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Speaker 1: Hey, guys, ready or not, twenty twenty four is here

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Speaker 1: and we here at breaking points, are already thinking of

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Speaker 1: ways we can up our game for this critical election.

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Speaker 2: We rely on our premium subs to expand coverage, upgrade

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Speaker 2: the studio ad staff give you, guys, the best independent

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Speaker 2: coverage that is possible. If you like what we're all about,

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Speaker 2: it just means the absolute world to have your support.

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Speaker 2: But enough with that, let's get to the show. Good morning, everybody,

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Speaker 2: Happy Monday. We have an amazing show for everybody today.

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Speaker 2: What do we have personal?

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Speaker 1: Indeed, we do many interesting things happening this morning and

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Speaker 1: this week. So we got to bring you some of

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Speaker 1: this Trump interview with the All In podcast folks, completely

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Speaker 1: changing tune on immigration to please his new donors.

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Speaker 3: It is incredible. I love it.

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Speaker 1: Sager hates it. So little reversal there and be interesting

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Speaker 1: to get into that one. Meanwhile, he says that he

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Speaker 1: has picked his vice presidential nominee, so and he also

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Speaker 1: says that person will be at the debate, So we've

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Speaker 1: got lots of speculation there. Commerce and Rocana is going

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Speaker 1: to be in studio to talk about why he will

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Speaker 1: not be at Benjamin and Yahoo's speech here to Congress

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Speaker 1: a lot we want to ask him about with regards

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Speaker 1: to that. We also have some other updates with regard

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Speaker 1: to Israel, that massive Lebanon war against Hezbola looking more

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Speaker 1: and more likely in the US, basically giving a green

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Speaker 1: light for that. We also had an uptick in deadly

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Speaker 1: strikes in the Gaza strip over the weekend. Meanwhile, we're

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Speaker 1: taking a look at the economics of various generations.

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Speaker 3: Looks like gen Z even though millennials.

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Speaker 1: Graduated into horrible economic crisis, it actually looks like gen

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Speaker 1: Z has it even worse than millennials did when we

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Speaker 1: were young and coming out of college.

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Speaker 3: So we'll take a look at those numbers.

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Speaker 1: Sager has a great look at Saudi involvement in nine

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Speaker 1: to eleven. A great friends there comes, of course, as

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Speaker 1: we're considering this big defense path so important context. And

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Speaker 1: we also have New York Times calmnists and author Peter

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Speaker 1: Goodman who is asking whether global trade was a mistake

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Speaker 1: in a new book that I took a look at it.

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Speaker 1: It's an excellent book. I really recommend its out how

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Speaker 1: the supply chain went completely haywire during COVID, Getting down

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Speaker 1: to the granular specifics of you know, trucking and ports

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Speaker 1: and shipping and all of that. So very excited to

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Speaker 1: talk to him as well. Before we get to any

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Speaker 1: of that, though, Sagar. This week is debate week.

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Speaker 2: That's right, kind of crazy debate night, the earliest presidential

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Speaker 2: debate in modern American history. We'll have live coverage here

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Speaker 2: at the desk with all of the crew. We're gonna

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Speaker 2: have a special section for our premium subscribers. They're going

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Speaker 2: to be able to ask questions during that debate. So

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Speaker 2: go ahead and sign up if you want to get

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Speaker 2: in on that Breakingpoints dot Com. We're really excited. We've

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Speaker 2: got all the coverage plans, special graphics, et cetera. So

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Speaker 2: just yeah, programming update. Then on Thursday, Thursday morning, we're

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Speaker 2: not going to have our normal show. We will go

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Speaker 2: live what is it around eight o'clock something like that.

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Speaker 2: We'll keep everybody updating and we'll go all the way

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Speaker 2: through after the night, we'll bring everybody some analysis and

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Speaker 2: all that.

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Speaker 3: So staying up late for you guys, Yeah, that's right,

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Speaker 3: major sacrifice.

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Speaker 2: It starts at nine pm, right, which is already an

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Speaker 2: attack on both of our lifestyles. Boddy that's that's the

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Speaker 2: sacrifice that we do for you. All right, So let's

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Speaker 2: go ahead with that and get to the show. As

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Speaker 2: Crystal alluded to, Trump sat for the All In podcast

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Speaker 2: popular technology podcast for those not familiar, hosted by for

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Speaker 2: venture capitalists.

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Speaker 3: And two of them are donors to him, by the way,

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Speaker 3: we said, no.

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Speaker 2: Two of them. Well, I don't know about I think Tamath. Yeah,

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Speaker 2: you're right, Tamath is a donor. David Sax certainly. I've

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Speaker 2: had David here on the program. You can watch that

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Speaker 2: interview if you're interested. All of them are very wealthy,

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Speaker 2: near billionaire status, if not billionaires literally themselves. Here is

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Speaker 2: a question from Jason Calcanus. Jason is kind of the

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Speaker 2: center left host of the All In Podcast, and he

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Speaker 2: asked Trump about high skilled immigration visas being stapled to

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Speaker 2: green cars. This has been a major priority for tech

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Speaker 2: oligarchs for more than a decade now at this point.

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Speaker 2: And just listen to how Trump answered the question. Let's

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Speaker 2: take a listen.

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Speaker 4: We need high skilled workers in this country. Yes, we

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Speaker 4: need to recruit the best and brightest from the world.

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Speaker 4: Every time we get somebody super intelligent from India or Europe,

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Speaker 4: any country three are immigrants, sir, Yeah, and three or

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Speaker 4: the four here are immigrants, the ones without the tize

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Speaker 4: and we can get these great people into our country.

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Speaker 4: And that's a loss for our adversaries and our competitors,

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Speaker 4: and it's a game for us. But I've never heard

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Speaker 4: you talk about this. Can you please promise us you

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Speaker 4: will give us more ability to import the best and

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Speaker 4: brightest around the world to a mirror.

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Speaker 5: I do promise, but I happen to agree. That's why

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Speaker 5: I promise, Otherwise I wouldn't promise. Let me just tell

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Speaker 5: you that it's so sad when we lose people from Harvard,

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Speaker 5: mit from the greatest schools and lesser schools that are

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Speaker 5: phenomenal schools. Also, what I want to do and what

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Speaker 5: I will do, is you graduate from a college. I

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Speaker 5: think you should get automatically as part of your diploma,

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Speaker 5: a green card to be able to stay in this country.

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Speaker 5: And that includes junior colleges too. Anybody graduates from a college,

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Speaker 5: you go in there for two years or four years.

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Speaker 5: If you graduate or you get a doctorate degree from

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Speaker 5: a college, you should be able to stay in this country.

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Speaker 5: And you know more stories than I do, But I

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Speaker 5: know of stories where people graduated from a top college

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Speaker 5: or from a college and they desperately wanted to stay here.

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Speaker 5: They had a plan for a company, a concept, and

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Speaker 5: they can't. They go back to India, they go back

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Speaker 5: to China. They do the same basic company in those

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Speaker 5: places and they become multi billionaires, employing thousands and thousands

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Speaker 5: of people. And it could have been done here. It

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Speaker 5: was such a big deal. Somebody graduates at the top

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Speaker 5: of the last they can't even make a deal with

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Speaker 5: a company because they don't think they're going to be

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Speaker 5: able to stay in the country.

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Speaker 6: That is going to end on day one.

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Speaker 2: That's going to end on day one. Let's just say

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Speaker 2: this is probably as big of a flip flop as

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Speaker 2: it gets there from Donald Trump. Look personally, I think

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Speaker 2: this policy incredible, idiotic, and stupid. Basically, we just continue

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Speaker 2: to turn universities into foreign visa farms. There's a lot

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Speaker 2: of reasons why we shouldn't go down that hill. That

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Speaker 2: being said, the most important part of this interview is

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Speaker 2: just to show everyone how Trump is very comfortable. I

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Speaker 2: think that's a kind way of saying it flip flopping

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Speaker 2: on previous held, long standing positions through his administration through

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Speaker 2: his advisors and others in exchange for basically campaign cash.

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Speaker 2: I mean, as crystal you said chum Off. Polyhopatilla and

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Speaker 2: David Sachs both hosted a Trump fundraiser in Silicon Valley

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Speaker 2: which raised big bucks, a lot of billionaires, A lot

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Speaker 2: of people who previously had not really entered the frey

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Speaker 2: in politics attended the fundraiser. This is just a preview

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Speaker 2: again into how Trump is conducting himself in this election.

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Speaker 2: And I want people to understand, like, whether you think

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Speaker 2: about the policy or not, Trump unambiguously was against his

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Speaker 2: policy back in twenty sixteen and in twenty twenty. The

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Speaker 2: reason he's changing his tune is this is the number

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Speaker 2: one priority for tech oligarchs. I have been involved in

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Speaker 2: these circles now for quite some times. There are entire

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Speaker 2: think tanks stood up here in Washington, specifically by the

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Speaker 2: technology industry to lobby for more H one B visas

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Speaker 2: and more of these student visa specifically because these are

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Speaker 2: the people who go to work for them. Yeah, that's

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Speaker 2: what they want. They want more. And look, let me

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Speaker 2: say also this, It's not that I'm against immigration. This

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Speaker 2: is not fair even for many of these people So

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Speaker 2: just to explain, in the H one B system, for example,

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Speaker 2: they're your sponsor. So like let's say Facebook sponsors you. Well,

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Speaker 2: if you get fired, you lose your visa. So what

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Speaker 2: does that mean? You really don't want to get fired.

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Speaker 2: It also means maybe you're going to take eighty five

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Speaker 2: percent less than an American citizen who can leave if

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Speaker 2: he wants, and everybody wins. Right, you get to get

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Speaker 2: paid less, you get a nice visa, you get to

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Speaker 2: stay here in San Mateo, and you get to buy

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Speaker 2: a house. It's cool. Same with these universities. You think

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Speaker 2: that these universities aren't going to just start charging one

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Speaker 2: hundred two hundred thousand dollars per year to every rich

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Speaker 2: kid from China and to India because they get automatic

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Speaker 2: green card. What does that mean again?

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Speaker 6: Oh?

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Speaker 2: US citizen, he's a problem, she's a problem. You gotta

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Speaker 2: Oh she can leave if she wants to. Oh you know,

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Speaker 2: Oh well what if she decides not to graduate or

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Speaker 2: something like that, they have you buy a chain. You're

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Speaker 2: like a slave. That's what a lot of these systems

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Speaker 2: eventually evolve into, not to mention just outright visa fraud.

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Speaker 2: So these are all things that you could go listen

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Speaker 2: to Stephen Miller, say, for example, but now you know,

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Speaker 2: because these tech people are putting money into his pockets.

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Speaker 2: Trump just like on several other issues either that he

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Speaker 2: doesn't care about or previously had flippedtopped on like TikTok.

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Speaker 2: If it's it's up for sale to the highest bidder.

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Speaker 2: That's why it's ridiculous.

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Speaker 3: I mean, I find it so entertaining because.

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Speaker 2: It's funny, like don't getting wrong, it's just.

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Speaker 3: So it's just such a shameless cash grab. It's incredible.

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Speaker 1: I really recommend you go and listen to the interview

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Speaker 1: we did with Matt Stoller, who was really he was

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Speaker 1: early to recognizing not just the different policies that Trump

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Speaker 1: has promoted, but he is His rhetoric is completely different

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Speaker 1: from twenty sixteen.

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Speaker 3: I mean, he.

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Speaker 1: Doesn't go after corporations at all. For those of you

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Speaker 1: who were all about the like bud Light boycott or whatever, Trump.

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Speaker 3: Got out there and was like, stop boycotting cud Like.

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Speaker 2: Guys are money. Yeah, that's right. The Anheuser family literally

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Speaker 2: cut them into check.

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Speaker 1: Even on something that's just like a core hot button

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Speaker 1: culture war issue, he took the side of the corporation.

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Speaker 3: It's incredible to me.

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Speaker 1: I mean personally, I support this policy, but you're one

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Speaker 1: hundred percent right, Zager. Just I support higher immigration levels.

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Speaker 1: So what will happen here is he goes even further

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Speaker 1: than Hillary Clinton did back in twenty sixteen because her program,

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Speaker 1: I think we have a five.

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Speaker 3: We can put up a five on the screen.

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Speaker 1: Hers was just critical with regards to STEM graduates. Trump says, no, no, no,

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Speaker 1: we want to staple the green card to all, including

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Speaker 1: junior colleges. So yeah, what would happen is, you know,

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Speaker 1: you'd have a lot of junior colleges or diploma mills

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Speaker 1: that set up like this is now your way to

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Speaker 1: get a green card, this is your way into the country. Again,

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Speaker 1: I fully support it because I support higher levels of immigration.

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Speaker 3: But it could not be more of a one and.

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Speaker 1: Eighty degree flip from where he has been and especially

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Speaker 1: the reason it's so funny because many flips on issues

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Speaker 1: all the time, He's like all over the map on

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Speaker 1: critical things like the Ukraine War and our policy vis

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Speaker 1: of e Israel, all kinds of things. He can be

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Speaker 1: all over the place, just depending on what audience he's

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Speaker 1: trying to please at the moment. But you know, the

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Speaker 1: assumption had always been there were maybe a few things

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Speaker 1: that he actually cared about. Immigration was at the top

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Speaker 1: of that list. This man doesn't care about anything. He's

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Speaker 1: decided the number one priority is getting the cash from

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Speaker 1: Wall Street, which he's.

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Speaker 3: Doing very successfully.

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Speaker 1: And we're gonna have some of the numbers there and

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Speaker 1: the big one that doesn't get as much attention as

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Speaker 1: Silicon Valley, and that is reflected certainly with this policy,

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Speaker 1: but also with his flip on say crypto, which is

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Speaker 1: another area where he's done a complete one eighty in

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Speaker 1: service of getting donors. And this is also we're going

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Speaker 1: to get to, you know, who he's thinking of for VP.

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Speaker 1: This is also why I think there's a chance that

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Speaker 1: Doug Bergram, former Microsoft executive, does end up as Trump's VP,

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Speaker 1: because what does he bring with him. He's you know,

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Speaker 1: no drama, he's sort of people say he looks like

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Speaker 1: George Washington. My daughter said he gets patriotic eagle. But anyway,

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Speaker 1: I could see Trump liking the look of him. But

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Speaker 1: Number one, he brings a lot of money and a

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Speaker 1: lot of Silicon Valley comfort to the table, and clearly

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Speaker 1: that's a thing that's important to tell.

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Speaker 3: It's amazing.

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Speaker 2: Yeah, Miss Bergham is himself a near billionaire. Crypto is

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Speaker 2: another good example. By the way, I support crypto, so like,

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Speaker 2: I'm fine with it, but like you just said, it's

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Speaker 2: one of those where it's like, dude, you're obviously doing

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Speaker 2: this for cash. Because Trump came out and this was

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Speaker 2: famous in the crypto bitcoin community, he was like, I'm

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Speaker 2: against bitcoin, this is bad. His administration actively lobbied against

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Speaker 2: Facebook Libra. If anybody wants to know, could go back

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Speaker 2: and look into that. I mean, he was a vocally

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Speaker 2: anti crypto, along with Steve Mnuschan, who worked in the government,

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Speaker 2: much through the chagrin of a lot of people in

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Speaker 2: the bitcoin world. Then just the other day, the Winkle

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Speaker 2: Vi who you may remember from the Social Network movie.

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Speaker 2: They're actually real, by the way, and they became fantastically

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Speaker 2: wealthy themselves because they were very early to bitcoin. They

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Speaker 2: opened their own exchange called Gemini. Well, both of the

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Speaker 2: winkle v endorsed Trump just like a couple of days ago,

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Speaker 2: openly because they're like, yeah, he supports bitcoin, I mean,

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Speaker 2: and so it's it's just naked. Biktok is a great example. Yeah,

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Speaker 2: I reckon. I so Jeff YaST you know, is American

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Speaker 2: billionaire's worth some twenty four billion dollars. I think he's

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Speaker 2: a mar Lago club member. He wasn't nearly as involved

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Speaker 2: back in twenty twenty. This time around he makes his

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Speaker 2: inroads to Trump. He's one of the largest single shareholders

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Speaker 2: in byte Dance, which is the Chinese holding company that

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Speaker 2: owns TikTok. A substantial portion of his own net worth

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Speaker 2: is up in byte Dance. So what does he do.

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Speaker 2: He donates huge amounts to the Trump campaign ingratiates himself,

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Speaker 2: and now all of a sudden, Trump is pro TikTok.

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Speaker 2: Now again, each of these policies, you can evaluate them

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Speaker 2: on their face, like crypto TikTok, immigration, whatever, that's fine,

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Speaker 2: But what are we doing here whenever it's so naked

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Speaker 2: and it's out in the open. So for all of those,

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Speaker 2: you know, like ultra pro Trump people, I just think,

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Speaker 2: look at the very least he got to make your

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Speaker 2: peace with this and understand that whoever's got the cash

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Speaker 2: is actually who's going to win. Not all that different

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Speaker 2: last time around, but at least there was some rhetoric.

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Speaker 2: And this is the thing too.

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Speaker 1: He's dropped even the rhetorical allusions to any sort of

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Speaker 1: a different like populist Republican.

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Speaker 2: He tried to pull himself out more recently at a

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Speaker 2: faith and fam was like Freedom Coalition or whatever event

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Speaker 2: talking about He's like, we need some migrant UFC events.

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Speaker 2: Let's take a lesson Dana White.

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Speaker 5: Did anyone ever hear of Dana? He's a legendre UFC,

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Speaker 5: ultimate fighter, ultimate fighting, and he is He's a fantastic man.

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Speaker 5: I said, Dana, I have an idea. Why don't you

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Speaker 5: set up a migrant league of fighters and have your

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Speaker 5: regular league of fighters, and then you have the champion

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Speaker 5: of your league. These are the greatest fighters in the world,

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Speaker 5: fight the champion of the migrants.

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Speaker 2: I think the migrant.

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Speaker 5: Guy might win, that's how tough they are. He didn't

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Speaker 5: like that idea too much, but actually not the worst

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Speaker 5: idea I've ever had.

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Speaker 2: So it's like he's trying to pull himself out. He's

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Speaker 2: trying to get with the immigration hawks. And that's another

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Speaker 2: one where I had no respect for people whose major

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Speaker 2: issue is like immigration, for example. And then when Trump,

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Speaker 2: who is like their god king, you know, betrays them,

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Speaker 2: they don't say any thing, So shout out to you know,

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Speaker 2: there's a lot of real ones out there, people like

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Speaker 2: Ryan Gerdoski knows they really care about the issues. They're

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Speaker 2: actually consistent. They'll criticize people whenever they actually go against

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Speaker 2: the grave. But here you have Steve Bannon, who is

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Speaker 2: you know again, he's like the so called ideological godfather

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Speaker 2: Maga of Jacksonianism. He's like the major defender of the policy.

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Speaker 2: Just listen to the most milk toast criticism here of

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Speaker 2: Trump whenever he outrighted flip flops on this. Let's take

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Speaker 2: a listen.

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Speaker 7: The exit visa should be clipped to the to the

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Speaker 7: to the diploma, the exit visa. We can't make the

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Speaker 7: world okay, We can't keep the world on our shoulders

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Speaker 7: and keep spending money on all these forever wars in

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Speaker 7: this international apparatus, in this empire. We want the nations

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Speaker 7: of the earth to also make themselves great again. People

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Speaker 7: buy and large want to live back where they come

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Speaker 7: from and where their folks are and what their culture

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Speaker 7: and society is. Yes, let's take them in a selective basis,

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Speaker 7: trade them up, let them root for college football and

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Speaker 7: get all that. You know, you look at the college

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Speaker 7: football stands the diversity, it's fabulous. But then it's time

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Speaker 7: to go back home and make your country great again.

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Speaker 7: Work for your country and make it great again. That

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Speaker 7: is the way we go as as nations of the earth,

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Speaker 7: as nations of the earth, and we move together. We

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Speaker 7: can't suck it all in like Britain, and you can't

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Speaker 7: do that, then it's going to be these are gonna

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Speaker 7: be shells of each other.

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Speaker 2: Well what you know what word I didn't hear? You

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Speaker 2: know what word I didn't hear that entire time. Trump,

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Speaker 2: the guy who said the policy, this is what I'm

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Speaker 2: talking about. It's like if you this is if a

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Speaker 2: Democrat said this, if Mitt Romney said this, if Mike

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Speaker 2: Penn said this, it would be slaughter out in the open.

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Speaker 2: He wants to replace us, He wants to just.

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Speaker 3: A debate stage during the Republican primary.

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Speaker 2: The only difference is always have been like, yeah, that's

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Speaker 2: stupid either way. But these people, they have no integrity,

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Speaker 2: Like you know in general, they are just willing to

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Speaker 2: go along because they know if the clip goes viral,

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Speaker 2: then Trump will find out and they're going to be

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Speaker 2: out of as good graces and they'll stop being Maga warriors.

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Speaker 2: So there are very few out there who are being genuine,

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Speaker 2: you know, in their critics here. But the nakedness of it,

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Speaker 2: it's just too much. It's too much. And you you know,

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Speaker 2: we have this political story which just details you know,

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Speaker 2: so many key instances like this where Trump keeps flip

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Speaker 2: flopping his policy positions after meeting with rich people. For example,

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Speaker 2: the Alam podcast is what they start with. They point

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Speaker 2: to the TikTok ban, they point to the cryptocurrency. But

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Speaker 2: there have been other just cartoonish elements here with Trump,

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Speaker 2: for example, recently had a fundraiser. He's like, anybody who

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Speaker 2: donates a million dollars can come and take this microphone

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Speaker 2: right now and speak at my event. And they had

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Speaker 2: like three people do it. Yeah, three people just walked

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Speaker 2: up there like, yeah, I'm ranted about whatever. You know, Israel,

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Speaker 2: you know anything wants. Miriam Adelson cuts him one hundred

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Speaker 2: million dollar check. It's flying around Nicky Haley in her

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Speaker 2: Gulf Sands jet and what is it? What does Uh

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Speaker 2: Trump say on the policy? He's like becoming even more

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Speaker 2: pro Israel and basically tacitly agreed that he will allow

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Speaker 2: israeally total control of the West Bank. He won't even

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Speaker 2: rhetorically push against it. Yea, So how is that not

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Speaker 2: foreign interference in our elections? That's right, all of these

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Speaker 2: cases buy in our foreign policy. Starting their people is

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Speaker 2: basically for sale to the highest bidder of whatever they want.

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Speaker 2: And again, you can have policy which you agree with

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Speaker 2: disagree with, but that's not how you know, at least allegedly,

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Speaker 2: this entire drain the swamp ridder from twenty sixteen. What happened. Man,

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Speaker 2: It's gone. It's just totally gone.

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Speaker 1: Absolutely gone. But you can't say it's not paying off.

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Speaker 1: Of course, a six up on the screen. You know,

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Speaker 1: Biden had a big cash advantage and has been able

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Speaker 1: to run a bunch of ads and you know, sort

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Speaker 1: of get started early. Apparently they used to have a

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Speaker 1: one hundred million dollar cash advantage. But Trump has outraised

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Speaker 1: Biden by eighty one million dollars in the last two months.

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Speaker 1: And now the gap between the two of them when

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Speaker 1: you look all together at both the direct campaign contributions

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Speaker 1: and the outside groups, which are just important in terms

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Speaker 1: of fundraising, Trump.

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Speaker 3: Has effectively closed the gap.

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Speaker 1: So his shameless Wall Street and Silicon Valley and Miria

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Speaker 1: madleson cash grab definitely paying off. And I also want

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Speaker 1: to say there was also a huge fundraising surge in

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Speaker 1: smaller dollar contributions to Trump after he was found guilty.

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Speaker 1: So it's not all just because of the shameless cash grab.

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Speaker 1: It's also partly because of the cult of personality.

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Speaker 3: But there you go.

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Speaker 1: So it's it's working for him in terms of those goals,

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Speaker 1: and I think he rightly he sees this landscape. Who

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Speaker 1: he famously said, I could shoot someone on Fifth Avenue,

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Speaker 1: they still be It's the case he could shoot his

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Speaker 1: own original policy in the head on Fifth Avenue and

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Speaker 1: people would still oh, well if Trump, if Trump said,

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Speaker 1: it must be fine and all good.

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Speaker 2: Here's the question, how many of these boomers who are

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Speaker 2: going to he listened to the Steve Bannon podcast whatever,

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Speaker 2: it's war room, right, how are they even going to

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Speaker 2: know the Trump flip flop? If that's the way that

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Speaker 2: you milk toast criticize, They're not going to know same

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Speaker 2: on Fox News. It's like, are they really going to

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Speaker 2: cover this over on Fox for real? This is going

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Speaker 2: to be part of the Jesse Waters monologue, Like not

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Speaker 2: a chance. I'm waiting and I'm hoping that somebody will

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Speaker 2: actually have have some integrity on this issue. But you know,

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Speaker 2: I'm not delusional. And the more that we look at

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Speaker 2: all of the you know from this from the campaign

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Speaker 2: so far, is this really is a road to help

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Speaker 2: Because it's not just Trump, you know, who's holding big

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Speaker 2: dollar fundraisers. Biden is doing it as well. Biden on

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Speaker 2: these glitzy stages. He just had George Clooney and Julia Roberts.

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Speaker 2: The art of the mega campaign fundraise seems to be

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Speaker 2: more overt today than ever before.

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Speaker 1: True, right, there's not even a pretense around it. I mean,

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Speaker 1: the Democrats don't even pretend like they're going to do

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Speaker 1: campaign finance re forma right.

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Speaker 2: They just rent out what is it what they have

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Speaker 2: that New York City place and they have three presidents

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Speaker 2: up there and you get to pay fifteen hundred dollars

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Speaker 2: or whatever a take and they raise twenty five million

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Speaker 2: bucks in a single night. Why should they even tweet

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Speaker 2: or hit your campaign in box. Sure they're gonna make

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Speaker 2: some money, but the vast majority of the dollars have

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Speaker 2: been coming in late for the Biden people. For him,

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Speaker 2: he doesn't want to go out there actively campaign. He

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Speaker 2: just wants to go hit a room full of rich folks.

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Speaker 2: Read Hoffman for example, another Silicon Valley billionaire. He's hold

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Speaker 2: raising huge fundraisers for the Biden campaign. And I mean,

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Speaker 2: don't get me wrong, by the way, eighty five percent

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Speaker 2: or whatever a venture capitalists are still donating Democrat. It's

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Speaker 2: just that there's also super ultra wealthy ones on the

433
00:20:08,640 --> 00:20:11,959
Speaker 2: right now as well. So in both cases, everybody is

434
00:20:12,000 --> 00:20:13,800
Speaker 2: just getting in on the game, and it's more of

435
00:20:13,840 --> 00:20:16,080
Speaker 2: a club of elite's at the top than ever before.

436
00:20:16,160 --> 00:20:18,399
Speaker 1: Really, So I'm not even sure that's true with the

437
00:20:18,640 --> 00:20:20,240
Speaker 1: regard to the venture capitalist anymore.

438
00:20:20,240 --> 00:20:21,680
Speaker 3: If you look at Wall Street overall.

439
00:20:21,720 --> 00:20:24,600
Speaker 1: So Obama was the first Democrat that like won the

440
00:20:24,600 --> 00:20:29,479
Speaker 1: Wall Street donation bid war right, he was able to

441
00:20:29,520 --> 00:20:31,560
Speaker 1: outfunder him, and this was touted is like a positive

442
00:20:31,600 --> 00:20:34,520
Speaker 1: thing at the time. By the way, anyway, since Obama,

443
00:20:34,880 --> 00:20:39,399
Speaker 1: obviously with Hillary than Biden last time around, the Democrats

444
00:20:39,400 --> 00:20:42,880
Speaker 1: have been sucking up more Wall Street cash than Republicans. Yes,

445
00:20:43,040 --> 00:20:47,000
Speaker 1: right now, Trump is ahead of Biden, and it's the

446
00:20:47,040 --> 00:20:50,040
Speaker 1: first time again since before since back during George W.

447
00:20:50,119 --> 00:20:50,639
Speaker 2: Bush.

448
00:20:50,880 --> 00:20:55,040
Speaker 1: So he has flipped that dynamic very successfully, and it's

449
00:20:55,040 --> 00:20:57,160
Speaker 1: not only through these things. And we also covered how

450
00:20:57,400 --> 00:21:00,320
Speaker 1: you know, he's just very naked. He'll go into room

451
00:21:00,359 --> 00:21:03,360
Speaker 1: full of billionaires or you know, very high net worth

452
00:21:03,359 --> 00:21:05,359
Speaker 1: individuals and tell them, listen, you got to give to

453
00:21:05,359 --> 00:21:06,920
Speaker 1: me because I'm going to give your tax cut, like

454
00:21:06,960 --> 00:21:09,199
Speaker 1: I'm going to make sure that there's a return on

455
00:21:09,320 --> 00:21:13,040
Speaker 1: investment in that cash. He went to oil executives and

456
00:21:13,119 --> 00:21:14,960
Speaker 1: told them, hey, you need to raise a billion dollars

457
00:21:14,960 --> 00:21:16,760
Speaker 1: for me, because I'm going to make you lots of money,

458
00:21:17,040 --> 00:21:19,280
Speaker 1: and I'm going to roll back any sort of regulation

459
00:21:19,480 --> 00:21:21,840
Speaker 1: I'm going to take. I'm going to completely unleash it.

460
00:21:21,960 --> 00:21:23,439
Speaker 1: Like you do whatever you want. You're going to make

461
00:21:23,480 --> 00:21:24,760
Speaker 1: a ton of money. It's going to be worth it

462
00:21:24,800 --> 00:21:29,560
Speaker 1: for you. So there's a culture of just brazenness that

463
00:21:29,680 --> 00:21:33,159
Speaker 1: I think has really developed. I mean, you know, Trump

464
00:21:33,200 --> 00:21:35,800
Speaker 1: always takes things to the next level. But the Supreme

465
00:21:35,800 --> 00:21:39,240
Speaker 1: Court is basically said that unless you're literally like Bob Menendez,

466
00:21:39,280 --> 00:21:42,919
Speaker 1: taking gold bars in exchange for explicit business promises, then

467
00:21:42,920 --> 00:21:45,359
Speaker 1: it's all fine and good. So this is the hell

468
00:21:45,760 --> 00:21:48,639
Speaker 1: that they have unleashed, where foreign policy is up for

469
00:21:48,680 --> 00:21:51,080
Speaker 1: sale to the highest bidder, tax policy up for sale

470
00:21:51,119 --> 00:21:53,560
Speaker 1: of the highest bidder, immigration policy up for sale of

471
00:21:53,600 --> 00:21:56,320
Speaker 1: the highest bidder. The funny thing too about the immigration policy,

472
00:21:56,359 --> 00:21:59,040
Speaker 1: which again I support because I support higher immigration levels,

473
00:21:59,040 --> 00:22:00,680
Speaker 1: and I do think that what Trump is talking about

474
00:22:00,680 --> 00:22:04,080
Speaker 1: here would open a massive pathway to a lot more immigrants.

475
00:22:04,080 --> 00:22:05,800
Speaker 1: And I do also think he makes a good point

476
00:22:06,040 --> 00:22:08,719
Speaker 1: about no. Part of the reason that this country has

477
00:22:08,720 --> 00:22:10,600
Speaker 1: been as strong and successful as it is is because

478
00:22:10,600 --> 00:22:13,200
Speaker 1: we have been a magnet for the brightest minds around

479
00:22:13,240 --> 00:22:16,240
Speaker 1: the world through our university and education system. And to

480
00:22:16,560 --> 00:22:19,159
Speaker 1: then say, okay, well, now that we've trained you up,

481
00:22:19,200 --> 00:22:21,720
Speaker 1: you have to leave, I think is counterproductive in the

482
00:22:21,880 --> 00:22:24,560
Speaker 1: terms of the national interests. But you know, the funny

483
00:22:24,560 --> 00:22:27,000
Speaker 1: thing about it is to your point, soar if Biden

484
00:22:27,040 --> 00:22:31,399
Speaker 1: proposed this, not a fucking chance, not a chance, not

485
00:22:31,560 --> 00:22:34,480
Speaker 1: a chance would this be allowed through Trump could actually

486
00:22:34,480 --> 00:22:37,360
Speaker 1: get it done, though, because you see the slavishness of

487
00:22:37,400 --> 00:22:41,159
Speaker 1: the level of devotion to him, the cult like you know,

488
00:22:41,280 --> 00:22:45,440
Speaker 1: approach to anything that he utters. So if he actually

489
00:22:45,480 --> 00:22:47,119
Speaker 1: I don't know if he will, I don't believe a

490
00:22:47,160 --> 00:22:49,560
Speaker 1: word this man says. Who knows what he actually would

491
00:22:49,600 --> 00:22:52,440
Speaker 1: do in office? But if he actually decided he wanted

492
00:22:52,480 --> 00:22:55,800
Speaker 1: to deliver for David Sachs and about Paula Halpatilla and

493
00:22:55,840 --> 00:22:58,080
Speaker 1: the other his other Silicon Valley buddies. And he's got

494
00:22:58,119 --> 00:23:00,280
Speaker 1: Doug Bergham on the ticket, then I think there is

495
00:23:00,320 --> 00:23:00,960
Speaker 1: a good chance.

496
00:23:00,800 --> 00:23:01,320
Speaker 3: That he does it.

497
00:23:01,359 --> 00:23:04,600
Speaker 1: And he could actually do it where Biden the Democrats couldn't.

498
00:23:04,760 --> 00:23:06,720
Speaker 1: It's like the Nixon goes to China thing. It's like,

499
00:23:06,800 --> 00:23:09,360
Speaker 1: you know, Clinton being the one who could actually end welfare.

500
00:23:09,680 --> 00:23:11,800
Speaker 1: When you go against the grain of what your party

501
00:23:11,800 --> 00:23:14,720
Speaker 1: typically stands for, you sort of force your own partisans

502
00:23:14,760 --> 00:23:16,919
Speaker 1: into line. The other party may already agree with you,

503
00:23:17,000 --> 00:23:20,040
Speaker 1: and then there you go. So the irony here is

504
00:23:20,040 --> 00:23:21,680
Speaker 1: that if anyone was going to get this done, it

505
00:23:21,680 --> 00:23:22,480
Speaker 1: would be Donald Trump.

506
00:23:22,520 --> 00:23:24,560
Speaker 2: Yeah, yeah, you're probably right, maybe he will do I

507
00:23:24,600 --> 00:23:26,600
Speaker 2: will just say, look, we already have an O one visa.

508
00:23:26,640 --> 00:23:28,760
Speaker 2: It's called a talent visa, and if you're allegedly so great,

509
00:23:28,760 --> 00:23:30,760
Speaker 2: you can apply for it. Currently has a ninety seven

510
00:23:30,800 --> 00:23:33,840
Speaker 2: percent acceptance rate. Just so people know, it's not like

511
00:23:33,880 --> 00:23:36,439
Speaker 2: people are hard up right now for talent visas to

512
00:23:36,560 --> 00:23:41,760
Speaker 2: the country. Let's go to the next part you alluded to,

513
00:23:41,800 --> 00:23:44,680
Speaker 2: the vice president. Trump says he has picked his vice president.

514
00:23:44,760 --> 00:23:46,840
Speaker 2: Let's go and put that up there on the screen.

515
00:23:47,200 --> 00:23:50,480
Speaker 2: Donald Trump told NBC News, quote, in my mind, yes,

516
00:23:50,800 --> 00:23:54,360
Speaker 2: I picked the person that will quote most likely then

517
00:23:54,480 --> 00:23:57,400
Speaker 2: be at the Thursday debate against Joe Biden. He says,

518
00:23:57,440 --> 00:23:59,320
Speaker 2: they will be there. I think we have a lot

519
00:23:59,359 --> 00:24:02,840
Speaker 2: of people come. So Trump said, nobody knows his choice yet.

520
00:24:03,080 --> 00:24:06,520
Speaker 2: Currently there are multiple people who are in contention. NBC

521
00:24:06,560 --> 00:24:10,240
Speaker 2: claims Doug Berghm, jd Vance, and Marco Rubio are quote,

522
00:24:10,280 --> 00:24:13,359
Speaker 2: the possible top contenders. I don't know how much I

523
00:24:13,359 --> 00:24:16,439
Speaker 2: would take that list necessarily to the bank. But Doug Bergham,

524
00:24:16,480 --> 00:24:19,239
Speaker 2: I don't think there's any chance is not near the

525
00:24:19,280 --> 00:24:21,800
Speaker 2: top of the list. He is blank slate. People can

526
00:24:21,800 --> 00:24:23,960
Speaker 2: go watch our interview with him, you know, if you're interested.

527
00:24:24,440 --> 00:24:27,200
Speaker 2: It doesn't look in terms of his political experience and

528
00:24:27,200 --> 00:24:29,399
Speaker 2: all that. Let's just be kind and say it's not

529
00:24:29,600 --> 00:24:33,159
Speaker 2: near the big leagues. But he has been making the

530
00:24:33,320 --> 00:24:37,040
Speaker 2: rounds on television and kind of slavishly selling himself as

531
00:24:37,080 --> 00:24:41,000
Speaker 2: a Trump defender. Here, for example, is a recent interview

532
00:24:41,040 --> 00:24:43,840
Speaker 2: just gave yesterday talking about the veepstakes. Let's take a.

533
00:24:43,800 --> 00:24:45,480
Speaker 8: List, but the real thing which we ought to be

534
00:24:45,480 --> 00:24:48,560
Speaker 8: talking about is Joe Biden's choice for VP, because as

535
00:24:48,560 --> 00:24:52,680
Speaker 8: you showed earlier in the show with Joe, with him

536
00:24:52,840 --> 00:24:55,919
Speaker 8: obviously failing right now in front of the world stage,

537
00:24:55,920 --> 00:24:58,880
Speaker 8: in the national stage, and then he picked four years ago,

538
00:24:58,960 --> 00:25:01,840
Speaker 8: someone who's got no busines experience, no operating experience.

539
00:25:02,119 --> 00:25:04,120
Speaker 6: Between Biden Harris, they've.

540
00:25:03,880 --> 00:25:06,520
Speaker 8: Never created a private sector job in their life. And

541
00:25:06,560 --> 00:25:08,560
Speaker 8: then here we are facing a set of issues that

542
00:25:08,600 --> 00:25:11,320
Speaker 8: a businessman like Trump can really take care of, which

543
00:25:11,359 --> 00:25:14,080
Speaker 8: is our economy. Trump's proven that you can take care

544
00:25:14,080 --> 00:25:16,879
Speaker 8: of the border, and Trump's energy policy is going to

545
00:25:17,320 --> 00:25:20,119
Speaker 8: change the whole national security scene. So I think that

546
00:25:20,200 --> 00:25:23,000
Speaker 8: the you know, the focus ought to be on Biden's choice.

547
00:25:23,000 --> 00:25:24,760
Speaker 8: And who knows if Biden's even going to make it

548
00:25:24,800 --> 00:25:25,639
Speaker 8: to the starting line.

549
00:25:25,720 --> 00:25:28,399
Speaker 2: So who knows if Biden's It's like, what, dude, answer

550
00:25:28,400 --> 00:25:30,159
Speaker 2: the question. It's like, are you actually in the running

551
00:25:30,359 --> 00:25:32,320
Speaker 2: for a VP or not. He also went on CNN

552
00:25:32,400 --> 00:25:35,320
Speaker 2: he said Trump was a dictator or sorry, Biden was

553
00:25:35,359 --> 00:25:38,880
Speaker 2: a dictator actually when asked a question about Trump. Let's

554
00:25:38,920 --> 00:25:41,000
Speaker 2: flip this also, and let's go to the next part

555
00:25:41,280 --> 00:25:44,240
Speaker 2: just to show you there's like multiple competing factions. As

556
00:25:44,280 --> 00:25:48,240
Speaker 2: I understand it, Apparently Rupert Murdoch has been pushing Doug Bergham,

557
00:25:48,280 --> 00:25:51,200
Speaker 2: and he really doesn't like JD. Vance. Donald Trump Junior, though,

558
00:25:51,240 --> 00:25:53,760
Speaker 2: has kind of his own coacherie of people. Him and

559
00:25:53,840 --> 00:25:56,800
Speaker 2: JD Vance have become relatively close. JD for example, appeared

560
00:25:56,840 --> 00:26:00,720
Speaker 2: on Trump Junior's podcast on Rumble Trump Juniors and tweeting

561
00:26:01,000 --> 00:26:04,400
Speaker 2: about JD Vance. He wants somebody who's more ideologically aligned

562
00:26:04,920 --> 00:26:08,159
Speaker 2: with the quote unquote America First agenda. This is one

563
00:26:08,200 --> 00:26:10,480
Speaker 2: of those where I just don't know who is going

564
00:26:10,560 --> 00:26:14,480
Speaker 2: to win out All's look, it's certainly possible Trump picks

565
00:26:14,480 --> 00:26:18,680
Speaker 2: somebody who ideologically could be his enforcer, somebody like JD.

566
00:26:18,880 --> 00:26:22,199
Speaker 2: It is also equally possible that he picks somebody like

567
00:26:22,440 --> 00:26:24,640
Speaker 2: Marco Rubio. Now, one of the reasons that I've heard

568
00:26:24,640 --> 00:26:27,720
Speaker 2: about Rubio Crystal is that they are very excited about

569
00:26:27,720 --> 00:26:30,080
Speaker 2: the burgeoning Hispanic vote and they want somebody who can

570
00:26:30,200 --> 00:26:32,960
Speaker 2: genuinely speak Spanish, who can cut ads for them that

571
00:26:33,000 --> 00:26:36,119
Speaker 2: they could play all across South Texas, Florida, et cetera.

572
00:26:36,359 --> 00:26:38,800
Speaker 2: The other one is that Trump himself right now is

573
00:26:38,840 --> 00:26:43,520
Speaker 2: so beholden and so excited by cash and by billionaires

574
00:26:43,680 --> 00:26:50,480
Speaker 2: that Doug Bergum both has traditional Reaganite policy. Obviously he'll

575
00:26:50,480 --> 00:26:52,240
Speaker 2: just say whatever he needs to say, you know, to

576
00:26:52,240 --> 00:26:54,359
Speaker 2: take the job. He himself has got a lot of money,

577
00:26:54,400 --> 00:26:56,160
Speaker 2: so he could both write checks and he can get

578
00:26:56,160 --> 00:26:58,640
Speaker 2: a lot of rich friends, yeah, to donate. And he's

579
00:26:58,640 --> 00:27:01,480
Speaker 2: not offensive in any way. Like he makes the billionaires

580
00:27:01,720 --> 00:27:04,560
Speaker 2: very very happy and right now obviously they're in his

581
00:27:04,640 --> 00:27:06,879
Speaker 2: ear and Trump has been taking a lot of advice

582
00:27:06,920 --> 00:27:09,600
Speaker 2: from them. Everything I've read currently is that the like

583
00:27:09,720 --> 00:27:11,840
Speaker 2: old guard GOP, he has been donating a lot of

584
00:27:11,840 --> 00:27:15,040
Speaker 2: money Trump. This time around, they're pushing Trump somebody like

585
00:27:15,040 --> 00:27:18,320
Speaker 2: Burgham and Tim Scott very heavily. So we will find out.

586
00:27:18,560 --> 00:27:20,439
Speaker 2: I doubt well, actually, I'm actually I'm curious. What do

587
00:27:20,440 --> 00:27:21,800
Speaker 2: you think. Do you actually think he's going to tell

588
00:27:21,840 --> 00:27:22,560
Speaker 2: us on debate day?

589
00:27:22,640 --> 00:27:22,760
Speaker 6: No?

590
00:27:22,880 --> 00:27:24,480
Speaker 2: Yeah, I don't think so. Why because you wouldn't want

591
00:27:24,480 --> 00:27:26,920
Speaker 2: that to upstage whatever he's about to do. Yeah, maybe

592
00:27:26,920 --> 00:27:29,040
Speaker 2: it'll be the day after. I'm not sure, but I.

593
00:27:28,960 --> 00:27:30,640
Speaker 1: Think he's going to wait till the RNC, I think

594
00:27:30,680 --> 00:27:33,320
Speaker 1: to announce. I mean, I just think he'll want the bill,

595
00:27:33,880 --> 00:27:36,159
Speaker 1: but exactly he wants the show. I mean to announce it,

596
00:27:36,200 --> 00:27:38,160
Speaker 1: like at the debate or after that it's just kind

597
00:27:38,160 --> 00:27:40,520
Speaker 1: of like lack the pop that he would that he

598
00:27:40,560 --> 00:27:44,640
Speaker 1: would want. I don't know, I'm feeling the burgamentum who knows.

599
00:27:44,720 --> 00:27:45,280
Speaker 2: I think you're right.

600
00:27:45,480 --> 00:27:47,240
Speaker 1: I mean Tim Scott is another one where like the

601
00:27:47,240 --> 00:27:49,800
Speaker 1: donor class really loves him, So I could see the

602
00:27:49,840 --> 00:27:53,800
Speaker 1: logic there. Listen, Trump last time made a very strategic choice.

603
00:27:53,840 --> 00:27:56,080
Speaker 1: He needed to back in twenty sixteen. He needed to

604
00:27:56,119 --> 00:27:59,040
Speaker 1: solidify standing with evangelicals who were a little shaky with him.

605
00:27:59,400 --> 00:28:01,800
Speaker 1: Mike Pence was the perfect pick, and I think was

606
00:28:01,880 --> 00:28:04,480
Speaker 1: you know, really responsible for helping to get him over

607
00:28:04,520 --> 00:28:06,960
Speaker 1: the top at then, especially after Access Hollywood. It was

608
00:28:06,960 --> 00:28:11,520
Speaker 1: a very clever choice, and Pence was incredibly loyal to

609
00:28:11,600 --> 00:28:14,560
Speaker 1: him all the way up until basically January sixth, so

610
00:28:14,760 --> 00:28:18,480
Speaker 1: you know, on every level, it was a tactically wise

611
00:28:18,560 --> 00:28:21,359
Speaker 1: choice for Trump. I think he will make another choice

612
00:28:21,400 --> 00:28:23,919
Speaker 1: that he feels to be in his tactical interest because remember,

613
00:28:23,920 --> 00:28:25,840
Speaker 1: this man is not just fighting to get back in

614
00:28:25,840 --> 00:28:27,719
Speaker 1: the White House. He really is also fighting for his

615
00:28:27,920 --> 00:28:31,560
Speaker 1: like freedom. Because there is a good chance that even

616
00:28:31,600 --> 00:28:34,640
Speaker 1: though these various case the Document's case, for example, even

617
00:28:34,680 --> 00:28:37,480
Speaker 1: though they've been slow rolled and are not going to

618
00:28:37,480 --> 00:28:40,080
Speaker 1: come to some sort of conclusion before the election. If

619
00:28:40,080 --> 00:28:43,640
Speaker 1: he doesn't win, he's facing tremendous legal jeopardy, and so

620
00:28:43,760 --> 00:28:46,000
Speaker 1: I think that's something not to lose sight of, which

621
00:28:46,040 --> 00:28:49,600
Speaker 1: is why I mean, listen, who knows. I don't have

622
00:28:49,640 --> 00:28:52,040
Speaker 1: any special insight into the mind of Donald Trump, nor

623
00:28:52,080 --> 00:28:53,920
Speaker 1: do I want to. But I just find it hard

624
00:28:53,920 --> 00:28:55,760
Speaker 1: to believe he's going to pick someone like Jade Vance

625
00:28:55,960 --> 00:28:58,640
Speaker 1: because what does he bring? What does he bring? Coalitionally,

626
00:28:59,040 --> 00:29:01,800
Speaker 1: you know, he doesn't bring. There's not a demographic group

627
00:29:01,840 --> 00:29:04,680
Speaker 1: that Trump's gonna imagine he brings to the table. There's

628
00:29:04,720 --> 00:29:07,560
Speaker 1: not a group of donors like the donors to If anything,

629
00:29:07,560 --> 00:29:09,880
Speaker 1: they don't really like JD. Vans, like the Rupert Murdocks

630
00:29:09,920 --> 00:29:13,440
Speaker 1: of the world, are uncomfortable with him. That's true, he

631
00:29:13,520 --> 00:29:18,360
Speaker 1: is friends. But the other thing is that like Jadvans

632
00:29:18,400 --> 00:29:21,440
Speaker 1: is trying to channel what Trump said in twenty sixteen,

633
00:29:21,720 --> 00:29:24,880
Speaker 1: and it's no longer actually an ideological match. Even so,

634
00:29:25,320 --> 00:29:27,840
Speaker 1: I don't know, we'll see what direction he goes in.

635
00:29:28,080 --> 00:29:32,720
Speaker 1: But given the ideological direction he's moved in, given what

636
00:29:32,800 --> 00:29:35,960
Speaker 1: he's prioritized in terms of this campaign, I don't know

637
00:29:36,000 --> 00:29:38,240
Speaker 1: there's a lot there in terms of like a Tim

638
00:29:38,280 --> 00:29:41,480
Speaker 1: Scott or Doug Bergham, someone who really is ASoP to

639
00:29:41,520 --> 00:29:44,280
Speaker 1: the donor class. And we should also say too and

640
00:29:44,320 --> 00:29:47,479
Speaker 1: give Biden his you know, his credit. It's not just

641
00:29:47,520 --> 00:29:50,160
Speaker 1: that they've grown more comfortable with Trump and he's given

642
00:29:50,200 --> 00:29:53,000
Speaker 1: the Hey, i'll give you your tax cuts, I'll give your deregulation.

643
00:29:53,720 --> 00:29:56,560
Speaker 1: I'll you know, flip flop on TikTok, I'll flip flop

644
00:29:56,600 --> 00:29:59,680
Speaker 1: on crypto, flip flop on carried interest, like whatever you want,

645
00:29:59,720 --> 00:30:03,200
Speaker 1: I'll do before immigration. It's also that Wall Street really

646
00:30:03,240 --> 00:30:06,440
Speaker 1: hates Biden's Anti trust division. In particular. They hate it

647
00:30:06,720 --> 00:30:11,360
Speaker 1: because so many Wall Street like rank and file workers,

648
00:30:11,560 --> 00:30:15,240
Speaker 1: they get their bonuses based on mergers and acquisitions, and

649
00:30:15,480 --> 00:30:19,440
Speaker 1: Biden's anti trust division has really put a lid on

650
00:30:19,680 --> 00:30:23,120
Speaker 1: all new mergers and acquisitions. So that is a big

651
00:30:23,200 --> 00:30:26,920
Speaker 1: part of why Wall Street really dislikes Joe Biden in particular,

652
00:30:27,040 --> 00:30:29,440
Speaker 1: really dislikes Lena Khan, who he has sort of turned

653
00:30:29,440 --> 00:30:32,680
Speaker 1: the policy over towards and has really charted a much

654
00:30:32,920 --> 00:30:37,400
Speaker 1: better course in terms of anti trust enforcement. And they

655
00:30:37,520 --> 00:30:40,200
Speaker 1: absolutely hate that. I'm sure they're not in love. Also

656
00:30:40,280 --> 00:30:43,560
Speaker 1: with the you know, the new labor organizing in the

657
00:30:43,560 --> 00:30:45,640
Speaker 1: way Joe Biden's n L RBS positioned. But I do

658
00:30:45,680 --> 00:30:48,360
Speaker 1: think anti trust is sort of like the key rub

659
00:30:48,440 --> 00:30:51,040
Speaker 1: for them. So it's not just that they're more comfy

660
00:30:51,080 --> 00:30:53,240
Speaker 1: with Trump. It's also that they're unhappy with some of

661
00:30:53,280 --> 00:30:55,240
Speaker 1: the Biden economic policies and the way it's hurt their

662
00:30:55,280 --> 00:30:55,720
Speaker 1: bottom line.

663
00:30:55,760 --> 00:30:57,960
Speaker 2: Yeah, certainly, Look, don't get me wrong, they don't like him,

664
00:30:58,360 --> 00:31:01,280
Speaker 2: you know Trump Also it helped if Trump is like, yeah, sure,

665
00:31:01,320 --> 00:31:04,320
Speaker 2: whatever you want. In terms of the polity last time

666
00:31:04,360 --> 00:31:07,240
Speaker 2: around it was a little bit different. We will see. Certainly,

667
00:31:08,240 --> 00:31:11,200
Speaker 2: I think Jdy' still got a decent shot just because

668
00:31:11,360 --> 00:31:14,120
Speaker 2: Trump Junior really likes him. And do you think do.

669
00:31:14,120 --> 00:31:16,120
Speaker 3: You think the dad cares what Trump Junior thinks?

670
00:31:16,160 --> 00:31:17,760
Speaker 2: I just really kind of doubt what I think is

671
00:31:17,800 --> 00:31:19,720
Speaker 2: at FaceTime at mar A Lago matters with a man

672
00:31:19,760 --> 00:31:22,400
Speaker 2: who's constantly pulling people around him, and I know JD's

673
00:31:22,400 --> 00:31:23,000
Speaker 2: basically benness.

674
00:31:23,080 --> 00:31:25,200
Speaker 1: I get a vibe of a lot of disrespect towards

675
00:31:25,280 --> 00:31:26,560
Speaker 1: Don Junior from Dad.

676
00:31:26,640 --> 00:31:28,680
Speaker 2: I'm more saying that's how he's been able to get in. Look,

677
00:31:29,120 --> 00:31:30,959
Speaker 2: he likes people who go on TV. JD goes on

678
00:31:31,000 --> 00:31:33,320
Speaker 2: TV and defends him, So does Doug Burgham, so does

679
00:31:33,360 --> 00:31:36,560
Speaker 2: Tim Scott JD actually is articulate versus some of the

680
00:31:36,600 --> 00:31:40,320
Speaker 2: other candidates there who are in the race. Coalitionally, it's true.

681
00:31:40,400 --> 00:31:44,400
Speaker 2: I mean, Ohio, You're gonna win Ohio no matter what. Again,

682
00:31:44,480 --> 00:31:48,040
Speaker 2: it really feels about how comfortable he is in a

683
00:31:48,200 --> 00:31:50,720
Speaker 2: victory and what it's going to look like, and also

684
00:31:50,840 --> 00:31:54,600
Speaker 2: the optics that he wants on television, because Trump himself

685
00:31:54,600 --> 00:31:56,560
Speaker 2: doesn't like to go in and do all. He likes

686
00:31:56,600 --> 00:31:58,920
Speaker 2: the spar but he just want to do the daily hits,

687
00:31:58,920 --> 00:32:01,560
Speaker 2: Whereas I think the VP candidate, just like all of

688
00:32:01,600 --> 00:32:03,640
Speaker 2: these people have been all over television. He wants them

689
00:32:03,680 --> 00:32:06,720
Speaker 2: on TV constantly defending him like a surrogate. So who

690
00:32:06,760 --> 00:32:10,000
Speaker 2: he thinks will representatively do a really good job against

691
00:32:10,080 --> 00:32:14,440
Speaker 2: Kamala Harris and also just on television constantly defending him.

692
00:32:14,680 --> 00:32:16,600
Speaker 2: That is what's going to come into play because he's

693
00:32:16,640 --> 00:32:19,040
Speaker 2: always about the optics and about how it's going to

694
00:32:19,120 --> 00:32:21,720
Speaker 2: look going into the race. So I'm curious too to

695
00:32:21,760 --> 00:32:23,280
Speaker 2: see what he does. I would give all of them

696
00:32:23,360 --> 00:32:26,280
Speaker 2: a relatively egal shot, I do think Burgham. I don't know,

697
00:32:26,280 --> 00:32:29,280
Speaker 2: I'm just feeling Doug Burgham, Yeah, yeah, as well, maybe I'm.

698
00:32:29,480 --> 00:32:31,480
Speaker 3: It would be so funny because you guys got to

699
00:32:31,520 --> 00:32:33,400
Speaker 3: go back and watch the interview.

700
00:32:32,880 --> 00:32:36,360
Speaker 1: I never in a million years would have thought he

701
00:32:36,440 --> 00:32:37,800
Speaker 1: had shot at anything.

702
00:32:38,040 --> 00:32:40,400
Speaker 3: Is just go watch it. Just go watch it. That's

703
00:32:40,440 --> 00:32:41,160
Speaker 3: all I have to say.

704
00:32:43,480 --> 00:32:45,000
Speaker 2: All right, let's move to the next part. And this

705
00:32:45,080 --> 00:32:46,960
Speaker 2: is very relevant to many of the things that we

706
00:32:46,960 --> 00:32:49,840
Speaker 2: talk about here on the show, just about how gen

707
00:32:49,960 --> 00:32:53,960
Speaker 2: Z may actually have it worse off financially than millennials.

708
00:32:53,960 --> 00:32:59,600
Speaker 2: Millennials who graduated into a terrible economy with sluggish employment. Well,

709
00:32:59,640 --> 00:33:02,520
Speaker 2: it turns out inflation plus sluggish employment may be the

710
00:33:02,640 --> 00:33:04,480
Speaker 2: worst of all worlds. So let's put this up there

711
00:33:04,680 --> 00:33:07,640
Speaker 2: on the screen. We have here the article, but let's

712
00:33:07,680 --> 00:33:09,760
Speaker 2: actually go to the next part with the charts, because

713
00:33:09,800 --> 00:33:13,680
Speaker 2: this really demonstrates to everybody. So here we have gen

714
00:33:13,760 --> 00:33:16,600
Speaker 2: Z inflation adjusted change for sixteen to twenty four year

715
00:33:16,640 --> 00:33:19,880
Speaker 2: olds who are spending one hundred and forty percent more

716
00:33:19,920 --> 00:33:23,880
Speaker 2: on vehicle insurance, one hundred and ten percent more on housing,

717
00:33:24,120 --> 00:33:27,520
Speaker 2: with a real wage increase of just twenty five to

718
00:33:27,600 --> 00:33:31,200
Speaker 2: thirty percent, so barely keeping up with the level of

719
00:33:31,240 --> 00:33:35,520
Speaker 2: food inflation, with housing and with car insurance dramatically outpacing

720
00:33:35,560 --> 00:33:38,440
Speaker 2: it by almost fivefold. If you go to the next part,

721
00:33:38,480 --> 00:33:41,720
Speaker 2: you can actually see this as well. The average credit

722
00:33:41,720 --> 00:33:44,040
Speaker 2: card balance has increased the most for people who are

723
00:33:44,320 --> 00:33:47,080
Speaker 2: Gen Z forty two point nine percent, right up there

724
00:33:47,080 --> 00:33:49,600
Speaker 2: with our fellow millennials at forty two and a half percent,

725
00:33:49,880 --> 00:33:52,680
Speaker 2: twenty nine percent for Gen X, just fourteen percent for boomers,

726
00:33:52,680 --> 00:33:56,960
Speaker 2: and seven percent for the Silent generation. Next part please

727
00:33:57,000 --> 00:33:59,720
Speaker 2: as well, you can see here being hit hard the

728
00:33:59,760 --> 00:34:03,560
Speaker 2: war inflation. The way that they calculate that is just

729
00:34:03,760 --> 00:34:07,240
Speaker 2: about the level of price increase over the course of

730
00:34:07,280 --> 00:34:10,160
Speaker 2: your working life. So obviously you can see there for

731
00:34:10,320 --> 00:34:12,480
Speaker 2: millennials and for gen Z, but there's also a lot

732
00:34:12,480 --> 00:34:16,160
Speaker 2: of goods and services that people need to spend on

733
00:34:16,320 --> 00:34:19,320
Speaker 2: necessities whenever they're younger. That's going to take up a huge,

734
00:34:19,320 --> 00:34:22,120
Speaker 2: more bigger portion of their income. And that gets us

735
00:34:22,120 --> 00:34:24,160
Speaker 2: to the last chart, if we can put that, please,

736
00:34:24,480 --> 00:34:28,080
Speaker 2: the outside share on necessities, where you can see that

737
00:34:28,320 --> 00:34:32,640
Speaker 2: compared to all ages, rent is twenty percent of a

738
00:34:32,680 --> 00:34:37,200
Speaker 2: Gen Z overall spending just six percent eight percent for

739
00:34:37,440 --> 00:34:40,080
Speaker 2: all ages, so almost three times more over there for rent.

740
00:34:40,400 --> 00:34:43,799
Speaker 2: Dining out is roughly similar, car insurance roughly similar, but

741
00:34:43,880 --> 00:34:47,520
Speaker 2: gas is higher. The rent equation and housing just shows

742
00:34:47,600 --> 00:34:50,640
Speaker 2: us again how much worse it is for the younger

743
00:34:50,680 --> 00:34:52,960
Speaker 2: that you are. You're not in a house, which means

744
00:34:52,960 --> 00:34:55,840
Speaker 2: you are subject to the worst single part of inflation

745
00:34:56,200 --> 00:35:00,120
Speaker 2: with housing, with rent and your inability also to s

746
00:35:00,120 --> 00:35:02,160
Speaker 2: save to buy that house. So it all comes back

747
00:35:02,160 --> 00:35:03,880
Speaker 2: to housing. As they say, and as we continue to

748
00:35:03,880 --> 00:35:05,040
Speaker 2: say here on the show, it.

749
00:35:05,000 --> 00:35:06,960
Speaker 1: Really is astonishing when you think about it, when you

750
00:35:07,000 --> 00:35:09,560
Speaker 1: think about, you know, millennials, we're basically like in college

751
00:35:09,680 --> 00:35:13,880
Speaker 1: or graduating into this massive economic crisis where the bottom

752
00:35:13,960 --> 00:35:18,759
Speaker 1: just completely fell out, and that impacted impacted millennials employment,

753
00:35:19,040 --> 00:35:22,760
Speaker 1: It impacted their earning prospects. Really that lingers actually throughout

754
00:35:22,760 --> 00:35:25,840
Speaker 1: an entire career for sure. And so even though you

755
00:35:25,960 --> 00:35:30,319
Speaker 1: had this massive economic crash, just the fact of how

756
00:35:30,400 --> 00:35:36,840
Speaker 1: much housing, food, car insurance, health insurance, how much those

757
00:35:36,920 --> 00:35:39,640
Speaker 1: costs have gone up, has actually made it so that

758
00:35:39,800 --> 00:35:45,440
Speaker 1: even without this you know, singular financial crash type event,

759
00:35:46,239 --> 00:35:49,000
Speaker 1: gen z is doing worse than millennials at the same

760
00:35:49,040 --> 00:35:51,720
Speaker 1: point in their lives. It really is quite eye opening,

761
00:35:51,880 --> 00:35:54,279
Speaker 1: it truly is. And just to get go over a

762
00:35:54,320 --> 00:35:57,719
Speaker 1: couple of the numbers again, gen Z workers, they're more

763
00:35:57,760 --> 00:36:00,480
Speaker 1: likely to go to college, they're more likely to have jobs,

764
00:36:00,840 --> 00:36:04,480
Speaker 1: and they make more money right in nominal terms, not

765
00:36:04,560 --> 00:36:07,560
Speaker 1: of inflation and justine nominal terms, than millennials did. So

766
00:36:07,600 --> 00:36:09,000
Speaker 1: you look at that and say, okay, well, they should

767
00:36:09,000 --> 00:36:12,360
Speaker 1: be doing pretty good, right wrong, because they're paying thirty

768
00:36:12,440 --> 00:36:16,480
Speaker 1: one percent more for housing than millennials did when they

769
00:36:16,520 --> 00:36:20,840
Speaker 1: graduated college after ingesting for inflation. Car insurance by people

770
00:36:20,880 --> 00:36:24,240
Speaker 1: sixteen to twenty four more than doubled over that time period.

771
00:36:24,640 --> 00:36:30,160
Speaker 1: Health insurance spending forty six percent increase from when millennials

772
00:36:30,160 --> 00:36:32,480
Speaker 1: were coming out of college and having to figure out

773
00:36:32,760 --> 00:36:35,960
Speaker 1: health insurance. So when you add all of those things

774
00:36:36,080 --> 00:36:39,279
Speaker 1: up and then you look at tepid wage growth that

775
00:36:39,400 --> 00:36:44,640
Speaker 1: does not even come close to comparing, it is quite astonishing.

776
00:36:44,719 --> 00:36:47,440
Speaker 1: And it also obviously dovetails with our politics. And you know,

777
00:36:47,480 --> 00:36:50,080
Speaker 1: all these people, oh, the economy's great and non employments low,

778
00:36:50,280 --> 00:36:52,279
Speaker 1: stock market is a lot. You think these people have

779
00:36:52,360 --> 00:36:54,600
Speaker 1: investments in the stock market. They're just trying to be

780
00:36:54,600 --> 00:36:57,239
Speaker 1: able to afford a grocery bill. They're just trying to

781
00:36:57,280 --> 00:36:59,319
Speaker 1: be able to make it in terms of rent. I mean,

782
00:36:59,360 --> 00:37:02,759
Speaker 1: that's really one that's such an incredible burden. And so

783
00:37:02,960 --> 00:37:05,239
Speaker 1: of course they don't feel like the economy is good.

784
00:37:05,280 --> 00:37:07,400
Speaker 1: Of Course they don't feel like this economy was designed

785
00:37:07,400 --> 00:37:10,200
Speaker 1: to work for them, because it's not. And it's also

786
00:37:10,239 --> 00:37:13,719
Speaker 1: really explains why you've seen such an age divergence in

787
00:37:13,800 --> 00:37:16,920
Speaker 1: terms of perceptions and reality of the economy.

788
00:37:16,920 --> 00:37:17,799
Speaker 3: And then that's.

789
00:37:17,600 --> 00:37:21,479
Speaker 1: Trickling down into political choices obviously, but it's quite something

790
00:37:21,520 --> 00:37:22,520
Speaker 1: to see it laid out like this.

791
00:37:22,640 --> 00:37:25,360
Speaker 2: Yeah, well we have some of that. Actually, CBS News

792
00:37:25,440 --> 00:37:27,440
Speaker 2: just put out a new pull about young people.

793
00:37:27,520 --> 00:37:27,680
Speaker 6: Now.

794
00:37:27,760 --> 00:37:30,480
Speaker 2: Whether we agree with the actual numbers on Biden or

795
00:37:30,520 --> 00:37:33,880
Speaker 2: Trump or not, they had good insight into what the

796
00:37:33,920 --> 00:37:36,760
Speaker 2: outlook of this generation is. Let's take a listen.

797
00:37:36,840 --> 00:37:38,360
Speaker 9: We're going to look at all the key groups in

798
00:37:38,360 --> 00:37:40,360
Speaker 9: this election, but I wanted to start with this one.

799
00:37:40,520 --> 00:37:42,800
Speaker 9: What's interesting about them is they feel like they've already

800
00:37:42,800 --> 00:37:45,520
Speaker 9: been tested in their lives. This is a generation the

801
00:37:45,600 --> 00:37:48,000
Speaker 9: younger part of them who were in high school or

802
00:37:48,080 --> 00:37:50,879
Speaker 9: college during COVID and the lockdowns, and most of them

803
00:37:50,880 --> 00:37:55,000
Speaker 9: tell us that interrupted their education. They also look back

804
00:37:55,239 --> 00:37:58,279
Speaker 9: say they were more concerned about gun violence during those

805
00:37:58,400 --> 00:38:03,040
Speaker 9: years than older generations. But what's really interesting here is

806
00:38:04,320 --> 00:38:09,080
Speaker 9: they are also feeling like the older generation has handed them,

807
00:38:09,120 --> 00:38:12,960
Speaker 9: has left them a world that's more dangerous and a

808
00:38:13,000 --> 00:38:16,239
Speaker 9: climate that's worse, and that motivates a lot of the

809
00:38:16,280 --> 00:38:19,480
Speaker 9: issues that they care about. Having said that, Margaret, you

810
00:38:19,520 --> 00:38:22,240
Speaker 9: can look at polling from the sixties when the Baby

811
00:38:22,239 --> 00:38:25,759
Speaker 9: Boomers were the young generation, then from the nineties when

812
00:38:25,760 --> 00:38:28,560
Speaker 9: it was Gen X. There have always been generation gaps

813
00:38:28,640 --> 00:38:33,000
Speaker 9: in America. But for this generation today, they're the most

814
00:38:33,080 --> 00:38:36,680
Speaker 9: racially diverse generation that the country has ever seen, and

815
00:38:36,760 --> 00:38:39,480
Speaker 9: that comes out in their politics too. They tell us

816
00:38:39,480 --> 00:38:41,759
Speaker 9: they feel that politics would be better not just with

817
00:38:41,840 --> 00:38:45,280
Speaker 9: more young people in it, but also with more minority

818
00:38:45,360 --> 00:38:49,600
Speaker 9: voices in politics, with more women in elected office, and

819
00:38:49,640 --> 00:38:53,200
Speaker 9: they feel that way much more so than the oldest

820
00:38:53,320 --> 00:38:54,120
Speaker 9: generation does.

821
00:38:54,440 --> 00:38:57,080
Speaker 2: So there you go. Also, the funny thing is as

822
00:38:57,160 --> 00:38:59,839
Speaker 2: usual media, they're like, oh, race and all that, Like, yeah,

823
00:38:59,840 --> 00:39:02,160
Speaker 2: what about some diverse opinion. That's really what I think

824
00:39:02,200 --> 00:39:04,520
Speaker 2: a lot of people are thinking as well. So as

825
00:39:04,600 --> 00:39:07,799
Speaker 2: usual people, they can see it on the surface, but

826
00:39:07,840 --> 00:39:10,839
Speaker 2: then they never estimate their own culpability. But we can't

827
00:39:10,880 --> 00:39:13,000
Speaker 2: put our own people off the hook. We don't vote,

828
00:39:13,120 --> 00:39:16,160
Speaker 2: you know, even close to the same numbers. Not enthused,

829
00:39:16,440 --> 00:39:19,759
Speaker 2: not excited, not engage, in the political process, lack a

830
00:39:19,760 --> 00:39:22,880
Speaker 2: lot of more community roots. There's a lot of reasons

831
00:39:22,920 --> 00:39:24,960
Speaker 2: for that, but structurally it just means you're not going

832
00:39:25,000 --> 00:39:26,799
Speaker 2: to have as much of a voice, you know, in

833
00:39:26,840 --> 00:39:29,680
Speaker 2: the system, and thus the system chugs along for the

834
00:39:29,760 --> 00:39:31,640
Speaker 2: old for the boomers, and for the silent generation.

835
00:39:31,920 --> 00:39:35,479
Speaker 1: Yeah, I mean, they're certainly not wrong that the way

836
00:39:35,560 --> 00:39:40,120
Speaker 1: the economy has been set up and the ideological project,

837
00:39:40,280 --> 00:39:44,160
Speaker 1: you know, predominantly of the boomers has it's massively inflated

838
00:39:44,200 --> 00:39:45,040
Speaker 1: asset prices.

839
00:39:45,080 --> 00:39:46,000
Speaker 3: So what does that mean.

840
00:39:46,040 --> 00:39:48,399
Speaker 1: That means that they're like, Okay, my parents were able

841
00:39:48,400 --> 00:39:51,279
Speaker 1: to get a home. Remember the concept of a starter home,

842
00:39:51,560 --> 00:39:53,319
Speaker 1: you know, the idea that you like, get a job

843
00:39:53,360 --> 00:39:55,200
Speaker 1: and then you can buy it. Likes that's dead, that

844
00:39:55,239 --> 00:39:57,560
Speaker 1: doesn't exist. I don't know if I'll ever be able

845
00:39:57,560 --> 00:39:59,480
Speaker 1: to buy a home, is what they're thinking. They're looking

846
00:39:59,520 --> 00:40:01,600
Speaker 1: at the cost continuing to go up and up and up.

847
00:40:01,840 --> 00:40:04,759
Speaker 1: Mortgage rates obviously have you know, made it so much

848
00:40:04,800 --> 00:40:08,480
Speaker 1: more expensive. You're competing now against Wall Street buyers who

849
00:40:08,560 --> 00:40:10,719
Speaker 1: are coming in or people who are already you know,

850
00:40:10,840 --> 00:40:14,280
Speaker 1: wealthy and older who can put plunk down all cash offers.

851
00:40:14,640 --> 00:40:16,799
Speaker 1: You just feel like you don't stand a chance. You

852
00:40:16,800 --> 00:40:20,040
Speaker 1: feel like your parents' generation had a lot more opportunities

853
00:40:20,080 --> 00:40:20,799
Speaker 1: open to.

854
00:40:20,880 --> 00:40:22,200
Speaker 3: Them than you do.

855
00:40:22,680 --> 00:40:25,800
Speaker 1: And you know that's really antithetical to our self conception

856
00:40:26,040 --> 00:40:28,440
Speaker 1: as a country, like the idea of the country, the

857
00:40:28,480 --> 00:40:30,880
Speaker 1: sort of like you know, the core American dream ideas.

858
00:40:31,000 --> 00:40:33,680
Speaker 1: Things just keep getting better, and you know, we as

859
00:40:33,760 --> 00:40:36,719
Speaker 1: parents too, like it'll even I'll be able to pass

860
00:40:36,760 --> 00:40:38,719
Speaker 1: forward something to my kids that will be even better

861
00:40:38,719 --> 00:40:41,520
Speaker 1: and they'll have more opportunities than I did. Young people

862
00:40:41,760 --> 00:40:43,680
Speaker 1: don't feel it that way, and they haven't felt that

863
00:40:43,680 --> 00:40:47,360
Speaker 1: way for quite a while, really since the financial crash,

864
00:40:47,400 --> 00:40:50,320
Speaker 1: I think and everybody who has come after, and inflation

865
00:40:50,400 --> 00:40:54,280
Speaker 1: has been such an incredible burden for this generation.

866
00:40:54,000 --> 00:40:55,319
Speaker 3: To be able to cope with.

867
00:40:55,719 --> 00:40:59,760
Speaker 1: The wages have ticked up some, but it's not nearly

868
00:40:59,800 --> 00:41:02,120
Speaker 1: an enough to deal with when you look at things

869
00:41:02,160 --> 00:41:04,279
Speaker 1: like health, insurance, housing, etc.

870
00:41:05,160 --> 00:41:07,040
Speaker 2: Well, you referenced starter homes. I was telling you. I

871
00:41:07,080 --> 00:41:09,960
Speaker 2: read that book about Grand Expectations about America. It was

872
00:41:10,000 --> 00:41:12,200
Speaker 2: really inspirational. Honestly, it was a cool country. We used

873
00:41:12,200 --> 00:41:13,680
Speaker 2: to build a lot of stuff. We had these things

874
00:41:13,719 --> 00:41:16,640
Speaker 2: called Levittowns. They're very famous with starter homes. So I'm

875
00:41:16,640 --> 00:41:20,839
Speaker 2: looking in Levittown, New York, in the neighborhood that was

876
00:41:20,880 --> 00:41:23,840
Speaker 2: supposed to be starter homes, which were very available to

877
00:41:24,040 --> 00:41:26,920
Speaker 2: the average middle class. The cheapest house that I can

878
00:41:26,920 --> 00:41:30,120
Speaker 2: find in Levittown is four hundred and fifteen thousand dollars.

879
00:41:30,320 --> 00:41:32,560
Speaker 2: That is a complete starter up, and it's a condo.

880
00:41:32,640 --> 00:41:34,640
Speaker 2: It's a one bed, one bath if you want a

881
00:41:34,680 --> 00:41:38,239
Speaker 2: fourteen hundred, fourteen hundred square foot house, which is like

882
00:41:38,480 --> 00:41:42,200
Speaker 2: kind of redone but still done in the nineteen fifties

883
00:41:42,200 --> 00:41:45,440
Speaker 2: whenever it was born. Six hundred and fifty k good luck,

884
00:41:45,960 --> 00:41:48,480
Speaker 2: good luck pains, six hundred and fifty five thousand dollars

885
00:41:48,680 --> 00:41:51,280
Speaker 2: four house that was built what in the nineteen fifties

886
00:41:51,520 --> 00:41:54,560
Speaker 2: starter home fourteen hundred square feet which was considered a

887
00:41:54,600 --> 00:41:58,480
Speaker 2: starter home at that time, and no garage parking. That's

888
00:41:58,520 --> 00:42:00,640
Speaker 2: the country that we live in right now. And that's like,

889
00:42:00,840 --> 00:42:03,320
Speaker 2: I mean, we're not talking about Manhattan, We're talking about Levittown,

890
00:42:04,040 --> 00:42:05,839
Speaker 2: you know, far away. It's probably still what in hour

891
00:42:05,920 --> 00:42:08,040
Speaker 2: driver something like that. And there's a couple of other

892
00:42:08,120 --> 00:42:11,120
Speaker 2: Levittowns across America. I think one inn PA as well,

893
00:42:11,280 --> 00:42:13,879
Speaker 2: similar in terms of their prices. There's a good ride

894
00:42:13,960 --> 00:42:15,920
Speaker 2: up there about how all the old starter homes from

895
00:42:15,960 --> 00:42:19,239
Speaker 2: the nineteen fifties to the nineteen seventies are now are

896
00:42:19,320 --> 00:42:23,560
Speaker 2: selling for orders of magnitude more in terms of percentage

897
00:42:23,600 --> 00:42:25,680
Speaker 2: of income than they did at a time. So we

898
00:42:25,719 --> 00:42:28,200
Speaker 2: have a crisis and nobody just seems to care about it.

899
00:42:28,360 --> 00:42:30,920
Speaker 2: And that's why, you know, the rent piece of this

900
00:42:31,080 --> 00:42:33,839
Speaker 2: for the younger generation, I think, you know, they're going

901
00:42:33,880 --> 00:42:36,480
Speaker 2: to be the most like pro housing generation ever just

902
00:42:36,520 --> 00:42:38,719
Speaker 2: because they got more screwed than anybody else. Yeah, it's

903
00:42:38,719 --> 00:42:40,600
Speaker 2: going to take a long time before a lot of

904
00:42:40,600 --> 00:42:42,399
Speaker 2: the boomer political power phase away.

905
00:42:42,480 --> 00:42:43,520
Speaker 3: Yeah, no, that's right.

906
00:42:46,200 --> 00:42:48,920
Speaker 1: Very excited to be joined today by Peter Goodman. He

907
00:42:49,120 --> 00:42:51,680
Speaker 1: is the global economics correspondent for the New York Times,

908
00:42:51,680 --> 00:42:53,759
Speaker 1: and more importantly for our purposes, let's put this up

909
00:42:53,760 --> 00:42:54,280
Speaker 1: on the screen.

910
00:42:54,320 --> 00:42:55,279
Speaker 3: He's the author of.

911
00:42:55,239 --> 00:42:59,320
Speaker 1: A terrific new book, How the World Ran Out of Everything,

912
00:42:59,480 --> 00:43:02,760
Speaker 1: that takes a look at the catastrophe of the supply

913
00:43:02,880 --> 00:43:06,000
Speaker 1: chain on every level during COVID and also takes it

914
00:43:06,040 --> 00:43:09,279
Speaker 1: back to, you know, the origins of what created so

915
00:43:09,400 --> 00:43:12,680
Speaker 1: much fragility and some lesson learns, lessons learned from moving forward.

916
00:43:12,719 --> 00:43:14,520
Speaker 1: Great to see you, Peter, congratulations in the book.

917
00:43:15,040 --> 00:43:17,479
Speaker 6: Great to see you guys. Thanks so much so.

918
00:43:17,440 --> 00:43:19,320
Speaker 1: I just gave my little synopsis. But why didn't you

919
00:43:19,360 --> 00:43:21,719
Speaker 1: talk about why you wanted to write this book? Because

920
00:43:21,719 --> 00:43:27,520
Speaker 1: you were covering all of these major backups, nawfoos, shortages,

921
00:43:27,600 --> 00:43:30,120
Speaker 1: et cetera as they were unfolding, right.

922
00:43:30,200 --> 00:43:32,600
Speaker 10: I mean, I never expected to write about such a

923
00:43:32,640 --> 00:43:35,239
Speaker 10: wonky subject as the global supply chain. I mean, it's

924
00:43:35,320 --> 00:43:37,520
Speaker 10: kind of in everything that I've written about for the

925
00:43:37,600 --> 00:43:40,800
Speaker 10: last three decades. But to go hard at it, I

926
00:43:40,840 --> 00:43:44,640
Speaker 10: mean it happened really because we all discovered that this

927
00:43:44,800 --> 00:43:47,239
Speaker 10: system that we don't think about it. I mean, it's

928
00:43:47,239 --> 00:43:50,280
Speaker 10: a series of overlapping systems, a whole army of people

929
00:43:50,560 --> 00:43:53,200
Speaker 10: who make our products and get them to our door.

930
00:43:53,840 --> 00:43:56,880
Speaker 6: It just kind of buckled and collapsed right when we

931
00:43:56,920 --> 00:43:57,560
Speaker 6: needed it most.

932
00:43:57,640 --> 00:44:00,279
Speaker 10: I mean I was living in London and lockdown Down

933
00:44:00,640 --> 00:44:02,800
Speaker 10: had a baby born in the first wave.

934
00:44:02,560 --> 00:44:03,160
Speaker 6: Of the pandemic.

935
00:44:03,239 --> 00:44:06,680
Speaker 10: Our son was born on April eighth, twenty twenty, and

936
00:44:06,719 --> 00:44:08,920
Speaker 10: my wife was pretty stoic about the fact that, you know,

937
00:44:08,960 --> 00:44:12,279
Speaker 10: I couldn't be in the hospital an hour after he

938
00:44:12,400 --> 00:44:16,960
Speaker 10: was born. We couldn't get the usual national health service checkups,

939
00:44:17,040 --> 00:44:19,560
Speaker 10: and her parents couldn't fly in from New York to

940
00:44:19,560 --> 00:44:21,560
Speaker 10: help with the baby. But where we all just kind

941
00:44:21,600 --> 00:44:23,560
Speaker 10: of lost it was then we get home and we

942
00:44:23,640 --> 00:44:26,840
Speaker 10: discovered that we can't find hand sanitizer anywhere, and we

943
00:44:26,880 --> 00:44:28,880
Speaker 10: can't even find the ingredients.

944
00:44:28,400 --> 00:44:29,799
Speaker 6: To make hand sanitize her.

945
00:44:30,560 --> 00:44:33,600
Speaker 10: And this was just sort of cosmically bewildering, and I

946
00:44:33,600 --> 00:44:36,960
Speaker 10: think most people can relate to that. So as I

947
00:44:37,000 --> 00:44:40,400
Speaker 10: found myself writing about all of the constituent components of

948
00:44:40,400 --> 00:44:44,920
Speaker 10: this collapse, the container shipping crisis, the supposed shortage of

949
00:44:45,000 --> 00:44:48,319
Speaker 10: truck drivers and warehouse workers, which was really just the

950
00:44:48,360 --> 00:44:51,480
Speaker 10: result of downgrading people's jobs to the point where we

951
00:44:51,560 --> 00:44:53,200
Speaker 10: ran out of people willing to do them in the

952
00:44:53,239 --> 00:44:56,440
Speaker 10: middle of a pandemic, I realized that this was indeed

953
00:44:56,480 --> 00:44:57,719
Speaker 10: a book, right.

954
00:44:57,800 --> 00:45:00,319
Speaker 2: I mean, no, you did a fantastic job here, and

955
00:45:00,560 --> 00:45:03,200
Speaker 2: we have this book review, which I think is really

956
00:45:03,320 --> 00:45:05,120
Speaker 2: hits at the crux of what we're talking about. We

957
00:45:05,160 --> 00:45:07,719
Speaker 2: can put it up there on the screen. Was global

958
00:45:07,760 --> 00:45:11,120
Speaker 2: trade a mistake? You can tell us whether you agree

959
00:45:11,440 --> 00:45:14,320
Speaker 2: with that question or not, But most importantly you focus

960
00:45:14,400 --> 00:45:17,320
Speaker 2: in on just in time manufacturing and how the entire

961
00:45:17,840 --> 00:45:23,960
Speaker 2: modern consumer economy was constructed around this global exchange of goods,

962
00:45:24,120 --> 00:45:26,920
Speaker 2: and that with a supply shock like the pandemic, it

963
00:45:27,080 --> 00:45:30,799
Speaker 2: threw things for a loop that had devastating consequences for

964
00:45:30,920 --> 00:45:33,240
Speaker 2: a lot of American consumers. So where do you follow

965
00:45:33,239 --> 00:45:36,279
Speaker 2: on the question and specifically here with just in time manufacturing.

966
00:45:36,960 --> 00:45:39,279
Speaker 10: Well, I don't think global trade or just in time

967
00:45:39,320 --> 00:45:43,160
Speaker 10: manufacturing and mistakes. I think the mistake was allowing a

968
00:45:43,239 --> 00:45:49,319
Speaker 10: system to be constructed by publicly traded, profit maximizing corporations

969
00:45:49,320 --> 00:45:53,960
Speaker 10: that were largely deregulated to do these things while we're

970
00:45:54,239 --> 00:45:57,000
Speaker 10: in the thrall of this kind of ruthless form of

971
00:45:57,040 --> 00:46:00,160
Speaker 10: efficiency that, as I demonstrated in the book, isn't actually

972
00:46:00,200 --> 00:46:03,160
Speaker 10: that efficient. We can get into this in detail, but

973
00:46:03,239 --> 00:46:05,840
Speaker 10: you know, one of the most incredible things I discovered

974
00:46:05,840 --> 00:46:07,360
Speaker 10: in the book was in the middle of the pandemic,

975
00:46:07,800 --> 00:46:13,840
Speaker 10: rail companies were actually sending cargo to the wrong destinations,

976
00:46:14,000 --> 00:46:17,879
Speaker 10: intentionally resulting in delays and product shortages because they were

977
00:46:17,920 --> 00:46:20,480
Speaker 10: so obsessed with proving to Wall Street that they were

978
00:46:20,560 --> 00:46:24,200
Speaker 10: lowering their dwell time. You know this metric that had

979
00:46:24,200 --> 00:46:27,200
Speaker 10: currency on Wall Street, that's how long cargo sits in

980
00:46:27,200 --> 00:46:28,280
Speaker 10: any particular place.

981
00:46:28,640 --> 00:46:31,520
Speaker 6: So I found this engineer in Idaho who.

982
00:46:31,480 --> 00:46:35,400
Speaker 10: Is just appalled to discover that he's hauling things to

983
00:46:35,440 --> 00:46:38,160
Speaker 10: the wrong destinations because some guy running a railyard in

984
00:46:38,239 --> 00:46:42,000
Speaker 10: Nebraska is just attaching cargo to whatever the next train

985
00:46:42,160 --> 00:46:45,600
Speaker 10: is that's moving out of there, never mind who happens

986
00:46:45,640 --> 00:46:48,160
Speaker 10: to be waiting for that cargo. So the mistake was

987
00:46:48,600 --> 00:46:53,480
Speaker 10: allowing monopoly companies, you know, to develop. I mean, a

988
00:46:53,520 --> 00:46:58,400
Speaker 10: lot of the industries that I'm writing about, transportation, meat packing,

989
00:46:58,719 --> 00:47:02,399
Speaker 10: have you know leaders who have market share that would

990
00:47:02,400 --> 00:47:05,560
Speaker 10: make the robber barons blush and just in time was

991
00:47:05,640 --> 00:47:08,480
Speaker 10: this idea pioneered by Toyota at the end of the

992
00:47:08,520 --> 00:47:11,439
Speaker 10: Second World War that instead of just making as much

993
00:47:11,480 --> 00:47:15,400
Speaker 10: stuff as we possibly could a la Henry Ford, just

994
00:47:15,600 --> 00:47:18,640
Speaker 10: make what you need to replenish the cars that you've

995
00:47:18,640 --> 00:47:22,319
Speaker 10: already sold. Get your suppliers to bring parts and raw

996
00:47:22,360 --> 00:47:24,560
Speaker 10: materials to the assembly line just as you need them.

997
00:47:24,719 --> 00:47:28,400
Speaker 10: That worked out very well for Toyota. It dropped consumer

998
00:47:28,480 --> 00:47:31,240
Speaker 10: prices very low. It did reduce a lot of waste,

999
00:47:31,239 --> 00:47:35,600
Speaker 10: But along comes again the paramounts of shareholder interest. I

1000
00:47:35,640 --> 00:47:37,200
Speaker 10: spent a lot of time looking at the role of

1001
00:47:37,280 --> 00:47:41,239
Speaker 10: McKinsey and other consultants in turning Just in Time into

1002
00:47:41,280 --> 00:47:45,279
Speaker 10: this crude imperative for companies to just slash inventory to

1003
00:47:45,360 --> 00:47:48,240
Speaker 10: the bone, take the money that they used to waste

1004
00:47:48,280 --> 00:47:51,880
Speaker 10: as they see it, sticking parts and warehouses as a

1005
00:47:51,920 --> 00:47:54,839
Speaker 10: hedge against trouble like the pandemic, and then just give

1006
00:47:54,880 --> 00:47:59,319
Speaker 10: them money to themselves through executive compensation, through bonuses, through

1007
00:47:59,360 --> 00:48:03,320
Speaker 10: dividend and share buybacks that make the investor class unhappy,

1008
00:48:03,360 --> 00:48:05,919
Speaker 10: but leave the rest of us running out of all

1009
00:48:05,960 --> 00:48:09,680
Speaker 10: sorts of vital things, you know, basic chemicals to make medicines,

1010
00:48:10,120 --> 00:48:13,360
Speaker 10: protective gear in the middle of the pandemic, computer chips,

1011
00:48:13,400 --> 00:48:16,080
Speaker 10: which means we can't make medical devices. I mean, we

1012
00:48:16,160 --> 00:48:20,520
Speaker 10: are still right now paying the costs of this successive

1013
00:48:20,560 --> 00:48:21,920
Speaker 10: embrace of just in Time.

1014
00:48:22,600 --> 00:48:24,879
Speaker 1: I think one of the most important reasons to read

1015
00:48:24,920 --> 00:48:28,440
Speaker 1: your book also is to really wrap your head around

1016
00:48:28,880 --> 00:48:30,759
Speaker 1: some of the ways that we were really lied to

1017
00:48:31,400 --> 00:48:34,320
Speaker 1: during this period of time. For example, a sort of

1018
00:48:34,400 --> 00:48:37,120
Speaker 1: micro example, you know, we were told, oh, there's this

1019
00:48:37,320 --> 00:48:40,120
Speaker 1: shortage of truckers, like people just they don't want to work,

1020
00:48:40,360 --> 00:48:41,560
Speaker 1: They just don't want to work hard.

1021
00:48:41,760 --> 00:48:43,120
Speaker 3: So there's not enough truckers.

1022
00:48:43,680 --> 00:48:46,360
Speaker 1: So you know what we need to do is actually

1023
00:48:46,400 --> 00:48:50,080
Speaker 1: get Congress to fund these education programs that, by the way,

1024
00:48:50,080 --> 00:48:52,960
Speaker 1: way the trucking companies are going to nobly run. And

1025
00:48:53,000 --> 00:48:55,840
Speaker 1: I'm sure that's not you know, that's not a kickback whatsoever.

1026
00:48:56,400 --> 00:48:58,759
Speaker 1: Instead of actually looking at the fact you've made it

1027
00:48:58,880 --> 00:49:02,719
Speaker 1: so people cannot live on these jobs, you're putting them

1028
00:49:02,719 --> 00:49:04,759
Speaker 1: in massive debt. Of course you have a short of

1029
00:49:04,840 --> 00:49:08,880
Speaker 1: strucker because you've made the job so incredibly miserable. And

1030
00:49:08,920 --> 00:49:10,680
Speaker 1: then at the macro level, So that's a sort of

1031
00:49:10,840 --> 00:49:12,839
Speaker 1: micro example that I'd love you to talk more about

1032
00:49:12,880 --> 00:49:15,640
Speaker 1: because I think it's a really really important one. But

1033
00:49:15,719 --> 00:49:18,360
Speaker 1: also at the macro level, you know, the big story

1034
00:49:18,400 --> 00:49:19,640
Speaker 1: about inflation.

1035
00:49:19,960 --> 00:49:20,520
Speaker 3: Wasn't they did.

1036
00:49:20,560 --> 00:49:23,040
Speaker 1: They'd say something about the supply chain, but the real

1037
00:49:23,120 --> 00:49:26,480
Speaker 1: problem was that people got money during the pandemic. Oh,

1038
00:49:26,520 --> 00:49:29,280
Speaker 1: they got the child tax credit, they got those direct checks,

1039
00:49:29,520 --> 00:49:31,439
Speaker 1: and people went out there and they were spending money

1040
00:49:31,560 --> 00:49:34,520
Speaker 1: like crazy. And that was the That was the one

1041
00:49:34,600 --> 00:49:38,680
Speaker 1: and only cause of inflation. Was this spending that benefited

1042
00:49:38,840 --> 00:49:42,239
Speaker 1: average people. Your book really takes a look at the

1043
00:49:42,280 --> 00:49:46,000
Speaker 1: way that that at its core was also an incredible

1044
00:49:46,360 --> 00:49:50,320
Speaker 1: lie in service of you know, people who in service

1045
00:49:50,360 --> 00:49:53,720
Speaker 1: of people's ideological project in service of hiding these corporate

1046
00:49:53,719 --> 00:49:57,520
Speaker 1: shenanigans also, and just a sort of greedy profit maximization

1047
00:49:57,600 --> 00:49:58,640
Speaker 1: that you expose as well.

1048
00:49:59,080 --> 00:50:02,480
Speaker 6: Yeah, I really agree cciate that. Careful read. It's true

1049
00:50:02,719 --> 00:50:04,080
Speaker 6: that time and again.

1050
00:50:04,480 --> 00:50:06,840
Speaker 10: I mean this to me is sort of reminiscent of

1051
00:50:06,880 --> 00:50:10,120
Speaker 10: how you know, the subprime mortgage crisis gets blamed, or

1052
00:50:10,160 --> 00:50:13,640
Speaker 10: really the derivatives crisis that then trashes the financial system,

1053
00:50:13,840 --> 00:50:17,480
Speaker 10: that trashes the regular economy that all of us depend on,

1054
00:50:17,600 --> 00:50:18,520
Speaker 10: that gets blamed on.

1055
00:50:18,560 --> 00:50:20,880
Speaker 6: Poor people, you know, who were greedy.

1056
00:50:20,520 --> 00:50:24,080
Speaker 10: About buying houses and instead of the Wall Street players

1057
00:50:24,320 --> 00:50:27,319
Speaker 10: who gorged on synthetic derivatives. And you know, again we're

1058
00:50:27,320 --> 00:50:30,719
Speaker 10: told to your point, Crystal, that yeah, inflation is you know,

1059
00:50:30,840 --> 00:50:34,080
Speaker 10: the cause of is the result of having you know,

1060
00:50:34,280 --> 00:50:36,319
Speaker 10: helped people who were thrown out of work or who

1061
00:50:36,360 --> 00:50:39,239
Speaker 10: couldn't pay their bills, and you know, they went out

1062
00:50:39,280 --> 00:50:41,920
Speaker 10: and just extravagantly blew it all on pelotons and the

1063
00:50:41,960 --> 00:50:44,800
Speaker 10: supply chain couldn't handle it. Now we're dealing with inflation.

1064
00:50:45,520 --> 00:50:50,360
Speaker 10: I mean, the reality is that engineered scarcity is part

1065
00:50:50,640 --> 00:50:54,839
Speaker 10: of our global economy, and monopoly power is not some

1066
00:50:54,880 --> 00:50:59,040
Speaker 10: sort of accident. It's the result of corporate strategies. And

1067
00:50:59,320 --> 00:51:02,440
Speaker 10: you know, in fact, I tell the story of how

1068
00:51:03,160 --> 00:51:08,239
Speaker 10: the Trump administration used an executive order to keep workers

1069
00:51:08,360 --> 00:51:12,120
Speaker 10: laboring in slaughterhouses, even when it was very clear that

1070
00:51:12,160 --> 00:51:15,320
Speaker 10: they were super spreaders. When local public health authorities across

1071
00:51:15,360 --> 00:51:17,759
Speaker 10: the country said, we've got to shut these plants down.

1072
00:51:18,000 --> 00:51:19,120
Speaker 6: People are getting sick.

1073
00:51:18,960 --> 00:51:23,600
Speaker 10: And the Trump administration dropped this executive order that forced,

1074
00:51:23,960 --> 00:51:26,680
Speaker 10: among others, a woman whose story I tell in the book,

1075
00:51:26,719 --> 00:51:29,680
Speaker 10: a refugee from meandmar named Tin I, who kept going

1076
00:51:29,719 --> 00:51:31,520
Speaker 10: to work, was one of five people who died at

1077
00:51:31,560 --> 00:51:35,320
Speaker 10: the Greeley, Colorado plant owned by JBS Foods. This is

1078
00:51:35,360 --> 00:51:38,719
Speaker 10: the world's largest meat packer. It's run by two convicted

1079
00:51:38,760 --> 00:51:43,640
Speaker 10: felons from Brazil who fraudulently amassed tens of billions of

1080
00:51:43,640 --> 00:51:47,000
Speaker 10: dollars to buy up slaughterhouses for companies control eighty five

1081
00:51:47,040 --> 00:51:50,120
Speaker 10: percent of the meat packing capacity in the United States.

1082
00:51:50,360 --> 00:51:53,160
Speaker 10: And the cynicism of this executive order was premised on

1083
00:51:53,200 --> 00:51:55,839
Speaker 10: the idea that if we don't keep people laboring in slaughterhouses,

1084
00:51:55,880 --> 00:51:58,920
Speaker 10: Americans are going to go hungry. And in fact, as

1085
00:51:58,960 --> 00:52:01,040
Speaker 10: I reveal in the book, at the time when this

1086
00:52:01,280 --> 00:52:04,719
Speaker 10: order drops, the meat packers including JBS, are sitting on

1087
00:52:04,840 --> 00:52:10,200
Speaker 10: record volumes of frozen product. They're exporting product to China,

1088
00:52:10,239 --> 00:52:15,239
Speaker 10: among other places. So we asked Tini and other slaughterhouse

1089
00:52:15,280 --> 00:52:19,640
Speaker 10: workers to sacrifice their lives in the name of feeding everyone.

1090
00:52:19,800 --> 00:52:23,400
Speaker 10: Where really we were just funneling fattern profits to monopoly companies.

1091
00:52:23,680 --> 00:52:26,880
Speaker 10: And that is the reveal of this book again and

1092
00:52:26,960 --> 00:52:31,360
Speaker 10: again that we blame, to your point, truck drivers for

1093
00:52:31,440 --> 00:52:35,799
Speaker 10: somehow losing their appetite for driving trucks. We've got ten

1094
00:52:35,880 --> 00:52:38,440
Speaker 10: times I'm sorry, We've got three times as many people

1095
00:52:38,600 --> 00:52:42,400
Speaker 10: as we need with commercial driver's licenses in the United States.

1096
00:52:42,800 --> 00:52:45,000
Speaker 10: Why is it that so many people walk away from

1097
00:52:45,120 --> 00:52:47,799
Speaker 10: truck driving? Well, I spent three days riding along with

1098
00:52:47,840 --> 00:52:50,719
Speaker 10: the truck driver from Kansas City down to Dallas and

1099
00:52:50,760 --> 00:52:52,719
Speaker 10: back in the middle of winter. And boy, I can

1100
00:52:52,719 --> 00:52:54,600
Speaker 10: tell you from having slept in the bunk for a

1101
00:52:54,640 --> 00:52:57,520
Speaker 10: couple of nights, from being there as this driver is

1102
00:52:57,520 --> 00:53:00,120
Speaker 10: worrying about where's.

1103
00:52:59,120 --> 00:52:59,840
Speaker 6: He going to park.

1104
00:53:00,400 --> 00:53:02,799
Speaker 10: He's got to caffeinate enough to not fall asleep at

1105
00:53:02,840 --> 00:53:04,799
Speaker 10: the wheel, but not so much that he has to

1106
00:53:04,800 --> 00:53:06,160
Speaker 10: stop and use the restroom.

1107
00:53:06,600 --> 00:53:07,880
Speaker 6: I mean, these are the sorts.

1108
00:53:07,640 --> 00:53:10,640
Speaker 10: Of thoughts that fill the heads of people were entrusting

1109
00:53:10,640 --> 00:53:12,800
Speaker 10: to deliver stuff while we're asking them to be away

1110
00:53:12,800 --> 00:53:16,239
Speaker 10: from their families, to have less and less control over

1111
00:53:16,280 --> 00:53:19,279
Speaker 10: their schedules, to be at the mercy of this just

1112
00:53:19,320 --> 00:53:22,279
Speaker 10: in time system where we basically treat them like their

1113
00:53:22,320 --> 00:53:26,040
Speaker 10: own time and their family time is limitless and valueless.

1114
00:53:26,680 --> 00:53:28,560
Speaker 2: Yeah, I mean, Peter, one of the things that you

1115
00:53:28,600 --> 00:53:31,040
Speaker 2: write about is that, and also that they mentioned in

1116
00:53:31,080 --> 00:53:33,000
Speaker 2: their view, you know naive enough to think that this

1117
00:53:33,120 --> 00:53:34,880
Speaker 2: is just going to go away, But we are going

1118
00:53:34,920 --> 00:53:37,280
Speaker 2: to have to reach some equilibrium. What does the future

1119
00:53:37,280 --> 00:53:37,640
Speaker 2: look like.

1120
00:53:38,719 --> 00:53:40,920
Speaker 10: I mean, we're going to we have to welcome this

1121
00:53:41,000 --> 00:53:45,520
Speaker 10: labor mobilization. Because Henry Ford, who's a very problematic character,

1122
00:53:45,560 --> 00:53:47,160
Speaker 10: who I he was quite a bit.

1123
00:53:47,040 --> 00:53:47,439
Speaker 6: In the book.

1124
00:53:47,440 --> 00:53:49,440
Speaker 10: He did know a thing or two about supply chains

1125
00:53:49,440 --> 00:53:54,759
Speaker 10: and mass assembly. He said directly, as he doubled wages

1126
00:53:54,840 --> 00:53:58,600
Speaker 10: for workers in nineteen fourteen and was called a communist

1127
00:53:58,640 --> 00:54:01,640
Speaker 10: by parts of the business world, he said, look, I'm

1128
00:54:01,640 --> 00:54:04,040
Speaker 10: a capitalist. I'm trying to make my products, trying to

1129
00:54:04,080 --> 00:54:07,040
Speaker 10: drop the price really low so they can have mass appeal.

1130
00:54:07,640 --> 00:54:10,280
Speaker 10: And I need people showing up for work who aren't

1131
00:54:10,280 --> 00:54:12,560
Speaker 10: worried about paying their own bills and who are happy

1132
00:54:12,560 --> 00:54:14,600
Speaker 10: to be there and feel part of it. It's a

1133
00:54:14,920 --> 00:54:18,359
Speaker 10: and he specifically said, any business that's premised on low

1134
00:54:18,400 --> 00:54:22,319
Speaker 10: wage labor is inherently unreliable. So we should embrace the

1135
00:54:22,400 --> 00:54:26,880
Speaker 10: fact that, you know, rail workers I traveled with traveling

1136
00:54:26,920 --> 00:54:31,839
Speaker 10: maintenance crews, that they've managed to extract some paid sick leave,

1137
00:54:32,000 --> 00:54:36,520
Speaker 10: not enough, but some through Biden's bleed pulpit, resolving their

1138
00:54:36,600 --> 00:54:37,480
Speaker 10: threat of a strike.

1139
00:54:37,880 --> 00:54:40,040
Speaker 6: We should we should be happy that dock.

1140
00:54:39,880 --> 00:54:42,480
Speaker 10: Workers, who are often treated as sort of aristocrats or

1141
00:54:42,600 --> 00:54:44,880
Speaker 10: the supply chain, you know, their only move is to

1142
00:54:45,280 --> 00:54:48,520
Speaker 10: threaten to monkey wrench the supply chain to get more

1143
00:54:48,640 --> 00:54:51,120
Speaker 10: job security in the face of automation. We should be

1144
00:54:51,160 --> 00:54:53,080
Speaker 10: glad that they're well paid. I mean, those those are

1145
00:54:53,160 --> 00:54:56,120
Speaker 10: tough jobs. Truck driving has always been a difficult job.

1146
00:54:56,320 --> 00:54:59,960
Speaker 10: But back when the teamsters weren't charge, you know, another problematicgainst,

1147
00:55:00,520 --> 00:55:04,960
Speaker 10: but nonetheless an illustration of what happens to wages and

1148
00:55:05,040 --> 00:55:08,600
Speaker 10: working conditions when there's strong labor power. We didn't have

1149
00:55:08,680 --> 00:55:11,319
Speaker 10: a shortage of truck drivers back when the teamsters were

1150
00:55:11,320 --> 00:55:12,840
Speaker 10: in charge. So we don't want to go back to

1151
00:55:12,920 --> 00:55:15,480
Speaker 10: the seventies. We don't want the government setting the prices

1152
00:55:15,520 --> 00:55:18,080
Speaker 10: of everything, but we need more transparency in the market.

1153
00:55:18,520 --> 00:55:22,759
Speaker 10: We need the international shipping cartel, something we haven't talked about.

1154
00:55:22,800 --> 00:55:26,520
Speaker 10: You know, there's basically three alliances, like air alliances, that

1155
00:55:26,680 --> 00:55:30,960
Speaker 10: dominate the most lucrative routes across the Pacific and from

1156
00:55:31,000 --> 00:55:35,360
Speaker 10: Asia to Europe. We need regulations so that these entities

1157
00:55:35,360 --> 00:55:38,240
Speaker 10: are treated more like utilities. I mean, utilities make money,

1158
00:55:38,440 --> 00:55:41,920
Speaker 10: their profit making entities. But we understand that electricity is

1159
00:55:41,920 --> 00:55:43,920
Speaker 10: really vital. We don't think about it much, but when

1160
00:55:43,920 --> 00:55:45,960
Speaker 10: it fails, we sure do. And we need to take

1161
00:55:46,000 --> 00:55:49,600
Speaker 10: the same approach to these crucial components of the supply chain.

1162
00:55:51,160 --> 00:55:53,359
Speaker 1: I have a media question for you, which is I'm

1163
00:55:53,360 --> 00:55:57,600
Speaker 1: thinking specifically about the meat shortage thing, which I saw covered,

1164
00:55:57,719 --> 00:56:00,560
Speaker 1: you know, credulously across a lot of meat outlets of

1165
00:56:00,640 --> 00:56:02,280
Speaker 1: oh my god, there's going to be a meat shortage,

1166
00:56:02,320 --> 00:56:03,799
Speaker 1: and oh, I guess we just have to keep these

1167
00:56:03,840 --> 00:56:04,560
Speaker 1: letterhouses going.

1168
00:56:04,600 --> 00:56:05,279
Speaker 3: What are you going to do?

1169
00:56:05,960 --> 00:56:07,640
Speaker 1: You may have written about it and I missed it,

1170
00:56:07,719 --> 00:56:09,960
Speaker 1: but I didn't see reported anywhere what you just said

1171
00:56:09,960 --> 00:56:13,080
Speaker 1: about how actually they were sitting on this tremendous surplus

1172
00:56:13,120 --> 00:56:14,719
Speaker 1: that they were, you know, selling to China and had

1173
00:56:14,760 --> 00:56:15,760
Speaker 1: frozen and.

1174
00:56:15,600 --> 00:56:16,480
Speaker 2: Freezers and whatever.

1175
00:56:16,800 --> 00:56:19,200
Speaker 3: This was never actually going to be an issue. So

1176
00:56:20,040 --> 00:56:20,640
Speaker 3: why is that?

1177
00:56:20,840 --> 00:56:22,560
Speaker 1: Why was the oh we're going to run out of

1178
00:56:22,560 --> 00:56:24,480
Speaker 1: bacon and we're going to run on a pork story?

1179
00:56:24,840 --> 00:56:27,000
Speaker 1: Why did so much of the media run with that

1180
00:56:27,200 --> 00:56:29,440
Speaker 1: and not actually even do just the basics of checking,

1181
00:56:29,560 --> 00:56:31,400
Speaker 1: like is this even actually true?

1182
00:56:31,960 --> 00:56:34,759
Speaker 10: Well, I think it would have been hard to check

1183
00:56:34,840 --> 00:56:37,160
Speaker 10: the part about the surplus in real time, because it

1184
00:56:37,200 --> 00:56:42,480
Speaker 10: took Congress actually using its power to demand documents to

1185
00:56:43,280 --> 00:56:46,279
Speaker 10: produce some emails that brought that home. But I will

1186
00:56:46,320 --> 00:56:48,319
Speaker 10: say this, you know, I mean it's not just my

1187
00:56:48,520 --> 00:56:52,520
Speaker 10: colleagues and the media, it's also you know, mainstream economists.

1188
00:56:52,560 --> 00:56:56,280
Speaker 10: I mean, we like to think about supply and demand

1189
00:56:56,360 --> 00:56:58,799
Speaker 10: because we learned about it in textbooks in college and

1190
00:56:58,840 --> 00:57:02,200
Speaker 10: grad school. And let's face it, supply and demand is

1191
00:57:02,239 --> 00:57:05,440
Speaker 10: a really beautiful model that does explain certainly part of

1192
00:57:05,480 --> 00:57:11,120
Speaker 10: these supply chain shocks. I think that market concentration and

1193
00:57:11,239 --> 00:57:14,040
Speaker 10: monopoly power, you know, these are things that we're kind

1194
00:57:14,040 --> 00:57:17,160
Speaker 10: of trained not to think about. And the economists who

1195
00:57:17,160 --> 00:57:20,520
Speaker 10: are easiest for beat reporters to get hold of generally

1196
00:57:20,560 --> 00:57:23,400
Speaker 10: work for companies that are interested in making equities go up.

1197
00:57:23,440 --> 00:57:25,280
Speaker 10: I mean, that's just the reality. That's not some sort

1198
00:57:25,320 --> 00:57:28,680
Speaker 10: of conspiracy. That's just the reality that a reporter who's

1199
00:57:28,720 --> 00:57:31,240
Speaker 10: on deadline, who needs an economist to make sense of

1200
00:57:31,320 --> 00:57:34,280
Speaker 10: some arcane subject that they don't really know about they

1201
00:57:34,280 --> 00:57:35,920
Speaker 10: need to get expert enough to write about in the

1202
00:57:35,920 --> 00:57:39,600
Speaker 10: next fifteen minutes, can easily get hold of somebody at

1203
00:57:39,600 --> 00:57:42,520
Speaker 10: a bank that's invested in making equities go up to

1204
00:57:42,520 --> 00:57:45,160
Speaker 10: go find somebody who really understands monopoly power. There's a

1205
00:57:45,160 --> 00:57:47,880
Speaker 10: good chance to that person is that some nonprofit and

1206
00:57:47,880 --> 00:57:51,800
Speaker 10: they're busy dealing with some sick kid who's home from school, or.

1207
00:57:51,760 --> 00:57:53,280
Speaker 6: You know, they can't afford child kids.

1208
00:57:53,360 --> 00:57:56,760
Speaker 10: I mean, there's just friction in the system there, and

1209
00:57:57,000 --> 00:57:59,480
Speaker 10: so it's not something that we're trained to think about much.

1210
00:57:59,720 --> 00:58:03,320
Speaker 10: Once you start to see monopoly power in the economy,

1211
00:58:03,440 --> 00:58:04,600
Speaker 10: you can't unsee it.

1212
00:58:05,840 --> 00:58:07,520
Speaker 6: Once you're there, you're there.

1213
00:58:07,520 --> 00:58:10,280
Speaker 10: And I do hope that my book will be part

1214
00:58:10,440 --> 00:58:13,400
Speaker 10: of I think a movement amongst those of us thinking

1215
00:58:13,480 --> 00:58:16,240
Speaker 10: about it to bring that home for people. And I

1216
00:58:16,240 --> 00:58:18,200
Speaker 10: hope no one will ever see a package that lands

1217
00:58:18,240 --> 00:58:20,280
Speaker 10: at their door, you know, the same ever again.

1218
00:58:20,440 --> 00:58:24,320
Speaker 1: And my last question Peter Is. You know, obviously you

1219
00:58:24,400 --> 00:58:26,160
Speaker 1: learned a lot. Your book is helping us learn a

1220
00:58:26,160 --> 00:58:29,520
Speaker 1: lot about what actually went wrong during the pandemic, about

1221
00:58:29,520 --> 00:58:35,160
Speaker 1: how this almost like religious devotion to cutting inventory created

1222
00:58:35,240 --> 00:58:37,720
Speaker 1: all this fragility that you know, wasn't in the interest

1223
00:58:37,720 --> 00:58:40,640
Speaker 1: of anyone, wasn't even in the interest medium to long

1224
00:58:40,760 --> 00:58:43,959
Speaker 1: term interest of these these companies that were so you know.

1225
00:58:43,920 --> 00:58:45,680
Speaker 3: Devoted to that direction.

1226
00:58:46,160 --> 00:58:49,080
Speaker 1: But do you think that in a deeper sense, like

1227
00:58:49,240 --> 00:58:54,400
Speaker 1: the country, those companies, policymakers actually learned anything from what

1228
00:58:54,480 --> 00:58:57,000
Speaker 1: should have been an incredibly searing experience.

1229
00:58:57,960 --> 00:58:59,960
Speaker 6: I think policy makers have learned something.

1230
00:59:00,040 --> 00:59:02,120
Speaker 10: I mean, I think it's not an accident that the

1231
00:59:02,120 --> 00:59:05,240
Speaker 10: Biden administration is now engaging in industrial policy, whatever you

1232
00:59:05,280 --> 00:59:08,320
Speaker 10: think about that, and we're spending tens of billions of

1233
00:59:08,360 --> 00:59:11,240
Speaker 10: dollars in subsidies to make sure that computer chips are

1234
00:59:11,240 --> 00:59:14,320
Speaker 10: made in the United States. There's a concerted effort to

1235
00:59:14,320 --> 00:59:17,760
Speaker 10: make sure that the electric vehicle industry has time to

1236
00:59:17,840 --> 00:59:19,919
Speaker 10: develop in the US, which is why there are trade

1237
00:59:19,960 --> 00:59:23,560
Speaker 10: protections against Chinese imports. Again, reasonable people can disagree about

1238
00:59:23,560 --> 00:59:25,560
Speaker 10: the permutations of this. I mean, I talk to people

1239
00:59:25,600 --> 00:59:27,320
Speaker 10: all the time who say climate change is not going

1240
00:59:27,400 --> 00:59:29,880
Speaker 10: to wait for us to sort out the trading rules.

1241
00:59:29,920 --> 00:59:32,160
Speaker 10: You know, we need to buy what's needed right now

1242
00:59:32,200 --> 00:59:35,440
Speaker 10: to deal with that crisis. But clearly there's been a

1243
00:59:35,600 --> 00:59:39,640
Speaker 10: policy shift in the United States in terms of the

1244
00:59:39,760 --> 00:59:43,640
Speaker 10: people who run publicly traded corporations. Yes, there's a push

1245
00:59:43,680 --> 00:59:47,240
Speaker 10: to diversify away from heavy reliance on China.

1246
00:59:47,320 --> 00:59:48,880
Speaker 6: I mean, I just came back from a couple of weeks.

1247
00:59:48,720 --> 00:59:53,840
Speaker 10: In India where Walmart is shifting production that used to

1248
00:59:53,840 --> 00:59:54,360
Speaker 10: be in China.

1249
00:59:54,400 --> 00:59:55,880
Speaker 6: It's not an abandonment of China.

1250
00:59:55,960 --> 00:59:58,080
Speaker 10: China is going to continue to be, you know, right

1251
00:59:58,120 --> 01:00:00,880
Speaker 10: at the center of global manufacturing. It's a sort of

1252
01:00:01,360 --> 01:00:04,240
Speaker 10: marginal shift. I mean, fifteen years ago, if you flew

1253
01:00:04,280 --> 01:00:06,400
Speaker 10: down to Bentonville, Arkansas, and you were trying to get

1254
01:00:06,400 --> 01:00:10,800
Speaker 10: your product on the shelf of a superstore, the Walmart

1255
01:00:10,880 --> 01:00:13,080
Speaker 10: buyer would ask you, well, where's this product made? And

1256
01:00:13,120 --> 01:00:15,280
Speaker 10: if the answer was something other than China, you had

1257
01:00:15,320 --> 01:00:18,080
Speaker 10: a problem because that indicated that you weren't making it

1258
01:00:18,160 --> 01:00:21,120
Speaker 10: at the cheapest possible price or at the most efficient scale.

1259
01:00:21,280 --> 01:00:23,760
Speaker 10: And now if the answer is only China, you have

1260
01:00:23,800 --> 01:00:28,640
Speaker 10: a problem. That's viewed as you're putting us at risk

1261
01:00:28,720 --> 01:00:30,880
Speaker 10: of these geopolitical ships. I mean, you got the Trump

1262
01:00:30,960 --> 01:00:35,240
Speaker 10: tariffs on imports from China. Now the Biden tariffs continued.

1263
01:00:35,400 --> 01:00:38,120
Speaker 10: Whoever wins the presidential election in November, you could pretty

1264
01:00:38,160 --> 01:00:41,400
Speaker 10: much count on trade animosity between the US and China continuing.

1265
01:00:41,400 --> 01:00:44,440
Speaker 6: You got the shipping crisis. So these things are changing.

1266
01:00:44,480 --> 01:00:46,680
Speaker 10: But you know, as I say in the book, I

1267
01:00:46,760 --> 01:00:50,400
Speaker 10: am dubious that the further away we get from the pandemic,

1268
01:00:50,920 --> 01:00:54,200
Speaker 10: this will stick. Because the simple fact is that if

1269
01:00:54,240 --> 01:00:57,560
Speaker 10: you are running a company that's publicly traded and you're

1270
01:00:57,640 --> 01:01:02,360
Speaker 10: suggesting that we move production away from the lowest cost provider,

1271
01:01:02,480 --> 01:01:05,000
Speaker 10: or we think about more redundancy, or let's put more

1272
01:01:05,080 --> 01:01:08,520
Speaker 10: parts in a warehouse, you're essentially arguing, let's dilute the

1273
01:01:08,560 --> 01:01:11,320
Speaker 10: next quarter's earnings. And Wall Street might punish you for that,

1274
01:01:11,640 --> 01:01:15,000
Speaker 10: and by the time some crisis happens that will reveal

1275
01:01:15,200 --> 01:01:17,560
Speaker 10: that we should all be grateful that you took these steps.

1276
01:01:17,680 --> 01:01:19,120
Speaker 6: It's a good chance you're out of a job.

1277
01:01:19,160 --> 01:01:22,280
Speaker 10: Whereas if you're still saying, let's carry on with the

1278
01:01:22,280 --> 01:01:24,440
Speaker 10: same sort of globalization that we've all lived through for

1279
01:01:24,480 --> 01:01:27,200
Speaker 10: the last three decades, there will be a shock. I mean,

1280
01:01:27,240 --> 01:01:29,840
Speaker 10: there will be another pandemic, a typhoon. You know, who

1281
01:01:29,920 --> 01:01:32,560
Speaker 10: knows something we're not thinking about that will reveal that

1282
01:01:33,000 --> 01:01:36,160
Speaker 10: as folly. But with any luck, by then you know,

1283
01:01:36,200 --> 01:01:38,520
Speaker 10: you'll be on some beach, you know, in a hammock

1284
01:01:38,680 --> 01:01:39,680
Speaker 10: hoisting a cocktail.

1285
01:01:39,960 --> 01:01:41,439
Speaker 6: It'll happen on somebody else's watch.

1286
01:01:41,480 --> 01:01:45,760
Speaker 10: And that short termism that has driven our particular kind

1287
01:01:45,800 --> 01:01:48,560
Speaker 10: of capitalism and globalization is still with us.

1288
01:01:49,000 --> 01:01:49,320
Speaker 3: Yeah.

1289
01:01:49,400 --> 01:01:52,000
Speaker 1: I mean, basically, if you're arguing for those sorts of redundancies,

1290
01:01:52,120 --> 01:01:55,040
Speaker 1: because so much of executive compensation is tied to the

1291
01:01:55,080 --> 01:01:57,720
Speaker 1: stock price, you're basically arguing for cutting your own pay,

1292
01:01:57,800 --> 01:02:02,320
Speaker 1: which they are probably pretty unlikely to go in that direction.

1293
01:02:02,640 --> 01:02:03,880
Speaker 1: I just want to say to people, it is a

1294
01:02:03,880 --> 01:02:04,600
Speaker 1: wonky subject.

1295
01:02:04,600 --> 01:02:05,800
Speaker 3: It's a very readable book.

1296
01:02:06,200 --> 01:02:09,800
Speaker 1: You take us through a small businessman in what was

1297
01:02:09,840 --> 01:02:13,080
Speaker 1: in Mississippi trying to get his product manufactured and time

1298
01:02:13,120 --> 01:02:15,480
Speaker 1: for Christmas, and you use that as a story to

1299
01:02:15,520 --> 01:02:17,880
Speaker 1: go through each of these pieces of the supply chain

1300
01:02:17,880 --> 01:02:21,040
Speaker 1: which completely collapsed during COVID, and help us make sense

1301
01:02:21,280 --> 01:02:23,400
Speaker 1: retrospectively of some of the things we were experiencing in

1302
01:02:23,400 --> 01:02:25,320
Speaker 1: our own lives and draw some lessons from the future.

1303
01:02:25,320 --> 01:02:27,520
Speaker 1: I really highly recommend it and I really appreciate you,

1304
01:02:27,520 --> 01:02:29,040
Speaker 1: Peter taking some time with us this morning.

1305
01:02:29,120 --> 01:02:31,360
Speaker 6: Appreciate Oh, I really appreciate you guys. Thank you so

1306
01:02:31,440 --> 01:02:32,600
Speaker 6: much for your excellent questions.

1307
01:02:32,920 --> 01:02:34,000
Speaker 3: It's our pleasure, all right.

1308
01:02:34,040 --> 01:02:35,360
Speaker 2: Thank you guys so much for watching with a great

1309
01:02:35,360 --> 01:02:37,120
Speaker 2: show for everyone tomorrow, and we'll see you all later