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Speaker 1: Hi, I'm Molly John Fast and this is Fast Politics,

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Speaker 1: where we discussed the top political headlines with some of

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Speaker 1: today's best minds, and the Supreme Court will decide if

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Speaker 1: Trump's birthright citizenship order can stand. We have such a

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Speaker 1: great job for you today. Think like an economist. Justin

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Speaker 1: Wolfers stops by to talk about the bad economic vibes

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Speaker 1: coming from the Trump administration. Then we'll talk to The

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Speaker 1: New York Times owner Peter S. Goodman about Costco's lawsuit

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Speaker 1: against the Trump administration or the tariff policies harm to

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Speaker 1: their businesses. But first the news.

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Speaker 2: Miley, this is really exciting.

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Speaker 3: You and I have been working for months on a

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Speaker 3: series where we're going to start a conversation on the

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Speaker 3: DEM's Project twenty twenty nine and what they should do

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Speaker 3: when they regain power, because Republicans were really prepared and

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Speaker 3: we want to be too. So you and I have

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Speaker 3: been talking to some very smart people. It's time for

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Speaker 3: our audience to hear about it. Are you excited?

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Speaker 1: We did something like this about Project twenty twenty five,

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Speaker 1: about the Republicans Project twenty twenty five, and we were

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Speaker 1: like one of the first people to get on that

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Speaker 1: story and By the way, Donald Trump was like, no,

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Speaker 1: I don't want to do it. I'm just kidding, and

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Speaker 1: everyone's like, okay, he's not going to do it. So

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Speaker 1: it was very frustrating for all of us. This is

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Speaker 1: very different. We are just talking to some really smart academics.

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Speaker 1: We're sort of spitballing how to solve these problems. I

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Speaker 1: want to say this is not the official anything for

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Speaker 1: Project twenty twenty nine. We're just trying to get the

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Speaker 1: ball rolling, get people thinking about broad sweeping anti corruption

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Speaker 1: legislation the way that was passed after Nixon. There was

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Speaker 1: a real failure I think on the part of the

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Speaker 1: Biden administration to pass those kind of broad sweeping anti

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Speaker 1: corruption legislations. You know, the problem was so much of

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Speaker 1: what we see in Washington d c our norms and

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Speaker 1: not laws. And the problem with the norm is it's

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Speaker 1: fine if you have someone who is a sort of

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Speaker 1: normal president because they observe the norms. But when you

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Speaker 1: have a Donald Trump and you get norms, they just

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Speaker 1: run right through them because they say, well, it's not illegal,

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Speaker 1: so who cares. And that is why we're trying to

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Speaker 1: get people talking about this. This first topic of campaign

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Speaker 1: finance reform seems very unsexy, but it's actually the nuts

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Speaker 1: and baults of everything else that follows. If you have

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Speaker 1: candidates who are funded by crypto or by tech companies,

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Speaker 1: or by cigarette companies though that is not really the

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Speaker 1: thing anymore, or by oil companies, then those politicians end

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Speaker 1: up just serving those interests. And that's why Campaign finance

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Speaker 1: reform is why we started, and we talked to some really,

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Speaker 1: really smart people who just gave us ideas on how

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Speaker 1: to get things going. It is probably the best thing

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Speaker 1: we have ever done.

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Speaker 3: I think some of the parts that are coming out

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Speaker 3: even after this are some of the best things we've

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Speaker 3: ever done. This one's like amazing, and then I'm so

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Speaker 3: excited for the audience to see the rest of it

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Speaker 3: because I really am so proud of it.

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Speaker 1: You're never going to find forty five minutes on campaign finance.

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Speaker 3: Reform, but there's really answers in there. There's things people

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Speaker 3: haven't heard before. I'm Mike one of the people. I've

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Speaker 3: read more about this than ninety nine point nine nine

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Speaker 3: nine percent of people, and I still learned a lot.

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Speaker 1: So if you want to nerd out, go over to

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Speaker 1: our YouTube and nerd out with us.

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Speaker 2: And please share it with a friend and discuss it.

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Speaker 1: Share it with a friend who loves campaign finance reform.

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Speaker 1: If you know someone nerdy, share it with them. Please.

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Speaker 3: All right, Molly, let's get down to brass texts, and

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Speaker 3: by that I mean brass techie decorations inside Epstein Island.

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Speaker 1: It's pretty weak. We were talking about nerdy. Yes, continue listen.

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Speaker 2: My humor is appreciated by a few listeners.

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Speaker 1: Yes.

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Speaker 3: Anyway, So a judge is going to release the Jeffrey

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Speaker 3: Epstein grand jury documents. Robert Garcia's Oversight Committee released some

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Speaker 3: of the more disturbing photos of this estee trudge this week.

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Speaker 1: Jesse is talking about the dents chair.

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Speaker 3: I even think they'll above the fireplace painting is one

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Speaker 3: of the scariest things I've ever seen.

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Speaker 1: We had on this podcast. Robert Garcia. He is our

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Speaker 1: buddy and we love him. He is the ranking member

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Speaker 1: of Oversight, and he is proof that if you put

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Speaker 1: someone on committees, to head committees who is actually young

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Speaker 1: and enthusiastic and wants to do the work and knows

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Speaker 1: how to push the message, they will do it. And

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Speaker 1: you know why we keep seeing Epstein in the news.

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Speaker 1: Jesse do you know.

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Speaker 3: Why smart tacticians like Robert Garcia and Rocanna.

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Speaker 1: All they do is talk about it, and all they

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Speaker 1: do is release stuff, and all they do is trip

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Speaker 1: drip up, and so good for him, good good good.

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Speaker 1: Here we go. So the judge is going to release

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Speaker 1: the Epstein grand jury documents. Grand jury documents, they tend

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Speaker 1: to have a lot of a pretty high level of redaction.

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Speaker 1: So I think you're going to get more from other stuff.

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Speaker 1: But it's certainly possible, yep.

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Speaker 3: Speaking of the Epstein cover up, you may recall a

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Speaker 3: character used to refer to as Big Govan Bongo Dan Bongino.

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Speaker 3: Who now is that the FBI. He talked to mister

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Speaker 3: Hennity last night and many people are saying he gave

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Speaker 3: away the game.

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Speaker 4: Let's listen, remember this.

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Speaker 5: Just before you became the deputy FBI director. You put

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Speaker 5: a post on x right after this happened, and you said,

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Speaker 5: there's a massive cover up because the person that planted

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Speaker 5: those pipe bombs, they don't want you to know who

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Speaker 5: it is because it's either a connected anti Trump insider

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Speaker 5: or an inside job. You said that, you know, long

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Speaker 5: before you even thought of as deputy FBI director.

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Speaker 6: Yeah, That's why I said to you this investigations just begun.

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Speaker 6: We are pretty comfortable we have our guy. I think

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Speaker 6: is again legal process starts to service and information facts

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Speaker 6: start to come out. The public is going to be

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Speaker 6: very comfortable with the investigation that was conducted under Director

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Speaker 6: Patel and his leadership. He's been great on this, but

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Speaker 6: I don't want to You know, listen, I was paid

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Speaker 6: in the past, Sean for my opinions. That's clear, and

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Speaker 6: one day I'll be back in that space. But that's

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Speaker 6: not what I'm paid for now. I'm paid to be

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Speaker 6: your deputy director, and we base investigations on facts.

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Speaker 4: And you know, it was interesting.

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Speaker 6: I was looking out in the crowd today at the presser.

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Speaker 2: That sounds like the sound of joy Molly.

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Speaker 1: Okay, So he's saying I was paid to make shit

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Speaker 1: up and to have opinions and to outrage bait. By

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Speaker 1: the way, can you believe this fucking guy is deputy

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Speaker 1: director of the FBI.

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Speaker 2: It is one of the many horrors of this administration.

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Speaker 1: Now he uses our tax dollars to just get around. No,

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Speaker 1: that's his boss cash Battel.

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Speaker 3: Well, what you heard today is is boss cash Baitel

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Speaker 3: gets his girlfriend's drug, friend's hope safe, FBI paid ubers.

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Speaker 1: Yeah, it's all so fucking bad, but it is great

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Speaker 1: that the FBI just keeps leaking and Lencoln. So look,

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Speaker 1: I think none of us should be surprised to know

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Speaker 1: that Bngino is taking liberties. And that was his job

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Speaker 1: was to juice the algorithm and to outrage bait, and

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Speaker 1: now his job is to I don't know. I can't

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Speaker 1: even think of Jesse.

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Speaker 3: I'll move on to a much greater pastures. I'm going

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Speaker 3: to shock you here. Pete tig Sith, seems like you

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Speaker 3: whired about the boat bombing.

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Speaker 1: Yeah, now I'm going to say that, Actually, what's worse

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Speaker 1: than Pete Hegseth lying about the boat bombing is everybody's

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Speaker 1: favorite Tom Cotton lying about the video he saw right,

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Speaker 1: Because Tom Cotton was like, it's totally exonerated, and everyone

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Speaker 1: else was like what we saw was bad shit.

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Speaker 3: Do you mean to tell me Tom Cotton thought doing

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Speaker 3: a war crime was justified?

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Speaker 2: That doesn't seem like him.

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Speaker 1: It's ironic because Tom Cotton loves war. But it's also

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Speaker 1: like the other thing about is did Tom Cotton think

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Speaker 1: no one would ever see it? Like I mean that

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Speaker 1: kind of brazen lying. I have a lot of respect

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Speaker 1: for that kind of lying. And yet I'm kidding, do

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Speaker 1: we still do fuck that guy? Because Tom Cotton?

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Speaker 2: Yeah, not a fan.

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Speaker 1: Not a fan.

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Speaker 3: This is not looking good as next week, Representative shre

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Speaker 3: Thanadar will be putting impeachment motions against Whiskey Pete.

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Speaker 1: Yeah, you got impeach Whiskey Pete. I mean, I don't

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Speaker 1: know that Trump ever fires him, but you still got

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Speaker 1: to get on the record for impeaching that guy.

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Speaker 4: Yeah.

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Speaker 3: Yeah, they got to take the stand and make people

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Speaker 3: vote that they're keeping this guy because I'm going to

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Speaker 3: tell you something, this is going to be his last scandal.

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Speaker 1: Oh yeah, Whiskey Peet.

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Speaker 3: Speaking of never ending cars, we got to talk jerrymandering.

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Speaker 3: The Supreme Court upheld Texas's redistricting map, giving the Republicans

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Speaker 3: a bunch of seats, and now the House in Indiana

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Speaker 3: has passed their redistricting map, but looks like there's trouble ahead.

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Speaker 1: Yeah, so they have a new partisan redistricting setting up

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Speaker 1: a showdown in the Senate or there might not be

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Speaker 1: enough support to send the bills of the governor. I

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Speaker 1: just want to point out that this is so fucking

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Speaker 1: sketchy and sleazy, it would deliver two more GOP seats. Again,

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Speaker 1: all of this stuff works until it doesn't, Right, Like

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Speaker 1: we know the Texas seats are pretty smartly I use

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Speaker 1: that in quotes Jerry Mander to deliver for Republicans. But

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Speaker 1: like all this stuff, you don't get to get more votes.

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Speaker 1: You just make the margins different. So eventually a Jerrymander

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Speaker 1: becomes a dummy Mander. Besides the fact that it's so

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Speaker 1: fucking sleezy, you know, and sketchy and anti democratic, et cetera,

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Speaker 1: et cetera, it is very very very important to realize

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Speaker 1: that like Donald Trump is not popular, right, none of

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Speaker 1: this is popular. He is not popular, the party is

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Speaker 1: not popular. They are hitching their wagonto even more on

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Speaker 1: popularity by doing this, and so like they think they

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Speaker 1: can get around this, but they may actually make everything

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Speaker 1: worderse Over at our YouTube channel, we have some really

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Speaker 1: exciting stuff. Jesse and I have made a documentary. It's

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Speaker 1: called Project twenty twenty nine, a Reimagining. It's a series

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Speaker 1: about how democrats can deliver popular policies when they regain power.

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Speaker 1: The first episode is up now, it's the first part

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Speaker 1: of the series, and we're going to examine what went

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Speaker 1: wrong with some of the Biden administration's approach to policies

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Speaker 1: that may have prevented Democrats from being able to deliver

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Speaker 1: the broad anti corruption legislation that needed to happen, and

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Speaker 1: by the way, that would have prevented some of the

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Speaker 1: corruption we're seeing right now. The first episode dives deep

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Speaker 1: into the first step of fixing American politics. It may

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Speaker 1: sound unsexy, but it's a big, important issue and that

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Speaker 1: big subject is campaign finance reform. For this episode, we

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Speaker 1: talk to some of the smartest people we know, professors

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Speaker 1: and academics, people like Lawrence Lessig, Tiffany Muller, Michael Waldman,

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Speaker 1: and Tom Moore. Republicans were prepared for when they got

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Speaker 1: the levers of power. Democrats need that same kind of preparation.

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Speaker 1: That's why we need to start the conversation on how

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Speaker 1: Democrats can do the same thing. So please head over

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Speaker 1: to our YouTube channel and search Molli Jong Fast Project

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Speaker 1: twenty twenty nine or go to the Fast Politics YouTube

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Speaker 1: channel page and you'll find it there and help us

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Speaker 1: spread the word and stay tuned for more episodes. Justin

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Speaker 1: Wolfer is the host of We Think Like an Economist

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Speaker 1: podcast and a professor at the UNI University of Michigan.

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Speaker 1: Justin Warfer's Molly John Fast, what's happening with the jobs numbers?

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Speaker 7: Who knows?

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Speaker 4: Have you seen him?

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Speaker 6: Now?

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Speaker 7: I've been looking. I looked under my bed, by the bed. Actually,

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Speaker 7: I thought I might have let them under the clothes,

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Speaker 7: I asked, Betsy. We haven't seen them anyway, mate?

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Speaker 4: Why why?

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Speaker 7: I don't think I misplaced them. I think it might

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Speaker 7: be because there was a government shut down for six weeks,

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Speaker 7: which we only allowed essential services to continue, and generating

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Speaker 7: the data that will help guide us towards economic nirvana

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Speaker 7: is not seen as essential. So some of the data

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Speaker 7: was simply never collected for the first time in eighty years.

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Speaker 7: And other parts of the data were collected on a

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Speaker 7: slower timeline, and we're going to see them in two weeks.

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Speaker 7: And so, Molly, I understand. You look like you're on

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Speaker 7: the edge of your seat. You're feeling jittery. You're like,

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Speaker 7: where are my numbers? What's going on with the economy?

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Speaker 7: This is all I can think about and I can

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Speaker 7: sleep last night, so breathe. It's we're coming toward the

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Speaker 7: end of this deep dark data back out.

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Speaker 1: So these jobs numbers are because of the government shut

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Speaker 1: down or.

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Speaker 7: Are laid because of the government check So my guess,

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Speaker 7: Molly is you saw some headlines about week jobs numbers

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Speaker 7: and you want to talk about them. Mm hmm, Okay,

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Speaker 7: let me explain that. Okay, So we have the official

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Speaker 7: government jobs numbers put together by the best statisticians in

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Speaker 7: the world, fantastic, high quality, not perfect, but the least

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Speaker 7: imperfect we have.

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Speaker 1: Do We still have those though, even though Donald Trump

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Speaker 1: fired the head of the Bureau of Labor and.

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Speaker 7: Statistics, we still have lots of very high quality statisticians.

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Speaker 7: We have fewered than we once had, but we have

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Speaker 7: enough that America's economic statistics will continue to be first

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Speaker 7: class as soon as we fund them enough that they

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Speaker 7: can open and publish data. When the government can't do that,

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Speaker 7: everyone starts to look for private sector alternatives. There's one

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Speaker 7: called the ADP Payroll Report. ADP, for many of our

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Speaker 7: members of our audience processes your check, your payroll check

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Speaker 7: each month, and so that means they know a lot

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Speaker 7: about how many people are working, and so they crunch

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Speaker 7: their numbers and come up with another estimate. Now, the

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Speaker 7: problem is the statistical sophistication of the folks there. They

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Speaker 7: don't ADP doesn't print everyone's pay off, and so therefore

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Speaker 7: it's not clear which parts of the economy they do

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Speaker 7: and don't cover, and so therefore their numbers are simply

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Speaker 7: less reliable. Now, one number from ADP is not very exciting,

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Speaker 7: but if you have four numbers in a row, you

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Speaker 7: could sort of start to feel like four noisy numbers.

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Speaker 7: You can average it out and come up with some sense, again,

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Speaker 7: not a perfect sense. We've seen four very weak numbers

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Speaker 7: in a row, so it is left a lot of

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Speaker 7: people on edge when we get the real data that

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Speaker 7: we really know and we really trust. We are currently

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Speaker 7: feeling quite pessimistic. It could be that job growth has slowed,

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Speaker 7: it could have stalled, or we could be in reverse.

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Speaker 1: So we don't know. So we really have nothing. The

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Speaker 1: numbers we have something.

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Speaker 7: We have good reason, some reason to be quite pessimistic

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Speaker 7: about the last few months.

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Speaker 1: Right.

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Speaker 7: There are no certainties in my Worldmarde, there's just guesses.

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Speaker 1: So we have some reason to be pessimistic about the

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Speaker 1: last three months three months, and that reason is because

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Speaker 1: what looks like job lost, yes.

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Speaker 7: Could be overall job loss. And we also know that

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Speaker 7: the DOGE job cuts are finally going to hit the

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Speaker 7: statistics because when they tried to fire them, they got reinstated,

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Speaker 7: and then they had to fire them on a slower thing,

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Speaker 7: and blah blah blah. You know, nothing got done right

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Speaker 7: the first time, if it was even doing right at all,

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Speaker 7: And so we'll see some of those federal government job

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Speaker 7: cuts start to hit the numbers pretty much straight away.

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Speaker 1: Give me a cent of how many people were fired

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Speaker 1: because of DOGE.

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Speaker 7: The last number I saw is we're looking at about

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Speaker 7: one hundred and fifty thousand government jobs in October. Now

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Speaker 7: there may be more to come.

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Speaker 1: Some though, were reinstated, right, like the people who guard

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Speaker 1: the nukes. Yep, right, I mean there were certain people

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Speaker 1: that were fired that we're not supposed to be fired.

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Speaker 7: I honestly, Molly, it's outrageous. These people call themselves small

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Speaker 7: government folks, yet what they want to do is suck

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Speaker 7: on the government tit and put people out the front

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Speaker 7: of our nukes defending it, as if the free market

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Speaker 7: couldn't just do that for us.

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Speaker 1: That's right, Just pay me, We.

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Speaker 7: Need a sarcasm font with an Australian accent.

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Speaker 1: We do. Well, let's just go back to the actual

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Speaker 1: question here, which is, I don't mean to be cranky

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Speaker 1: with you, so we think.

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Speaker 7: Like, well, be cranky.

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Speaker 1: One hundred and twenty five thousand fired, What percentage of

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Speaker 1: which you think well hired? So everyone gets rehired for

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Speaker 1: the three months.

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Speaker 7: So we think that so there's actually many more people fired,

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Speaker 7: a bunch were reinstated. The net is about one hundred

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Speaker 7: and fifty thousand for October.

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Speaker 4: That's all I got for you.

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Speaker 1: Make that makes sense In the larger numbers, like what

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Speaker 1: percentage of government of loss job loss? Is that quite small?

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Speaker 7: So one, it's quite small, and too. The other thing

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Speaker 7: that we want to do when we look at economic

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Speaker 7: statistics is see what the underlying economic forces. Those just

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Speaker 7: dead right. I think that this as a one off

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Speaker 7: to sort of look the other way. So the numbers

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Speaker 7: look bad, they were reflecting a genuine reality that a

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Speaker 7: bunch of public servants lost their job. That reality, of course,

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Speaker 7: is several months old, but it will hit the data.

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Speaker 7: But it doesn't in and of itself tell us much

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Speaker 7: about the economy's underlying momentum.

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Speaker 1: So let's talk about the economy's underlying momentum. There's certainly

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Speaker 1: a number of factors. What is the biggest? So like,

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Speaker 1: Donald Trump is getting blamed for the economy, which is

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Speaker 1: a non partisan activity. Blaming the president for the economy

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Speaker 1: always happens. You don't like it, you shouldn't like it,

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Speaker 1: but it's what happens. It's sometimes true. The president has

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Speaker 1: usually less control over the economy than you would think.

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Speaker 1: That said, Donald Trump has done a couple of things

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Speaker 1: when he came in that seemed like they would have

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Speaker 1: huge economic impact that we might be feeling around now.

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Speaker 1: Is that so talk us through what those things are

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Speaker 1: and what you think the impact is?

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Speaker 4: So far right?

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Speaker 7: So, you know, the president came in actually did very

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Speaker 7: little apart from those for a couple of months. Then

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Speaker 7: he pivoted to tariffs. The big tariff announcement was in April.

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Speaker 7: But then you know, a week later he lost the

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Speaker 7: courage of his convictions and had a ninety day pause. Shockingly,

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Speaker 7: end of the ninety day pause, surprisingly he had not

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Speaker 7: secured ninety deals in ninety days, and you'll be surprised.

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Speaker 7: He then gave himself a twenty four day extension and

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Speaker 7: then eventually put in place a set of tariffs that

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Speaker 7: was remarkably like what we had begun with, and then

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Speaker 7: proceeded to cut them what looks like a somewhat random way,

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Speaker 7: as he would hear various complaints or meet with various

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Speaker 7: foreign leaders. But basically, we've had tariffs now in place

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Speaker 7: for about four months. We've only seen data actually as

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Speaker 7: far as the first one or two months of that.

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Speaker 7: So that's one big thing is what's going on with tariffs?

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Speaker 1: And there's tariffs. Well, I just want you to answer

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Speaker 1: this because I'm actually interested What did she.

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Speaker 7: Just say, I'm actually interested in economics.

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Speaker 1: No, I'm interested in this answer. Let's ahead of verse.

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Speaker 7: I'm actually interested in your next question, mark.

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Speaker 1: What countries are these tariffs? Because like Trump has said

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Speaker 1: a lot of stuff, but like it's hard for me

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Speaker 1: to know what actually happened.

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Speaker 7: The answer is all of them in my native Australia,

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Speaker 7: which is a country that buys more stuff from America

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Speaker 7: than the other way round.

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Speaker 8: There were no.

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Speaker 7: Updates on tariffs for the Hurd and McDonald Islands, and

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Speaker 7: so the penguins there remains in flux. They're not sure

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Speaker 7: whether no news is good news. Tariffs remained remarkably high

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Speaker 7: on China. They went astronomically silly. Then they got back

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Speaker 7: to milly absurd. And actually Canada has very low tariffs,

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Speaker 7: even as the President keeps talking about them, because most

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Speaker 7: trade with Canada falls under the existing free trade agreement.

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Speaker 7: So the tariffs don't affect nearest neighbors, even as we

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Speaker 7: bluster that we're coming after them. So look, there's a

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Speaker 7: lot there. And so that actually leads to an important

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Speaker 7: second shock, which is uncertainty. Uncertainly not just about tariffs.

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Speaker 7: I can tell you that I'm sure this is true

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Speaker 7: with the fancy dinner parties. You go to Molly with

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Speaker 7: titans of industry, that all they do is talking.

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Speaker 1: About I just sitting here drinking my diet coke, and

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Speaker 1: all of a sudden we get titans of industry.

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Speaker 7: I go on, Yes, you don't go to dinner parties.

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Speaker 1: I don't even eat. I just drink die coke.

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Speaker 7: That's amazing, that's okay. But titans of industry who are

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Speaker 7: seen in New York, which I do believe is the

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Speaker 7: city you're coming to us from. Many people also sit

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Speaker 7: around talking about the president, which is do I have

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Speaker 7: the right bathroom policy or will the president come after me?

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Speaker 7: What does dipolicy look like? Or will the President come

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Speaker 7: after me? Am I getting my imports from the right countries?

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Speaker 1: All?

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Speaker 7: Will the President come after me? The poor CEO of

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Speaker 7: Intel walked into the White House and walked out with

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Speaker 7: ten percent less of his company that somehow slid down

399
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Speaker 7: the cushions of the tear Treasury Secretary's couch, never to

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Speaker 7: be seen again.

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Speaker 1: Then Donald Trump bought to a million dollars of debt

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Speaker 1: for Intel. He with his personal money.

403
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Speaker 4: That's terrific.

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Speaker 7: It's nice that he said, help make money.

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Speaker 1: Ways I don't think he's trying to help. That's my

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Speaker 1: hottest take.

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Speaker 7: You are so cynical, So cynical.

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Speaker 1: Okay, So tariffs we'll have a big effect in certain times.

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Speaker 7: Two uncertainty. Three and immigration shock.

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Speaker 1: Let's talk about the immigration shop because.

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Speaker 7: Really big deal, and we don't talk about it enough.

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Speaker 1: We don't have more people being deported, right, we don't

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Speaker 1: because he's because they're very bad at what they do,

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Speaker 1: thank god. So the numbers are not actually higher than

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Speaker 1: they were under Obama or Biden. But they have created

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Speaker 1: things like what we saw in Georgia with the South

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Speaker 1: Korean Car Company plan in which we had Brian camp

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Speaker 1: workerly hard to get this Hondai factory filled with South

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Speaker 1: Koreans who were training American workers. Ice went in there,

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Speaker 1: arrested the South Koreans, put them in a Louisiana detention center,

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Speaker 1: flew them home, and effectively whatever happened.

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Speaker 7: There lots of photographs of executives in chains.

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Speaker 1: Yeah, they didn't like that.

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Speaker 7: And what was really important we didn't see it over

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Speaker 7: here was that was front page news throughout the region

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Speaker 7: and it was interpreted directly as anti Asian racism, which

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Speaker 7: weeks and weeks, yes, and will affect a different part

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Speaker 7: of the economy, which is what we call foreign direct investment,

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Speaker 7: foreign companies building factories in the United States, which is

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Speaker 7: what the President wanted. They won't do that now in

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Speaker 7: case they're dragged out in handcuffs, which is what those

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Speaker 7: foreign companies don't want. It's sort of outrages that they

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Speaker 7: don't want to avoid handcuffs.

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Speaker 1: How dare they?

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Speaker 7: There are certain New York parties I'm told we're wearing

436
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Speaker 7: handcuffs as mandatory, and it's just understood that it's part

437
00:23:04,320 --> 00:23:06,920
Speaker 7: of the invitation. It's not one show in New York

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Speaker 7: amazing place, New York City. All right, So the so

439
00:23:13,480 --> 00:23:16,800
Speaker 7: that's investment, but that's part of it, but that's by

440
00:23:16,840 --> 00:23:18,520
Speaker 7: no means all of it. In fact, it might even

441
00:23:18,560 --> 00:23:21,639
Speaker 7: be a small part. The other is literally fewer people

442
00:23:21,640 --> 00:23:24,360
Speaker 7: in America. And you might be right that they're dragging

443
00:23:24,400 --> 00:23:27,800
Speaker 7: fewer people out through ice detention centers, but very few

444
00:23:27,800 --> 00:23:30,240
Speaker 7: people are coming in and some people are leaving. And

445
00:23:30,280 --> 00:23:34,399
Speaker 7: so American population growth, which has been you can open

446
00:23:34,560 --> 00:23:37,320
Speaker 7: a hot dog stand in any corner of New York

447
00:23:37,680 --> 00:23:39,920
Speaker 7: or indeed any city, and your sales tend to grow

448
00:23:39,960 --> 00:23:42,399
Speaker 7: because there are more people. It's an important source of

449
00:23:42,400 --> 00:23:45,400
Speaker 7: growth for many businesses. There's not going to be more

450
00:23:45,400 --> 00:23:47,400
Speaker 7: people next year. There's not going to be fear it'll

451
00:23:47,400 --> 00:23:50,600
Speaker 7: be about dead. Even that's a very unusual circumstance that

452
00:23:50,680 --> 00:23:53,840
Speaker 7: probably hasn't occurred through your lifetime only. And so that's

453
00:23:53,880 --> 00:23:56,359
Speaker 7: going to mean less growth in demand. It's also going

454
00:23:56,400 --> 00:23:59,199
Speaker 7: to mean problems and supply. This is the story that

455
00:23:59,240 --> 00:24:01,760
Speaker 7: farmers can't get the crops picked right now. So when

456
00:24:01,800 --> 00:24:07,280
Speaker 7: you disrupt what had been a fairly standard slow population growth,

457
00:24:07,320 --> 00:24:10,000
Speaker 7: everything's a little bit different. And so that's going to

458
00:24:10,040 --> 00:24:12,760
Speaker 7: mean many of our economic indicators are not measured on

459
00:24:12,800 --> 00:24:15,439
Speaker 7: a per person basis. For instance, we talk about how

460
00:24:15,440 --> 00:24:17,640
Speaker 7: many jobs do we have, we talk about how much

461
00:24:17,720 --> 00:24:20,520
Speaker 7: GDP we have. If we have not as many people

462
00:24:20,600 --> 00:24:22,520
Speaker 7: or not as much population growth, those numbers are going

463
00:24:22,560 --> 00:24:25,280
Speaker 7: to look worse. They're going to look worse even if

464
00:24:25,320 --> 00:24:27,919
Speaker 7: they aren't worse. That's the first point. But second is

465
00:24:27,960 --> 00:24:30,320
Speaker 7: anytime you have a stark adjustment like that, actually you

466
00:24:30,400 --> 00:24:33,720
Speaker 7: create lots of frictions and may potentially create bottlenecks like

467
00:24:33,920 --> 00:24:35,240
Speaker 7: not being able to pick your crops.

468
00:24:35,600 --> 00:24:38,879
Speaker 1: And you have less people paying into Social Security.

469
00:24:39,119 --> 00:24:42,440
Speaker 7: I would say you had fewer people paying into social Security.

470
00:24:42,960 --> 00:24:48,760
Speaker 1: Well, you are the radar here, so explain what that means.

471
00:24:48,880 --> 00:24:53,520
Speaker 1: These are our people who are taking from government, but

472
00:24:53,600 --> 00:24:56,360
Speaker 1: they are giving because even if you're not a citizen,

473
00:24:56,520 --> 00:24:58,280
Speaker 1: you still pay taxes.

474
00:24:58,680 --> 00:25:02,320
Speaker 7: Right, So, Molly, I'm going to answer your question and

475
00:25:02,400 --> 00:25:04,200
Speaker 7: tell you why I don't like it. What you're doing

476
00:25:04,280 --> 00:25:06,760
Speaker 7: is you're trying to say this discussion about immigration is

477
00:25:06,800 --> 00:25:09,159
Speaker 7: fundamental economic I'm going to have an economist explain the

478
00:25:09,160 --> 00:25:11,359
Speaker 7: economics of it, and I will happily do so. People

479
00:25:11,400 --> 00:25:13,480
Speaker 7: who think that immigrants are taken from you and I

480
00:25:13,520 --> 00:25:15,919
Speaker 7: don't understand the reality is about half of them have

481
00:25:15,960 --> 00:25:18,840
Speaker 7: fake Social Security numbers. Here I'm talking about undocumented workers,

482
00:25:19,440 --> 00:25:22,280
Speaker 7: which means they do pay into Social Security, but because

483
00:25:22,320 --> 00:25:25,080
Speaker 7: they're fake numbers, they don't take a penny out. And

484
00:25:25,320 --> 00:25:27,520
Speaker 7: there's lots of reports showing that they don't take a

485
00:25:27,520 --> 00:25:30,879
Speaker 7: penny out. So therefore, in fact, they are subsidizing yours

486
00:25:30,920 --> 00:25:34,040
Speaker 7: and my well, not mine, but maybe your parents. That's

487
00:25:34,119 --> 00:25:37,240
Speaker 7: the economic answer. So, and it's important because there is

488
00:25:37,240 --> 00:25:39,719
Speaker 7: a view that these people are taking from the government,

489
00:25:39,760 --> 00:25:42,520
Speaker 7: perse it's false. Let me come back and tell you

490
00:25:42,560 --> 00:25:44,560
Speaker 7: why I object to the question. The issue here is

491
00:25:44,640 --> 00:25:48,400
Speaker 7: far more fundamental than economics. The issue of immigration, I

492
00:25:48,480 --> 00:25:51,400
Speaker 7: think should not be about how does it affect my wallet.

493
00:25:51,720 --> 00:25:55,639
Speaker 7: We immigrants are people I would like to be thought

494
00:25:55,640 --> 00:25:58,360
Speaker 7: of as a person first, and.

495
00:25:58,359 --> 00:25:59,439
Speaker 2: I have a life.

496
00:25:59,600 --> 00:26:02,880
Speaker 7: I have a family, I have dreams, I have things

497
00:26:02,880 --> 00:26:05,800
Speaker 7: I contribute. This country made a promise to me. I

498
00:26:05,880 --> 00:26:09,320
Speaker 7: made a promise to it, and I think overwhelmingly that's

499
00:26:09,359 --> 00:26:12,840
Speaker 7: the most important thing at play here. Excuse my moralizing.

500
00:26:13,320 --> 00:26:13,919
Speaker 1: I just want to.

501
00:26:14,040 --> 00:26:16,159
Speaker 7: Say that if you want to talk about economic impacts

502
00:26:16,200 --> 00:26:19,119
Speaker 7: of immigration, let me focus on another couple that are

503
00:26:19,200 --> 00:26:21,159
Speaker 7: very important. One this is true of me. It's not

504
00:26:21,160 --> 00:26:23,720
Speaker 7: true of you, Molly. I am one of America's great exporters.

505
00:26:24,080 --> 00:26:29,600
Speaker 7: I export millions of dollars and therefore close the trade

506
00:26:29,640 --> 00:26:32,600
Speaker 7: deficit that president claims to so much about.

507
00:26:33,080 --> 00:26:33,840
Speaker 4: How do I do that.

508
00:26:33,880 --> 00:26:37,560
Speaker 7: I'm a university professor, and I educate students from all

509
00:26:37,600 --> 00:26:39,920
Speaker 7: around the world. And when they fly around the world

510
00:26:39,960 --> 00:26:42,480
Speaker 7: and spend forty thousand dollars a year in oun other Michigan,

511
00:26:43,480 --> 00:26:49,080
Speaker 7: they create high quality jobs, They receive an American education,

512
00:26:49,680 --> 00:26:52,600
Speaker 7: and forever will be transformed in a way that transmits

513
00:26:52,600 --> 00:26:55,359
Speaker 7: American soft power. The President is making it hard for

514
00:26:55,400 --> 00:26:57,640
Speaker 7: those kids to get across the border. So I am,

515
00:26:57,720 --> 00:27:00,959
Speaker 7: and the University of Michigan is a great American exporter

516
00:27:01,040 --> 00:27:02,840
Speaker 7: that wants to engage with the rest of the world

517
00:27:03,080 --> 00:27:06,639
Speaker 7: and help solve our trade deficit, and the present will

518
00:27:06,680 --> 00:27:09,760
Speaker 7: not let us do it. Here is not putting It's

519
00:27:09,800 --> 00:27:11,960
Speaker 7: not the equivalent of putting tariffs on imports. It's the

520
00:27:12,000 --> 00:27:15,760
Speaker 7: equivalent of putting tariffs on exports. This is crazy, and

521
00:27:15,800 --> 00:27:18,240
Speaker 7: these are wonderful jobs. The people who work at the

522
00:27:18,320 --> 00:27:21,080
Speaker 7: University of high quality jobs. They enjoy their life. They

523
00:27:21,080 --> 00:27:22,720
Speaker 7: work at a desk, they don't have a saw back,

524
00:27:22,920 --> 00:27:25,240
Speaker 7: but we aren't allowed to do it anymore. So that's

525
00:27:25,359 --> 00:27:28,200
Speaker 7: a very important thing. Another very important thing the H

526
00:27:28,280 --> 00:27:31,600
Speaker 7: one B VISA program is bringing in educated people in

527
00:27:31,720 --> 00:27:35,760
Speaker 7: areas where the United States has shortages. Those educated people

528
00:27:35,800 --> 00:27:38,800
Speaker 7: are working in the most innovative parts of the United States.

529
00:27:39,680 --> 00:27:45,040
Speaker 7: They have a huge impact on new technologies and therefore productivity, innovation,

530
00:27:45,520 --> 00:27:48,080
Speaker 7: and the future of the United States. Try doing the

531
00:27:48,080 --> 00:27:52,400
Speaker 7: world's best cutting edge science without talent from around the world,

532
00:27:52,520 --> 00:27:56,960
Speaker 7: you can't do it. The secret to America's technological innovation

533
00:27:57,400 --> 00:28:02,080
Speaker 7: supremacy has been we have been the home of science

534
00:28:02,400 --> 00:28:04,200
Speaker 7: from all around the world. We have been the place

535
00:28:04,280 --> 00:28:07,320
Speaker 7: scientist wanted to come. Now we're not letting them across

536
00:28:07,320 --> 00:28:07,720
Speaker 7: the border.

537
00:28:08,280 --> 00:28:08,560
Speaker 4: Right.

538
00:28:08,960 --> 00:28:12,520
Speaker 7: Do you want to hear about another shock? Yes? All right,

539
00:28:12,600 --> 00:28:17,119
Speaker 7: So Tariff's was one, and then we had immigration that

540
00:28:17,280 --> 00:28:19,880
Speaker 7: was another. Uncertainly was another. Yeah, I want to tell

541
00:28:19,880 --> 00:28:22,080
Speaker 7: you one more that we is not the usual language

542
00:28:22,119 --> 00:28:25,720
Speaker 7: of economics. God, I've never used this. I think there's

543
00:28:25,760 --> 00:28:29,760
Speaker 7: a competence shock. Normally, when economists talk about the economy,

544
00:28:29,760 --> 00:28:32,840
Speaker 7: we think everyone's making pretty smart decisions and the left

545
00:28:32,840 --> 00:28:35,199
Speaker 7: wing guys are doing stuff. The right wing goes don't like.

546
00:28:35,200 --> 00:28:36,640
Speaker 7: And the right wing guys are doing stuff the left

547
00:28:36,640 --> 00:28:38,280
Speaker 7: wing guys don't like, but at least they're doing it

548
00:28:38,320 --> 00:28:41,880
Speaker 7: moderately well. Right, these guys aren't doing it well. And

549
00:28:41,960 --> 00:28:45,640
Speaker 7: so the sense that the world's largest economy is being

550
00:28:45,720 --> 00:28:48,520
Speaker 7: driven by a set of policymakers who don't know what

551
00:28:48,560 --> 00:28:52,520
Speaker 7: they're doing is enough to cause people to pull back

552
00:28:52,560 --> 00:28:55,760
Speaker 7: on investment. And I fear that's part of what's going

553
00:28:55,760 --> 00:28:58,720
Speaker 7: on right now. And this is an administration that took

554
00:28:58,760 --> 00:29:03,040
Speaker 7: ten months to understand that America doesn't grow bananas, and

555
00:29:03,120 --> 00:29:06,640
Speaker 7: therefore ten months to understand that tariffs on bananas would

556
00:29:06,680 --> 00:29:10,680
Speaker 7: not lead to banana factory jobs in the United States. Right,

557
00:29:11,240 --> 00:29:13,840
Speaker 7: they finally backed off. But it's not just that, right,

558
00:29:13,880 --> 00:29:16,360
Speaker 7: This is firing the head of the BLS. This is

559
00:29:16,400 --> 00:29:19,120
Speaker 7: undermining the Federal Reserve, This is undermining the rule of law,

560
00:29:19,480 --> 00:29:20,840
Speaker 7: and on and on and on and on and on

561
00:29:20,880 --> 00:29:26,320
Speaker 7: and goes. These guys create chaos everywhere they go. This

562
00:29:26,440 --> 00:29:29,720
Speaker 7: isn't just about uncertainty. This is actually about implementing bad policies.

563
00:29:30,080 --> 00:29:32,200
Speaker 7: Bad policies are bad for the future of America. The

564
00:29:32,240 --> 00:29:34,040
Speaker 7: weak of the future of America, the less likely I

565
00:29:34,080 --> 00:29:36,160
Speaker 7: am to invest in it, and I think that's a

566
00:29:36,240 --> 00:29:37,200
Speaker 7: real part of the story.

567
00:29:37,600 --> 00:29:41,040
Speaker 1: Yeah no, But all this is going to be solved

568
00:29:41,400 --> 00:29:45,280
Speaker 1: when Donald Trump makes Kevin Hassett the director of the

569
00:29:45,320 --> 00:29:51,360
Speaker 1: third Just kidding, You don't kidding, now, I am? I

570
00:29:51,400 --> 00:29:52,040
Speaker 1: am kidding.

571
00:29:52,160 --> 00:29:54,280
Speaker 7: Oh you're kidding a king. If you want to talk

572
00:29:54,320 --> 00:29:56,120
Speaker 7: about a competent shock, if you want to talk about

573
00:29:56,160 --> 00:29:59,719
Speaker 7: the least distinguished economist ever to hold that role, if

574
00:29:59,760 --> 00:30:03,160
Speaker 7: you anap about it, a naked partisan who refuses to

575
00:30:03,200 --> 00:30:08,120
Speaker 7: face reality. If I just it's unimaginable.

576
00:30:09,240 --> 00:30:12,880
Speaker 1: The twenty twenty six baby, it's coming up.

577
00:30:13,520 --> 00:30:16,120
Speaker 7: Just I want you to compare this to Bush appointed

578
00:30:16,200 --> 00:30:20,440
Speaker 7: Ben Binenki, who subsequently won the Nobel Prize in economics.

579
00:30:20,840 --> 00:30:24,800
Speaker 1: Kevin's gonna have a Fox show? Justin Wolfers, Will you

580
00:30:24,840 --> 00:30:25,320
Speaker 1: come back?

581
00:30:26,040 --> 00:30:29,480
Speaker 7: Only for you mine, always for you, mine and your audience?

582
00:30:29,560 --> 00:30:30,120
Speaker 4: Who I love.

583
00:30:32,640 --> 00:30:35,160
Speaker 1: Peter Goodman is a reporter at the New York Times

584
00:30:35,200 --> 00:30:37,520
Speaker 1: and the author of How the World Ran Out of

585
00:30:37,600 --> 00:30:42,640
Speaker 1: Everything Inside the Global Supply Chain. Peter Goodman, Welcome to

586
00:30:42,720 --> 00:30:43,640
Speaker 1: past politics.

587
00:30:43,720 --> 00:30:44,960
Speaker 4: Thanks so much for having me both.

588
00:30:45,200 --> 00:30:49,560
Speaker 1: Today, we want to talk about tariffs, yet another brilliant

589
00:30:49,600 --> 00:30:52,120
Speaker 1: Trump idea that is having some problems.

590
00:30:52,120 --> 00:30:53,000
Speaker 7: With the implementation.

591
00:30:53,280 --> 00:30:57,120
Speaker 1: First, can we talk about this lawsuit? Sure, I didn't

592
00:30:57,160 --> 00:30:59,280
Speaker 1: even know you could do that. So talk us through

593
00:30:59,520 --> 00:31:03,240
Speaker 1: Costco suing the Trump administration over tips.

594
00:31:03,440 --> 00:31:07,320
Speaker 8: Well, there's a lot of legality to this that's not

595
00:31:07,680 --> 00:31:13,960
Speaker 8: terribly interesting involving how long Costco has to win their

596
00:31:14,080 --> 00:31:15,480
Speaker 8: case against.

597
00:31:15,200 --> 00:31:16,320
Speaker 4: The Trump administration.

598
00:31:16,480 --> 00:31:19,120
Speaker 8: But what's most interesting about it is that this is

599
00:31:19,160 --> 00:31:23,400
Speaker 8: a large company that is well known to people all

600
00:31:23,440 --> 00:31:29,480
Speaker 8: over America, Red States, Blue States, Maga Country, Liberal coastal Enclaves,

601
00:31:29,840 --> 00:31:34,640
Speaker 8: and unlike just about every other prominent brand in America,

602
00:31:35,200 --> 00:31:39,760
Speaker 8: they're not shrinking from the fight against the Trump administration

603
00:31:39,920 --> 00:31:45,840
Speaker 8: on what they view as an illegal, highly disruptive impact

604
00:31:46,000 --> 00:31:49,200
Speaker 8: on their business through this global trade war. And their

605
00:31:49,280 --> 00:31:52,680
Speaker 8: lawsuit essentially argues like, this is not an emergency, you know,

606
00:31:52,800 --> 00:31:53,760
Speaker 8: call it what you will.

607
00:31:53,800 --> 00:31:54,000
Speaker 4: I mean.

608
00:31:54,040 --> 00:32:00,160
Speaker 8: Trump has cited this Emergency Economic Powers Act as justification

609
00:32:00,320 --> 00:32:04,640
Speaker 8: for unilaterally tearing up treaties that have been negotiated by

610
00:32:04,680 --> 00:32:08,680
Speaker 8: other administrations through trade blocks, through the World Trade Organization

611
00:32:08,760 --> 00:32:11,320
Speaker 8: with other countries around the world. And he's done so

612
00:32:11,440 --> 00:32:15,800
Speaker 8: by saying, hey, it's an emergency in essence that you

613
00:32:16,080 --> 00:32:22,000
Speaker 8: Costco are bringing in cotton briefs made in Bangladesh. When

614
00:32:22,280 --> 00:32:25,520
Speaker 8: we don't send cotton briefs back to Bangladesh or anything

615
00:32:25,520 --> 00:32:29,000
Speaker 8: else for that matter, there's this bilateral trade deficit that's

616
00:32:29,000 --> 00:32:31,600
Speaker 8: an emergency. But what's really interesting to me about this

617
00:32:31,680 --> 00:32:33,960
Speaker 8: case is if you think back to the spring, when

618
00:32:34,040 --> 00:32:37,800
Speaker 8: for about thirty seconds, there was the possibility that Amazon

619
00:32:38,320 --> 00:32:41,240
Speaker 8: would on a discount website called Hall that most of

620
00:32:41,280 --> 00:32:44,160
Speaker 8: us have never heard of. They were threatening to break

621
00:32:44,320 --> 00:32:50,120
Speaker 8: out the cost impact of the tariffs on their website.

622
00:32:50,200 --> 00:32:52,840
Speaker 8: And Scott Bessett was in the middle of this press

623
00:32:52,880 --> 00:32:54,960
Speaker 8: briefing and he was going on for ten minutes about

624
00:32:55,000 --> 00:32:57,640
Speaker 8: how the tariffs were fixing up every American problem under

625
00:32:57,640 --> 00:33:01,040
Speaker 8: the sun, and Carolyn Levitt stepped then when bessen was

626
00:33:01,080 --> 00:33:02,880
Speaker 8: asked this question by a reporter of the room, you know,

627
00:33:02,960 --> 00:33:05,480
Speaker 8: doesn't this show that we Americans are.

628
00:33:05,440 --> 00:33:08,800
Speaker 4: Actually paying these tariffs? And this is a shot.

629
00:33:09,040 --> 00:33:11,240
Speaker 8: I can't remember the exact terminology, but I think she

630
00:33:11,320 --> 00:33:14,280
Speaker 8: called it a hostile act from Amazon. And by that

631
00:33:14,360 --> 00:33:17,479
Speaker 8: afternoon Trump was on the phone with Jeff Bezos, and

632
00:33:18,040 --> 00:33:20,400
Speaker 8: by the end of the day, Trump was saying, Jeff

633
00:33:20,560 --> 00:33:22,920
Speaker 8: is really nice guy. He fixed this. They're not doing it.

634
00:33:23,240 --> 00:33:26,560
Speaker 8: That's how it's gone. So this really breaks from that mold.

635
00:33:26,720 --> 00:33:26,920
Speaker 2: Yeah.

636
00:33:26,960 --> 00:33:28,560
Speaker 1: You know what's funny when we were talking about I

637
00:33:28,600 --> 00:33:31,680
Speaker 1: was actually thinking about that Amazon tariff thing because it

638
00:33:31,760 --> 00:33:34,880
Speaker 1: was actually a great idea to be able to see

639
00:33:34,920 --> 00:33:38,280
Speaker 1: exactly how the tariffs would make things more expensive. And

640
00:33:38,680 --> 00:33:43,480
Speaker 1: for an administration that pretended to care about fraud, waste,

641
00:33:43,520 --> 00:33:48,040
Speaker 1: and abuse, that pretended to be pro transparency, you would

642
00:33:48,040 --> 00:33:52,560
Speaker 1: think that this would be a move towards transparency.

643
00:33:52,720 --> 00:33:55,200
Speaker 4: Who thinks this administration cares about transparency.

644
00:33:55,480 --> 00:34:00,760
Speaker 8: This administration cares about messaging, and the message is that

645
00:34:01,200 --> 00:34:04,720
Speaker 8: some days there is no inflation, or if there is inflation,

646
00:34:04,800 --> 00:34:08,279
Speaker 8: it's Joe Biden's fault. Any inflation due to tariffs, that's

647
00:34:08,320 --> 00:34:11,480
Speaker 8: in your imagination. That's just our political opponent's trying to

648
00:34:11,480 --> 00:34:14,440
Speaker 8: throw something at us. And that one consistent message is

649
00:34:14,760 --> 00:34:18,400
Speaker 8: we are not paying for the tariffs. The foreign producers

650
00:34:18,440 --> 00:34:21,160
Speaker 8: of the goods sent our way, they're paying for the tariffs.

651
00:34:21,360 --> 00:34:23,960
Speaker 4: And here you have a very large company.

652
00:34:24,000 --> 00:34:27,520
Speaker 8: We're roughly one out of every three Americans shops at Costco,

653
00:34:27,840 --> 00:34:30,160
Speaker 8: and this company is saying, well, hang on, we're paying

654
00:34:30,160 --> 00:34:30,920
Speaker 8: for the tariffs.

655
00:34:30,960 --> 00:34:33,120
Speaker 4: And you know what that means. Our customers are paying

656
00:34:33,160 --> 00:34:34,320
Speaker 4: for the tariffs.

657
00:34:34,000 --> 00:34:37,080
Speaker 1: So there's tariff money. I think that the admin is

658
00:34:37,120 --> 00:34:39,520
Speaker 1: probably waiting around to find out what the Supreme Court does,

659
00:34:39,560 --> 00:34:43,040
Speaker 1: because if the Supreme Court rules it illegal, they're supposedly

660
00:34:43,040 --> 00:34:43,960
Speaker 1: going to have to pay it.

661
00:34:43,960 --> 00:34:45,560
Speaker 4: Back, right right, right.

662
00:34:45,640 --> 00:34:50,279
Speaker 8: But there's this deadline that cost Co citing of December fifteenth,

663
00:34:50,400 --> 00:34:55,480
Speaker 8: where for tedious administrative reasons, if this is not resolved,

664
00:34:55,640 --> 00:34:58,319
Speaker 8: Costco's position is, even if we win, we're not going

665
00:34:58,360 --> 00:35:01,360
Speaker 8: to get the money back, and that's why they're taking

666
00:35:01,400 --> 00:35:03,400
Speaker 8: this action to file this lawsuit.

667
00:35:03,680 --> 00:35:05,719
Speaker 1: It's such an interesting thing because it's like in so

668
00:35:05,760 --> 00:35:09,080
Speaker 1: many different companies in Trump world, at every point we've

669
00:35:09,120 --> 00:35:14,719
Speaker 1: seen billionaires, millionaires, corporate entity is just cave even like

670
00:35:14,840 --> 00:35:19,440
Speaker 1: in advance for example, I'm thinking about Sherry Redstone, I'm

671
00:35:19,440 --> 00:35:21,600
Speaker 1: thinking about you know, at every point they've just been like,

672
00:35:21,920 --> 00:35:26,279
Speaker 1: you might want this. A great example is Amazon with Milania, the.

673
00:35:26,280 --> 00:35:27,480
Speaker 4: Forty million dollar deal.

674
00:35:27,640 --> 00:35:29,759
Speaker 1: Yeah, let me just make sure that none of this

675
00:35:29,920 --> 00:35:33,320
Speaker 1: bothers you, and then you have like an actual lawsuit.

676
00:35:33,719 --> 00:35:37,640
Speaker 8: I mean, it's interesting that the largest law firms in America,

677
00:35:37,880 --> 00:35:40,640
Speaker 8: most of them, at least the most powerful ones like

678
00:35:40,680 --> 00:35:43,400
Speaker 8: Paul Weiss, have essentially said, even if we file a

679
00:35:43,480 --> 00:35:48,759
Speaker 8: lawsuit against the executive order that's aimed to cripple us

680
00:35:48,760 --> 00:35:51,160
Speaker 8: and destroy our business, even if we win, we lose

681
00:35:51,320 --> 00:35:55,560
Speaker 8: because we require good relations with the administration in order

682
00:35:55,600 --> 00:35:58,960
Speaker 8: to do our business. Yet here's this company is a

683
00:35:59,040 --> 00:36:02,880
Speaker 8: discounter for like the everyman, and they're the ones who

684
00:36:02,960 --> 00:36:05,040
Speaker 8: are actually standing up to Trump. And by the way,

685
00:36:05,040 --> 00:36:06,760
Speaker 8: this is the same company that stood up to Trump

686
00:36:06,760 --> 00:36:11,359
Speaker 8: on DII. Virtually every large corporation in America has run

687
00:36:11,440 --> 00:36:13,840
Speaker 8: screaming from the pledges they made back when it was,

688
00:36:13,960 --> 00:36:19,000
Speaker 8: you know, politically in their favor to pledge allegiance to diversity,

689
00:36:19,040 --> 00:36:23,680
Speaker 8: equity inclusion programs. And Costco actually had a vote where

690
00:36:23,719 --> 00:36:26,359
Speaker 8: they convened a conference and they said, okay, look, you know,

691
00:36:26,360 --> 00:36:28,200
Speaker 8: we've looked at this proposal to get rid of DEI.

692
00:36:28,360 --> 00:36:31,080
Speaker 8: We happen to think that diversity is a good part

693
00:36:31,120 --> 00:36:32,000
Speaker 8: of our business.

694
00:36:32,080 --> 00:36:34,200
Speaker 4: We think it's a comparative advantage, and we're sticking with it.

695
00:36:34,280 --> 00:36:37,799
Speaker 8: So this is a company that, by all accounts, is

696
00:36:37,840 --> 00:36:40,839
Speaker 8: fairly conservative with a small c in terms of how

697
00:36:40,880 --> 00:36:42,440
Speaker 8: it goes about its business.

698
00:36:42,440 --> 00:36:45,480
Speaker 4: They don't like to make huge changes. I've been told by.

699
00:36:45,480 --> 00:36:48,680
Speaker 8: Friends who work in the environmental consulting world that Costco's

700
00:36:48,840 --> 00:36:52,160
Speaker 8: slow to come to the table in terms of emissions

701
00:36:52,239 --> 00:36:55,280
Speaker 8: or sustainability in the supply chain. But once they do something,

702
00:36:55,280 --> 00:36:58,320
Speaker 8: they really do it. They don't like to be pushed around.

703
00:36:58,560 --> 00:37:01,680
Speaker 8: It's interesting that they're not really sort of grandstanding here.

704
00:37:01,719 --> 00:37:04,799
Speaker 8: They're just saying, we're not rolling over. We still think

705
00:37:04,840 --> 00:37:07,919
Speaker 8: we live in a democracy that has courts, and if

706
00:37:07,960 --> 00:37:10,480
Speaker 8: we are faced with the threat to our business that

707
00:37:10,560 --> 00:37:14,840
Speaker 8: we think is illegal and unreasonable, we're gonna use our rights.

708
00:37:14,880 --> 00:37:18,720
Speaker 8: And that's interesting given that most large businesses are behaving

709
00:37:18,760 --> 00:37:22,080
Speaker 8: as if you know, courts, the law, the facts, like,

710
00:37:22,120 --> 00:37:25,440
Speaker 8: none of this really particularly matters. What matters is the

711
00:37:25,520 --> 00:37:29,319
Speaker 8: dictates of this administration, which will take extraordinary measures to

712
00:37:29,640 --> 00:37:31,040
Speaker 8: do what it wants to do.

713
00:37:31,239 --> 00:37:34,560
Speaker 1: Yeah, it's really shocking you expect Donald Trump to push

714
00:37:34,719 --> 00:37:37,799
Speaker 1: But again, like there is this Supreme Court fight with

715
00:37:37,920 --> 00:37:41,239
Speaker 1: the Koch brother right, that's going to come down that

716
00:37:41,360 --> 00:37:44,040
Speaker 1: decision in June. The Supreme Court is either going to

717
00:37:44,120 --> 00:37:47,600
Speaker 1: have to disappoint Leonard Leo and the one surviving Coke

718
00:37:47,640 --> 00:37:49,640
Speaker 1: brother or disappoint Donald Trump.

719
00:37:50,080 --> 00:37:53,080
Speaker 8: Yeah, I mean it's interesting because of course Trump is

720
00:37:53,120 --> 00:37:58,280
Speaker 8: already intimated that he's unhappy with Leonard Leo for other reasons.

721
00:37:58,320 --> 00:38:00,799
Speaker 4: And so there's there are these heating.

722
00:38:00,560 --> 00:38:04,800
Speaker 8: Notions of what the court means in the Trump age,

723
00:38:05,120 --> 00:38:09,279
Speaker 8: and it seems pretty clear that Donald Trump's view is

724
00:38:09,600 --> 00:38:12,719
Speaker 8: five point justices to the Supreme Court. Hey, all this

725
00:38:12,960 --> 00:38:16,360
Speaker 8: judicial philosophy stuff, that's all fine when you're tap dancing

726
00:38:16,400 --> 00:38:19,000
Speaker 8: in front of the Senate, like I own you, I

727
00:38:19,120 --> 00:38:23,520
Speaker 8: own your vote. You vote with me, whether there's ideological

728
00:38:23,760 --> 00:38:25,239
Speaker 8: judicial consistency or not.

729
00:38:25,400 --> 00:38:26,520
Speaker 4: You're on my team.

730
00:38:27,040 --> 00:38:30,960
Speaker 8: And Leonard Leo, say what you will about him, actually

731
00:38:31,000 --> 00:38:35,239
Speaker 8: does have a judicial philosophy and does have beliefs.

732
00:38:35,560 --> 00:38:37,279
Speaker 4: You may agree with them or disagree with them.

733
00:38:37,320 --> 00:38:39,920
Speaker 8: You find them it may find them repellent or heroic, whatever,

734
00:38:40,200 --> 00:38:43,520
Speaker 8: But there actually is a judicial philosophy at work, and

735
00:38:43,560 --> 00:38:47,520
Speaker 8: that's now colliding with this Trump position that you're on

736
00:38:47,560 --> 00:38:49,080
Speaker 8: our team or you're the enemy.

737
00:38:49,520 --> 00:38:53,080
Speaker 1: Yeah, it is like a zero sum a little bit,

738
00:38:53,320 --> 00:38:56,480
Speaker 1: right in what sense you you're either with Trump or

739
00:38:56,480 --> 00:38:58,359
Speaker 1: you're against him. Right, there's not a lot of room

740
00:38:58,400 --> 00:38:58,960
Speaker 1: for nuance.

741
00:38:59,360 --> 00:39:02,200
Speaker 8: I mean, people say it's a protection racket, right, that's

742
00:39:02,239 --> 00:39:06,360
Speaker 8: the term that gets thrown around. So you're either inside

743
00:39:06,440 --> 00:39:10,000
Speaker 8: the perimeter and you get the perks, or you're outside

744
00:39:10,120 --> 00:39:13,560
Speaker 8: and it's lonely out there and you don't have a

745
00:39:13,600 --> 00:39:17,239
Speaker 8: lot of avenues for protection. And so back to Costco,

746
00:39:17,719 --> 00:39:21,160
Speaker 8: they're saying, we're not playing that way. We think outside

747
00:39:21,239 --> 00:39:24,200
Speaker 8: the perimeter is this thing called American democracy in the

748
00:39:24,280 --> 00:39:26,879
Speaker 8: rule of law, and we still happen to think that

749
00:39:26,880 --> 00:39:27,680
Speaker 8: that matters.

750
00:39:28,040 --> 00:39:32,000
Speaker 1: So let's talk about this battery stuff. It's not surprising,

751
00:39:32,120 --> 00:39:35,040
Speaker 1: So explain to us this central premise here with these

752
00:39:35,320 --> 00:39:40,840
Speaker 1: environmentally friendly but not really the car batteries, the clean batteries.

753
00:39:41,239 --> 00:39:45,080
Speaker 8: Yeah, so I just spent a year investigating a part

754
00:39:45,080 --> 00:39:47,319
Speaker 8: of the global supply chain that we're invited to think

755
00:39:47,320 --> 00:39:47,879
Speaker 8: about never.

756
00:39:48,120 --> 00:39:50,439
Speaker 4: You know, it's something I didn't know anything about. Most

757
00:39:50,440 --> 00:39:51,640
Speaker 4: people don't know anything about it.

758
00:39:51,880 --> 00:39:54,200
Speaker 8: To the extent to which we think about the battery

759
00:39:54,239 --> 00:39:57,600
Speaker 8: in our car, which is very rarely. We're invited to

760
00:39:57,680 --> 00:40:01,920
Speaker 8: think that we're participating in in the circular economy, in

761
00:40:02,000 --> 00:40:05,200
Speaker 8: the recycling miracle, because it's true that the largest battery

762
00:40:05,239 --> 00:40:08,759
Speaker 8: manufacturers in the US have these sophisticated plants where they

763
00:40:08,760 --> 00:40:09,359
Speaker 8: go get spent.

764
00:40:09,440 --> 00:40:10,800
Speaker 4: We're talking about lead batteries.

765
00:40:10,840 --> 00:40:14,000
Speaker 8: By the way, these are conventional lead batteries in millions

766
00:40:14,040 --> 00:40:16,600
Speaker 8: of cars, including lots of evs, because even evs have

767
00:40:17,120 --> 00:40:19,759
Speaker 8: small mostly have small lead batteries the power and the

768
00:40:19,760 --> 00:40:21,000
Speaker 8: software systems.

769
00:40:20,600 --> 00:40:21,160
Speaker 4: When they're off.

770
00:40:21,239 --> 00:40:24,600
Speaker 8: So these large battery manufacturers go around, they gather up

771
00:40:24,680 --> 00:40:28,759
Speaker 8: spent lead batteries. They use machinery to extract the lead

772
00:40:28,840 --> 00:40:31,839
Speaker 8: from within, and they melt it down to get new

773
00:40:31,920 --> 00:40:34,279
Speaker 8: leads so they can make new batteries. But there have

774
00:40:34,360 --> 00:40:37,720
Speaker 8: been stricter and stricter regulations in the US to limit

775
00:40:37,960 --> 00:40:41,000
Speaker 8: lead poisoning of communities, and there's been growth, and so

776
00:40:41,080 --> 00:40:43,480
Speaker 8: they've needed to go find some new sources of lead.

777
00:40:43,480 --> 00:40:48,840
Speaker 8: They've gone around the world, and increasingly they're buying from Nigeria.

778
00:40:48,920 --> 00:40:52,319
Speaker 8: So I spent a year with a reporting partner at

779
00:40:52,320 --> 00:40:58,480
Speaker 8: the Examination, Will Fitzgibbon, looking at how these smelters operating

780
00:40:58,560 --> 00:41:01,920
Speaker 8: with none of these sorts of parts, no emissions controls,

781
00:41:02,480 --> 00:41:07,520
Speaker 8: workers breaking apart battery shirt lists, no goggles, no gloves,

782
00:41:07,640 --> 00:41:10,879
Speaker 8: using machetes their bare hands to rip out the lead

783
00:41:10,920 --> 00:41:14,120
Speaker 8: from inside, and then that stuff gets trucked up to

784
00:41:14,200 --> 00:41:18,080
Speaker 8: these giant smelters, just big furnaces basically that are largely

785
00:41:18,160 --> 00:41:21,880
Speaker 8: open air, you know, or the corrugated metal sheets on

786
00:41:21,920 --> 00:41:24,880
Speaker 8: the rooftops. But you can see the smoke just pouring

787
00:41:24,920 --> 00:41:29,000
Speaker 8: out in every direction. You can smell it. It's just foul.

788
00:41:29,200 --> 00:41:33,840
Speaker 8: There's a dust of black ash that's settling on everything.

789
00:41:33,880 --> 00:41:37,440
Speaker 8: And they're villages right next to these smelters in this

790
00:41:37,480 --> 00:41:41,080
Speaker 8: town of Oki Joe, north of Legos. And so what

791
00:41:41,120 --> 00:41:45,960
Speaker 8: we did was we actually found seventy people living in

792
00:41:46,000 --> 00:41:49,359
Speaker 8: the midst of these smelters and tested their blood. They

793
00:41:49,440 --> 00:41:52,400
Speaker 8: volunteered to be tested, and we found that roughly seven

794
00:41:52,480 --> 00:41:55,200
Speaker 8: out of ten of them have lead in their blood

795
00:41:55,400 --> 00:42:00,399
Speaker 8: at alarming levels. Every worker we tested had extraordinary high

796
00:42:00,480 --> 00:42:01,200
Speaker 8: levels of lead.

797
00:42:01,400 --> 00:42:03,480
Speaker 1: So like lead poisoning, right.

798
00:42:03,400 --> 00:42:05,800
Speaker 4: Yeah, we're talking irreversible brain damage.

799
00:42:05,960 --> 00:42:10,200
Speaker 8: We're talking about schools right up against these factories with kids,

800
00:42:10,280 --> 00:42:13,359
Speaker 8: you know, breathing this stuff. And I talked to a

801
00:42:13,440 --> 00:42:15,759
Speaker 8: mom of a three year old girl who said, my

802
00:42:15,840 --> 00:42:19,040
Speaker 8: daughter's constantly coughing and black particles are coming out of

803
00:42:19,040 --> 00:42:21,520
Speaker 8: her mouth. I talked to a sixty five year old

804
00:42:21,560 --> 00:42:24,560
Speaker 8: man who was shaking uncontrollably, said he could never sleep.

805
00:42:24,560 --> 00:42:26,319
Speaker 8: He brought me into his house. He said, look, my

806
00:42:26,480 --> 00:42:29,520
Speaker 8: walls are black from this smoke. There's just no relief.

807
00:42:29,640 --> 00:42:33,560
Speaker 8: And so we traced the lead from these smelters in

808
00:42:33,760 --> 00:42:37,319
Speaker 8: Nigeria to the US through the port of Baltimore and

809
00:42:37,400 --> 00:42:40,759
Speaker 8: eventually got the second largest battery of manufacturer in the US,

810
00:42:40,840 --> 00:42:43,640
Speaker 8: a company called East penn to acknowledge that it was

811
00:42:43,640 --> 00:42:46,640
Speaker 8: buying this lead, it was using this lead to make

812
00:42:46,680 --> 00:42:50,000
Speaker 8: new batteries, and then they said, we're not doing that anymore.

813
00:42:50,080 --> 00:42:50,879
Speaker 1: Do you believe them?

814
00:42:51,520 --> 00:42:58,000
Speaker 8: I do believe them, because they plausibly were relying on

815
00:42:58,560 --> 00:43:02,319
Speaker 8: the assurances of the trading company they buy from, a

816
00:43:02,320 --> 00:43:05,320
Speaker 8: bunch of different middleman trading companies, including the Swiss company.

817
00:43:05,160 --> 00:43:05,919
Speaker 4: Called traffic Eura.

818
00:43:06,239 --> 00:43:09,680
Speaker 8: I don't believe that they tried particularly hard to find

819
00:43:09,680 --> 00:43:12,320
Speaker 8: out where's our lead coming from, and they sort of

820
00:43:12,360 --> 00:43:14,840
Speaker 8: cop to that. When I eventually got the CEO to

821
00:43:14,880 --> 00:43:17,440
Speaker 8: talk to me, which took months and had to ambush

822
00:43:17,520 --> 00:43:18,560
Speaker 8: him at a trade show.

823
00:43:18,640 --> 00:43:21,279
Speaker 4: And when he eventually talked to me, he said said, look,

824
00:43:21,440 --> 00:43:23,480
Speaker 4: was I too trusting? You know, I'll take that shot.

825
00:43:23,600 --> 00:43:26,239
Speaker 8: But here's the thing I asked him, Okay, so you're

826
00:43:26,239 --> 00:43:27,920
Speaker 8: not buying lead from Nigeria anymore.

827
00:43:28,080 --> 00:43:29,440
Speaker 4: Where are you're making up the difference?

828
00:43:29,560 --> 00:43:33,719
Speaker 8: Well, we're boosting our purchases from South Korea and Australia. Well,

829
00:43:33,760 --> 00:43:35,760
Speaker 8: the trade data shows that a lot of this Nigerian

830
00:43:35,840 --> 00:43:38,840
Speaker 8: lead is ending up in South Korea, and East Penn

831
00:43:39,000 --> 00:43:42,440
Speaker 8: buys lead batteries from South Korea. So I said, well,

832
00:43:42,480 --> 00:43:44,839
Speaker 8: how do you know you're not still buying Nigerian lead

833
00:43:44,920 --> 00:43:47,240
Speaker 8: through South Korea? He said, well, it's a good question.

834
00:43:47,320 --> 00:43:49,160
Speaker 8: It's very hard to trace metals. I mean, this is

835
00:43:49,200 --> 00:43:52,799
Speaker 8: the nature of global supply chages, is the engineered so

836
00:43:52,840 --> 00:43:56,279
Speaker 8: there's plausible deniability. There's so many participants, there's so many

837
00:43:56,280 --> 00:44:00,319
Speaker 8: countries involved that any single actor can essentially you know,

838
00:44:00,360 --> 00:44:02,279
Speaker 8: it's like you're standing on the tennis court with your

839
00:44:02,280 --> 00:44:02,960
Speaker 8: doubles partner.

840
00:44:02,960 --> 00:44:04,000
Speaker 4: I thought you had that one.

841
00:44:04,080 --> 00:44:07,520
Speaker 8: I mean that's like, that's how the global supply chain works.

842
00:44:07,880 --> 00:44:13,080
Speaker 1: Do you think that there is a way to get

843
00:44:13,120 --> 00:44:15,520
Speaker 1: the lend out of batteries that is safer?

844
00:44:15,880 --> 00:44:18,160
Speaker 4: Oh, there definitely is. Yeah. I mean we have these

845
00:44:18,200 --> 00:44:19,480
Speaker 4: plants in the States.

846
00:44:19,719 --> 00:44:23,560
Speaker 8: They're present in Europe where they're very strict stames, but

847
00:44:23,600 --> 00:44:24,279
Speaker 8: it costs.

848
00:44:24,040 --> 00:44:24,960
Speaker 4: Millions of dollars.

849
00:44:25,280 --> 00:44:27,160
Speaker 8: And I mean I just got off the phone actually

850
00:44:27,160 --> 00:44:29,239
Speaker 8: with the guy one of these plants in Nigeria. He said, look,

851
00:44:29,239 --> 00:44:33,160
Speaker 8: I would love to put in an automatic breaking system

852
00:44:33,200 --> 00:44:35,440
Speaker 8: instead of having these guys with the machetes do the

853
00:44:35,480 --> 00:44:36,560
Speaker 8: work with their bare hands.

854
00:44:36,719 --> 00:44:39,560
Speaker 4: Do you have four million dollars lying around? He would

855
00:44:39,560 --> 00:44:40,360
Speaker 4: have to borrow it.

856
00:44:40,640 --> 00:44:44,239
Speaker 8: The prevailing interest rates in Nigeria are fifteen percent, and

857
00:44:44,760 --> 00:44:46,239
Speaker 8: who's gonna pay for that?

858
00:44:46,320 --> 00:44:46,480
Speaker 4: Now?

859
00:44:46,520 --> 00:44:50,920
Speaker 8: The sad part is if we hypothetically relied just on

860
00:44:51,080 --> 00:44:55,160
Speaker 8: that responsibly produced lead in Nigeria and all the costs

861
00:44:55,160 --> 00:44:57,520
Speaker 8: got passed on through the chain the consumer in the

862
00:44:57,600 --> 00:45:00,600
Speaker 8: US buying a battery. It's a hard hypothet all we

863
00:45:00,719 --> 00:45:02,840
Speaker 8: kind of modeled it. It wouldn't be much more. You know,

864
00:45:02,880 --> 00:45:05,360
Speaker 8: it's like single digit number of dollars more.

865
00:45:05,600 --> 00:45:08,360
Speaker 1: It's not like making an iPhone in the United States.

866
00:45:08,719 --> 00:45:10,319
Speaker 4: Oh, not at all, not at all.

867
00:45:10,360 --> 00:45:14,280
Speaker 8: It's just that the trading companies who get the real

868
00:45:14,400 --> 00:45:18,440
Speaker 8: margins on this, they would have to give up profit,

869
00:45:18,560 --> 00:45:20,200
Speaker 8: you know, they look they'd rather buy.

870
00:45:19,960 --> 00:45:21,400
Speaker 4: From a responsible supplier.

871
00:45:21,400 --> 00:45:23,400
Speaker 8: In fact, there was one in Nigeria that we focused on,

872
00:45:23,520 --> 00:45:27,640
Speaker 8: called Green Recycling, that went out of business because they

873
00:45:27,680 --> 00:45:31,560
Speaker 8: couldn't pay as much for the spent batteries because they

874
00:45:31,640 --> 00:45:35,960
Speaker 8: were carrying the costs of putting in the automated braking

875
00:45:36,000 --> 00:45:39,480
Speaker 8: equipment and the emissions controls and so they weren't poisoning

876
00:45:39,560 --> 00:45:42,439
Speaker 8: the environment. The head of that company said, yeah, maybe

877
00:45:42,480 --> 00:45:44,800
Speaker 8: if we'd killed more people would still be in business.

878
00:45:44,880 --> 00:45:48,120
Speaker 8: I mean, it was actually a competitive disadvantage to them

879
00:45:48,200 --> 00:45:48,720
Speaker 8: to do.

880
00:45:49,040 --> 00:45:49,879
Speaker 4: The right thing.

881
00:45:49,920 --> 00:45:52,400
Speaker 8: And of course, you know, we don't go buying batteries

882
00:45:52,440 --> 00:45:55,120
Speaker 8: in the US with some sort of option over where

883
00:45:55,120 --> 00:45:56,080
Speaker 8: the lead comes from.

884
00:45:56,320 --> 00:45:58,279
Speaker 1: Yeah, it's one of those things where it's like if

885
00:45:58,320 --> 00:46:00,560
Speaker 1: you know, then all of a sudden, you know it's

886
00:46:00,560 --> 00:46:03,799
Speaker 1: not okay. So it's one of the many places where

887
00:46:03,880 --> 00:46:05,960
Speaker 1: journalism is doing the heavy lifting.

888
00:46:06,520 --> 00:46:10,240
Speaker 8: This is certainly a story that wasn't supposed to be tolls.

889
00:46:10,520 --> 00:46:12,600
Speaker 8: You know, there was nobody waiting for me to call

890
00:46:12,640 --> 00:46:15,280
Speaker 8: them up so they could help me understand the supply

891
00:46:15,400 --> 00:46:16,959
Speaker 8: chain for recycled lead.

892
00:46:17,120 --> 00:46:18,440
Speaker 4: This is a secret trade.

893
00:46:18,600 --> 00:46:20,440
Speaker 8: And the truth is if they shut these plants down

894
00:46:20,480 --> 00:46:21,720
Speaker 8: in Nigeria, which is possible.

895
00:46:21,800 --> 00:46:24,000
Speaker 4: I mean, as we speak, the Nigerian government since our.

896
00:46:23,920 --> 00:46:27,640
Speaker 8: Story ran has sealed up the worst polluting factories in

897
00:46:27,680 --> 00:46:28,000
Speaker 8: this town.

898
00:46:28,040 --> 00:46:31,120
Speaker 4: We're focused on for them. Well, good for them, except.

899
00:46:30,719 --> 00:46:32,400
Speaker 8: You know a lot of people work at those plants

900
00:46:32,440 --> 00:46:35,680
Speaker 8: would much rather have them improved as opposed to closed

901
00:46:35,719 --> 00:46:38,480
Speaker 8: and It's not as if, to your point, we're going

902
00:46:38,520 --> 00:46:41,040
Speaker 8: to suddenly, you know, bring all this stuff back to

903
00:46:41,080 --> 00:46:43,200
Speaker 8: the US and do it at a high standard. It'll

904
00:46:43,239 --> 00:46:45,960
Speaker 8: move to some other country in Africa, It'll move somewhere

905
00:46:45,960 --> 00:46:48,600
Speaker 8: else in South Asia. I mean, there has to be

906
00:46:48,680 --> 00:46:53,800
Speaker 8: accountability at our end where it's the international auto industry,

907
00:46:53,880 --> 00:46:57,880
Speaker 8: it's the battery manufacturers who are asking us to feel

908
00:46:57,920 --> 00:47:00,560
Speaker 8: good about buying their products. You know, we're helping solve

909
00:47:00,680 --> 00:47:06,560
Speaker 8: climate change, we're limiting pollution, while they're simultaneously relying for

910
00:47:06,680 --> 00:47:11,719
Speaker 8: supplies on a very nasty, tragic situation that they would

911
00:47:11,800 --> 00:47:13,000
Speaker 8: much rather we not examined.

912
00:47:13,120 --> 00:47:15,799
Speaker 1: Peter, thank you so much for coming on. I hope

913
00:47:15,800 --> 00:47:16,759
Speaker 1: you'll come back.

914
00:47:16,680 --> 00:47:19,000
Speaker 4: Oh anytime, Mollie, thank you so much for having me.

915
00:47:21,320 --> 00:47:23,920
Speaker 4: No moment second.

916
00:47:24,040 --> 00:47:27,200
Speaker 3: Jesse Cannon, I'm going to take you back to a

917
00:47:27,239 --> 00:47:30,239
Speaker 3: time it was twenty twelve and all we heard was

918
00:47:30,680 --> 00:47:33,919
Speaker 3: Barack Obama as the secret Muslim. What did we know

919
00:47:34,400 --> 00:47:37,359
Speaker 3: that the first secret Muzzlim at our government would be

920
00:47:37,400 --> 00:47:44,279
Speaker 3: what GOP Republican Representative Corey Mills. And there's blockbuster new

921
00:47:44,320 --> 00:47:48,399
Speaker 3: reporting from our former colleague Roger Sellenberger that really has

922
00:47:48,480 --> 00:47:52,080
Speaker 3: a lot of strange stuff in this This guy is wild.

923
00:47:52,440 --> 00:47:55,880
Speaker 1: It makes me wish that The Daily Beast still existed,

924
00:47:56,080 --> 00:47:59,920
Speaker 1: because if it did, this story would have been a blockbuster.

925
00:48:00,440 --> 00:48:02,640
Speaker 1: It's on his substack. You can read it. It's the

926
00:48:02,680 --> 00:48:07,120
Speaker 1: same standards George Santos with a gun. The untold story

927
00:48:07,160 --> 00:48:10,799
Speaker 1: of Corey Mills, a mercenary in Congress. He tried to

928
00:48:11,000 --> 00:48:15,080
Speaker 1: leverage his legislative role to the benefit of his arms business.

929
00:48:15,120 --> 00:48:20,000
Speaker 1: That's right, arms business, you heard me, arms like guns,

930
00:48:20,040 --> 00:48:21,960
Speaker 1: selling guns. He took the witness stand.

931
00:48:22,360 --> 00:48:24,840
Speaker 3: How else are you going to finance spyke sex workers

932
00:48:24,840 --> 00:48:25,640
Speaker 3: in Afghanistan?

933
00:48:25,840 --> 00:48:27,200
Speaker 1: Ohs does that come in there?

934
00:48:27,840 --> 00:48:28,040
Speaker 4: Yeah?

935
00:48:28,120 --> 00:48:32,600
Speaker 1: What I'm thinking about. My man is also married. He

936
00:48:32,760 --> 00:48:39,400
Speaker 1: was cyberstalking and threatening his ex girlfriend with cyber porn.

937
00:48:40,000 --> 00:48:42,320
Speaker 1: He's got the kind of story that makes you wonder

938
00:48:42,520 --> 00:48:48,920
Speaker 1: why he's not a Fox Weekend host. Yeah, Corey Mills

939
00:48:49,000 --> 00:48:51,960
Speaker 1: is not as famous as George Santos, but he may

940
00:48:51,960 --> 00:48:52,479
Speaker 1: be soon.

941
00:48:53,280 --> 00:48:56,160
Speaker 3: We should really say, Roger is one of the best

942
00:48:56,160 --> 00:48:58,440
Speaker 3: investigative reporters. He should really go and check out his

943
00:48:58,480 --> 00:49:01,120
Speaker 3: substack and read up on this an insane story that

944
00:49:01,160 --> 00:49:03,479
Speaker 3: this man is in our government and not booted out,

945
00:49:03,680 --> 00:49:05,439
Speaker 3: but Mike Johnson's majority is too.

946
00:49:05,360 --> 00:49:09,720
Speaker 1: Thin, So read this, Read a substack, Corey Mills, George

947
00:49:09,719 --> 00:49:12,880
Speaker 1: Santos with a gun, The untold story of a mercenary

948
00:49:12,920 --> 00:49:17,719
Speaker 1: in Congress. That's it for this episode of Fast Politics.

949
00:49:18,200 --> 00:49:23,919
Speaker 1: Tune in every Monday, Wednesday, Thursday and Saturday to hear

950
00:49:24,200 --> 00:49:28,560
Speaker 1: the best minds and politics make sense of all this chaos.

951
00:49:28,840 --> 00:49:31,680
Speaker 1: If you enjoy this podcast, please send it to a

952
00:49:31,760 --> 00:49:35,760
Speaker 1: friend and keep the conversation going. Thanks for listening.