: just pull things into your spreadsheets. Right, so you have

835
00:39:57,040 --> 00:39:59,640
Speaker 6: your Excel spreadsheets that contain all of the county by

836
00:39:59,680 --> 00:40:03,120
Speaker 6: county data from all of the returns, and then ideally

837
00:40:03,280 --> 00:40:06,000
Speaker 6: you want to figure out what that implies about the results,

838
00:40:06,080 --> 00:40:08,319
Speaker 6: and the technically correct way to do that is a

839
00:40:08,600 --> 00:40:11,000
Speaker 6: basy in calculation. It takes a new account all the

840
00:40:11,000 --> 00:40:12,719
Speaker 6: information because you don't know which piece of information you're

841
00:40:12,719 --> 00:40:13,799
Speaker 6: going to get, so you need to know how to

842
00:40:13,800 --> 00:40:17,080
Speaker 6: feed them into your calculation, and then that should then

843
00:40:17,080 --> 00:40:20,200
Speaker 6: output a range of distributions with various probabilities of various

844
00:40:20,200 --> 00:40:22,239
Speaker 6: different outcomes, and you price that into your beta on

845
00:40:22,320 --> 00:40:24,640
Speaker 6: various things based on those elements, and you figure out

846
00:40:24,640 --> 00:40:25,960
Speaker 6: what the prices are supposed to be, and then you

847
00:40:26,000 --> 00:40:26,680
Speaker 6: make the good trades.

848
00:40:27,840 --> 00:40:30,640
Speaker 2: See weren't you at Jane Street before? What was an

849
00:40:30,680 --> 00:40:31,839
Speaker 2: election night? Like there?

850
00:40:33,440 --> 00:40:36,280
Speaker 6: Well, I mean all hands on deck, right, so everyone's there.

851
00:40:36,640 --> 00:40:40,879
Speaker 6: It's a working night, and you use what tools you have,

852
00:40:41,160 --> 00:40:45,960
Speaker 6: and you you know, use what instruments are available for

853
00:40:46,000 --> 00:40:47,440
Speaker 6: you to trade because it's the middle of the night.

854
00:40:47,520 --> 00:40:50,520
Speaker 6: So like you know, obviously if the US dock market

855
00:40:50,560 --> 00:40:54,040
Speaker 6: was opened, everything would be dramatically different. But you are

856
00:40:54,080 --> 00:40:55,120
Speaker 6: somewhat limited, right, I.

857
00:40:55,120 --> 00:40:59,640
Speaker 4: Have one last question as an AI productivity optimist, Like

858
00:40:59,680 --> 00:41:03,880
Speaker 4: I don't know anything about how to code a system

859
00:41:03,920 --> 00:41:05,880
Speaker 4: that will ingest all the data and set up a

860
00:41:05,880 --> 00:41:09,319
Speaker 4: basian model in your vision of what AI could do.

861
00:41:09,800 --> 00:41:11,880
Speaker 4: Can I in a couple of years, could I go

862
00:41:11,960 --> 00:41:14,200
Speaker 4: to Chad GBT and say, like, write the code that

863
00:41:14,280 --> 00:41:16,440
Speaker 4: will pull this in and then build some kind of model.

864
00:41:16,719 --> 00:41:17,479
Speaker 6: You can do that now?

865
00:41:17,760 --> 00:41:18,080
Speaker 9: All right?

866
00:41:18,560 --> 00:41:18,920
Speaker 6: All right?

867
00:41:20,000 --> 00:41:20,280
Speaker 3: Vs?

868
00:41:20,280 --> 00:41:24,160
Speaker 4: Skanda and Neil. Thank you so much. I feel prepared.

869
00:41:27,440 --> 00:41:30,040
Speaker 4: V is it ninety one percent? So there's still some

870
00:41:30,080 --> 00:41:31,920
Speaker 4: ambiguity about whether he was on stage.

871
00:41:31,719 --> 00:41:32,520
Speaker 2: Or We're still.

872
00:41:49,280 --> 00:41:49,680
Speaker 6: All right?

873
00:41:49,760 --> 00:41:53,960
Speaker 2: The final stretch here with Brad Setzer, Senior fellow at

874
00:41:53,960 --> 00:41:58,040
Speaker 2: the Council for Foreign Relations. Who better to tie up

875
00:41:58,239 --> 00:42:01,880
Speaker 2: all the disparate things we've been talking about in the

876
00:42:01,880 --> 00:42:06,560
Speaker 2: previous two sessions, then, Brad, we always enjoy speaking with

877
00:42:06,640 --> 00:42:11,080
Speaker 2: you because we can basically throw anything at these Yeah,

878
00:42:11,400 --> 00:42:13,439
Speaker 2: I'm pretty sure you might be close to the top

879
00:42:13,840 --> 00:42:17,040
Speaker 2: for number of odd loots appearances. But why don't we

880
00:42:17,080 --> 00:42:19,800
Speaker 2: start with something really specific? Because you published a paper

881
00:42:19,840 --> 00:42:24,120
Speaker 2: recently all about globalization. The title is the Surprising Resilience

882
00:42:24,160 --> 00:42:30,319
Speaker 2: of Globalization, an examination of claims of Economic fragmentation, and

883
00:42:30,360 --> 00:42:34,200
Speaker 2: your conclusion was basically that we are still globalizing, and

884
00:42:34,200 --> 00:42:37,959
Speaker 2: to some extent since twenty sixteen, we've globalized even more.

885
00:42:38,120 --> 00:42:39,960
Speaker 2: Walk us through how you come to that.

886
00:42:41,280 --> 00:42:44,120
Speaker 9: Well, First, thanks for inviting me, and thanks for asking

887
00:42:44,120 --> 00:42:47,000
Speaker 9: me about my recent paper. You are the first person

888
00:42:47,040 --> 00:42:48,880
Speaker 9: who actually seems to have read the whole title.

889
00:42:49,400 --> 00:42:52,040
Speaker 2: I promise I did actually read it. I read it

890
00:42:52,080 --> 00:42:55,359
Speaker 2: earlier today, but I'm.

891
00:42:54,320 --> 00:42:59,840
Speaker 9: Impressed, and then thanks to everyone for sticking around. Appreciate it.

892
00:43:01,719 --> 00:43:06,640
Speaker 9: So most papers, or many of my papers, originate out

893
00:43:06,680 --> 00:43:11,480
Speaker 9: of a sense that a narrative has taken hold, and

894
00:43:11,520 --> 00:43:15,839
Speaker 9: that narrative is sort of perpetuated itself, even when that

895
00:43:15,960 --> 00:43:20,160
Speaker 9: narrative isn't fully backed by all of the detailed data.

896
00:43:21,280 --> 00:43:24,120
Speaker 9: And there have been two narratives that have been you know,

897
00:43:24,120 --> 00:43:28,440
Speaker 9: they're closely related, narratives that have been very prevalent and

898
00:43:28,520 --> 00:43:31,920
Speaker 9: prevalent at the IMF, prevalent at Davos, prevalent in the

899
00:43:31,920 --> 00:43:35,560
Speaker 9: financial media, prevalence on Bloomberg. One is that the world

900
00:43:35,640 --> 00:43:39,200
Speaker 9: is deglobalizing, and the other, which is related but not

901
00:43:39,280 --> 00:43:43,400
Speaker 9: quite the same, as the world is fragmenting, different political

902
00:43:43,440 --> 00:43:50,560
Speaker 9: blocks are interacting less economically. That thesis seemed at odds

903
00:43:51,239 --> 00:43:56,560
Speaker 9: with a couple of things. One I spend a lot

904
00:43:56,600 --> 00:44:02,799
Speaker 9: of time. Don't ask why trade in pharmaceuticals. No, It's

905
00:44:02,840 --> 00:44:06,960
Speaker 9: just it's an interesting subsector of the global economy. It's

906
00:44:07,000 --> 00:44:12,160
Speaker 9: a hobby. Yeah, I mean, I'm certainly not paid from

907
00:44:12,160 --> 00:44:17,759
Speaker 9: my odd take on the pharmaceutical industry. And the pharmaceutical

908
00:44:17,760 --> 00:44:22,759
Speaker 9: industry has continued to globalize. US imports of pharmaceuticals have

909
00:44:22,880 --> 00:44:28,120
Speaker 9: doubled since twenty sixteen. The US imports from low tax jurisdictions,

910
00:44:28,120 --> 00:44:30,080
Speaker 9: which is a big part of pharmaceutical trade. It's not

911
00:44:30,120 --> 00:44:33,359
Speaker 9: with low cost jurisdictions, it's low tax duristictions. About half

912
00:44:33,360 --> 00:44:36,920
Speaker 9: of our imports are from five tax hubs. They've doubled.

913
00:44:37,600 --> 00:44:40,320
Speaker 9: One quarter of those imports come from the great Country

914
00:44:40,320 --> 00:44:44,600
Speaker 9: of Ireland. So that's not a story of deglobalization. That

915
00:44:44,719 --> 00:44:48,720
Speaker 9: is a story of continuity. It's a story of globalization

916
00:44:49,000 --> 00:44:53,839
Speaker 9: continuing because there's a tax advantage filter globalization. But then

917
00:44:53,840 --> 00:44:55,799
Speaker 9: the other component of the argument is the one that

918
00:44:55,880 --> 00:45:00,360
Speaker 9: sort of irritates people. I looked at the data. Everybody

919
00:45:00,360 --> 00:45:03,279
Speaker 9: tries to look at the data. And you know, if

920
00:45:03,320 --> 00:45:07,000
Speaker 9: you look at the data for China, biggest economy and

921
00:45:07,040 --> 00:45:09,600
Speaker 9: the biggest potential source of fragmentation, I mean, you can

922
00:45:09,640 --> 00:45:13,000
Speaker 9: fragment with Russia, which has happened, but fragmenting with China

923
00:45:13,000 --> 00:45:17,680
Speaker 9: would be big. And I didn't really see the evidence.

924
00:45:17,840 --> 00:45:22,040
Speaker 9: So China's exports to the world are up by about

925
00:45:22,160 --> 00:45:26,400
Speaker 9: of manufacturers or up by about a trillion dollars since

926
00:45:26,640 --> 00:45:29,880
Speaker 9: twenty nineteen, so since the peak of the trade war,

927
00:45:30,080 --> 00:45:34,239
Speaker 9: since the pandemic. China's imports are up, manufactures up two

928
00:45:34,280 --> 00:45:38,480
Speaker 9: hundred billion, China's surplus of manufacturer goods is up eight

929
00:45:38,600 --> 00:45:41,520
Speaker 9: hundred billion. And I'm pretty confident because I have some

930
00:45:41,640 --> 00:45:44,120
Speaker 9: sense of magnitudes. Is that's not all trade with Russia.

931
00:45:44,719 --> 00:45:46,560
Speaker 9: There's a little bit which is trade with Russia, but

932
00:45:46,560 --> 00:45:51,360
Speaker 9: it is mostly because trade deficits amongst democracies have risen.

933
00:45:51,960 --> 00:45:54,680
Speaker 9: So the classic offsets to China's surplus or are the

934
00:45:54,760 --> 00:45:59,240
Speaker 9: deficits in the UK, the US, and India not geopolitically

935
00:45:59,280 --> 00:46:03,520
Speaker 9: aligned with China, but the global counterpart. So my overarching

936
00:46:03,600 --> 00:46:08,239
Speaker 9: thesis is the world has continued to globalize, but in

937
00:46:08,320 --> 00:46:11,439
Speaker 9: unhealthy ways. Unhealthy because there's still a lot of tax

938
00:46:11,520 --> 00:46:16,680
Speaker 9: driven globalization, and unhealthy because this increase in China's exports

939
00:46:17,080 --> 00:46:19,799
Speaker 9: is a reflection of deep weaknesses which have already been

940
00:46:19,800 --> 00:46:24,400
Speaker 9: discussed in China's domestic economy, which make China incapable of

941
00:46:24,440 --> 00:46:28,360
Speaker 9: growing at the pace at once without relying more, not less,

942
00:46:28,680 --> 00:46:29,440
Speaker 9: on exports.

943
00:46:30,320 --> 00:46:34,160
Speaker 4: So that's the theme, a lot to chew on, and

944
00:46:34,200 --> 00:46:37,719
Speaker 4: that's what we're gonna do. But the trade war that

945
00:46:37,840 --> 00:46:40,719
Speaker 4: started in twenty eighteen, does it show up with the

946
00:46:40,800 --> 00:46:43,799
Speaker 4: data in any meaningful sense, like when you look at

947
00:46:43,800 --> 00:46:47,920
Speaker 4: the data now versus some counterfactual where tariffs had put

948
00:46:47,960 --> 00:46:49,920
Speaker 4: in place, do you see fingerprints of it?

949
00:46:51,200 --> 00:46:54,800
Speaker 9: Yes. The most obvious is that you know the US

950
00:46:54,920 --> 00:46:57,879
Speaker 9: is the one country that currently doesn't import any cars

951
00:46:57,880 --> 00:47:02,960
Speaker 9: from China. Since the trade war, China has become the

952
00:47:03,000 --> 00:47:06,480
Speaker 9: world's biggest auto exporter, and the US market is effectively

953
00:47:06,560 --> 00:47:11,239
Speaker 9: for now walled off. If you look at the bilateral

954
00:47:11,280 --> 00:47:14,600
Speaker 9: trade data between the US and China, the first thing

955
00:47:14,600 --> 00:47:18,360
Speaker 9: to notice is they no longer agree. In the bilateral data.

956
00:47:18,600 --> 00:47:20,920
Speaker 9: From the US side, we think our trade with China's

957
00:47:20,960 --> 00:47:25,360
Speaker 9: gone down, and significantly if you look at that same

958
00:47:25,440 --> 00:47:28,360
Speaker 9: data from the Chinese side, China thinks it's exports to

959
00:47:28,440 --> 00:47:33,520
Speaker 9: the US are broadly unchanged. Now you can still say

960
00:47:33,520 --> 00:47:37,000
Speaker 9: there's an impact because China's exports to Europe, the obvious counterfactional,

961
00:47:37,040 --> 00:47:43,880
Speaker 9: have gone up. So there's some evidence of a bilateral decoupling.

962
00:47:44,360 --> 00:47:48,440
Speaker 9: There is a lot of evidence of tariff avoidance. And

963
00:47:48,480 --> 00:47:52,360
Speaker 9: then at a global level, there's no real evidence of

964
00:47:52,440 --> 00:47:57,440
Speaker 9: a serious decoupling or fragmentation, because a serious fragmentation, in

965
00:47:57,480 --> 00:47:59,840
Speaker 9: my view at least, is one where China runs a

966
00:47:59,880 --> 00:48:04,480
Speaker 9: smaller surplus with democracies where China trades balances amongst the

967
00:48:04,520 --> 00:48:07,320
Speaker 9: axis of autocracies, that clearly hasn't happened.

968
00:48:07,640 --> 00:48:12,520
Speaker 2: You mentioned earlier tax incentives to globalization, and I'm trying

969
00:48:12,560 --> 00:48:14,719
Speaker 2: to think how to frame this question, but like, why

970
00:48:14,760 --> 00:48:19,239
Speaker 2: are we so obsessed with tariffs if you know, the

971
00:48:19,360 --> 00:48:21,879
Speaker 2: ultimate cost of a product is not the only thing

972
00:48:22,120 --> 00:48:24,720
Speaker 2: driving decisions about where it's made and where it's going.

973
00:48:26,000 --> 00:48:28,760
Speaker 9: I mean, in all honesty, I think it's because Donald

974
00:48:28,800 --> 00:48:33,280
Speaker 9: Trump won the twenty sixteen election, and Donald Trump believes

975
00:48:33,280 --> 00:48:36,640
Speaker 9: tariff's matter. Donald Trump is, He's a tariff man, he

976
00:48:36,760 --> 00:48:40,520
Speaker 9: really is. The other one is, Look, there is absolutely

977
00:48:40,600 --> 00:48:45,560
Speaker 9: no lobby, powerful lobby that is pushing back against importing

978
00:48:45,560 --> 00:48:49,800
Speaker 9: more pharmaceuticals from Ireland. And there's a very powerful lobby

979
00:48:50,239 --> 00:48:54,800
Speaker 9: that wants this current pattern to remain by producing outside

980
00:48:54,840 --> 00:48:58,040
Speaker 9: the United States and moving intellectual property outside the United States.

981
00:48:58,120 --> 00:49:02,439
Speaker 9: The American pharmaceutical industry has reduced its effective tax rate

982
00:49:02,880 --> 00:49:05,920
Speaker 9: to ten roughly ten percent. Why wouldn't you want to

983
00:49:05,960 --> 00:49:11,240
Speaker 9: maintain that The opposite side, the loser side, is mostly

984
00:49:11,280 --> 00:49:13,560
Speaker 9: the taxpayer. There's not a lot of jobs at stake,

985
00:49:13,600 --> 00:49:17,000
Speaker 9: although there's some so a couple of shocking to me

986
00:49:17,600 --> 00:49:23,560
Speaker 9: little nuggets. The US pharmaceutical industry top six companies roughly

987
00:49:23,640 --> 00:49:27,080
Speaker 9: made sixty to seventy billion dollars in twenty twenty three

988
00:49:27,440 --> 00:49:33,480
Speaker 9: top six companies. Those top six companies paid collectively some

989
00:49:33,520 --> 00:49:36,440
Speaker 9: a little bit of offsets zero in tax to the

990
00:49:36,520 --> 00:49:42,080
Speaker 9: US federal government. They reported losing money on their US operations,

991
00:49:42,480 --> 00:49:45,399
Speaker 9: even though the US has well known much higher pharmaceutical

992
00:49:45,440 --> 00:49:48,600
Speaker 9: prices than the rest of the world, And they report

993
00:49:48,680 --> 00:49:51,879
Speaker 9: making all of their profit and paying all of their

994
00:49:51,960 --> 00:50:01,200
Speaker 9: tax in other jurisdictions. So everyone except seems to win.

995
00:50:02,400 --> 00:50:05,280
Speaker 4: What was the effect, if any so one of the things,

996
00:50:05,320 --> 00:50:09,120
Speaker 4: regardless of who wins tomorrow's vote, At some point there's

997
00:50:09,200 --> 00:50:11,799
Speaker 4: going to be a The Tax Cut and Jobs Act

998
00:50:11,840 --> 00:50:13,600
Speaker 4: is going to come up, though I think the corporate

999
00:50:13,680 --> 00:50:16,040
Speaker 4: side is permanent that that part is going to be

1000
00:50:16,200 --> 00:50:18,640
Speaker 4: less controversial or not going to be a thing. But

1001
00:50:18,960 --> 00:50:21,279
Speaker 4: what was the effect of the Tax Cut and Jobs Act?

1002
00:50:21,280 --> 00:50:25,560
Speaker 4: Because there was some impulse at least claimed that, oh,

1003
00:50:25,560 --> 00:50:28,719
Speaker 4: this will encourage companies to recognize their revenues in the

1004
00:50:28,840 --> 00:50:31,880
Speaker 4: United States and crack down on that to some extent,

1005
00:50:32,239 --> 00:50:34,960
Speaker 4: at least in the realm of pharmaceuticals as you've described,

1006
00:50:34,960 --> 00:50:37,759
Speaker 4: that hasn't happened. What was the intent and what was

1007
00:50:37,800 --> 00:50:38,640
Speaker 4: the effect.

1008
00:50:38,280 --> 00:50:41,680
Speaker 9: Of that bill? Look, first of all, you broke my

1009
00:50:41,719 --> 00:50:45,520
Speaker 9: heart by saying there's nothing that's going to happen on

1010
00:50:45,560 --> 00:50:47,160
Speaker 9: the corporate tax code next year?

1011
00:50:47,480 --> 00:50:47,799
Speaker 8: Is there?

1012
00:50:48,880 --> 00:50:53,040
Speaker 9: Like it is obviously going to be part of a negotiation.

1013
00:50:53,120 --> 00:50:53,880
Speaker 3: Okay, Yeah, that's right.

1014
00:50:54,680 --> 00:50:57,320
Speaker 9: It is the great chance that we have to correct

1015
00:50:57,360 --> 00:51:00,880
Speaker 9: some of the flaws. In my view, the tax.

1016
00:51:00,680 --> 00:51:04,160
Speaker 4: Cuts the corporate side doesn't expire automatically the way some

1017
00:51:04,200 --> 00:51:05,160
Speaker 4: of the personal does.

1018
00:51:05,080 --> 00:51:07,000
Speaker 9: So you know how much detail do you want to

1019
00:51:07,000 --> 00:51:09,719
Speaker 9: go into. The twenty one percent does not expire, the

1020
00:51:09,800 --> 00:51:12,279
Speaker 9: ten and a half percent low guilty rate, which is

1021
00:51:12,280 --> 00:51:14,160
Speaker 9: for your global intangibles income, which is.

1022
00:51:14,120 --> 00:51:15,320
Speaker 3: Really anything about this stuff.

1023
00:51:15,360 --> 00:51:18,719
Speaker 9: Clearly it goes up to thirteen point one twenty five,

1024
00:51:18,760 --> 00:51:21,480
Speaker 9: which of course some people care about. And the Foreign

1025
00:51:21,480 --> 00:51:25,120
Speaker 9: derived Intangible's Income tax or FITTY goes up to the

1026
00:51:25,160 --> 00:51:28,759
Speaker 9: god awful higher rate of sixteen percent. So there are

1027
00:51:28,840 --> 00:51:32,919
Speaker 9: some ratchet ups. So what happened with the Tax Cuts

1028
00:51:32,920 --> 00:51:35,279
Speaker 9: and Jobs Act? First of all, the corporate side was

1029
00:51:35,320 --> 00:51:38,919
Speaker 9: a total revolution. Before the Tax Cuts and Jobs Act,

1030
00:51:39,160 --> 00:51:43,120
Speaker 9: the US had a system called deferment, a deferral where

1031
00:51:43,560 --> 00:51:46,919
Speaker 9: profits earned abroad in theory were taxed at the US

1032
00:51:47,040 --> 00:51:49,840
Speaker 9: headline tax rate of thirty five, but only if the

1033
00:51:49,840 --> 00:51:52,919
Speaker 9: profit was returned to the United States. Profits were never

1034
00:51:53,000 --> 00:51:56,320
Speaker 9: returned to the US companies borrowed against their offshore profits.

1035
00:51:56,760 --> 00:52:00,440
Speaker 9: And that was essentially a system that sort of worked,

1036
00:52:00,719 --> 00:52:03,040
Speaker 9: but it meant that US companies had on the US

1037
00:52:03,080 --> 00:52:05,120
Speaker 9: side of their balance sheet a lot of debt and

1038
00:52:05,160 --> 00:52:06,560
Speaker 9: on the foreur in side of their balance sheet a

1039
00:52:06,560 --> 00:52:09,919
Speaker 9: lot of assets. It wasn't great. So the main thing

1040
00:52:10,080 --> 00:52:13,040
Speaker 9: that tax cuts and JOBZAC did was it got rid

1041
00:52:13,160 --> 00:52:17,120
Speaker 9: of deferral. You pay tax as you go. Once you

1042
00:52:17,160 --> 00:52:19,919
Speaker 9: pay your US tax, you're free to move your money

1043
00:52:19,920 --> 00:52:21,960
Speaker 9: wherever you want. That was supposed to bring a lot

1044
00:52:21,960 --> 00:52:25,439
Speaker 9: of money back. Obviously lowered the headline tax rate from

1045
00:52:25,760 --> 00:52:30,160
Speaker 9: thirty five to twenty one. It created this new global

1046
00:52:30,200 --> 00:52:33,840
Speaker 9: minimum on intangibles, which is sort of a strange concept

1047
00:52:33,880 --> 00:52:38,240
Speaker 9: but essentially intellectual property that everyone pays on their global income.

1048
00:52:38,320 --> 00:52:40,880
Speaker 9: So in theory it's sound territorial, but it's not entirely.

1049
00:52:41,280 --> 00:52:44,080
Speaker 9: And then it created a separate low tax rate, the

1050
00:52:44,120 --> 00:52:47,799
Speaker 9: foreign derived intangible's income tax rate for companies that move

1051
00:52:47,880 --> 00:52:50,279
Speaker 9: their intellectual property back to the US and used it

1052
00:52:50,320 --> 00:52:54,560
Speaker 9: to export. Pharmaceutical companies make most of their profit, although

1053
00:52:54,560 --> 00:52:57,920
Speaker 9: they don't say it on their US sales. They preferred

1054
00:52:57,920 --> 00:53:01,240
Speaker 9: to keep their intellectual property and production abroad and remain

1055
00:53:01,320 --> 00:53:03,600
Speaker 9: in the ten and a half percent guilty bucket. So

1056
00:53:03,719 --> 00:53:09,480
Speaker 9: no change there. Apple, same thing, Microsoft broadly the same thing,

1057
00:53:09,960 --> 00:53:13,799
Speaker 9: but some companies did adjust. Facebook and Google return their

1058
00:53:13,800 --> 00:53:16,360
Speaker 9: intellectual property to the US you see this very clearly

1059
00:53:16,400 --> 00:53:20,800
Speaker 9: in their corporate returns, and now sell their intellectual property

1060
00:53:20,800 --> 00:53:23,600
Speaker 9: to their Irish subsidiary where they book most of their

1061
00:53:23,640 --> 00:53:28,120
Speaker 9: ad revenue globally. Qualcom has also adjusted its global taxbusher.

1062
00:53:28,160 --> 00:53:30,600
Speaker 9: So it's not a story of no change, but it

1063
00:53:30,680 --> 00:53:35,040
Speaker 9: is a story of mixed change. And it is a

1064
00:53:35,160 --> 00:53:38,680
Speaker 9: story where, at least in my view, the six biggest

1065
00:53:38,719 --> 00:53:42,560
Speaker 9: pharmaceutical companies clearly pay less to the US government after

1066
00:53:42,719 --> 00:53:45,280
Speaker 9: the Tax Cuts and Jobs Act than they did before

1067
00:53:45,600 --> 00:53:47,719
Speaker 9: because they actually had to bring some money back from

1068
00:53:47,719 --> 00:53:50,640
Speaker 9: their offshore tax subsidiaries at they're thirty five percent to

1069
00:53:50,640 --> 00:53:55,600
Speaker 9: cover their ongoing cost and Apple now mostly for even

1070
00:53:55,640 --> 00:53:58,840
Speaker 9: more complex reasons, but Apple books more of its profit

1071
00:53:58,880 --> 00:54:01,600
Speaker 9: in Ireland than in the United State States and Apple

1072
00:54:01,680 --> 00:54:05,560
Speaker 9: is now paying roughly as much in tax to Ireland

1073
00:54:06,040 --> 00:54:08,879
Speaker 9: as is it pay into the United States. That's why

1074
00:54:08,880 --> 00:54:11,960
Speaker 9: Ireland has a sovereign Wealth Fund. So there are still

1075
00:54:12,080 --> 00:54:15,040
Speaker 9: changes that could be put in place that broadly speaking,

1076
00:54:15,040 --> 00:54:20,520
Speaker 9: wouldn't significantly increase the corporate tax burden, but would increase

1077
00:54:20,600 --> 00:54:23,760
Speaker 9: the amount that the biggest and most successful US companies

1078
00:54:23,800 --> 00:54:25,880
Speaker 9: paying the US. So hence you broke my heart. You

1079
00:54:25,920 --> 00:54:26,920
Speaker 9: said there's nothing to be done.

1080
00:54:27,120 --> 00:54:30,080
Speaker 3: It was just ignorant, It was it was just ignorant.

1081
00:54:30,680 --> 00:54:32,840
Speaker 2: I realized I should have said this in the intro.

1082
00:54:33,000 --> 00:54:36,480
Speaker 2: But in addition to writing and researching and tweeting about

1083
00:54:36,520 --> 00:54:40,040
Speaker 2: all these issues, you also have real life experience when

1084
00:54:40,040 --> 00:54:42,759
Speaker 2: it comes to trade policy. You were an advisor to

1085
00:54:42,920 --> 00:54:45,879
Speaker 2: a US trade representative, Catherine Tie, who has also been

1086
00:54:46,200 --> 00:54:49,720
Speaker 2: on the show. Maybe you can't get into specifics here,

1087
00:54:49,920 --> 00:54:52,400
Speaker 2: but like give us a sense of what the most

1088
00:54:52,440 --> 00:54:56,560
Speaker 2: surprising thing was when you were actually in that advisor

1089
00:54:56,680 --> 00:55:00,520
Speaker 2: role when it comes to the construction the rail, I

1090
00:55:00,520 --> 00:55:03,640
Speaker 2: guess of making trade policy, I.

1091
00:55:03,560 --> 00:55:08,080
Speaker 9: Guess one surprise, and it's just a cultural thing about

1092
00:55:08,160 --> 00:55:12,680
Speaker 9: usdr as I previously worked at the US Treasury, is

1093
00:55:12,719 --> 00:55:15,520
Speaker 9: that financial markets, which you know, are the obsession of

1094
00:55:15,560 --> 00:55:19,320
Speaker 9: this town. Presumably this crowd are weighted at about zero.

1095
00:55:20,280 --> 00:55:25,080
Speaker 9: In USCR internal decision making, people do not get a

1096
00:55:25,160 --> 00:55:27,720
Speaker 9: report on what happened in the market at the start

1097
00:55:27,760 --> 00:55:31,120
Speaker 9: of a significant meeting at USDR, whereas that would be

1098
00:55:31,160 --> 00:55:35,080
Speaker 9: kind of the norm at the US Treasury. So culturally

1099
00:55:35,520 --> 00:55:39,760
Speaker 9: it's not driven by the market. Culturally, US trade policy

1100
00:55:39,880 --> 00:55:45,360
Speaker 9: is driven by lawyers, and lawyers care a lot about process.

1101
00:55:46,000 --> 00:55:48,560
Speaker 9: So I think what surprised me the most is the

1102
00:55:48,600 --> 00:55:52,480
Speaker 9: weight that is given to following the procedural niceties of

1103
00:55:52,520 --> 00:55:56,280
Speaker 9: the various different trade laws, which I think are actually

1104
00:55:56,360 --> 00:55:59,920
Speaker 9: quite relevant if Trump were to win, which I person

1105
00:56:00,120 --> 00:56:03,160
Speaker 9: we certainly do not hope is the case, but those

1106
00:56:03,280 --> 00:56:08,920
Speaker 9: procedural niceties become constraints on how quickly he can restart

1107
00:56:09,040 --> 00:56:10,200
Speaker 9: various trade wars.

1108
00:56:10,760 --> 00:56:16,839
Speaker 4: You mentioned in the beginning that globalization continues despite all

1109
00:56:16,960 --> 00:56:20,040
Speaker 4: the memes and despite all of the narrative, but you

1110
00:56:20,080 --> 00:56:24,399
Speaker 4: described it as an unhealthy form of globalization. Was there

1111
00:56:24,440 --> 00:56:26,799
Speaker 4: a point where it was healthy in your view? And

1112
00:56:26,880 --> 00:56:30,000
Speaker 4: is there a turning point where the globalization process went

1113
00:56:30,040 --> 00:56:31,200
Speaker 4: from healthy to unhealthy?

1114
00:56:32,280 --> 00:56:37,759
Speaker 9: So in general, I think globalization in the nineteen nineties

1115
00:56:38,400 --> 00:56:41,920
Speaker 9: had a different impact on the US economy than globalization

1116
00:56:42,320 --> 00:56:45,920
Speaker 9: after the nineteen nineties. If you look at at trade

1117
00:56:45,960 --> 00:56:48,080
Speaker 9: patterns in the nineteen nineties, and you know there's a

1118
00:56:48,120 --> 00:56:51,080
Speaker 9: significant interruption in the Asian financial crisis, and I think

1119
00:56:51,120 --> 00:56:54,400
Speaker 9: most people in Asia would say globalization went wrong in

1120
00:56:54,440 --> 00:56:59,720
Speaker 9: the nineteen nineties. But during that period, broadly speaking, experts

1121
00:56:59,719 --> 00:57:03,520
Speaker 9: and in him were both expanding symmetrically, and you didn't

1122
00:57:03,560 --> 00:57:08,680
Speaker 9: have an expansion and explosion of the offshore balance sheets

1123
00:57:08,719 --> 00:57:13,400
Speaker 9: of big banks and their special investment vehicles like the

1124
00:57:13,440 --> 00:57:18,240
Speaker 9: obsession of Wall Street in the pre global financial crisis period.

1125
00:57:18,480 --> 00:57:20,680
Speaker 9: So to me, that was a healthier form of globalization.

1126
00:57:20,760 --> 00:57:25,160
Speaker 9: What went wrong, well, a technical thing checked the box

1127
00:57:25,160 --> 00:57:27,880
Speaker 9: made it really easy for US companies to shift intellectual

1128
00:57:27,920 --> 00:57:33,200
Speaker 9: property offshore. That unleashed a wave of tax driven globalization

1129
00:57:33,360 --> 00:57:35,280
Speaker 9: that we have not yet, in my view, been able

1130
00:57:35,320 --> 00:57:40,480
Speaker 9: to rein in. It created incentives wherever broadening sectors of

1131
00:57:40,480 --> 00:57:42,560
Speaker 9: the US economy. So one of the things I point

1132
00:57:42,640 --> 00:57:46,960
Speaker 9: out in the Aspen Econometic Strategy paper is that semiconductor

1133
00:57:47,000 --> 00:57:52,760
Speaker 9: equipment manufacturing actually a pretty strategically important industry, has between

1134
00:57:52,840 --> 00:57:56,760
Speaker 9: two thousand and five and twenty twenty three twenty four,

1135
00:57:57,320 --> 00:57:59,600
Speaker 9: moved a lot of its manufacturing and all of its

1136
00:57:59,680 --> 00:58:02,640
Speaker 9: profit to Southeast Asia. Why we thought that was in

1137
00:58:02,640 --> 00:58:07,880
Speaker 9: our strategic interest is beyond me. But it wasn't just

1138
00:58:07,920 --> 00:58:10,920
Speaker 9: a one off. It's been a continuous process. And then

1139
00:58:11,040 --> 00:58:15,360
Speaker 9: obviously China enters the WTO, the Chinese surplus explodes, and

1140
00:58:15,440 --> 00:58:20,600
Speaker 9: I think that generated a period of unhealthy globalization as well.

1141
00:58:21,160 --> 00:58:23,840
Speaker 9: And so that's why I'm a little worried right now

1142
00:58:24,040 --> 00:58:29,280
Speaker 9: that the increase in China's surplus judged on the global basis,

1143
00:58:29,280 --> 00:58:31,840
Speaker 9: not on the bilateral basis against the US, is on

1144
00:58:31,920 --> 00:58:35,400
Speaker 9: a magnitude comparable as a share of world GDP. To

1145
00:58:35,520 --> 00:58:38,080
Speaker 9: that scene immediately after WTO.

1146
00:58:37,760 --> 00:58:56,600
Speaker 2: Entry, there seems to be some consensus about diagnosing the

1147
00:58:56,680 --> 00:59:00,400
Speaker 2: problems in the Chinese economy, so not enough domestic assumption

1148
00:59:00,560 --> 00:59:04,440
Speaker 2: to high savings, et cetera. And yet it still seems

1149
00:59:04,600 --> 00:59:08,560
Speaker 2: relatively committed to the export driven model. Why is that?

1150
00:59:10,200 --> 00:59:13,520
Speaker 9: The pithy answer would be that there can be no

1151
00:59:13,680 --> 00:59:20,920
Speaker 9: consensus in China that doesn't include President She. So actually,

1152
00:59:20,920 --> 00:59:24,040
Speaker 9: I don't think there is consensus because I think President

1153
00:59:24,120 --> 00:59:29,480
Speaker 9: She doesn't share this diagnosis. I think President She, generally speaking,

1154
00:59:29,600 --> 00:59:35,080
Speaker 9: views support for households as unproductive, and he views investment,

1155
00:59:35,160 --> 00:59:40,360
Speaker 9: particularly investment in high tech sectors, as productive. The intellectual

1156
00:59:40,520 --> 00:59:45,040
Speaker 9: leap that giving checks to households, taking less from households

1157
00:59:45,560 --> 00:59:50,320
Speaker 9: lets household spend more, and therefore supports investments, not just consumption,

1158
00:59:50,440 --> 00:59:53,880
Speaker 9: but it supports investment throughout the economy is not one

1159
00:59:53,920 --> 00:59:58,920
Speaker 9: that president, she obviously shares. So, yeah, I don't think

1160
00:59:59,000 --> 01:00:02,360
Speaker 9: there is yet consensus.

1161
01:00:03,960 --> 01:00:06,120
Speaker 4: One of the things that people love to talk about

1162
01:00:06,400 --> 01:00:09,440
Speaker 4: is just forever for as long as is the future

1163
01:00:09,440 --> 01:00:11,920
Speaker 4: of the dollar, and you know, just one of those

1164
01:00:11,920 --> 01:00:13,560
Speaker 4: things people just love to talk about it.

1165
01:00:13,640 --> 01:00:14,200
Speaker 9: I've noticed.

1166
01:00:14,800 --> 01:00:16,560
Speaker 3: Yeah, when you look at it, it.

1167
01:00:16,560 --> 01:00:18,400
Speaker 9: Is not a topic that I prefer to talk about,

1168
01:00:18,400 --> 01:00:19,280
Speaker 9: but I will talk about it.

1169
01:00:19,360 --> 01:00:20,520
Speaker 3: No, you have to talk about it.

1170
01:00:20,560 --> 01:00:24,000
Speaker 4: He didn't talk about it, all right, Tracy, what she introduced,

1171
01:00:24,040 --> 01:00:25,640
Speaker 4: she said, we could ask Brad anything.

1172
01:00:25,760 --> 01:00:27,080
Speaker 3: So this is on my mind.

1173
01:00:27,160 --> 01:00:31,720
Speaker 4: When you look at unhealthy globalization, do you see any

1174
01:00:31,880 --> 01:00:37,360
Speaker 4: strains on the existing the dollar regime or any reasons

1175
01:00:37,400 --> 01:00:39,640
Speaker 4: to think that there is going to be a meaningful

1176
01:00:39,760 --> 01:00:43,960
Speaker 4: change in the trajectory of dollar usage, either within the

1177
01:00:44,040 --> 01:00:48,280
Speaker 4: trade for goods and services globally or the use of dollar.

1178
01:00:48,120 --> 01:00:49,880
Speaker 3: In financial transactions.

1179
01:00:49,320 --> 01:00:54,680
Speaker 9: Globally, not really. So there has been one obviously important

1180
01:00:54,800 --> 01:00:59,280
Speaker 9: and significant change, which is the sanctions on Russia. You know,

1181
01:00:59,440 --> 01:01:04,160
Speaker 9: Russia is one of the top ten global economies, produces

1182
01:01:04,160 --> 01:01:06,520
Speaker 9: a lot of oil in the world wants oil. We

1183
01:01:07,000 --> 01:01:10,240
Speaker 9: meaning in this case, the US, the EU, the sanctioning

1184
01:01:10,280 --> 01:01:15,400
Speaker 9: coalition the G ten countries have generally not actually sanctioned

1185
01:01:15,440 --> 01:01:19,320
Speaker 9: dollar in europayment. But even though we have not sanctioned

1186
01:01:19,320 --> 01:01:22,880
Speaker 9: dollar in europayment, Russia obviously is very concerned that we could,

1187
01:01:23,440 --> 01:01:26,160
Speaker 9: particularly because we've frozen all the central Bank's assets, and

1188
01:01:26,200 --> 01:01:30,800
Speaker 9: that was a pretty big step. Russia, to be fair,

1189
01:01:31,440 --> 01:01:36,320
Speaker 9: was the country that did the most before twenty twenty

1190
01:01:36,360 --> 01:01:40,120
Speaker 9: twenty two the invasion to reduce dollar usage. Didn't get

1191
01:01:40,240 --> 01:01:43,400
Speaker 9: rid of it, but Russia had moved almost all its

1192
01:01:43,440 --> 01:01:46,439
Speaker 9: reserves out of the dollar. It had certainly removed all

1193
01:01:46,480 --> 01:01:50,320
Speaker 9: of its reserves out of visible dollars, stuff that the

1194
01:01:50,440 --> 01:01:53,640
Speaker 9: US can see in this normal data reporting, and it

1195
01:01:53,680 --> 01:01:57,120
Speaker 9: had migrated to basically using the Euro for most of

1196
01:01:57,160 --> 01:02:01,160
Speaker 9: its oil and gas transactions. You could say that's just logical.

1197
01:02:01,240 --> 01:02:05,440
Speaker 9: Russia traded mostly with Europe before the invasion, but it

1198
01:02:05,520 --> 01:02:08,440
Speaker 9: was using the euro to denominate trade with China, not

1199
01:02:08,560 --> 01:02:11,439
Speaker 9: the yuan, not the dollar, And I think the main

1200
01:02:11,600 --> 01:02:15,640
Speaker 9: lesson of the sanctions it has been that if you

1201
01:02:15,680 --> 01:02:18,880
Speaker 9: want to diversify out of the dollar and you want

1202
01:02:18,920 --> 01:02:21,680
Speaker 9: protection against sanctions, which is the one thing that you

1203
01:02:21,760 --> 01:02:25,280
Speaker 9: get with diversification out of the dollar, diversifying out of

1204
01:02:25,320 --> 01:02:28,880
Speaker 9: the Euro isn't diversifying far enough, so you essentially have

1205
01:02:28,920 --> 01:02:32,480
Speaker 9: to diversify into using the yuan. Now, the yuan has

1206
01:02:32,520 --> 01:02:35,880
Speaker 9: a bunch of disadvantages. The wan is not accepted globally.

1207
01:02:35,880 --> 01:02:38,000
Speaker 9: If you're an African country and you get yuan for

1208
01:02:38,080 --> 01:02:40,720
Speaker 9: selling something to China, you can't use that yuan to

1209
01:02:40,720 --> 01:02:43,520
Speaker 9: buy stuff from your neighbor. It's not that kind of

1210
01:02:43,560 --> 01:02:48,840
Speaker 9: global currency yet. The dollar in euror and in general,

1211
01:02:49,000 --> 01:02:52,360
Speaker 9: holding financial assets in yuan means you've been holding a

1212
01:02:52,400 --> 01:02:55,680
Speaker 9: depreciating currency with lower yields than in the dollar. And

1213
01:02:55,720 --> 01:02:59,360
Speaker 9: then by the way China uses is geopolitical and g

1214
01:02:59,520 --> 01:03:03,680
Speaker 9: you want. Mostly it's been over its trade leverage pretty aggressively,

1215
01:03:04,360 --> 01:03:06,840
Speaker 9: and you would have to assume if you have a

1216
01:03:06,880 --> 01:03:09,200
Speaker 9: lot of your financial assets in yuan, or your trade

1217
01:03:09,280 --> 01:03:13,280
Speaker 9: is denominated in yuan, that you are potentially subject to

1218
01:03:13,920 --> 01:03:18,520
Speaker 9: Chinese financial pressure. So you you get a little bit

1219
01:03:18,520 --> 01:03:22,640
Speaker 9: of defense against US and European sanctions, but at a

1220
01:03:22,680 --> 01:03:26,160
Speaker 9: pretty significant cost, and you just don't see it. So

1221
01:03:26,280 --> 01:03:29,000
Speaker 9: one one anecdote, you know, because you know, it goes

1222
01:03:29,080 --> 01:03:31,960
Speaker 9: a little interesting. It was. It was sort of striking

1223
01:03:32,000 --> 01:03:34,080
Speaker 9: to me because I hadn't been to China for quite

1224
01:03:34,080 --> 01:03:35,960
Speaker 9: some time. I was a little nervous about it, to

1225
01:03:35,960 --> 01:03:40,680
Speaker 9: be honest, and heard a bank treasurer from a big

1226
01:03:40,760 --> 01:03:45,000
Speaker 9: Chinese bank talk about how they were thinking about the world.

1227
01:03:45,040 --> 01:03:48,640
Speaker 9: And you know what that Chinese bank was worried about.

1228
01:03:49,040 --> 01:03:51,560
Speaker 9: I was worried about the fact that Yuan lending rates

1229
01:03:51,600 --> 01:03:55,800
Speaker 9: were being forced down and that was squeezing Yuan net

1230
01:03:55,800 --> 01:03:58,960
Speaker 9: interest margins and fair things. That's what all banks tend

1231
01:03:59,000 --> 01:04:01,360
Speaker 9: to worry about. Although it was king to me that

1232
01:04:01,600 --> 01:04:04,400
Speaker 9: this bank treasurer was more or less saying, you know,

1233
01:04:04,440 --> 01:04:07,960
Speaker 9: the official lending rate, which the Chinese had been deemphasizing,

1234
01:04:08,400 --> 01:04:11,280
Speaker 9: was actually really important. The other thing he was complaining

1235
01:04:11,280 --> 01:04:14,080
Speaker 9: about is, well, there's all these lending quotas. Like again,

1236
01:04:14,120 --> 01:04:16,520
Speaker 9: I was like, I thought you'd reformed your commercial banks.

1237
01:04:16,560 --> 01:04:19,680
Speaker 9: You weren't doing quotas. No, no, no quotas for manufacturing,

1238
01:04:19,720 --> 01:04:23,600
Speaker 9: quotas for lending to innovation. The Treasurer obviously was sort

1239
01:04:23,600 --> 01:04:27,160
Speaker 9: of implying quotas that required us to lend to companies

1240
01:04:27,200 --> 01:04:29,960
Speaker 9: that were going to generate losses in the future. So

1241
01:04:30,040 --> 01:04:32,880
Speaker 9: what was the great hope. Well, they looked at the

1242
01:04:32,960 --> 01:04:36,480
Speaker 9: Japanese banking system and discovered that the Japanese banks do

1243
01:04:36,560 --> 01:04:40,160
Speaker 9: this great dollar business that generates half their interest income,

1244
01:04:40,720 --> 01:04:44,400
Speaker 9: and they looked at that with with envy. You could

1245
01:04:44,960 --> 01:04:47,520
Speaker 9: choose your own interest margin in dollars and you weren't

1246
01:04:47,560 --> 01:04:50,800
Speaker 9: forced to lend to loss making companies in dollars. So,

1247
01:04:51,360 --> 01:04:57,120
Speaker 9: just as an anecdote, you see growth in the dollar business,

1248
01:04:57,600 --> 01:05:02,600
Speaker 9: offshore dollar business of Chinese state banks, which completely runs

1249
01:05:02,600 --> 01:05:05,760
Speaker 9: against the d dollarization narrative and is very much a

1250
01:05:05,760 --> 01:05:08,800
Speaker 9: function of China's own domestic weakness. So I think that

1251
01:05:09,000 --> 01:05:09,840
Speaker 9: to me that was telling.

1252
01:05:10,160 --> 01:05:13,439
Speaker 2: You had a great line in the paper, just going

1253
01:05:13,480 --> 01:05:16,480
Speaker 2: back to the like lending quota point, but you said

1254
01:05:16,920 --> 01:05:20,240
Speaker 2: free markets appear to favor a country that hasn't freed

1255
01:05:20,640 --> 01:05:24,040
Speaker 2: its own market. Ie, China has probably benefited the most

1256
01:05:24,040 --> 01:05:27,880
Speaker 2: from the trade liberalization of the nineteen nineties and early

1257
01:05:27,880 --> 01:05:29,960
Speaker 2: two thousands. Why is that?

1258
01:05:32,280 --> 01:05:36,120
Speaker 9: Well, again, Tracy, thanks for really closely reading my paper.

1259
01:05:36,720 --> 01:05:37,200
Speaker 6: I try.

1260
01:05:37,640 --> 01:05:40,760
Speaker 9: I actually thought that was a good line. Ummm, you're

1261
01:05:40,800 --> 01:05:44,960
Speaker 9: the first person who's noticed it. Um I'd throw in, like, hopefully,

1262
01:05:45,040 --> 01:05:48,840
Speaker 9: like some witty quips and a forty page paper just

1263
01:05:48,880 --> 01:05:52,760
Speaker 9: to test to see if anyone actually reads U tast

1264
01:05:53,000 --> 01:05:56,800
Speaker 9: you did. Look, I am not the first to make

1265
01:05:56,840 --> 01:06:02,040
Speaker 9: this observation. I think it's an observation that has influenced

1266
01:06:02,280 --> 01:06:05,320
Speaker 9: politics and policy in the United States and in Europe.

1267
01:06:06,640 --> 01:06:12,280
Speaker 9: China does not have a full market economy. The government

1268
01:06:12,800 --> 01:06:16,760
Speaker 9: runs the banking system. The banking system still dominates the

1269
01:06:16,800 --> 01:06:20,800
Speaker 9: distribution of credit within the Chinese economy. It favors some

1270
01:06:20,840 --> 01:06:25,560
Speaker 9: sectors over others. The Chinese state, in its many layers

1271
01:06:25,680 --> 01:06:28,520
Speaker 9: at the central government level but also at the provincial level,

1272
01:06:28,880 --> 01:06:35,000
Speaker 9: provides a lot of equity investment for Chinese companies. And

1273
01:06:35,080 --> 01:06:37,360
Speaker 9: so you can argue that China doesn't just have one

1274
01:06:37,400 --> 01:06:40,320
Speaker 9: industrial policy, kind of has twenty because all the different

1275
01:06:40,360 --> 01:06:43,120
Speaker 9: provinces have their own industrial policy trying to build up

1276
01:06:43,160 --> 01:06:47,400
Speaker 9: provincial champions that become national champions, and in the process

1277
01:06:47,480 --> 01:06:51,160
Speaker 9: they get cheap capital, very cheap capital. There isn't a

1278
01:06:51,520 --> 01:06:53,920
Speaker 9: mean the private equity industry in China exists, but it's

1279
01:06:53,920 --> 01:06:56,720
Speaker 9: not demanding you lever up to get a fifteen percent

1280
01:06:56,920 --> 01:07:01,760
Speaker 9: internal rate of return. It exists to provide a bit

1281
01:07:01,800 --> 01:07:04,600
Speaker 9: of a veneer of private capital for strategy investments and

1282
01:07:04,600 --> 01:07:09,600
Speaker 9: strategic sectors. There's a lot of patient capital that has

1283
01:07:09,640 --> 01:07:13,960
Speaker 9: gone in to sectors that are quite capital intensive and

1284
01:07:14,000 --> 01:07:17,040
Speaker 9: that are willing to accept high risk and low rates

1285
01:07:17,040 --> 01:07:21,160
Speaker 9: of return in part because it is state capital. And

1286
01:07:21,280 --> 01:07:25,840
Speaker 9: as a result, in those sectors where this internal competitive

1287
01:07:25,840 --> 01:07:32,520
Speaker 9: hothouse generates globally competitive products, production migrates to China. So

1288
01:07:32,600 --> 01:07:35,800
Speaker 9: that is the trend that was famously exhibited in the

1289
01:07:35,840 --> 01:07:39,960
Speaker 9: solar industry. Joe loves excavators. It's a slightly different story,

1290
01:07:41,120 --> 01:07:43,240
Speaker 9: but you know, twenty years ago China was importing a

1291
01:07:43,280 --> 01:07:47,280
Speaker 9: lot of excavators actually from the United States. Then Caterpillar

1292
01:07:47,320 --> 01:07:49,320
Speaker 9: sets up shop in China. Then a bunch of Chinese

1293
01:07:49,320 --> 01:07:52,720
Speaker 9: companies with state capital backing them, they're not all state owned,

1294
01:07:53,160 --> 01:07:56,480
Speaker 9: get into the excavator business. Then Chinese demand for excavator

1295
01:07:56,560 --> 01:08:01,160
Speaker 9: goes ballistic. With the property market, the property market tanks

1296
01:08:01,280 --> 01:08:07,040
Speaker 9: and guess who's exporting excavators to the world. I know so,

1297
01:08:07,160 --> 01:08:10,040
Speaker 9: and obviously everyone's petrified that this is the same pattern

1298
01:08:10,040 --> 01:08:14,960
Speaker 9: will replicate itself in electric cars and potentially legacy semiconductors

1299
01:08:15,200 --> 01:08:18,400
Speaker 9: and potentially cutting edge chips. But that's a little there's

1300
01:08:18,400 --> 01:08:20,080
Speaker 9: a little tech war going on to something.

1301
01:08:20,680 --> 01:08:24,680
Speaker 4: If Trump wins tomorrow, Look, it seems very plausible that

1302
01:08:24,760 --> 01:08:27,960
Speaker 4: we could get some sort of radically different approach to everything,

1303
01:08:28,000 --> 01:08:29,960
Speaker 4: certainly on the trade front. So let's just sort of

1304
01:08:30,000 --> 01:08:32,720
Speaker 4: accept that that, you know, again, per the models and

1305
01:08:32,760 --> 01:08:37,960
Speaker 4: the aggregators of fifty percent chance, if Harris wins, as

1306
01:08:38,000 --> 01:08:41,280
Speaker 4: you see it, what are the priorities when looking at

1307
01:08:41,479 --> 01:08:45,400
Speaker 4: unhealthy globalization? Not like necessarily what she's thinking, but from

1308
01:08:45,400 --> 01:08:50,320
Speaker 4: your perspective, what are the priorities towards addressing this unhealthy

1309
01:08:50,400 --> 01:08:52,120
Speaker 4: version of globalization that you describe.

1310
01:08:53,640 --> 01:08:59,479
Speaker 9: Looks start well, I would start to some degree with

1311
01:09:00,040 --> 01:09:02,400
Speaker 9: some of the points that Secretary Yellen and Layale Brain

1312
01:09:02,439 --> 01:09:07,560
Speaker 9: would have made about China's own unbalanced economy. And fundamentally,

1313
01:09:07,600 --> 01:09:09,559
Speaker 9: the US has, in my view, and interest in a

1314
01:09:09,560 --> 01:09:12,559
Speaker 9: more balanced Chinese economy, and we have an interest in

1315
01:09:12,640 --> 01:09:15,160
Speaker 9: convincing our allies and partners who also join us and

1316
01:09:15,160 --> 01:09:18,120
Speaker 9: putting pressure to get a more balanced Chinese economy. That's

1317
01:09:18,160 --> 01:09:22,200
Speaker 9: a long, hard slog. It depends a bit on choices

1318
01:09:22,400 --> 01:09:27,120
Speaker 9: China makes so one interesting example least I find it interesting.

1319
01:09:27,120 --> 01:09:30,080
Speaker 9: You know, Trump talks a lot about replacing the income

1320
01:09:30,160 --> 01:09:32,920
Speaker 9: tax with tariffs. That's been one of his ideas. It

1321
01:09:32,960 --> 01:09:34,720
Speaker 9: is unclear if he's actually gonna do it, but it's

1322
01:09:34,720 --> 01:09:41,599
Speaker 9: an idea. China currently collects more revenue from tariffs than

1323
01:09:41,640 --> 01:09:44,240
Speaker 9: from its personal income tax. It already has achieved this,

1324
01:09:45,080 --> 01:09:48,280
Speaker 9: partially because it still has somewhat significant tariffs, and partially

1325
01:09:48,280 --> 01:09:50,639
Speaker 9: because it only collects one percent of GDP and personal

1326
01:09:50,640 --> 01:09:52,760
Speaker 9: income tax, which is a very low number. We collect eight,

1327
01:09:53,400 --> 01:09:57,320
Speaker 9: so that to me is necessary. It's a part of

1328
01:09:57,360 --> 01:10:01,680
Speaker 9: the broader policy package that generates more balanced Chinese economy.

1329
01:10:01,960 --> 01:10:04,599
Speaker 9: But it is not something that the US Congress can change.

1330
01:10:06,120 --> 01:10:09,599
Speaker 9: So the other component for addressing unhealthy globalization is something

1331
01:10:09,640 --> 01:10:12,160
Speaker 9: that the US Congress can change, which is the US

1332
01:10:12,200 --> 01:10:16,160
Speaker 9: tax law. So my immediate priority, if I were given

1333
01:10:16,200 --> 01:10:20,040
Speaker 9: advice to, hopefully President Harris, would be Look, there's a

1334
01:10:20,040 --> 01:10:25,000
Speaker 9: budget negotiation Washington, DC will be consumed with the expiration

1335
01:10:25,120 --> 01:10:28,960
Speaker 9: of the tax cuts. Twenty twenty five is a fiscal year.

1336
01:10:29,400 --> 01:10:31,519
Speaker 9: It is a year which is set up in DC

1337
01:10:32,120 --> 01:10:36,920
Speaker 9: to debate the structure of taxation, and Republicans, and this

1338
01:10:36,960 --> 01:10:40,240
Speaker 9: is conventional wisdom, have an incentive to come to the

1339
01:10:40,280 --> 01:10:44,040
Speaker 9: table because if nothing happens, we have a cliff and

1340
01:10:44,320 --> 01:10:48,400
Speaker 9: all of Trump's personal income tax cuts expire, Republicans don't

1341
01:10:48,439 --> 01:10:51,880
Speaker 9: go to Washington to raise people's tax so they have

1342
01:10:51,960 --> 01:10:55,280
Speaker 9: an incentive to bargain. And my hope would be as

1343
01:10:55,360 --> 01:10:59,519
Speaker 9: part of that bargain, some of the remaining incentives in

1344
01:10:59,560 --> 01:11:04,080
Speaker 9: the corporate tax code that have clearly encouraged or not

1345
01:11:05,000 --> 01:11:08,920
Speaker 9: discourage the migration of intellectual property and production outside the

1346
01:11:09,000 --> 01:11:12,680
Speaker 9: United States get addressed. That'd be where I'd start. I

1347
01:11:12,720 --> 01:11:16,240
Speaker 9: also think one of the tensions, you know, one of

1348
01:11:16,240 --> 01:11:20,120
Speaker 9: the tensions in trades Trump's trade policy was that bilateral

1349
01:11:20,120 --> 01:11:22,800
Speaker 9: tariffs are way less effective than he thinks. You can

1350
01:11:22,800 --> 01:11:25,639
Speaker 9: get around them really easily. You put you know, ninety

1351
01:11:25,640 --> 01:11:28,759
Speaker 9: five percent Chinese content, a few screws in Southeast Asia,

1352
01:11:28,800 --> 01:11:32,880
Speaker 9: you go to a zero tariff. Right, It's trivial to

1353
01:11:32,880 --> 01:11:35,360
Speaker 9: get around with a little bit of work. So bilateral

1354
01:11:35,439 --> 01:11:38,600
Speaker 9: tariffs don't really work, but Trump loves them. One of

1355
01:11:38,640 --> 01:11:44,240
Speaker 9: the tensions in Biden administration views on trade, again widely accepted,

1356
01:11:44,680 --> 01:11:47,200
Speaker 9: is that the Biden administration talked a big game about

1357
01:11:47,280 --> 01:11:51,680
Speaker 9: friendshoring working with allies, and then you know, thanks to

1358
01:11:51,960 --> 01:11:58,760
Speaker 9: Joe Manchin, your friend, very important US Senator, Thanks to

1359
01:11:58,800 --> 01:12:01,800
Speaker 9: Joe Mansion, we have an inflation reduction Act, and thanks

1360
01:12:01,800 --> 01:12:04,439
Speaker 9: to Joe Manchin, that inflation Reduction Act didn't treat our

1361
01:12:04,479 --> 01:12:07,960
Speaker 9: friends very nicely. So I think there's a lot to

1362
01:12:08,080 --> 01:12:12,560
Speaker 9: do to kind of harmonize our industrial policies with our allies,

1363
01:12:13,080 --> 01:12:15,760
Speaker 9: and they have to make some changes too. I think

1364
01:12:15,760 --> 01:12:21,080
Speaker 9: the Europeans are ridiculously obsessed with following a super strict

1365
01:12:21,080 --> 01:12:24,519
Speaker 9: interpretation of what the WTO allows, which means that they

1366
01:12:24,560 --> 01:12:29,679
Speaker 9: won't do buy Europe on their EV subsidies inside Europe,

1367
01:12:30,320 --> 01:12:33,040
Speaker 9: even though China clearly did buy China on its EV

1368
01:12:33,160 --> 01:12:36,559
Speaker 9: subsidies inside China, they just didn't write it into the law.

1369
01:12:36,600 --> 01:12:40,200
Speaker 9: They just never qualified a foreign made car, actually initially

1370
01:12:40,240 --> 01:12:44,320
Speaker 9: never qualified a battery made in China by a foreign company.

1371
01:12:44,400 --> 01:12:48,160
Speaker 9: That only happened after the Chinese companies which now dominate

1372
01:12:48,200 --> 01:12:51,840
Speaker 9: global Batteri's got a good foothold. China has been super restrictive,

1373
01:12:52,320 --> 01:12:55,439
Speaker 9: and I think Europe should be symmetric. Do a kind

1374
01:12:55,479 --> 01:12:58,760
Speaker 9: of buy Europe deal and My idea is that like, hey,

1375
01:12:58,800 --> 01:13:02,200
Speaker 9: we have buy us Europe, we will You know, this

1376
01:13:02,280 --> 01:13:06,040
Speaker 9: is what I learned at USCR. You can deem European

1377
01:13:06,200 --> 01:13:10,240
Speaker 9: or allied goods to be American for purposes of qualifying

1378
01:13:10,280 --> 01:13:12,920
Speaker 9: for US subsidies. And we would offer to do that

1379
01:13:13,400 --> 01:13:17,640
Speaker 9: if Europe would deem American goods to be European for

1380
01:13:17,760 --> 01:13:21,960
Speaker 9: qualifying for European subsidies. So we kind of each create

1381
01:13:22,120 --> 01:13:25,600
Speaker 9: an open market towards each other while being pretty restrictive

1382
01:13:25,600 --> 01:13:28,400
Speaker 9: towards China. So those are I think, to me, the

1383
01:13:28,439 --> 01:13:30,560
Speaker 9: cutting edge of policy in the Harris administration.

1384
01:13:31,080 --> 01:13:34,559
Speaker 2: Would you be open to a potential position in a

1385
01:13:34,600 --> 01:13:35,600
Speaker 2: Harris administration?

1386
01:13:37,720 --> 01:13:41,240
Speaker 9: I had a suspicion, you might ask, I have never

1387
01:13:41,320 --> 01:13:51,560
Speaker 9: turned down an opportunity to serve my country.

1388
01:13:57,360 --> 01:14:00,240
Speaker 2: So that was our live recording of the podcast at

1389
01:14:00,280 --> 01:14:04,080
Speaker 2: Caveat in New York. I can't believe after all that

1390
01:14:04,080 --> 01:14:05,920
Speaker 2: that it's actually election day.

1391
01:14:05,960 --> 01:14:08,400
Speaker 4: Now, Wait, did we find out last night who's going

1392
01:14:08,439 --> 01:14:08,680
Speaker 4: to win?

1393
01:14:08,720 --> 01:14:09,880
Speaker 3: I forget did anyone?

1394
01:14:09,920 --> 01:14:12,320
Speaker 4: I think that's the one question we forgot to ask.

1395
01:14:12,400 --> 01:14:14,120
Speaker 4: We should have put.

1396
01:14:13,920 --> 01:14:17,479
Speaker 2: Everyone on the spot. Yeah maybe not okay, but we

1397
01:14:17,600 --> 01:14:19,720
Speaker 2: hope if you came to the show that you enjoyed it.

1398
01:14:19,800 --> 01:14:22,240
Speaker 2: We are hoping to do more of these events in

1399
01:14:22,280 --> 01:14:25,040
Speaker 2: the future, so if you liked it, please let us know.

1400
01:14:25,600 --> 01:14:28,400
Speaker 2: And in the meantime, a big thank you to everyone

1401
01:14:28,400 --> 01:14:33,280
Speaker 2: who worked to make this possible, notably Carmen Rodriguez, our producer,

1402
01:14:33,400 --> 01:14:36,240
Speaker 2: and Kate Seaberry at the Bloomberg Events team, as well

1403
01:14:36,280 --> 01:14:38,120
Speaker 2: as the entire crew at Caveat.

1404
01:14:38,240 --> 01:14:40,719
Speaker 4: Thank you so much, and again, we'll do it again

1405
01:14:40,720 --> 01:14:43,360
Speaker 4: in four years, but all the things in the meantime,

1406
01:14:43,479 --> 01:14:44,200
Speaker 4: shall we leave it there?

1407
01:14:44,280 --> 01:14:45,040
Speaker 3: Let's leave it there.

1408
01:14:45,400 --> 01:14:47,839
Speaker 2: This has been another episode of the All Thoughts podcast.

1409
01:14:47,920 --> 01:14:50,719
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway.

1410
01:14:51,120 --> 01:14:54,000
Speaker 4: I'm Jill Wassenthal. You can follow me at the Stalwart.

1411
01:14:54,200 --> 01:14:56,040
Speaker 4: Follow all of the guests that we had last night.

1412
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1413
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Speaker 4: Schneider He's at Jordan sch NYC. Follow Zvimashwitz He's at

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Speaker 4: the v Follow Neil Detta at renmac Llc. Follow Scanda

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Speaker 4: Emerneth at Irving Swisher, and follow Brad Setzer at Brad

1416
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Speaker 4: Underscore Setzer. Follow our producers Kerman Rodriguez at Kerman Erman

1417
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Speaker 4: dash Ol Bennett at dashbot and Klee Brooks at Kale Brooks.

1418
01:15:21,880 --> 01:15:24,400
Speaker 4: Thank you to our producer Moses Ondam. For more odd

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Speaker 4: Laws content, go to Bloomberg dot com slash od lots,

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Speaker 4: election twenty four to seven, in our discord discord dot

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