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Speaker 1: Hello there, Happy Monday. It is Columbus Day Indigenous People

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Speaker 1: Day depending on the state you live in. Yes, both

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Speaker 1: are used. At the end of the day, a lot

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Speaker 1: of people have today off, which should mean quite a

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Speaker 1: few of you have more time to be listening. So welcome.

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Speaker 1: For those of you trying the podcast out for the

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Speaker 1: first time, Thank you appreciate it. We've loved our growth lately.

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Speaker 1: A few pieces of housekeeping. The biggest thing in the

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Speaker 1: podcast household is we have a new dog, rescue Dog two.

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Speaker 1: She's a poodle mix. I bring it up because she

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Speaker 1: may or may not make her presence known during this

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Speaker 1: portion of my recording. That's mostly why I'm sharing. I'm

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Speaker 1: sharing that news with you. Those of you that follow

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Speaker 1: me very closely on social media know at the end

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Speaker 1: of June we lost we lost a dog that we

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Speaker 1: had for fourteen years, Ruby. She was a standard Poodle.

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Speaker 1: She was terrific and lived a very full life until

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Speaker 1: the end. So we've been waiting for the summer. I'll

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Speaker 1: be honest, and I wanted to make sure it was

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Speaker 1: a rescue. This time. We didn't have kids in the house,

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Speaker 1: so you feel like you can be a little more

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Speaker 1: accommodating two more rambunctious dogs. Shall we say. She's got

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Speaker 1: a ton of energy. She's got the puppy energy of

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Speaker 1: a two year old. And at the same time, you know,

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Speaker 1: I probably only have like six to nine months of

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Speaker 1: this rather than the three years of puppy behavior that

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Speaker 1: many of you I know are used to when you

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Speaker 1: get a new dog. Anyway, so that is my daughter's

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Speaker 1: in town visiting for fall break, and so she's been

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Speaker 1: a big help here. My son comes for fall break

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Speaker 1: to meet her. He's a bit bumped that he wasn't

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Speaker 1: here for but hey, she came a little bit earlier

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Speaker 1: than we expected. When you're on a rescue list, you

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Speaker 1: never know when they're going to say yes. Big thanks

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Speaker 1: to the folks in DC at City Dogs Rescue. They

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Speaker 1: do great work. It's almost all volunteers, as anybody knows.

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Speaker 1: You know, I hope if you're a pet lover you

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Speaker 1: help out any sort of dog and cat rescue in

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Speaker 1: your community. We know they do terrific work and it

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Speaker 1: is done simply. Most of the volunteers are there just

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Speaker 1: for the love of the animals. So big thanks to

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Speaker 1: City Dogs in Washington, d C. So that's housekeeping item

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Speaker 1: number one, Housekeeping it number two. My interview today is

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Speaker 1: with Mark Zandy, Moody's chief economist. As you know about

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Speaker 1: every quarter, I want to bring Mark Zandy in to

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Speaker 1: sort of give a state of the economy as it is,

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Speaker 1: where we're headed, what we need to be concerned about,

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Speaker 1: maybe what we're overreacting to underreacting to. We get through

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Speaker 1: a lot of variables in the economy. I'd like to

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Speaker 1: think I have asked every question you want asked of

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Speaker 1: Mark Sandy. But you know I've thought about this and

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Speaker 1: I'm going to have them on again just after January.

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Speaker 1: So keep this in mind if you ever have a

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Speaker 1: direct question of Mark Zandy, the chief economist at Moody's

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Speaker 1: that you would love to see me ask sentiment. We'll

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Speaker 1: keep track of them. I'll keep them, I'll keep them

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Speaker 1: on file. I absolutely would get that. Maybe there's some

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Speaker 1: specific questions I'm not getting to. I hope I got

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Speaker 1: to most of them that you thought of. It maybe

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Speaker 1: a couple that you didn't think of. It is worth

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Speaker 1: noting I'd taped the interview before China and the United

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Speaker 1: States had a escalating set of threats for the trade

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Speaker 1: war one hundred percent tariffs and responds to protectionism with

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Speaker 1: the minerals in China. For what it's worth, all of

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Speaker 1: it seems to be posturing before the actual negotiation between

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Speaker 1: to world leaders takes place in the next few weeks

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Speaker 1: to a month. So even though the markets are reacting,

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Speaker 1: and it is interesting, when do the markets react to

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Speaker 1: Trump teriff threats, it appears whenever it's about China. Any

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Speaker 1: other aspect of tariff threats don't seem to impact the

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Speaker 1: stock market China. That's enough. Another story which I think

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Speaker 1: tells you how important the Chinese economy is to the

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Speaker 1: world economy. Right, we are the dominant economy in the world,

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Speaker 1: but we're not alone, and you know we can have

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Speaker 1: we can have a lot of impact, and so can China.

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Speaker 1: So I think we're learning here and each country is

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Speaker 1: feeling each other out. I think each country thought they

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Speaker 1: could quote unquote when this trade war, and I think

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Speaker 1: both countries are finding out in some ways this is

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Speaker 1: an unwinnable trade war. I'll get to more of it

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Speaker 1: before we get to my interview with Sandy, but I

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Speaker 1: wanted to get that out of the way. But look,

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Speaker 1: I'm going to begin with what we've been talking about

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Speaker 1: for some time, and that is where we are in

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Speaker 1: the government shutdown. And I will tell you this, We're

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Speaker 1: nowhere near. We're nowhere close to seeing this resolved. And

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Speaker 1: the biggest reason is Donald Trump's not involved. Whatever you

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Speaker 1: think of Donald Trump, these days, you cannot negotiate with

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Speaker 1: Congressional Republicans without the sign off of Donald Trump. Congressional

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Speaker 1: Republicans cannot sign off on anything without getting permission from

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Speaker 1: Donald Trump. What do I mean by that? Permission? Sounds

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Speaker 1: you know, it sounds like I'm being snarky. But the

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Speaker 1: fact is, if Trump doesn't like something, he can absolutely

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Speaker 1: pull the rug out underneath from Republicans, as he has

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Speaker 1: right as he did as he does to his own

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Speaker 1: cabinet secretaries. He just did a big one on Howard Lutnik,

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Speaker 1: who was about to amp up tariffs on international pharmaceutical

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Speaker 1: companies until Donald Trump stepped in and said, nah, we're

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Speaker 1: not going to do that because he's paranoid about price

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Speaker 1: hikes and uncertain things. Right, Prescription drugs is one that

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Speaker 1: he's ultra sensitive to. He doesn't seem to be sensitive

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Speaker 1: to some things where his tariffs raise prices, but on pharmaceuticals.

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Speaker 1: He is sensitive to that. I think it gets what

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Speaker 1: he believes is a big part of his constituency, older,

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Speaker 1: culturally conservative Americans who have been voting Democrat for most

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Speaker 1: of most of this twenty first century until Donald Trump

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Speaker 1: essentially promised that he wasn't going to be a Republican

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Speaker 1: that tried to cut solid security, Medicare and Medicaid. Of course,

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Speaker 1: we're going to about to litigate a midterm election over

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Speaker 1: whether what the Republicans did is a cut to medicaid

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Speaker 1: or not, and what voters think of the medicaid policy

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Speaker 1: that Republicans have put in. But it's just a fact.

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Speaker 1: And with Donald Trump really not engaged yet in the

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Speaker 1: government shutdown at all, he is in the Middle East

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Speaker 1: as I record this, essentially or on his way to

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Speaker 1: the Middle East, getting ready for a victory lap. And frankly,

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Speaker 1: it's a victory lap he deserves on this one, because

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Speaker 1: you know, when you look at his style of diplomacy,

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Speaker 1: it's not a good style of diplomacy to deal with

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Speaker 1: the Europeans, it is not a good style of diplomacy

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Speaker 1: to deal with Southeast Asia, China, East Asia, you name it.

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Speaker 1: Not a good way. Maybe you could argue his style

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Speaker 1: works sort of kind of with the Indians, but that

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Speaker 1: so far has been a bit problematic. The one place

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Speaker 1: where his style of diplomacy I think can work is

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Speaker 1: in the Middle East. He's transactional, where many other of

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Speaker 1: an American president wouldn't feel comfortable, sort of doing the

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Speaker 1: kind of sleazy financial deals that are being done with

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Speaker 1: the Gulf States right now that get them engaged in

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Speaker 1: helping to pay for the rebuild of Gaza, get them

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Speaker 1: engaged with working with Israel, and if the Trumps make

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Speaker 1: a couple of bucks off of it, what does Donald

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Speaker 1: Trump care? And all of this right that it is

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Speaker 1: this sort of scratch my back, scratch your back kind

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Speaker 1: of mindset. It's unethical. It's some then that I think

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Speaker 1: we're not comfortable our government doing, but it's going to

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Speaker 1: get the job done in some ways because there are

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Speaker 1: no rules in the Middle East at times. I think

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Speaker 1: that that's why you're seeing this style where ninety percent

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Speaker 1: of the time it's ineffective, but in this case it's

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Speaker 1: an effective way to go. I don't know if another

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Speaker 1: American president could have bullied Netnahu into taking this deal.

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Speaker 1: He didn't want to take any deal because his right

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Speaker 1: flank wasn't going to accept any deal. Any deal that

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Speaker 1: stopped this war clearly wasn't going to be acceptable to

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Speaker 1: the far right. One thing Donald Trump wanted was a victory, right,

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Speaker 1: He wanted to take the win. And it's an interesting

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Speaker 1: parallel because he basically it was interesting when they announced

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Speaker 1: the deal Hamas accepted, but not quite on the terms

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Speaker 1: that Israel wanted. Trump went ahead and said, great, great

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Speaker 1: job Hamas, glad you took this deal, and it left

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Speaker 1: Netnah who completely naked, right, he yanked the rug. Bibe

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Speaker 1: did not want to say that Hamas agreed to those terms.

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Speaker 1: He wanted it continue to press forward, and Trump essentially

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Speaker 1: told him, no, you're not going to do it. Take

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Speaker 1: the win and move on. Now. Of course, the question

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Speaker 1: is going to be whether politically BB can survive without

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Speaker 1: having the threat of war. Right Who's entire political career

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Speaker 1: has been about playing off of fear, fear of a Ran,

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Speaker 1: fear of Hamas, fear of Hesbelah. But it's always been

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Speaker 1: fear fear fear. In some ways, He's had, you know,

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Speaker 1: the last two years incredibly successful dealing with Iran, dealing

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Speaker 1: with Lebanon, and Hesbela essentially is kneecapped Hesbela completely. Even

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Speaker 1: the uties are laying off, You're seeing diplomatic ties being

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Speaker 1: forged with many a Gulf state, and with all of

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Speaker 1: those fear factors off the table, it is likely going

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Speaker 1: to mean that this is probably the beginning of the

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Speaker 1: end of bb NET. Now, who's political career is. Does

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Speaker 1: he have another six months? Does he stretch this a year?

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Speaker 1: We'll see. I told you about that poll last week

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Speaker 1: that showed two thirds of Israeli voters believe he should resign.

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Speaker 1: About two thirds of those wanted him to resign immediately,

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Speaker 1: another third we're willing to wait till the war is over. Well,

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Speaker 1: the war is essentially on its way to being over,

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Speaker 1: So we are now up to two thirds of Israelis

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Speaker 1: believe he needs to take responsibility. That it was on

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Speaker 1: his watch that an exposed Israel got attacked by Jamas

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Speaker 1: and all of it. You know, it was strange. Much

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Speaker 1: of the military strategy that bb signed off on dealing

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Speaker 1: with Iran, the hooties or hesblah, we're all really smart

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Speaker 1: and savvy. He never dealt He never listened to his

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Speaker 1: military advisors on how to deal with Gaza and Hamas,

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Speaker 1: which is arguably why it was so brutal, why it

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Speaker 1: was so terrible, why it was so poorly thought out,

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Speaker 1: and why it is made Israel among the most isolated

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Speaker 1: nations in the free world. And that's uh, that's sad.

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Speaker 1: For It's just sad. I'm very sad about the fact

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Speaker 1: that Israel is so isolated. I'm relieved that many of

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Speaker 1: the threats are gone. But how you conduct yourself over

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Speaker 1: time has a huge impact long term, and we're going

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Speaker 1: to see what kind of long term penalty israel Is

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Speaker 1: is going to have to pay for. How for the

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Speaker 1: horrendous way that BB and his team conducted the war

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Speaker 1: and gossip everywhere else was much more precision efficiency, sort

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Speaker 1: of the the the way the Israelis had been in

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Speaker 1: some ways admired by militaries around the world for their

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Speaker 1: for their Saturday is havvy and their strategy. Nobody was

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Speaker 1: admiring what they were doing in Gaza. There was nothing

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Speaker 1: like that, and in some ways that was driven by

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Speaker 1: just a far right fringe that was keeping BB in power.

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Speaker 1: But still, that is what President Trump is doing right now.

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Speaker 1: He's taking a victory Levet. What he is not doing

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Speaker 1: is in the room on the shutdown, and that at

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Speaker 1: the end of the day is why we are going

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Speaker 1: to be here until he engages and at this point

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Speaker 1: and this is this sort of gets to the theme

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Speaker 1: I want to hit on today, and that is the

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Speaker 1: sort of next level ugliness of our politics. You know,

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Speaker 1: there's always been this obviously politics and governing blur, but

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Speaker 1: there is a point where every successful government, no matter

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Speaker 1: which why you were governed, why you were elected, you

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Speaker 1: were elected because you're a liberal, you're elected because you

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Speaker 1: were a conservative, that ultimately, when you're governing you have

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Speaker 1: to do what's in the best interest of everybody. That

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Speaker 1: when you're governing, you don't just worry about your supporters,

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Speaker 1: you actually worry about the electorate as a whole. That's

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Speaker 1: the hallmark of this democracy. This administration governs has weaponized

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Speaker 1: everything through a political lens. When you look at what

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Speaker 1: Russell Boyd is doing at the Budget Department, this is

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Speaker 1: not a left right thing. This is dangerous behavior because

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Speaker 1: the minute we decide that you should govern politically and

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Speaker 1: only govern for those that support you, that is the

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Speaker 1: end of the republic as we know it is. I'm

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Speaker 1: not saying that our democracy ends. But what it becomes

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Speaker 1: is that each time one party gets elected, they get

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Speaker 1: in there and decide to purge the other party and

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Speaker 1: purge the government of You've heard Donald Trump say that

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Speaker 1: he wants to just lay off the Democrat part of

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Speaker 1: the government, right, which is why you know, in their

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Speaker 1: first round of doing this, Russell Voyd, who is as usual,

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Speaker 1: is sloppy with his initial you know, he comes across

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Speaker 1: as somebody that's very precise. But it's shocking how often

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Speaker 1: they do a lot of stupid things when they try

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Speaker 1: to do these layoffs or reduction, the reduction in force,

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Speaker 1: and that they overfired at CDC, and they overfired at HHS.

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Speaker 1: And why did they target, right, HHS is considered a

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Speaker 1: democratic cabinet agency. Right, It's obvious they do that when

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Speaker 1: you look which ones they consider the democratic agencies and

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Speaker 1: which one they consider the republican agencies. Like nobody has

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Speaker 1: essentially hardly anybody's been furloughed or laid off from the

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Speaker 1: Department of Olymit Security, but quite a few have been

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Speaker 1: laid off at the Department of Labor. And they went

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Speaker 1: with a hatchet at the Department of HHS, specifically at CDC,

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Speaker 1: and then they realized, oh wow, all these people are

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Speaker 1: experts at certain things. These aren't political acts. These are

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Speaker 1: reputable scientists that have incredible expertise in a lot of

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Speaker 1: areas that are crucial for the US government. To be

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Speaker 1: involved in. Public health is something government has to be

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Speaker 1: involved in. This is not something you can privatize, certainly,

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Speaker 1: and so it is this is what is so scary

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Speaker 1: about what's happening. And in some ways, Lindsay Graham gave

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Speaker 1: a piece of this in a recent appearance on Meet

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Speaker 1: the Press, and this goes at the weaponization of the

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Speaker 1: Justice Department, where essentially he justified what Trump was doing

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Speaker 1: by saying, but they went after Trump, and because Letitia

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Speaker 1: James went after Trump and went over the top something

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Speaker 1: that I look, I don't disagree that she shouldn't have.

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Speaker 1: She shouldn't have gone there. She could have, but she

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Speaker 1: went there for solely political reasons. You know, there it is.

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Speaker 1: It's certainly that doesn't mean he didn't do anything wrong,

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Speaker 1: but it's pretty clear she went after him. To quote,

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Speaker 1: get Trump on that front. But if you are upset

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Speaker 1: about the weaponization law of law enforcement, then the last

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Speaker 1: thing you ought to be doing is then weaponizing law enforcement.

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Speaker 1: But that's exactly what they're doing, right. Pam Bondi's just

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Speaker 1: despicable appearance in front of the Judiciary Committee last week,

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Speaker 1: where you know, we now have learned thanks to some

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Speaker 1: photographs that sort of leaked she wrote down. She clearly

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Speaker 1: had her staff she so cares about politicizing the Justice

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Speaker 1: Department that she prepared for her testimony with one line

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Speaker 1: Zingers to go after any Democrat that questioned her in

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Speaker 1: a tough way. So she like had some pre made

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Speaker 1: attacks on Sheldon Whitehouse and pre made attacks on different

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Speaker 1: Democrats that questioned what she was doing over there. And

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Speaker 1: it just just take a step back, take your partisan

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Speaker 1: hat off, or put your partisan hat on, and say

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Speaker 1: if that is how Merret Garland had behaved, okay, andage

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Speaker 1: Senate Judiciary Committee just coming up with these spending time

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Speaker 1: taxpayer dollars to get her, get his staff to write

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Speaker 1: one line zingers. Republicans would be rightfully apoplectic at the

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Speaker 1: politicizing of the Justice Department. But that's exactly what Pam

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Speaker 1: Bondi did. She literally spent taxpayer dollars coming up with

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Speaker 1: one liners and zingers to go after rather than explaining

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Speaker 1: if they're because she had no legal rationale for what

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Speaker 1: they did to Jim Comey. She had no legal rationale

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Speaker 1: for what they're doing to Leticia James. She had no

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Speaker 1: legal rationale to how they're just firing US attorneys if

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Speaker 1: they don't abide by the President's words. And you know,

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Speaker 1: this is another story that sort of has gotten lost.

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Speaker 1: The Washington Post has since reported and got multiple sources

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Speaker 1: to confirm that when in the infamous Donald Trump truth

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Speaker 1: social posts, that is going to probably get the Jim

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Speaker 1: Comy case thrown out of court, and likely we'll get

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Speaker 1: the Leticia James throw out of court because of the

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Speaker 1: obvious bias that was used to get them and diet it.

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Speaker 1: And if I remind you, the truth social Post stated this, Pam,

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Speaker 1: I have reviewed over thirty statements in posts saying that

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Speaker 1: essentially quote same old story as last time, All talk,

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Speaker 1: no action, nothing is being done. What about Kmy, Adam,

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Speaker 1: Shifty Shift, Letitia? They're all guilty as hell, but nothing

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Speaker 1: is going to be done. Then we almost put a

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Speaker 1: Democrat supported US attorney in Virginia and with a really

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Speaker 1: bad Republican past, awoke rhino who is never going to

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Speaker 1: do his job that's why two of the worst DEM

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Speaker 1: senators pushed him so hard, referring to Mark Warner and

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Speaker 1: Tim Kaine for agreeing to have you to confirm that

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Speaker 1: US attorney even lied to the media and said he

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Speaker 1: quit and that we had no case. No, I fired him,

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Speaker 1: and there is a great case. And many lawyers in

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Speaker 1: legal pundits say so, Lindsay Halligan is a really good

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Speaker 1: lawyer and likes you a lot. We can't delay any longer.

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Speaker 1: It's killing our reputation and our credibility. They impeach me twice,

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Speaker 1: induited me five times over. Nothing just must be served now,

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Speaker 1: President DJT, I repeat this because we now know this

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Speaker 1: was never intended to be a public truth social post,

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Speaker 1: so believe it or not, in the year twenty twenty

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Speaker 1: five your United States government, the President of the United

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Speaker 1: States sends a private direct message. Although he didn't the

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Speaker 1: seventy nine year old techno expert didn't know how to

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Speaker 1: do it. Pretty much all of our some of us

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Speaker 1: in our fifties have been there, but certainly many people

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Speaker 1: in there. Was this supposed to be public? I didn't know,

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Speaker 1: but apparently he was trying to send her a private message.

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Speaker 1: Apparently the only way he can send a private message

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Speaker 1: to the sitting Attorney General of the United States is

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Speaker 1: through his truth Social app. Seriously, but apparently that's what

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Speaker 1: it was, because this was never meant for the public.

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Speaker 1: This was supposed to be a direct message. This is

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Speaker 1: how your president of the United States communicates with our

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Speaker 1: attorney general. Our president is doing is communicating this way.

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Speaker 1: How what kind of direct messages have gotten through? This

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Speaker 1: is how he communicates even to his own staff. Look,

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Speaker 1: he was clearly threatening her and like, hey, you better

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Speaker 1: get it done. I already fired in a US attorney

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Speaker 1: that wouldn't do what I asked. I mean, it is

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Speaker 1: not hard to jump to the conclusions that he was

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Speaker 1: using this. You know, he didn't. He didn't give her

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Speaker 1: any any sort of honorific It was pam, let me

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Speaker 1: tell you what you're going to do. But I don't

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Speaker 1: think we have had nearly the amount of focus and

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Speaker 1: attention to the fact that the president is communicating with

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Speaker 1: his staff on a completely unsecured truth. Trust me, you

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Speaker 1: think truth socials are really secure, just up to snuff,

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Speaker 1: right that Devin Newness Man, that guy is a real

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Speaker 1: sharp guy, right, You trust him with your cybersecurity? You

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Speaker 1: trust him with the government cybersecurity. This is the way

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Speaker 1: the president. You Look, did you have any did you

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Speaker 1: have an issue with Hillary Clinton's emails and her private server?

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Speaker 1: This is a hundred times worse. Look, this was why

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Speaker 1: some of us thought what Hillary Clinton did was wrong.

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Speaker 1: Don't set these precedents. Don't sit here and say no, no, no,

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Speaker 1: But it's okay for me because I'm somehow I'm not

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Speaker 1: you know, I know what is what belongs in the

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Speaker 1: public record, and what doesn't. And this is what happens. Right,

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Speaker 1: We do these slippery slopes, and every time somebody decides

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Speaker 1: to change the way we do certain things, everything moves.

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Speaker 1: And now this guy has decided to have carte blanche.

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Speaker 1: He has no morals or ethics at all. There are

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Speaker 1: actually laws. These are again more laws that he's breaking. Here.

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Speaker 1: Nobody's going to prosecute him for the Presidential Records Act.

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Speaker 1: We we thought about trying to do that during the

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Speaker 1: U during the term that he was not serving, when

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Speaker 1: he clearly took classified material that belonged to the government,

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Speaker 1: not Donald J. Trump. But he of course does not

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Speaker 1: see the presidency as any different other than an extension

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Speaker 1: of himself, and he doesn't see any of it that way.

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Speaker 1: There's a reason results matter more than promises, just like

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Speaker 1: there's a reason Morgan and Morgan is America's largest injury

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Speaker 1: law firm. For the last thirty five years, they've recovered

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Speaker 1: twenty five billion dollars for more than half a million clients.

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Speaker 1: It includes cases where insurance companies offered next to nothing,

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Speaker 1: just hoping to get away with paying as little as possible.

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Speaker 1: Morgan and Morgan fought back ended up winning millions. In fact,

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Speaker 1: in Pennsylvania, one client was awarded twenty six million dollars,

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Speaker 1: which was a staggering forty times the amount that the

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Speaker 1: insurance company originally offered that original ofw for six hundred

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Speaker 1: and fifty thousand dollars twenty six million, six hundred and

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Speaker 1: fifty thousand dollars. So with more than one thousand lawyers

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Speaker 1: across the country, they know how to deliver for everyday people.

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Speaker 1: If you're injured, you need a lawyer, You need somebody

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Speaker 1: to get your back. Check out for the people dot com,

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Speaker 1: Slash podcast or Dow Pound Law Pound five two nine

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Speaker 1: law on your cell phone. And remember all law firms

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Speaker 1: are not the same, So check out Morgan and Morgan.

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Speaker 1: Their fee is free unless they win a US Congress

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Speaker 1: With any other president, oversight hearings would be set. Look

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Speaker 1: at all the hearings we had with Hillary Clinton's email

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Speaker 1: server where she was up there for hours being grilled

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Speaker 1: about the use of it. And again, I'm sorry, I

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Speaker 1: think she did have to answer for that because it

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Speaker 1: was wrong that she did it, because I know why

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Speaker 1: she did it. She did it to avoid Freedom of

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Speaker 1: Information Act requests. Okay, but she but she was held accountable.

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Speaker 1: And then some nobody's holding Donald Trump accountable for what

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Speaker 1: it is a brazen violation of the Government Records Act

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Speaker 1: one two, exposing all sorts of of of security issues

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Speaker 1: by using an unsecure truth Social app to communicate with

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Speaker 1: a member of the National Security Council. The Attorney General

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Speaker 1: is a member of the National Security Council, so in theory,

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Speaker 1: much of what they discuss is classified information all somehow

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Speaker 1: in this stew again of that, you know, because I'm

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Speaker 1: sure many people feel comfortable. If you feel comfortable with

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Speaker 1: the security of truth Social, go ahead and direct message

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Speaker 1: your social security number, Donald Trump, tell me if you

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Speaker 1: would be comfortable doing that. I don't think you would.

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Speaker 1: This is something that is just completely completely insane, and

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Speaker 1: we're like totally glossed over it because we're so used

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Speaker 1: to Donald Trump not sort of abiding by norms or

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Speaker 1: following the law. You know, when we say abiding by norms,

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Speaker 1: that's code for not following the law. Sort of totally

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Speaker 1: dismissive of laws in the US Congress's past. But of

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Speaker 1: course we have a Congress. This current Republican control Congress

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Speaker 1: is the single weakest Congress we have had, easily going

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Speaker 1: back to the FDR and the New Deal. Right, but

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Speaker 1: he at least had numbers on his side. That's why

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Speaker 1: he was overwhelmingly getting Congress to essentially do what he wanted.

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Speaker 1: He actually won a large political argument which gave him

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Speaker 1: a large majority. Donald Trump has never won a majority

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Speaker 1: of anything. Even winning the popular vote, he didn't get

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Speaker 1: fifty percent. He didn't get over fifty percent. And this

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Speaker 1: Congress is just rolling over and again. The concern is

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Speaker 1: we are just setting all sorts of new precedents and

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Speaker 1: there are going to be this this Donald Trump's decision

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Speaker 1: to weaponize and ruin the credibility whatever was left of

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Speaker 1: the FBI, it is gone right. He is cash Btel

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Speaker 1: is literally making Hoover seem like a statesman. We are

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Speaker 1: completely destroying the reputation of the rule of law in

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Speaker 1: this country, all because Donald Trump can't can't accept the

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Speaker 1: fact that he won. That's what's strange here. Right. He

430
00:26:40,000 --> 00:26:41,520
Speaker 1: lied to the country when he said he wouldn't be

431
00:26:41,520 --> 00:26:44,520
Speaker 1: focused on retribution. Right, he clearly was focused on retribution.

432
00:26:46,400 --> 00:26:48,800
Speaker 1: And in his own way, he thinks like a He

433
00:26:49,359 --> 00:26:53,120
Speaker 1: thinks like a movie mobster. Okay, not a real mobster, right,

434
00:26:53,359 --> 00:26:56,359
Speaker 1: Donald Trump, everything in him is sort of imaginary in

435
00:26:56,400 --> 00:26:58,359
Speaker 1: many ways, So he thinks like a movie mobster. And

436
00:26:58,400 --> 00:27:01,119
Speaker 1: in the movie, the mobster send a message so no,

437
00:27:01,320 --> 00:27:03,680
Speaker 1: everybody knows, you don't do this again. And he goes

438
00:27:03,720 --> 00:27:06,320
Speaker 1: after certain people so that he can make sure other

439
00:27:06,359 --> 00:27:12,800
Speaker 1: people abide by his wishes. This is movie mobster stuff,

440
00:27:13,640 --> 00:27:17,679
Speaker 1: and is it really is deteriorating what is left of

441
00:27:17,720 --> 00:27:21,080
Speaker 1: political discourse in this country. It is deteriorating the reputation

442
00:27:21,600 --> 00:27:25,320
Speaker 1: long term of the Republican Party. And the thing is,

443
00:27:25,440 --> 00:27:27,840
Speaker 1: you know who knows it? About half of the elected

444
00:27:27,840 --> 00:27:30,919
Speaker 1: Republicans in Congress, they all know this is ridiculous. They

445
00:27:30,960 --> 00:27:34,040
Speaker 1: all know that if the roles were reversed, they would

446
00:27:34,080 --> 00:27:37,440
Speaker 1: be apoplectic. Sometimes every once in a while they admit it.

447
00:27:38,160 --> 00:27:42,639
Speaker 1: The governor of Oklahoma, Kevin Stitt, is one of the

448
00:27:42,720 --> 00:27:47,639
Speaker 1: few Republican governors questioning the decision by Greg Abbott to

449
00:27:47,920 --> 00:27:51,600
Speaker 1: send National Guard troops for the president's use in the

450
00:27:51,600 --> 00:27:55,480
Speaker 1: state of Illinois. As he said, if Joe Biden sent

451
00:27:55,800 --> 00:27:58,119
Speaker 1: National Guard troops from the state of Illinois and Oklahoma,

452
00:27:58,160 --> 00:28:02,280
Speaker 1: there'd be a problem Oklahoma and and a lot of Republicans,

453
00:28:02,280 --> 00:28:03,960
Speaker 1: a lot of Oklahoma's would have a problem with that.

454
00:28:05,320 --> 00:28:09,840
Speaker 1: Good for Kevin Stitt for speaking out the lack of

455
00:28:09,920 --> 00:28:13,800
Speaker 1: people and again, I understand the political fear many of

456
00:28:13,800 --> 00:28:16,679
Speaker 1: these Republicans have, but this stuff is not conservative, and

457
00:28:16,720 --> 00:28:22,399
Speaker 1: this stuff is eroding, eroding the reputation of the US government,

458
00:28:22,440 --> 00:28:26,320
Speaker 1: eroding the reputation of democracy around the world, right, Because

459
00:28:26,320 --> 00:28:29,399
Speaker 1: if the US government, which is if the United States,

460
00:28:29,400 --> 00:28:33,040
Speaker 1: which is considered the leading democracy around the world, starts

461
00:28:33,040 --> 00:28:36,080
Speaker 1: to you know, essentially be abusive in its way and

462
00:28:36,160 --> 00:28:39,280
Speaker 1: its attempts to dibort people, who are we to who

463
00:28:39,320 --> 00:28:42,280
Speaker 1: are we to talk about human rights violations to take

464
00:28:42,280 --> 00:28:45,680
Speaker 1: place in Turkey, right? Or human rights violations to take

465
00:28:45,680 --> 00:28:51,240
Speaker 1: place in China where the Wigers are clearly clearly being

466
00:28:51,640 --> 00:28:58,480
Speaker 1: ex being forced basically enforced labor camps. But we have

467
00:28:58,600 --> 00:29:01,920
Speaker 1: no credibility on these issues anymore because of how our

468
00:29:02,040 --> 00:29:06,720
Speaker 1: democracy is behaving. We have made no legal We've really

469
00:29:06,840 --> 00:29:09,880
Speaker 1: not given any legal justification for bombing boats that come

470
00:29:09,920 --> 00:29:14,360
Speaker 1: out of Venezuela. I had an interesting conversation with Jim

471
00:29:14,360 --> 00:29:16,760
Speaker 1: Stevriti's for my new Sphere show. Please check it out

472
00:29:16,800 --> 00:29:19,760
Speaker 1: and on oh Sphere if you haven't tried it, do

473
00:29:19,800 --> 00:29:22,720
Speaker 1: a free trial and check out the interview. Stavradis was terrific.

474
00:29:23,760 --> 00:29:25,840
Speaker 1: We talked, We did a whole you know, we we

475
00:29:26,120 --> 00:29:28,200
Speaker 1: we did a tour of the world, but we also

476
00:29:28,240 --> 00:29:35,600
Speaker 1: talked about what would military leaders do. What would he do?

477
00:29:35,720 --> 00:29:39,600
Speaker 1: He was the former head of Southern Command and if

478
00:29:39,640 --> 00:29:42,160
Speaker 1: he was given the orders that Southern Command has been

479
00:29:42,160 --> 00:29:45,160
Speaker 1: given in Venezuela so far. I asked him how would

480
00:29:45,160 --> 00:29:46,560
Speaker 1: he handle it? And the first thing he did, get

481
00:29:46,560 --> 00:29:49,360
Speaker 1: his lawyer, he said, his jag lawyer, which would then

482
00:29:49,520 --> 00:29:51,920
Speaker 1: and if there was some question about the legality of it,

483
00:29:51,960 --> 00:29:53,760
Speaker 1: he would go back to the Secretary of Defense and

484
00:29:53,800 --> 00:29:58,480
Speaker 1: say what is the legal justification of this? And if

485
00:29:58,480 --> 00:30:01,000
Speaker 1: they created if they had a legal justification that he

486
00:30:01,040 --> 00:30:05,680
Speaker 1: felt that that was defensible, he would follow the order,

487
00:30:05,680 --> 00:30:07,440
Speaker 1: but if he couldn't follow the order, he would resign.

488
00:30:08,480 --> 00:30:11,080
Speaker 1: And I asked him, I said, that's what is the if?

489
00:30:12,600 --> 00:30:17,200
Speaker 1: What is the most likely scenario if a high level

490
00:30:18,200 --> 00:30:21,360
Speaker 1: general or admirals given what they believe is an illegal order?

491
00:30:21,400 --> 00:30:24,520
Speaker 1: And he said, they'd likely resign without saying it in public,

492
00:30:25,200 --> 00:30:32,760
Speaker 1: just simply resign. There's there's that in his His explanation

493
00:30:32,920 --> 00:30:38,240
Speaker 1: was there is such a high level of belief in

494
00:30:38,360 --> 00:30:42,240
Speaker 1: staying out of the political fray that many a general

495
00:30:42,320 --> 00:30:48,080
Speaker 1: or admiral would feel uncomfortable making themselves the story in

496
00:30:48,160 --> 00:30:50,640
Speaker 1: something like that. I know some of you may hear that,

497
00:30:50,720 --> 00:30:52,520
Speaker 1: because I told the story to a few others and

498
00:30:52,520 --> 00:30:55,600
Speaker 1: they were disappointed to hear that. Many of these generals

499
00:30:55,600 --> 00:30:59,360
Speaker 1: and admirals, if they choose resignation, would probably do so

500
00:30:59,440 --> 00:31:03,280
Speaker 1: silently and not not go public right away with why

501
00:31:03,320 --> 00:31:05,440
Speaker 1: they were resigning. Maybe they'd eventually go public, but not

502
00:31:05,560 --> 00:31:12,680
Speaker 1: right away. But that's just the that's that's how seriously

503
00:31:13,280 --> 00:31:17,040
Speaker 1: many in the military take the a political status of

504
00:31:17,080 --> 00:31:20,440
Speaker 1: the military, and what Donald Trump's trying to do right

505
00:31:20,440 --> 00:31:23,280
Speaker 1: now by politicizing the military, by trying to turn the military.

506
00:31:23,800 --> 00:31:26,840
Speaker 1: I mean, it was interesting to me to see the

507
00:31:26,880 --> 00:31:29,520
Speaker 1: story about Joe Biden in the Washington Post where Biden

508
00:31:29,640 --> 00:31:33,960
Speaker 1: was really seething apparently at how Donald Trump in that

509
00:31:34,720 --> 00:31:39,160
Speaker 1: speech in front of the military leaders seemed to run

510
00:31:39,200 --> 00:31:43,440
Speaker 1: down Biden personally like eight or nine times, right, totally nope. Again,

511
00:31:43,760 --> 00:31:48,600
Speaker 1: before Donald Trump, presidents drew the line at at sort

512
00:31:48,640 --> 00:31:53,880
Speaker 1: of dehumanizing previous presidents. Right, you may criticize previous policies,

513
00:31:54,160 --> 00:31:56,360
Speaker 1: but there was always there was some sort of respect

514
00:31:56,440 --> 00:31:59,720
Speaker 1: given to the person that once held the office. And

515
00:32:00,000 --> 00:32:03,760
Speaker 1: Donald Trump's lack of respect. And a supporter will tell

516
00:32:03,800 --> 00:32:07,320
Speaker 1: me he's he's treating Biden the way he thinks Biden

517
00:32:07,360 --> 00:32:12,240
Speaker 1: treated him. Of course, Biden gave Trump a post election

518
00:32:12,520 --> 00:32:17,040
Speaker 1: oval office meeting. Donald Trump did not do that. Joe

519
00:32:17,080 --> 00:32:20,560
Speaker 1: Biden accepted the results of the twenty twenty four election.

520
00:32:20,760 --> 00:32:23,440
Speaker 1: Donald Trump didn't accept the results of the twenty twenty election.

521
00:32:25,120 --> 00:32:30,440
Speaker 1: But he has just runs down everybody. Shoot, he's runs

522
00:32:30,440 --> 00:32:34,880
Speaker 1: down pretty much every president before him except Abraham Lincoln,

523
00:32:34,960 --> 00:32:38,240
Speaker 1: and then sort of has the has this weird obsession

524
00:32:38,280 --> 00:32:41,840
Speaker 1: with saying he's better. Some people think he's greater president

525
00:32:41,880 --> 00:32:45,200
Speaker 1: than Lincoln. He's lucky. Some people don't think he's being

526
00:32:45,200 --> 00:32:49,640
Speaker 1: compared with James Buchanan, and I'll just leave it at that.

527
00:32:49,880 --> 00:32:58,440
Speaker 1: But it is this politicizing of everything right, using the

528
00:32:58,480 --> 00:33:03,520
Speaker 1: government shutdown to own the attack Democrats. He's supposed to

529
00:33:03,600 --> 00:33:07,280
Speaker 1: govern for the entire United States of America. And you've

530
00:33:07,280 --> 00:33:10,640
Speaker 1: heard me rant about this before, but this inability to

531
00:33:10,800 --> 00:33:14,400
Speaker 1: want to go again. If a democratic administration refused to

532
00:33:14,480 --> 00:33:18,600
Speaker 1: govern for Republicans tried to find a way to prevent

533
00:33:19,360 --> 00:33:25,840
Speaker 1: government congressionally approved government money from going to a constituency

534
00:33:25,840 --> 00:33:29,719
Speaker 1: that votes more Republican than Democrat, there would be impeachment proceedings,

535
00:33:30,640 --> 00:33:34,880
Speaker 1: and by the way, it would be justified. What Donald

536
00:33:34,920 --> 00:33:39,960
Speaker 1: Trump is doing is illegal, will likely get reversed by

537
00:33:39,960 --> 00:33:43,880
Speaker 1: the courts, but in the meantime, he is setting some

538
00:33:44,000 --> 00:33:48,320
Speaker 1: precedents that this is somehow acceptable politics and the lack

539
00:33:48,480 --> 00:33:51,320
Speaker 1: as always and I know I'm just sort of old

540
00:33:51,360 --> 00:33:55,440
Speaker 1: man yelling at cloud here, but the inability of what's

541
00:33:55,560 --> 00:33:59,479
Speaker 1: left of the principal elected Republicans out there who cannot

542
00:33:59,480 --> 00:34:03,120
Speaker 1: bring them else to say this is wrong because they

543
00:34:03,200 --> 00:34:06,360
Speaker 1: know it's wrong, all because they are just trying to

544
00:34:06,400 --> 00:34:10,200
Speaker 1: survive politically, because oh, you know, some of them say hey,

545
00:34:10,200 --> 00:34:13,480
Speaker 1: if you got rid of me, somebody crazier would replace me.

546
00:34:13,719 --> 00:34:21,520
Speaker 1: That's just that's just wishful thinking. Nobody is irreplaceable, Nobody,

547
00:34:21,719 --> 00:34:25,200
Speaker 1: even James Franklin at Penn State, right, nobody is irreplaceable.

548
00:34:25,239 --> 00:34:25,920
Speaker 1: How'd you like that?

549
00:34:26,040 --> 00:34:26,200
Speaker 2: Right?

550
00:34:27,239 --> 00:34:28,680
Speaker 1: Giving you a hint a little bit of what I'm

551
00:34:28,680 --> 00:34:34,000
Speaker 1: gonna chat about in football after the interview. But it

552
00:34:34,080 --> 00:34:39,680
Speaker 1: is really the left. You know, look, we've got a

553
00:34:39,719 --> 00:34:41,920
Speaker 1: lot of crazy stuff that's happening right now with the

554
00:34:41,960 --> 00:34:45,200
Speaker 1: way he's conducting this government. But the idea that he

555
00:34:45,239 --> 00:34:48,880
Speaker 1: communicates with his staff via direct message on truth social

556
00:34:49,320 --> 00:34:52,359
Speaker 1: that sometimes can't make it out. He has put you know,

557
00:34:52,800 --> 00:34:56,680
Speaker 1: so much of national security at risk by doing that.

558
00:34:56,719 --> 00:35:01,240
Speaker 1: And again god only knows how other what other bad

559
00:35:01,320 --> 00:35:05,000
Speaker 1: idea ways that they're communicating with each other, including members

560
00:35:05,000 --> 00:35:07,719
Speaker 1: of the national security staff. And then the second thing

561
00:35:07,840 --> 00:35:15,040
Speaker 1: is the lack of outrage or concern that Again, this

562
00:35:15,080 --> 00:35:17,520
Speaker 1: goes to the whole two wrongs make a right. Donald

563
00:35:17,560 --> 00:35:21,520
Speaker 1: Trump governs as if two wrongs make a right, so weaponizing,

564
00:35:21,600 --> 00:35:25,399
Speaker 1: So if he believes that Leticia James unfairly prosecuted him,

565
00:35:25,440 --> 00:35:31,560
Speaker 1: he's gonna unfairly go after her well lucky for both

566
00:35:31,640 --> 00:35:35,200
Speaker 1: Jim Comy and Leticia James. Donald Trump said the quiet

567
00:35:35,200 --> 00:35:38,319
Speaker 1: part out loud because he didn't know how to send

568
00:35:38,360 --> 00:35:42,319
Speaker 1: a direct message to Pam Bondy on truth Social. But

569
00:35:42,440 --> 00:35:45,319
Speaker 1: imagine being a cabinet secretary and realizing before you go

570
00:35:45,360 --> 00:35:48,719
Speaker 1: to bed, oh God, did I check my direct messages

571
00:35:48,760 --> 00:35:50,719
Speaker 1: on truth Social to see if I have any new

572
00:35:50,880 --> 00:35:56,440
Speaker 1: orders to follow from dear leader. That's an this is

573
00:35:56,640 --> 00:36:02,920
Speaker 1: this is this is how we're running the country. Anyway,

574
00:36:03,920 --> 00:36:07,400
Speaker 1: Before I get to Mark Zandy, as I said, a

575
00:36:07,440 --> 00:36:11,440
Speaker 1: few little updates on the economy, I do again the

576
00:36:11,719 --> 00:36:17,520
Speaker 1: one percent tariff threat. Look, there's no doubt that our

577
00:36:18,000 --> 00:36:20,920
Speaker 1: trade relationship with China was a mess. Is a mess,

578
00:36:21,000 --> 00:36:23,960
Speaker 1: has been a mess before Trump got there has been

579
00:36:24,000 --> 00:36:27,480
Speaker 1: a mess. Trump knows one way of trying to deal

580
00:36:27,520 --> 00:36:31,480
Speaker 1: with them tariffs sledgehammer. Biden kept many of them in place. Right.

581
00:36:31,520 --> 00:36:34,600
Speaker 1: This is a very antagonistic relationship. But what we're both

582
00:36:34,600 --> 00:36:38,640
Speaker 1: finding out is we both need things from each other

583
00:36:38,680 --> 00:36:41,919
Speaker 1: and we're going to end up having a trade deal

584
00:36:42,360 --> 00:36:44,400
Speaker 1: that gives away some things that neither side's going to

585
00:36:44,440 --> 00:36:47,800
Speaker 1: be happy about. But that's the reality of the situation.

586
00:36:48,080 --> 00:36:50,000
Speaker 1: And if we because If we don't do that, we're

587
00:36:50,000 --> 00:36:53,839
Speaker 1: going to go to war. And but this is a

588
00:36:53,880 --> 00:36:57,120
Speaker 1: reminder when you start a trade war, it is really

589
00:36:57,160 --> 00:36:59,600
Speaker 1: hard to win a trade war. And we've started a

590
00:36:59,600 --> 00:37:04,520
Speaker 1: trade war, and we're having a really hard time quote

591
00:37:04,600 --> 00:37:10,080
Speaker 1: unquote trying to win this trade war. There are real

592
00:37:10,160 --> 00:37:16,719
Speaker 1: reasons why we've got to we've got to recalibrate our

593
00:37:16,760 --> 00:37:20,759
Speaker 1: economic relationship with China, but much of it has to

594
00:37:20,760 --> 00:37:22,480
Speaker 1: do with what we need to do here, right And

595
00:37:22,680 --> 00:37:26,240
Speaker 1: and one thing Donald Trump another thing that you know, Look,

596
00:37:26,360 --> 00:37:28,359
Speaker 1: I will point out when I think Donald Trump does

597
00:37:28,400 --> 00:37:32,040
Speaker 1: things that are correct. This Midi Steel I think is

598
00:37:32,040 --> 00:37:34,600
Speaker 1: one that only he could have pulled off given the

599
00:37:35,000 --> 00:37:39,760
Speaker 1: characters involved here. But he signed an executive order basically

600
00:37:39,800 --> 00:37:47,880
Speaker 1: trying to jump start UH production and research and h

601
00:37:48,200 --> 00:37:51,920
Speaker 1: and frankly the mining of rare earth metals in the

602
00:37:52,000 --> 00:37:58,200
Speaker 1: United States. And it is what is motivating the quote

603
00:37:58,680 --> 00:38:02,480
Speaker 1: the purchase of Greenland, and that we are way too

604
00:38:02,560 --> 00:38:07,920
Speaker 1: reliant on China for these rare earth minerals. Look, if

605
00:38:07,920 --> 00:38:09,719
Speaker 1: we had, if we had, if we knew how to

606
00:38:09,719 --> 00:38:12,200
Speaker 1: conduct better form policy with Latin America over the last

607
00:38:12,239 --> 00:38:14,640
Speaker 1: fifty years. And I say we, I mean the United states.

608
00:38:14,640 --> 00:38:16,760
Speaker 1: This is not just something that Trump doesn't do well.

609
00:38:16,960 --> 00:38:20,960
Speaker 1: This is something every president hasn't done well. We could

610
00:38:21,080 --> 00:38:25,319
Speaker 1: likely have dominance in our own hemisphere, but we have

611
00:38:25,480 --> 00:38:29,160
Speaker 1: so blown our relationships down in South America, with Brazil

612
00:38:29,200 --> 00:38:34,920
Speaker 1: in particular, Mexico slightly improved there, and within Canada. All

613
00:38:35,000 --> 00:38:40,560
Speaker 1: these antagonistic relationships we're creating. Our own hemisphere likely could

614
00:38:40,600 --> 00:38:43,120
Speaker 1: be the answer to many of the rare earth metals

615
00:38:43,120 --> 00:38:47,560
Speaker 1: that we could use, but we've been short sighted there

616
00:38:47,960 --> 00:38:54,040
Speaker 1: either way. Figuring out how to either try to find

617
00:38:54,040 --> 00:38:58,839
Speaker 1: these rare earth metals domestically or diversifying our supply chain

618
00:38:58,880 --> 00:39:02,279
Speaker 1: around the world will allow us to be tougher on China.

619
00:39:02,320 --> 00:39:07,680
Speaker 1: But right now we really can't. And that's the that's

620
00:39:07,719 --> 00:39:12,440
Speaker 1: the uncomfortable that's the uncomfortable truth there. All right. So

621
00:39:12,520 --> 00:39:16,360
Speaker 1: coming up, we got Mark Sandy again, I think I

622
00:39:16,480 --> 00:39:19,719
Speaker 1: call him my answer man on the economy. Let's just

623
00:39:19,760 --> 00:39:22,280
Speaker 1: say he's really concerned about the next six to nine months,

624
00:39:23,040 --> 00:39:27,719
Speaker 1: but he's surprisingly bullish about things perhaps a year or

625
00:39:27,800 --> 00:39:30,360
Speaker 1: more from now. So with that, let's sneak in a

626
00:39:30,360 --> 00:39:33,760
Speaker 1: break when we come back by conversation with Moody's Analytics

627
00:39:33,840 --> 00:39:51,920
Speaker 1: chief economists and my friend Mark Sandy Well, as we

628
00:39:52,000 --> 00:39:55,920
Speaker 1: begin the fourth quarter of the year, if you want

629
00:39:55,960 --> 00:39:58,040
Speaker 1: to look at it in quarters, and of course it's

630
00:39:58,080 --> 00:40:00,520
Speaker 1: supposed to be the first quarter of America's fifth school year,

631
00:40:00,600 --> 00:40:03,240
Speaker 1: but we have a government shutdown since we can't agree

632
00:40:03,320 --> 00:40:06,720
Speaker 1: on those things. I always want to bring back somebody

633
00:40:06,719 --> 00:40:09,120
Speaker 1: who makes I think makes the most amount of sense

634
00:40:09,160 --> 00:40:13,360
Speaker 1: about what's happening in this economy and how much of

635
00:40:13,400 --> 00:40:16,560
Speaker 1: this uncertainty can feel certain down the road. It's of

636
00:40:16,600 --> 00:40:19,200
Speaker 1: course Mark Zandi from Moody's Analytics.

637
00:40:19,480 --> 00:40:21,480
Speaker 2: Mark, good to see you, Chuck, good to be with you.

638
00:40:21,600 --> 00:40:22,680
Speaker 2: Thanks for the opportunity.

639
00:40:23,400 --> 00:40:28,799
Speaker 1: So I have been describing the economy this way. If

640
00:40:28,840 --> 00:40:33,240
Speaker 1: you have money, have some savings, and have the ability

641
00:40:33,280 --> 00:40:36,440
Speaker 1: to invest, this gotta be is going okay for you.

642
00:40:38,040 --> 00:40:43,360
Speaker 1: But if you don't, this is a scary economy. I

643
00:40:45,080 --> 00:40:48,480
Speaker 1: confess that's a simple, simplified way of putting it. But

644
00:40:48,600 --> 00:40:51,240
Speaker 1: that's what it looks like to me as a lay person.

645
00:40:51,440 --> 00:40:54,200
Speaker 1: What kind of is that too simplified of a description

646
00:40:54,320 --> 00:40:54,880
Speaker 1: or how would you do?

647
00:40:55,040 --> 00:40:57,799
Speaker 2: No, I think that's pretty apt. I think if you're

648
00:40:57,840 --> 00:40:59,880
Speaker 2: in the top part of the income and wealth distribution,

649
00:41:00,040 --> 00:41:04,120
Speaker 2: let's say the top third of the distribution, you're doing fine.

650
00:41:04,160 --> 00:41:07,279
Speaker 2: You got a job, you're getting a pay increase, get

651
00:41:07,280 --> 00:41:12,640
Speaker 2: a bonus, you own your own home, you own some stocks,

652
00:41:12,680 --> 00:41:16,400
Speaker 2: and of course stocks are on a tear, and you

653
00:41:16,400 --> 00:41:19,120
Speaker 2: you don't really owe anything. You might I might have

654
00:41:19,160 --> 00:41:23,120
Speaker 2: a mortgage, but you probably locked in back during the pandemic,

655
00:41:23,160 --> 00:41:25,680
Speaker 2: so you've got a three three and a half four

656
00:41:25,719 --> 00:41:28,360
Speaker 2: percent mortgage rate. So you're making more on your money

657
00:41:28,360 --> 00:41:30,760
Speaker 2: market account than on your you're paying on your mortgage.

658
00:41:30,800 --> 00:41:33,840
Speaker 2: So yeah, you're sitting pretty. If you're in the bottom

659
00:41:34,120 --> 00:41:37,760
Speaker 2: two thirds of the distribution of income, certainly the bottom third,

660
00:41:38,040 --> 00:41:42,240
Speaker 2: it's a struggle. You know, you probably have a job,

661
00:41:42,320 --> 00:41:44,880
Speaker 2: but unemployment is starting to not hire her, and you

662
00:41:44,920 --> 00:41:47,920
Speaker 2: don't want to lose your job because it's getting increasingly

663
00:41:48,120 --> 00:41:50,719
Speaker 2: hard to find another one. Hiring rates are very low.

664
00:41:51,880 --> 00:41:54,919
Speaker 2: You don't you know, you really don't own very much.

665
00:41:55,160 --> 00:41:57,000
Speaker 2: If you're in the middle part of the distribution, probably

666
00:41:57,080 --> 00:41:58,480
Speaker 2: own a home. But if you're in the bottom part,

667
00:41:58,520 --> 00:42:02,160
Speaker 2: you don't, and you owe on credit cards, auto. If

668
00:42:02,160 --> 00:42:05,239
Speaker 2: you're in the bottom third, you're probably on student loan debt.

669
00:42:05,920 --> 00:42:08,120
Speaker 2: So so it is more of a struggle. So I

670
00:42:08,120 --> 00:42:11,239
Speaker 2: think that way, thinking about the economy and whether it's

671
00:42:11,239 --> 00:42:14,680
Speaker 2: working for people works is very apt. Yes, I agree.

672
00:42:14,960 --> 00:42:17,799
Speaker 1: So you know, it's interesting because this creates sort of

673
00:42:18,239 --> 00:42:21,359
Speaker 1: I think political challenges more now for the Trump administration.

674
00:42:21,480 --> 00:42:24,279
Speaker 1: You know, you know the Biden administration, and it was

675
00:42:24,320 --> 00:42:26,240
Speaker 1: Biden and I've always thought it was a bit almost

676
00:42:26,480 --> 00:42:29,480
Speaker 1: because he spent most of his professional life where the

677
00:42:29,520 --> 00:42:33,080
Speaker 1: economy was judged. A good economy was based on whether

678
00:42:33,120 --> 00:42:35,440
Speaker 1: there were jobs being created. A bad economy is when

679
00:42:35,440 --> 00:42:38,600
Speaker 1: there weren't. And I do think Donald Trump looks at

680
00:42:38,640 --> 00:42:40,560
Speaker 1: a good economy is when the stock market does well.

681
00:42:40,600 --> 00:42:44,239
Speaker 1: A bad economy is when it doesn't. And like, ultimately,

682
00:42:44,760 --> 00:42:49,719
Speaker 1: both ideas miss the Hey can I afford this economy? Right?

683
00:42:49,800 --> 00:42:52,279
Speaker 1: Can I live in this economy? You know, it's one

684
00:42:52,280 --> 00:42:55,120
Speaker 1: thing to have a job. Can you afford participating in

685
00:42:55,160 --> 00:42:57,480
Speaker 1: the economy with your job? It's one thing if the

686
00:42:57,480 --> 00:42:59,200
Speaker 1: stock market's doing well, but do you have the money

687
00:42:59,280 --> 00:43:02,239
Speaker 1: to actually benefit from that? So I do see that

688
00:43:02,280 --> 00:43:05,279
Speaker 1: as political. But let's start with what you have to do,

689
00:43:05,320 --> 00:43:07,239
Speaker 1: which is trying to forecast, trying to understand what the

690
00:43:07,320 --> 00:43:11,360
Speaker 1: economy is. There's all these little tea leaves I was

691
00:43:11,400 --> 00:43:18,000
Speaker 1: reading about the other day that people are pulling back

692
00:43:18,040 --> 00:43:21,000
Speaker 1: on big home renovations and they're now doing smaller ones.

693
00:43:21,080 --> 00:43:25,040
Speaker 1: People are pulling back on big trips, so they're doing

694
00:43:25,120 --> 00:43:28,640
Speaker 1: maybe road trips that while that you're starting to see

695
00:43:28,640 --> 00:43:34,560
Speaker 1: these little signs of a pullback consumer pullback, and it's

696
00:43:34,640 --> 00:43:38,160
Speaker 1: not yet reflective anywhere else, not quite reflected in GDP. Yet,

697
00:43:39,360 --> 00:43:42,040
Speaker 1: how important are those little indicators to you? And what

698
00:43:42,600 --> 00:43:45,160
Speaker 1: ones do you look at, especially now that government data

699
00:43:45,239 --> 00:43:46,040
Speaker 1: has been paused.

700
00:43:47,200 --> 00:43:50,400
Speaker 2: Well, yeah, I mean I pay attention to the anecdotal

701
00:43:50,440 --> 00:43:55,200
Speaker 2: information in the kind of the little pieces of information

702
00:43:55,280 --> 00:43:59,040
Speaker 2: here and there that you get from different sources, but

703
00:43:59,160 --> 00:44:04,280
Speaker 2: I ultimately lie on the the data, the aggregate data.

704
00:44:04,400 --> 00:44:06,160
Speaker 2: I mean, you can get fooled by you know, the

705
00:44:06,200 --> 00:44:09,120
Speaker 2: economy is a big elephant, right, and depending on which

706
00:44:09,120 --> 00:44:10,680
Speaker 2: part of the elephant you touch, you get a very

707
00:44:10,719 --> 00:44:13,239
Speaker 2: different picture. So that you know, if I'm in one

708
00:44:13,320 --> 00:44:16,680
Speaker 2: part of the country or another, that will influence people's thinking.

709
00:44:16,719 --> 00:44:18,920
Speaker 2: If I'm in one talking to one industry or another

710
00:44:19,440 --> 00:44:21,879
Speaker 2: that influences people thinking. If I'm in the top part

711
00:44:21,880 --> 00:44:24,520
Speaker 2: of the distribution of income or the bottom, that influences

712
00:44:24,520 --> 00:44:27,640
Speaker 2: people thinking. So I try to be careful not to

713
00:44:27,680 --> 00:44:31,279
Speaker 2: get caught up too much in the anecdotes, in those

714
00:44:31,320 --> 00:44:34,239
Speaker 2: little straws as you as you put it, look at

715
00:44:34,280 --> 00:44:38,000
Speaker 2: the aggregate data and you know, there and for me,

716
00:44:38,880 --> 00:44:41,400
Speaker 2: at the end of the day, it's still about jobs.

717
00:44:41,440 --> 00:44:43,720
Speaker 2: And you know, we're creating jobs or they good paying jobs.

718
00:44:43,760 --> 00:44:47,520
Speaker 2: Is a pay enough that people can afford to, you know,

719
00:44:47,560 --> 00:44:50,240
Speaker 2: purchase the things that they need and that they want.

720
00:44:50,960 --> 00:44:54,160
Speaker 2: And there it feels like the economy is kind of

721
00:44:54,160 --> 00:44:56,560
Speaker 2: a struggle, a bit of a struggle of you know,

722
00:44:57,040 --> 00:45:00,479
Speaker 2: in aggregate we're not creating many jobs at all. Jobs

723
00:45:00,520 --> 00:45:03,080
Speaker 2: we are being created, are you know, in a very

724
00:45:03,120 --> 00:45:07,480
Speaker 2: few industries like healthcare. It just doesn't feel like it's

725
00:45:07,520 --> 00:45:10,359
Speaker 2: working for you know, a lot of Americans. So we're

726
00:45:10,360 --> 00:45:14,920
Speaker 2: not in recession, we're growing. GDP is positive, but it

727
00:45:15,080 --> 00:45:18,080
Speaker 2: just feels kind of punk. That might be the word

728
00:45:18,120 --> 00:45:18,439
Speaker 2: to use.

729
00:45:18,880 --> 00:45:24,120
Speaker 1: So if we see the general consensus apparently is a

730
00:45:24,160 --> 00:45:28,080
Speaker 1: thirty to forty percent chance of a recession next year, Yeah,

731
00:45:27,800 --> 00:45:31,120
Speaker 1: how should folks interpret a prediction like that?

732
00:45:31,760 --> 00:45:35,720
Speaker 2: Well, the most likely scenarios we kind of navigate through

733
00:45:35,880 --> 00:45:41,120
Speaker 2: without an actual downturn, So the economy produces enough job

734
00:45:41,239 --> 00:45:44,880
Speaker 2: so that unemployment really doesn't take off. Here we're okay.

735
00:45:45,160 --> 00:45:47,080
Speaker 2: It's not it may not be great, but we're okay.

736
00:45:47,120 --> 00:45:49,480
Speaker 1: But so kind of like the first I felt like

737
00:45:49,560 --> 00:45:52,600
Speaker 1: the economy in twenty oh one twenty oh two, where

738
00:45:52,640 --> 00:45:55,440
Speaker 1: it was a mild recession but we kind of got

739
00:45:55,440 --> 00:45:55,799
Speaker 1: through it.

740
00:45:56,040 --> 00:45:59,480
Speaker 2: Yeah, that's that's right. But you know, the risks are

741
00:45:59,480 --> 00:46:01,879
Speaker 2: to the downs side, right, I mean, you know, if

742
00:46:02,520 --> 00:46:06,920
Speaker 2: if things turn out different than that kind of that

743
00:46:07,040 --> 00:46:10,040
Speaker 2: economy we just described, it's going to turn out worse,

744
00:46:10,160 --> 00:46:12,960
Speaker 2: not better. You know, just to give a little bit

745
00:46:12,960 --> 00:46:15,840
Speaker 2: more context, kind of in a typical economy, the probability

746
00:46:15,920 --> 00:46:18,080
Speaker 2: recession would be fifteen percent. We tend to have a

747
00:46:18,080 --> 00:46:20,520
Speaker 2: recession once every six seven, eight years.

748
00:46:20,440 --> 00:46:23,560
Speaker 1: So every year, if there was no you would you

749
00:46:23,560 --> 00:46:25,520
Speaker 1: would say, well, you have to put it at fifteen percent.

750
00:46:25,520 --> 00:46:27,839
Speaker 1: But that's just because that's the way it is all

751
00:46:27,880 --> 00:46:28,280
Speaker 1: the time.

752
00:46:28,680 --> 00:46:32,840
Speaker 2: That's just it's so called unconditional probability. I mean, on average,

753
00:46:32,840 --> 00:46:35,600
Speaker 2: you get a recession every seven years. Therefore fifteen percent.

754
00:46:35,640 --> 00:46:38,640
Speaker 2: So if you're a thirty percent forty percent, well, you

755
00:46:38,640 --> 00:46:41,480
Speaker 2: know that's on the high side. It's not over fifty

756
00:46:41,680 --> 00:46:44,520
Speaker 2: that I'll take it, but you know, thirty forty is

757
00:46:44,680 --> 00:46:47,919
Speaker 2: uncomfortably high you know, the other way to think about

758
00:46:47,920 --> 00:46:50,160
Speaker 2: it might be nothing else can go wrong, right. The

759
00:46:50,160 --> 00:46:56,040
Speaker 2: economy is you know punk, it's it's vulnerable to anything

760
00:46:56,080 --> 00:46:58,879
Speaker 2: that might go off the rails here, and it doesn't

761
00:46:58,880 --> 00:47:00,080
Speaker 2: have to be a big thing. It could be a

762
00:47:00,080 --> 00:47:02,640
Speaker 2: small thing because the economy is asponible as it is.

763
00:47:03,840 --> 00:47:08,640
Speaker 1: What has been the impact of what feels because you know, look,

764
00:47:08,960 --> 00:47:13,279
Speaker 1: the DOGE cuts get a lot of attention, but there's

765
00:47:13,320 --> 00:47:16,160
Speaker 1: a real pullback on government jobs on the state and

766
00:47:16,200 --> 00:47:18,640
Speaker 1: local level because there's a lot of federal money is

767
00:47:18,680 --> 00:47:20,879
Speaker 1: no longer going to state and local, right, A lot

768
00:47:20,920 --> 00:47:22,760
Speaker 1: of we had a lot of COVID. You know, it's funny,

769
00:47:22,760 --> 00:47:26,440
Speaker 1: we lived almost a decade, decade, decade and a half.

770
00:47:26,520 --> 00:47:30,279
Speaker 1: First the Great Recession sort of triggered federal help for

771
00:47:30,360 --> 00:47:34,440
Speaker 1: state and local, and then COVID created more help for

772
00:47:34,480 --> 00:47:36,960
Speaker 1: state and local. And you know, I look at a

773
00:47:37,040 --> 00:47:39,600
Speaker 1: California which is going to struggle for the first time

774
00:47:39,640 --> 00:47:41,440
Speaker 1: with a budget deficit that they got to figure out,

775
00:47:41,480 --> 00:47:43,640
Speaker 1: they got to do. They're going to do something really hard.

776
00:47:43,680 --> 00:47:46,080
Speaker 1: I think a lot of states, I think there's going

777
00:47:46,120 --> 00:47:48,000
Speaker 1: to be a lot of sort of chickens coming home

778
00:47:48,000 --> 00:47:50,319
Speaker 1: to roost in a lot of states who have these

779
00:47:50,360 --> 00:47:53,400
Speaker 1: constitutional amendments that actually have to balance our budget. Right,

780
00:47:55,440 --> 00:47:58,240
Speaker 1: what is that risk factor of contraction of government workers

781
00:47:58,239 --> 00:48:00,960
Speaker 1: and how much could that trigger a recession.

782
00:48:01,560 --> 00:48:03,360
Speaker 2: Well, we're certainly seeing a lot of job loss at

783
00:48:03,400 --> 00:48:06,840
Speaker 2: the federal level. I mean, the number of federal government

784
00:48:06,840 --> 00:48:09,440
Speaker 2: employees down about one hundred thousand since the beginning of

785
00:48:09,440 --> 00:48:11,440
Speaker 2: the year. So we are making the numbers up, but

786
00:48:11,600 --> 00:48:15,000
Speaker 2: you know, rough word magnitude, we had three million federal

787
00:48:15,040 --> 00:48:17,040
Speaker 2: government workers at the start of the year. We're now

788
00:48:17,040 --> 00:48:20,200
Speaker 2: at two nine and we've probably got another one hundred

789
00:48:20,280 --> 00:48:20,759
Speaker 2: k to go.

790
00:48:21,320 --> 00:48:23,240
Speaker 1: Now, some people will hear that, say that doesn't seem

791
00:48:23,280 --> 00:48:24,880
Speaker 1: like much two point eight to three. I mean, you

792
00:48:25,040 --> 00:48:26,960
Speaker 1: round it up, it's still three million, right, Like, I mean,

793
00:48:27,680 --> 00:48:29,640
Speaker 1: you know what I mean, Like it's yea, why is

794
00:48:29,680 --> 00:48:30,360
Speaker 1: that a lot?

795
00:48:31,680 --> 00:48:34,879
Speaker 2: Well, in the context of federal government never lays off.

796
00:48:34,920 --> 00:48:38,560
Speaker 2: It's always the reliable source of of of jobs. And historically,

797
00:48:39,360 --> 00:48:41,839
Speaker 2: h you know, it's been around three million for as

798
00:48:41,840 --> 00:48:44,400
Speaker 2: long as I can remember. So losing one hundred k

799
00:48:44,680 --> 00:48:47,360
Speaker 2: and losing another one hundred k in a short period

800
00:48:47,360 --> 00:48:50,600
Speaker 2: of time six twelve months, you know that's meaningful. It

801
00:48:50,719 --> 00:48:55,080
Speaker 2: certainly you know, obviously for the broad DC area and.

802
00:48:55,200 --> 00:48:57,840
Speaker 1: No regional economy, you can feel it, right, Yeah.

803
00:48:58,400 --> 00:49:02,120
Speaker 2: That broad metropolitan area is in a recession. There's no

804
00:49:02,360 --> 00:49:05,920
Speaker 2: doubt about that. Now if if you're right, and I

805
00:49:05,960 --> 00:49:08,360
Speaker 2: think you know, you make a good point that you know,

806
00:49:08,480 --> 00:49:11,120
Speaker 2: federal government support the state and local first states and

807
00:49:11,120 --> 00:49:14,239
Speaker 2: then local governments is now starting to wane. And you

808
00:49:14,320 --> 00:49:18,239
Speaker 2: saw a tremendous amount of support in the in the pandemic.

809
00:49:19,640 --> 00:49:22,200
Speaker 1: A lot of teachers got raises from that money, right,

810
00:49:22,280 --> 00:49:26,640
Speaker 1: Like it was just a lot of public officials with cops, firefighters, teachers,

811
00:49:26,680 --> 00:49:30,160
Speaker 1: you know, the stuff politicians feel good about. Hey, look

812
00:49:30,239 --> 00:49:32,040
Speaker 1: we gave our teachers a raise, we gave our cops

813
00:49:32,040 --> 00:49:33,120
Speaker 1: and firefighters are raised.

814
00:49:33,160 --> 00:49:35,600
Speaker 2: Well. A bunch of other states they cut taxes, right

815
00:49:35,719 --> 00:49:39,280
Speaker 2: but you know they now that that's that's an issue

816
00:49:39,320 --> 00:49:41,600
Speaker 2: because they're not getting that support from the federal government

817
00:49:41,640 --> 00:49:43,560
Speaker 2: and likely not to going far. And now they have

818
00:49:43,600 --> 00:49:47,279
Speaker 2: a diminished tax base and so that's complicating things for them.

819
00:49:47,320 --> 00:49:49,920
Speaker 2: So yeah, the state local then there are a lot

820
00:49:49,960 --> 00:49:52,319
Speaker 2: more folks working in state and local government then and

821
00:49:52,360 --> 00:49:55,440
Speaker 2: then in the federal government, and that if that sector

822
00:49:55,520 --> 00:49:58,600
Speaker 2: is now not adding to payrolls and ultimately starting to

823
00:49:58,719 --> 00:50:01,799
Speaker 2: reduce perils and that becomes an even bigger deal. So yeah,

824
00:50:01,840 --> 00:50:04,759
Speaker 2: it's a It's just you know, the labor market has

825
00:50:06,160 --> 00:50:09,839
Speaker 2: gone flat here. It's not creating any jobs. The only

826
00:50:09,880 --> 00:50:13,080
Speaker 2: sectors that's creating jobs is healthcare, and everything else is

827
00:50:13,080 --> 00:50:16,000
Speaker 2: a little bit adding a little bit or reducing a

828
00:50:16,000 --> 00:50:19,680
Speaker 2: little bit. Government is reducing a little bit. At this point, all.

829
00:50:19,600 --> 00:50:22,480
Speaker 1: Right, let's talk about AI. Yeah, how is A How

830
00:50:22,520 --> 00:50:25,839
Speaker 1: are is AI having an impact on the job market yet?

831
00:50:26,840 --> 00:50:30,279
Speaker 2: Uh? Yeah, there's some evidence. You know, I mentioned the

832
00:50:30,360 --> 00:50:32,880
Speaker 2: hiring rate, the fact that if you look at the

833
00:50:32,960 --> 00:50:36,200
Speaker 2: number of people getting hired relatives of the workforce, it's

834
00:50:36,239 --> 00:50:38,000
Speaker 2: about as low as it gets when you're in the

835
00:50:38,040 --> 00:50:40,600
Speaker 2: middle of a recession. We're not in recession because businesses

836
00:50:40,600 --> 00:50:43,560
Speaker 2: aren't laying off, but they're not hiring. And one reason

837
00:50:43,640 --> 00:50:46,600
Speaker 2: they may not be hiring is related to AI. You know,

838
00:50:46,640 --> 00:50:49,600
Speaker 2: businesses are thinking, oh, you know, do I really need

839
00:50:49,640 --> 00:50:52,360
Speaker 2: to go out and hire those folks because artificial intelligence

840
00:50:52,360 --> 00:50:54,799
Speaker 2: will be able to empower my existing workforce to do

841
00:50:54,840 --> 00:50:55,839
Speaker 2: those do that work.

842
00:50:55,840 --> 00:50:58,520
Speaker 1: And I don't know, is this an experiment? Like my

843
00:50:58,680 --> 00:51:01,399
Speaker 1: sense is businesses are trying to see if they can

844
00:51:01,800 --> 00:51:04,200
Speaker 1: use AI to replace humans and then they're good and

845
00:51:04,200 --> 00:51:06,480
Speaker 1: then if they don't, they'll go and hire. But if

846
00:51:06,520 --> 00:51:09,919
Speaker 1: they can, then could then exponentially grow.

847
00:51:10,120 --> 00:51:15,480
Speaker 2: Yeah, absolutely, yeah, I think you know, AI has captured

848
00:51:15,480 --> 00:51:19,800
Speaker 2: the imagination, you know, particularly of the senior leaders management

849
00:51:19,800 --> 00:51:23,719
Speaker 2: of many large multinational corporations around the country. In fact,

850
00:51:23,760 --> 00:51:28,280
Speaker 2: they're selling themselves as AI companies increasingly because stock prices

851
00:51:28,280 --> 00:51:31,800
Speaker 2: are as high as they are juiced by the promise

852
00:51:31,880 --> 00:51:37,800
Speaker 2: of artificial intelligence creating all this wealth and genering a

853
00:51:37,800 --> 00:51:41,719
Speaker 2: lot of economic growth that they are now saying, we

854
00:51:41,800 --> 00:51:45,000
Speaker 2: are AI. Therefore we have to make AI work for

855
00:51:45,200 --> 00:51:48,920
Speaker 2: our businesses, and so they're asking their existing workforce to

856
00:51:49,080 --> 00:51:51,759
Speaker 2: figure that out. And you're right, I mean, so far,

857
00:51:52,640 --> 00:51:54,680
Speaker 2: you know, there's some success stories, but there's a lot

858
00:51:54,719 --> 00:51:57,880
Speaker 2: of failures as well, and must have to see how

859
00:51:57,920 --> 00:51:59,880
Speaker 2: this plays out, and some companies will have to backtrack

860
00:51:59,920 --> 00:52:03,080
Speaker 2: at some point. But I think ultimately, you know, businesses

861
00:52:03,120 --> 00:52:06,640
Speaker 2: will figure it out, and new companies when they form,

862
00:52:06,960 --> 00:52:09,759
Speaker 2: they're going to optimize around the AI technology, just like

863
00:52:09,800 --> 00:52:12,360
Speaker 2: they did the Internet, and so it will diffuse throughout

864
00:52:12,400 --> 00:52:14,800
Speaker 2: the economy and will have more of an impact on

865
00:52:14,840 --> 00:52:17,680
Speaker 2: the labor market going forward. Particularly certain occupations in certain

866
00:52:17,680 --> 00:52:21,799
Speaker 2: industries that are more likely to be affected by the

867
00:52:21,880 --> 00:52:22,560
Speaker 2: use of AI.

868
00:52:22,920 --> 00:52:25,799
Speaker 1: Yeah, politically, I think AI job, the fear of AI

869
00:52:25,880 --> 00:52:27,880
Speaker 1: job displacement, I think it is going to be a

870
00:52:27,920 --> 00:52:30,960
Speaker 1: big issue in twenty eight, But not until twenty eight, right,

871
00:52:31,000 --> 00:52:33,520
Speaker 1: Like I think we're I don't think we're there yet

872
00:52:33,880 --> 00:52:39,719
Speaker 1: on that. But when is there? You know, all these

873
00:52:39,800 --> 00:52:42,960
Speaker 1: data center investments, all this money that's going into this

874
00:52:43,080 --> 00:52:47,440
Speaker 1: AI expansion, is it create is there? It's not creating

875
00:52:47,560 --> 00:52:49,960
Speaker 1: new jobs, it's just computer power.

876
00:52:50,040 --> 00:52:55,000
Speaker 2: And so far it's it's more about it's not about jobs.

877
00:52:55,120 --> 00:52:59,320
Speaker 2: It's not creating jobs. It's more about GDP and.

878
00:52:59,280 --> 00:53:03,480
Speaker 1: It's creating a lot wealth, creating revenue. It's creating wealth.

879
00:53:03,840 --> 00:53:08,040
Speaker 1: It's we're really good at manufacturing money right now.

880
00:53:08,360 --> 00:53:10,279
Speaker 2: Well, here is an amazing thing. And this goes back

881
00:53:10,280 --> 00:53:11,680
Speaker 2: to where we started when we were talking about the

882
00:53:11,680 --> 00:53:13,239
Speaker 2: folks in the top part of the distribution of the

883
00:53:13,239 --> 00:53:17,560
Speaker 2: wealth distributioning. Well, the value of all US publicly traded

884
00:53:17,600 --> 00:53:21,640
Speaker 2: stocks is up ten trillion dollars in one year, So

885
00:53:22,040 --> 00:53:25,840
Speaker 2: it's sixty seven trillion dollars today. It was fifty seven

886
00:53:25,880 --> 00:53:30,399
Speaker 2: trillion dollars a year ago. Trillion dollars. And of course

887
00:53:30,440 --> 00:53:33,759
Speaker 2: if you own stocks, and particularly the AI stocks, you're

888
00:53:33,800 --> 00:53:36,160
Speaker 2: feeling pretty good and that's what's kind of driving the

889
00:53:36,160 --> 00:53:38,640
Speaker 2: economic training. So the real impact of AI so far,

890
00:53:39,239 --> 00:53:44,160
Speaker 2: it's not about jobs. It's more about wealth in GDP

891
00:53:45,080 --> 00:53:48,719
Speaker 2: and not more. In fact, if anything, it's reduced to

892
00:53:48,840 --> 00:53:51,680
Speaker 2: employment and the tech sector and some of the other

893
00:53:51,719 --> 00:53:53,840
Speaker 2: sectors that are that we just talked about.

894
00:53:54,080 --> 00:53:56,440
Speaker 1: So give me some historical parallels. We had this kind

895
00:53:56,480 --> 00:54:00,520
Speaker 1: of investment in tech in the nineties turn of this century.

896
00:54:00,840 --> 00:54:03,680
Speaker 1: We had this kind of investment in the Industrial Age.

897
00:54:03,680 --> 00:54:05,839
Speaker 1: We had this kind of investment in the build out

898
00:54:05,840 --> 00:54:11,239
Speaker 1: of the suburbs after the after World War Two? Is

899
00:54:11,280 --> 00:54:16,600
Speaker 1: this a bubble? And and it certainly looks bubblish, and

900
00:54:16,680 --> 00:54:19,239
Speaker 1: yet it's amazing to me only Jamie Diamond seems to

901
00:54:19,280 --> 00:54:22,600
Speaker 1: be the the only one in that world that seems

902
00:54:22,600 --> 00:54:25,080
Speaker 1: to be concerned that this could could all be a bubble.

903
00:54:25,880 --> 00:54:28,279
Speaker 1: How would you you know, is this something you can

904
00:54:28,360 --> 00:54:30,439
Speaker 1: forecast or you don't know if it's a bubble until

905
00:54:30,440 --> 00:54:31,160
Speaker 1: after it pops?

906
00:54:31,320 --> 00:54:34,759
Speaker 2: Well, uh, And I'm hearing more voices kind of uh

907
00:54:35,520 --> 00:54:38,680
Speaker 2: variations on that theme. And I think it's appropriate that

908
00:54:38,680 --> 00:54:43,239
Speaker 2: the you know, the stock market. Stock investors, uh in

909
00:54:43,360 --> 00:54:45,960
Speaker 2: are kind of getting over their skis, you know, they

910
00:54:46,120 --> 00:54:49,760
Speaker 2: there's there's this is real. These companies are jogger nots.

911
00:54:49,800 --> 00:54:53,480
Speaker 2: They're you know, they're they're they're making massive investments and

912
00:54:53,520 --> 00:54:58,600
Speaker 2: they're generating a lot of revenue. Uh. But uh that

913
00:54:58,760 --> 00:55:01,959
Speaker 2: is also generating a lot of euphoria around the prospects

914
00:55:02,480 --> 00:55:05,719
Speaker 2: that these companies uh, you know are are generating, and

915
00:55:05,760 --> 00:55:07,440
Speaker 2: it's driving up their stock price. So you can have

916
00:55:07,440 --> 00:55:09,520
Speaker 2: a situation and I think we do very similar to

917
00:55:09,560 --> 00:55:11,280
Speaker 2: what happened back in Y two K and the Internet

918
00:55:11,280 --> 00:55:16,600
Speaker 2: bubble and in previous huge technology periods of technological advance,

919
00:55:17,080 --> 00:55:19,840
Speaker 2: where investors kind of get ahead of the story. You know,

920
00:55:19,880 --> 00:55:22,839
Speaker 2: they they discount all the good news and then some

921
00:55:23,080 --> 00:55:27,360
Speaker 2: and then some and then once that happens, uh, you

922
00:55:27,400 --> 00:55:31,440
Speaker 2: get speculation. That's when investors in stocks and other assets

923
00:55:31,840 --> 00:55:34,960
Speaker 2: buy that stock or that asset simply because they think

924
00:55:34,960 --> 00:55:36,680
Speaker 2: they can sell it at a higher price down the road.

925
00:55:36,719 --> 00:55:37,000
Speaker 1: That's it.

926
00:55:37,040 --> 00:55:39,960
Speaker 2: They're not they're not doing they're not thinking about, you know,

927
00:55:40,120 --> 00:55:42,960
Speaker 2: what's where the value comes from. You know, will this

928
00:55:43,080 --> 00:55:46,160
Speaker 2: be more valuable in the future, or simply the euphoria

929
00:55:46,320 --> 00:55:48,799
Speaker 2: the speculation, and you know, I don't know that we're

930
00:55:48,880 --> 00:55:50,719
Speaker 2: quite there yet, Chuck. That what I That's what I

931
00:55:50,760 --> 00:55:52,400
Speaker 2: would call a bubble when you get that kind of

932
00:55:52,400 --> 00:55:55,640
Speaker 2: speculative Furvor. But it feels like that's the direction of

933
00:55:55,680 --> 00:55:59,520
Speaker 2: travel here, right. And in fact, you know, when I

934
00:55:59,200 --> 00:56:03,319
Speaker 2: look most economists and people in the market, so I'm

935
00:56:03,320 --> 00:56:06,520
Speaker 2: looking at the stock market four or five six times

936
00:56:06,520 --> 00:56:08,200
Speaker 2: a day, you know, I go see what's going on,

937
00:56:09,080 --> 00:56:11,239
Speaker 2: and usually when I see green on the screen, that's

938
00:56:11,280 --> 00:56:14,439
Speaker 2: means stock prices are up. I feel good. Now I'm

939
00:56:14,440 --> 00:56:17,640
Speaker 2: feeling when I see green, I'm getting more nervous about it.

940
00:56:30,840 --> 00:56:33,840
Speaker 1: I'm not quite at retirement thinking about retirement, but you know,

941
00:56:34,000 --> 00:56:37,200
Speaker 1: so I'm still kind of and at the same time, yeah,

942
00:56:37,200 --> 00:56:40,680
Speaker 1: you're like, geez, I know, I know there's going to

943
00:56:40,719 --> 00:56:43,480
Speaker 1: be a correction. How massive is it? Right? You just

944
00:56:43,520 --> 00:56:46,839
Speaker 1: talked about ten trillion dollars. That means we could lose

945
00:56:47,000 --> 00:56:51,040
Speaker 1: five trillion dollars of wealth and still be up five

946
00:56:51,120 --> 00:56:54,239
Speaker 1: trillion dollars. But if we lose five trillion dollars in

947
00:56:54,280 --> 00:56:56,440
Speaker 1: wealth in the next six months, people are gonna panic.

948
00:56:56,760 --> 00:56:59,080
Speaker 2: Yeah, exactly, you got it just right, So you know

949
00:56:59,560 --> 00:57:01,879
Speaker 2: this might be a little nerdy, but you know, to

950
00:57:01,920 --> 00:57:04,200
Speaker 2: measure this to your question, are we in a bubble?

951
00:57:05,800 --> 00:57:07,600
Speaker 2: The tried and true way of kind of looking at

952
00:57:07,600 --> 00:57:10,239
Speaker 2: that is the so called price earnings multiple. Take take

953
00:57:10,640 --> 00:57:14,200
Speaker 2: take the stock prices, look at it relative to the

954
00:57:14,200 --> 00:57:16,040
Speaker 2: earnings of the companies that you know.

955
00:57:17,320 --> 00:57:19,680
Speaker 1: I love doing that. Pallidteer is like one hundred and

956
00:57:19,760 --> 00:57:23,200
Speaker 1: fifty times earnings, but like Google is still only nineteen

957
00:57:23,240 --> 00:57:23,880
Speaker 1: times earnings.

958
00:57:24,440 --> 00:57:26,440
Speaker 2: You know, you're a pe. Wow, that's impressive.

959
00:57:27,840 --> 00:57:30,840
Speaker 1: You know, I'm not an economist, but too yeah.

960
00:57:30,920 --> 00:57:33,280
Speaker 2: Yeah, Well, anyway, so if I look at I have

961
00:57:33,800 --> 00:57:36,080
Speaker 2: what I call the economy wide price earnings multiple. That's

962
00:57:36,120 --> 00:57:38,600
Speaker 2: the Wilsher five thousand. It's the value of all stocks,

963
00:57:38,640 --> 00:57:43,840
Speaker 2: all stocks, divided by economy wide after tax corporate earnings.

964
00:57:43,840 --> 00:57:47,320
Speaker 2: So that's the Ice motile on average since nineteen sixteen.

965
00:57:47,320 --> 00:57:49,960
Speaker 2: That's as far back as I can calculate it. And

966
00:57:50,040 --> 00:57:53,760
Speaker 2: I'm making this up roughly, so it's I'm rounding it's ten.

967
00:57:53,960 --> 00:57:57,320
Speaker 2: That's the multiple's ten ten times stock prices are ten

968
00:57:57,440 --> 00:58:03,959
Speaker 2: times earnings. Right now today it's almost twenty twenty. There's

969
00:58:04,320 --> 00:58:07,240
Speaker 2: one other time in that historical period when it's been

970
00:58:07,320 --> 00:58:10,880
Speaker 2: higher Y two k it was twenty four so and

971
00:58:10,960 --> 00:58:13,600
Speaker 2: of course we're still going higher here. So I don't

972
00:58:13,640 --> 00:58:17,800
Speaker 2: know this so called mean reversion. You know, it feels

973
00:58:17,800 --> 00:58:21,960
Speaker 2: like to me, we're getting we're overvalued, we're bordering on

974
00:58:22,320 --> 00:58:26,080
Speaker 2: frothy and speculative. If stock prices continue to rise, then,

975
00:58:26,520 --> 00:58:28,520
Speaker 2: you know, as ring some alarm bells, I do think

976
00:58:28,520 --> 00:58:29,959
Speaker 2: we're going to see a correction at some point.

977
00:58:29,960 --> 00:58:33,480
Speaker 1: Then. I think what's odd about this is that a

978
00:58:34,120 --> 00:58:37,800
Speaker 1: lot of folks assume tariffs would slow down the growth

979
00:58:37,960 --> 00:58:42,080
Speaker 1: of our economy, right, would certainly hurt traditional companies because

980
00:58:42,120 --> 00:58:45,760
Speaker 1: of rising costs, you know, and all of those things.

981
00:58:45,840 --> 00:58:47,920
Speaker 1: And so here we are in this weird environment where

982
00:58:48,720 --> 00:58:53,960
Speaker 1: tariffs are having some impact, certainly on the consumer and

983
00:58:54,040 --> 00:58:58,520
Speaker 1: certainly on some businesses. But because this AI part is

984
00:58:58,560 --> 00:59:02,760
Speaker 1: an investment type of thing, it is it tied to

985
00:59:02,840 --> 00:59:05,120
Speaker 1: the tariff and in some ways Trump is has sort

986
00:59:05,160 --> 00:59:11,320
Speaker 1: of compartment, you know, has protected that space from his

987
00:59:11,600 --> 00:59:15,800
Speaker 1: protectionist policies. So how would you view that the impact

988
00:59:15,800 --> 00:59:20,240
Speaker 1: of the tariffs? It it? You know, every time I've

989
00:59:20,240 --> 00:59:23,040
Speaker 1: noticed this with a lot, every time we look at it,

990
00:59:23,040 --> 00:59:25,600
Speaker 1: it's like, yeah, it's coming, but it's not here yet. Yeah,

991
00:59:25,640 --> 00:59:28,600
Speaker 1: it's coming, but it's not here yet. Where are we now?

992
00:59:29,240 --> 00:59:31,000
Speaker 2: The thing is, there's a lot of cross cards here.

993
00:59:31,080 --> 00:59:31,200
Speaker 1: Right.

994
00:59:31,200 --> 00:59:33,760
Speaker 2: We just talked about the tailwind, and that's a I

995
00:59:34,040 --> 00:59:37,000
Speaker 2: and that's a powerful tailwind. You know, all the data centers,

996
00:59:37,040 --> 00:59:42,640
Speaker 2: all the investment in the electric electrical power, electric power,

997
00:59:43,080 --> 00:59:46,640
Speaker 2: all the wealth that's being generated, that's driving consumer spending

998
00:59:46,680 --> 00:59:48,840
Speaker 2: of those folks that own the stocks, the you know,

999
00:59:48,880 --> 00:59:53,240
Speaker 2: the high end network, the individuals. About half the growth

1000
00:59:53,280 --> 00:59:57,760
Speaker 2: in the economy is just AI. Right, So give you

1001
00:59:57,840 --> 01:00:01,120
Speaker 2: to give you a number GDP growth that's the value

1002
01:00:01,120 --> 01:00:02,960
Speaker 2: of all the things that we produce is two percent

1003
01:00:03,080 --> 01:00:06,800
Speaker 2: year over year two percent. If not for AI, it

1004
01:00:06,840 --> 01:00:10,920
Speaker 2: would be growing one percent. And that that's that's terraces

1005
01:00:10,920 --> 01:00:13,960
Speaker 2: and you're growing one percent. That's not a recession, but

1006
01:00:14,000 --> 01:00:16,600
Speaker 2: if that's really uncomfortable up.

1007
01:00:16,560 --> 01:00:18,480
Speaker 1: With your inflation at that point.

1008
01:00:18,720 --> 01:00:22,960
Speaker 2: Yeah, So the terrorists are doing damage to the economy.

1009
01:00:23,000 --> 01:00:26,360
Speaker 2: It's just that, you know, the the fallout is being

1010
01:00:26,400 --> 01:00:29,800
Speaker 2: masked to a significant degory by this powerful tail end

1011
01:00:29,880 --> 01:00:32,920
Speaker 2: of AI that's really come into its own over the

1012
01:00:33,000 --> 01:00:34,600
Speaker 2: last six, nine, twelve months.

1013
01:00:35,120 --> 01:00:38,640
Speaker 1: So this is it's so look at some point AI

1014
01:00:38,720 --> 01:00:45,280
Speaker 1: investment plateaus, right, and the terriff stick, so that that's

1015
01:00:45,320 --> 01:00:46,440
Speaker 1: where this is headed.

1016
01:00:46,240 --> 01:00:50,280
Speaker 2: Right, Well, I mean, if the terraces rise and level

1017
01:00:50,320 --> 01:00:52,760
Speaker 2: off and stop rising at some point, we're you know,

1018
01:00:52,920 --> 01:00:55,400
Speaker 2: the economy just to that. So you know, both those

1019
01:00:55,440 --> 01:00:57,720
Speaker 2: things could iron you know, kind of offset each other,

1020
01:00:57,800 --> 01:01:01,120
Speaker 2: so we could increasingly. This is the consensus view in

1021
01:01:01,160 --> 01:01:03,640
Speaker 2: my view that we you know, it's going to feel

1022
01:01:03,680 --> 01:01:05,840
Speaker 2: uncomfortable at times, but we're going to be able to

1023
01:01:05,880 --> 01:01:10,280
Speaker 2: avoid recession because of that AI tailwind that we're enjoying.

1024
01:01:10,480 --> 01:01:15,000
Speaker 2: But having said that, you know, the economy is soft,

1025
01:01:15,040 --> 01:01:17,400
Speaker 2: the job market is punk. You know, we're not seeing

1026
01:01:17,400 --> 01:01:21,720
Speaker 2: any job growth whatsoever. We are vulnerable to you know, again,

1027
01:01:21,840 --> 01:01:25,320
Speaker 2: whatever else might not stick the script, and there's certainly

1028
01:01:25,360 --> 01:01:27,800
Speaker 2: a lot of things that might not stick stick to script.

1029
01:01:27,800 --> 01:01:32,760
Speaker 1: Here a few I want to hit two other topics

1030
01:01:32,800 --> 01:01:37,600
Speaker 1: here to sort of understand gold. Yeah, whenever gold, I've

1031
01:01:37,640 --> 01:01:40,240
Speaker 1: sort of in my head, you know, when I see

1032
01:01:40,240 --> 01:01:43,000
Speaker 1: gold go higher, that's bad news for the American economy.

1033
01:01:43,400 --> 01:01:46,240
Speaker 1: It always gets me nervous. Yet this is a case

1034
01:01:46,280 --> 01:01:51,120
Speaker 1: where everything's going up gold too. Yeah, that's unusual.

1035
01:01:51,200 --> 01:01:55,520
Speaker 2: No, it is, I mean, and this goes back to

1036
01:01:55,560 --> 01:01:57,840
Speaker 2: the question of are we in a bubble and speculation

1037
01:01:58,200 --> 01:02:01,480
Speaker 2: in the fact that we're seeing prices rise for all

1038
01:02:01,560 --> 01:02:04,920
Speaker 2: kinds of assets at the same time adds to the

1039
01:02:04,960 --> 01:02:07,440
Speaker 2: concern that this is you know broader that you know,

1040
01:02:07,840 --> 01:02:10,360
Speaker 2: a bubble is developing, and gold prices are at record

1041
01:02:10,400 --> 01:02:13,320
Speaker 2: highs where we're four thousand dollars an ounce, uh for

1042
01:02:13,400 --> 01:02:17,800
Speaker 2: the first time, silver prices, obviously, crypto prices. Actually, interestingly enough,

1043
01:02:17,840 --> 01:02:20,200
Speaker 2: the only asset for which that's not this is not

1044
01:02:20,280 --> 01:02:22,200
Speaker 2: the case is real estate, right if you've looked.

1045
01:02:22,080 --> 01:02:23,960
Speaker 1: Well, that was going to be my next topic, which

1046
01:02:24,920 --> 01:02:28,280
Speaker 1: is sort of it is that's a strange aspect that

1047
01:02:28,320 --> 01:02:30,680
Speaker 1: people that that real estate is not seen as a

1048
01:02:30,720 --> 01:02:33,000
Speaker 1: safe harbor, but gold still is.

1049
01:02:33,280 --> 01:02:35,600
Speaker 2: Yeah, And I think the thing about gold is it's

1050
01:02:35,640 --> 01:02:38,640
Speaker 2: got in these one of these asset classes that were stocks,

1051
01:02:39,200 --> 01:02:42,440
Speaker 2: commodities like gold and crypto have its own kind of

1052
01:02:42,480 --> 01:02:46,120
Speaker 2: idiosyncratic aspects to it as well. In the case of gold,

1053
01:02:46,800 --> 01:02:49,680
Speaker 2: you know, it really has got to boost When Russia

1054
01:02:49,800 --> 01:02:54,120
Speaker 2: invaded Ukraine, in the US froze Russian reserves. Those are

1055
01:02:54,200 --> 01:02:58,200
Speaker 2: dollar reserves or dollar assets sitting in bank accounts around

1056
01:02:58,240 --> 01:03:01,520
Speaker 2: the world, and the US froze those assets, those dollar assets,

1057
01:03:02,040 --> 01:03:06,520
Speaker 2: and so countries around the world with those dollars assets

1058
01:03:06,560 --> 01:03:08,720
Speaker 2: begin to wonder, well, maybe they'll do that to me

1059
01:03:08,920 --> 01:03:11,600
Speaker 2: if they don't like something I'm doing. Therefore, I'm going

1060
01:03:11,680 --> 01:03:16,360
Speaker 2: to diversify away from dollars into let's say gold. So

1061
01:03:16,920 --> 01:03:20,320
Speaker 2: central banks around the world are now, you know, big

1062
01:03:20,400 --> 01:03:23,400
Speaker 2: investors in gold. The other thing is there's some you know,

1063
01:03:24,400 --> 01:03:27,560
Speaker 2: concerns about the safe haven status of the US right

1064
01:03:27,680 --> 01:03:29,840
Speaker 2: in the context of the trade in terior wars and

1065
01:03:30,400 --> 01:03:32,480
Speaker 2: kind of the repositioning in the US and the global

1066
01:03:32,560 --> 01:03:35,400
Speaker 2: economy and the financial system by the Trump administration. I

1067
01:03:35,480 --> 01:03:38,760
Speaker 2: think global investors are asking themselves, is the US really

1068
01:03:38,880 --> 01:03:40,640
Speaker 2: the place you want to go to put your money

1069
01:03:40,680 --> 01:03:43,720
Speaker 2: when times are tough? And if that, if you question that,

1070
01:03:43,960 --> 01:03:47,400
Speaker 2: then you know, you buy something like gold, you know,

1071
01:03:47,480 --> 01:03:51,960
Speaker 2: as a hedge. And then the final potential reason for

1072
01:03:52,120 --> 01:03:54,920
Speaker 2: what's going on in the gold market is inflation. So

1073
01:03:55,440 --> 01:03:58,440
Speaker 2: you know, there's inflation has been a problem since the pandemic,

1074
01:03:58,520 --> 01:04:01,880
Speaker 2: the Russian War, and then that head on energy and

1075
01:04:01,880 --> 01:04:04,960
Speaker 2: command prices push up inflation even more. And there's a

1076
01:04:05,000 --> 01:04:08,720
Speaker 2: lot of discussion. Concern about FED independence is that theors

1077
01:04:08,760 --> 01:04:11,440
Speaker 2: are going to remain an independent going forward, and if not,

1078
01:04:11,760 --> 01:04:13,520
Speaker 2: does that mean the Fed's going to keep raids too

1079
01:04:13,600 --> 01:04:16,200
Speaker 2: low for too long and juice up inflation. And if so,

1080
01:04:16,280 --> 01:04:20,600
Speaker 2: if you're worried about inflation here, going down the road here,

1081
01:04:21,040 --> 01:04:23,560
Speaker 2: you're going to buy something like gold. So you know,

1082
01:04:23,640 --> 01:04:25,520
Speaker 2: there's a lot of things coming together there, I think

1083
01:04:25,680 --> 01:04:28,720
Speaker 2: pushing up demand for that commodity.

1084
01:04:29,080 --> 01:04:30,840
Speaker 1: What is the risk to our economy if we're not

1085
01:04:30,920 --> 01:04:33,200
Speaker 1: a safe haven, Well, it.

1086
01:04:33,280 --> 01:04:35,680
Speaker 2: Means it means higher interest rates all else being equal.

1087
01:04:35,760 --> 01:04:39,919
Speaker 2: I mean, you know, especially in most times, that that's

1088
01:04:40,000 --> 01:04:42,600
Speaker 2: not that big. It's a deal. I mean, we benefit

1089
01:04:42,680 --> 01:04:44,960
Speaker 2: from that, but it's really a big deal when things

1090
01:04:45,080 --> 01:04:48,080
Speaker 2: aren't going well. When the world has a crisis, when

1091
01:04:48,120 --> 01:04:52,040
Speaker 2: we have a pandemic or a global financial crisis, or

1092
01:04:52,480 --> 01:04:57,560
Speaker 2: something goes off the rail somewhere, money comes from all

1093
01:04:57,600 --> 01:05:00,480
Speaker 2: over the world comes flowing into the United States. It

1094
01:05:00,640 --> 01:05:04,160
Speaker 2: really cushions the blow of that shock on our economy

1095
01:05:04,240 --> 01:05:06,080
Speaker 2: and it helps us navigate through and we kind of

1096
01:05:06,200 --> 01:05:08,840
Speaker 2: lead the way for the rest of the world. That's

1097
01:05:08,920 --> 01:05:12,800
Speaker 2: going to be harder to do if, in fact, investors

1098
01:05:12,840 --> 01:05:14,800
Speaker 2: don't view us as that safe harbor or is that

1099
01:05:14,880 --> 01:05:17,520
Speaker 2: safe haven, and the money doesn't come flowing in in

1100
01:05:17,640 --> 01:05:21,320
Speaker 2: the next crisis, and we have to pay more for capital,

1101
01:05:21,400 --> 01:05:24,400
Speaker 2: higher interest rates, and that's certainly a corrosive on our

1102
01:05:24,440 --> 01:05:26,680
Speaker 2: ability to invest and to do all the things that

1103
01:05:26,760 --> 01:05:27,240
Speaker 2: we want to do.

1104
01:05:27,560 --> 01:05:29,640
Speaker 1: Yeah, I just sort of like to how to connected

1105
01:05:29,680 --> 01:05:31,520
Speaker 1: to the average person, Why should I care for not

1106
01:05:31,640 --> 01:05:34,120
Speaker 1: a safe haven? What you're saying is, well, if you

1107
01:05:34,240 --> 01:05:36,480
Speaker 1: like lower interest rates on your credit card debt, if

1108
01:05:36,520 --> 01:05:38,680
Speaker 1: you like a lower interest rate on your mortgage, this

1109
01:05:38,880 --> 01:05:42,000
Speaker 1: is why you want the rest of the world feeling

1110
01:05:42,200 --> 01:05:43,520
Speaker 1: America as a safe harbor.

1111
01:05:43,800 --> 01:05:45,840
Speaker 2: Or your small business and you need to borrow money

1112
01:05:45,880 --> 01:05:48,400
Speaker 2: to expand your business or hire, or even if you're

1113
01:05:48,400 --> 01:05:50,120
Speaker 2: a large multinational and you need to go out and

1114
01:05:50,160 --> 01:05:52,520
Speaker 2: borrow money to invest in let's say those data centers.

1115
01:05:52,560 --> 01:05:53,720
Speaker 2: I mean, it's just going to be a lot more

1116
01:05:54,000 --> 01:05:58,240
Speaker 2: costly to do it. And most times this generally going

1117
01:05:58,280 --> 01:06:00,560
Speaker 2: to be more of a corrosive on the econom It's

1118
01:06:00,560 --> 01:06:02,800
Speaker 2: not a cliff of that. It's not like all of

1119
01:06:02,840 --> 01:06:04,919
Speaker 2: a sudden you go off a cliff because the safe

1120
01:06:04,960 --> 01:06:08,640
Speaker 2: haven status is under question. It's more of a weight

1121
01:06:08,760 --> 01:06:12,120
Speaker 2: on the economy that over time diminishes the economy's ability

1122
01:06:12,600 --> 01:06:15,600
Speaker 2: to do what we've done historically and that's kind of

1123
01:06:15,680 --> 01:06:16,760
Speaker 2: lead the global economy.

1124
01:06:17,040 --> 01:06:19,000
Speaker 1: I don't know if this is sort of outside your field,

1125
01:06:19,080 --> 01:06:23,160
Speaker 1: but how do you assess energy costs because it does

1126
01:06:23,280 --> 01:06:27,120
Speaker 1: seem as if that's becoming a right. We're seeing rising

1127
01:06:27,320 --> 01:06:30,840
Speaker 1: electricity bills all over the country. Is this you know

1128
01:06:31,200 --> 01:06:35,160
Speaker 1: how much of this is we haven't diversified our grid enough.

1129
01:06:35,280 --> 01:06:38,480
Speaker 1: How much of this is there's more of these AI companies,

1130
01:06:38,560 --> 01:06:42,000
Speaker 1: more demand on the grid itself, and we're having to

1131
01:06:42,120 --> 01:06:45,440
Speaker 1: do it. And is that easy to assess? And how

1132
01:06:45,440 --> 01:06:48,120
Speaker 1: do you factor that? Because you know, when when when

1133
01:06:48,800 --> 01:06:52,600
Speaker 1: energy costs rise, that impacts everybody. Right, that's just a

1134
01:06:52,800 --> 01:06:57,080
Speaker 1: giant sort of slow down on the economy, and that

1135
01:06:57,560 --> 01:07:01,880
Speaker 1: feels like something that that we're not really it's happening,

1136
01:07:01,960 --> 01:07:05,840
Speaker 1: and we haven't really focused on on how that could

1137
01:07:05,880 --> 01:07:08,479
Speaker 1: be a real sort of governor on our economic growth.

1138
01:07:08,920 --> 01:07:13,600
Speaker 2: Yeah, Well, if you're talking about electricity, the cost of electricity,

1139
01:07:13,680 --> 01:07:16,960
Speaker 2: and that's going up just like everything else, demand and supply.

1140
01:07:17,080 --> 01:07:19,240
Speaker 2: On the demand side, you know, all these data centers

1141
01:07:19,360 --> 01:07:22,240
Speaker 2: scarf up a lot of electricity to be able to

1142
01:07:23,040 --> 01:07:27,120
Speaker 2: run the servers and do the AI calculations, So that's

1143
01:07:27,600 --> 01:07:30,040
Speaker 2: juicing up demand and on the supply side of the

1144
01:07:30,040 --> 01:07:34,160
Speaker 2: electric power market. It's slow to respond, particularly in the

1145
01:07:34,240 --> 01:07:37,400
Speaker 2: context of you know, policy changes under President Trump, where

1146
01:07:37,400 --> 01:07:39,760
Speaker 2: he's moved away from clean energy, you know, moved away

1147
01:07:39,760 --> 01:07:40,200
Speaker 2: from soular.

1148
01:07:40,360 --> 01:07:43,280
Speaker 1: Just the shift itself slows us down. It doesn't like

1149
01:07:44,200 --> 01:07:47,440
Speaker 1: I'm not we're not weighing in on whether Biden's right

1150
01:07:47,520 --> 01:07:50,600
Speaker 1: or Trump's right. The transition itself slows us down.

1151
01:07:50,880 --> 01:07:53,600
Speaker 2: Absolutely. Now there's a lot of discussion about going to

1152
01:07:53,720 --> 01:07:56,520
Speaker 2: nuclear and that's the direction we're going to head here,

1153
01:07:56,680 --> 01:07:58,720
Speaker 2: but that takes time. It's a lot of time, a

1154
01:07:58,760 --> 01:08:01,400
Speaker 2: lot of time. There's least smaller nuclear facilities that you

1155
01:08:01,440 --> 01:08:03,880
Speaker 2: can get online more quickly, but they're small. You need

1156
01:08:04,320 --> 01:08:06,680
Speaker 2: big nuclear plants to be able to generate the power

1157
01:08:06,720 --> 01:08:08,840
Speaker 2: that we need, and that's just going to take time.

1158
01:08:08,920 --> 01:08:10,720
Speaker 2: So I would I would buckle in here on the

1159
01:08:11,200 --> 01:08:13,200
Speaker 2: that we're going to be paid more for electricity. The

1160
01:08:13,600 --> 01:08:16,560
Speaker 2: fortunate thing though, is oil prices, which obviously you know,

1161
01:08:16,640 --> 01:08:22,320
Speaker 2: we still draw many people still drive of gas powered cars.

1162
01:08:22,720 --> 01:08:26,040
Speaker 2: That's down, right, that's sixty sixty five bucks of barrowl that.

1163
01:08:26,160 --> 01:08:29,080
Speaker 1: But why if that's down, why isn't that having some

1164
01:08:29,600 --> 01:08:32,080
Speaker 1: impact on our electric bills? Because usually when the price

1165
01:08:32,120 --> 01:08:33,960
Speaker 1: of oil goes up, the price of every all energy

1166
01:08:34,000 --> 01:08:34,360
Speaker 1: goes up.

1167
01:08:34,479 --> 01:08:39,160
Speaker 2: Well, I mean no electric electric power is very little

1168
01:08:39,160 --> 01:08:41,479
Speaker 2: if it's oil powered. You know, there's natural gas, but

1169
01:08:41,680 --> 01:08:44,519
Speaker 2: natural gas prices are relatively low. It's still relatively low

1170
01:08:44,560 --> 01:08:47,160
Speaker 2: because we we produce a lot of natural gas here

1171
01:08:47,240 --> 01:08:49,160
Speaker 2: and it's hard to export to the rest of the world,

1172
01:08:49,280 --> 01:08:52,599
Speaker 2: although we're trying. But most of it is natural gas

1173
01:08:52,920 --> 01:08:57,479
Speaker 2: or you know, renewable solar wind and to a lesser degree,

1174
01:08:58,280 --> 01:09:01,280
Speaker 2: nuclear and coals becoming less of an issue. But oil

1175
01:09:01,439 --> 01:09:04,720
Speaker 2: is a very very small piece of the gotcha of

1176
01:09:04,840 --> 01:09:07,160
Speaker 2: the what's used to power electric power plants?

1177
01:09:07,360 --> 01:09:10,680
Speaker 1: Gotcha? So let's talk about real estate. There was an

1178
01:09:10,720 --> 01:09:14,559
Speaker 1: interesting little one of the million newsletters I read every morning.

1179
01:09:14,640 --> 01:09:18,320
Speaker 1: So I'm not going to say you're talking about right,

1180
01:09:18,400 --> 01:09:22,360
Speaker 1: there's so many of them, but one notice that it's like,

1181
01:09:22,800 --> 01:09:25,639
Speaker 1: so the the talking point of why real estate investment

1182
01:09:25,680 --> 01:09:30,160
Speaker 1: has been slow as well, inventory is low, but it's

1183
01:09:30,240 --> 01:09:33,360
Speaker 1: still one would assume if you're if if there are

1184
01:09:33,439 --> 01:09:36,599
Speaker 1: investors looking for safe havens, why are they only going

1185
01:09:36,640 --> 01:09:39,559
Speaker 1: to crypto and gold? Why aren't they going to real estate,

1186
01:09:39,600 --> 01:09:43,040
Speaker 1: which has traditionally been a pretty good inflation buffer.

1187
01:09:43,840 --> 01:09:47,800
Speaker 2: Well, there's the there's the residential side, which you mentioned

1188
01:09:47,840 --> 01:09:51,120
Speaker 2: the single family housing, and then there's the commercial real estate.

1189
01:09:51,200 --> 01:09:55,200
Speaker 2: And that's where generally investors have gone as cre commercial

1190
01:09:55,200 --> 01:09:58,799
Speaker 2: real estate, office properties, you know, retail malls.

1191
01:09:59,600 --> 01:10:01,720
Speaker 1: Uh some of the times, amazing what the price of

1192
01:10:01,760 --> 01:10:04,760
Speaker 1: some of these beautiful office buildings are going for it

1193
01:10:04,760 --> 01:10:06,760
Speaker 1: at the oh. I mean, if you ever want to

1194
01:10:06,840 --> 01:10:10,439
Speaker 1: own an office building, right, do they have a deal

1195
01:10:10,520 --> 01:10:10,680
Speaker 1: for you?

1196
01:10:11,280 --> 01:10:13,680
Speaker 2: Yeah? And I think a couple of things happened to

1197
01:10:13,880 --> 01:10:18,000
Speaker 2: commercial real estate. One is interest rates. When interest rates,

1198
01:10:18,960 --> 01:10:21,760
Speaker 2: real estate's very interest rate sensitive, much more than any

1199
01:10:22,120 --> 01:10:25,680
Speaker 2: other asset. And so when interest rates rose, when the

1200
01:10:25,720 --> 01:10:28,559
Speaker 2: FED jacked up interest rates to cool things off back

1201
01:10:28,840 --> 01:10:30,479
Speaker 2: you know a few years ago in twenty two and

1202
01:10:30,560 --> 01:10:34,839
Speaker 2: twenty three, going into twenty four, that caused the prices

1203
01:10:35,280 --> 01:10:38,080
Speaker 2: to come down for almost all CI. And then each

1204
01:10:38,840 --> 01:10:41,120
Speaker 2: property type had its own kind of story. And you

1205
01:10:41,200 --> 01:10:44,200
Speaker 2: mentioned office Obviously there it's remote work, and the demand

1206
01:10:44,280 --> 01:10:46,880
Speaker 2: for office space, you know, got crushed. But you know

1207
01:10:47,120 --> 01:10:50,720
Speaker 2: other property types also got have their own stories, Like

1208
01:10:50,800 --> 01:10:54,080
Speaker 2: in the multi family sector, that's not about demand, that's

1209
01:10:54,120 --> 01:10:58,040
Speaker 2: more about supply. That's where builders were got ahead of

1210
01:10:58,080 --> 01:11:00,000
Speaker 2: themselves and put up a lot of these huge lungs

1211
01:11:00,040 --> 01:11:05,599
Speaker 2: ux Trey apartment towers. While there's a lot of demand,

1212
01:11:05,640 --> 01:11:07,960
Speaker 2: there was just too much supply, and that's that's caused

1213
01:11:09,000 --> 01:11:12,639
Speaker 2: rents and prices to come in. So commercial real estate

1214
01:11:12,680 --> 01:11:15,479
Speaker 2: has kind of operated on its own independent dynamic, and

1215
01:11:15,560 --> 01:11:17,439
Speaker 2: it's been much more affected by the run up in

1216
01:11:17,479 --> 01:11:21,080
Speaker 2: interest rates than the other asset classes. On housing, you

1217
01:11:21,160 --> 01:11:25,280
Speaker 2: know that that's generally there's some investment in single family rental,

1218
01:11:25,560 --> 01:11:29,320
Speaker 2: but mostly that's you and I, you know, Merrick Households

1219
01:11:29,400 --> 01:11:34,120
Speaker 2: buying those homes and there the market has struggled in

1220
01:11:34,240 --> 01:11:36,960
Speaker 2: terms of sales because of the so called interest rate

1221
01:11:37,080 --> 01:11:39,920
Speaker 2: lock you know, rays for very low back in the pandemic,

1222
01:11:39,960 --> 01:11:42,439
Speaker 2: people got mortgages at you know, three, three, two and

1223
01:11:42,479 --> 01:11:42,880
Speaker 2: a half three.

1224
01:11:43,000 --> 01:11:44,479
Speaker 1: I'd love to sell my house, but I don't know

1225
01:11:44,520 --> 01:11:46,160
Speaker 1: what I get into. Yeah, exactly, I mean, you know,

1226
01:11:46,280 --> 01:11:47,840
Speaker 1: I mean that's a real thing. It's like you will

1227
01:11:47,880 --> 01:11:50,559
Speaker 1: make Yeah, It's like, boy, i don't want to pay

1228
01:11:50,680 --> 01:11:52,720
Speaker 1: that high interest rate in my mortgage. I've got this

1229
01:11:52,800 --> 01:11:54,000
Speaker 1: great low interest rate, right.

1230
01:11:54,160 --> 01:11:56,040
Speaker 2: Yeah. So if you have a three percent mortgage and

1231
01:11:56,120 --> 01:11:59,000
Speaker 2: existing mortgage rates now over six percent, are you really

1232
01:11:59,040 --> 01:12:02,240
Speaker 2: going to make that trade and the answers most people are,

1233
01:12:02,479 --> 01:12:03,519
Speaker 2: you know, at least not yet.

1234
01:12:16,400 --> 01:12:19,559
Speaker 1: So what could let's stick with housing? What what could

1235
01:12:21,800 --> 01:12:24,680
Speaker 1: what could government do besides lowering interest rates? So let's

1236
01:12:24,720 --> 01:12:27,639
Speaker 1: set interest rates aside? What else could government be doing

1237
01:12:28,280 --> 01:12:31,880
Speaker 1: to just improve the affordability of the housing market. Yeah,

1238
01:12:32,040 --> 01:12:32,439
Speaker 1: it's done a.

1239
01:12:32,439 --> 01:12:34,640
Speaker 2: Little bit of work here, I've got the paper out

1240
01:12:34,720 --> 01:12:39,439
Speaker 2: was a few colleagues. You could google Zandy affordable housing crisis.

1241
01:12:40,280 --> 01:12:43,679
Speaker 1: And this is a this is for what it's worth.

1242
01:12:43,880 --> 01:12:45,559
Speaker 1: When you talk to members of Congress and they say,

1243
01:12:45,600 --> 01:12:48,320
Speaker 1: what issue do we and the press not bring up enough?

1244
01:12:48,360 --> 01:12:50,680
Speaker 1: But your constituents talk about all the time, it's this

1245
01:12:50,840 --> 01:12:52,519
Speaker 1: issue one right, yeah.

1246
01:12:52,600 --> 01:12:54,680
Speaker 2: Yeah. In this paper, what we did we tried to

1247
01:12:54,880 --> 01:12:58,639
Speaker 2: estimate the balance between supply and demand for housing, both

1248
01:12:58,720 --> 01:13:01,280
Speaker 2: on the rental side and on the home ownership side,

1249
01:13:01,439 --> 01:13:04,559
Speaker 2: at a census tract level, so at a very detailed

1250
01:13:04,600 --> 01:13:08,479
Speaker 2: little geography so you can and it's very interesting, you see.

1251
01:13:08,600 --> 01:13:10,679
Speaker 2: And then we cut the data in lots of different ways,

1252
01:13:10,760 --> 01:13:13,400
Speaker 2: one of which is around price points, you know, different

1253
01:13:14,000 --> 01:13:16,880
Speaker 2: just different is it for the for high end consumers,

1254
01:13:17,400 --> 01:13:20,840
Speaker 2: kind of workforce or low income And what we found

1255
01:13:21,000 --> 01:13:23,639
Speaker 2: is no surprise. I just mentioned it. At the high

1256
01:13:23,720 --> 01:13:25,880
Speaker 2: end of the rental market, it's oversupplied. You got too

1257
01:13:25,960 --> 01:13:30,080
Speaker 2: many big luxury condo towers in d C. And Philly, Chicago,

1258
01:13:30,160 --> 01:13:33,000
Speaker 2: San Francisco, that kind of thing builders got ahead of themselves.

1259
01:13:34,439 --> 01:13:37,880
Speaker 2: Really interestingly, Chuck, you know, at the very lower end

1260
01:13:38,280 --> 01:13:43,720
Speaker 2: of the of the market, it's it's not overly undersupplied,

1261
01:13:43,880 --> 01:13:46,760
Speaker 2: it's kind of well balanced. And that's because there's a

1262
01:13:46,840 --> 01:13:50,840
Speaker 2: lot of tax subsidy already provided for low income rental,

1263
01:13:50,960 --> 01:13:54,000
Speaker 2: like light Tech that's low income housing tax credit. The

1264
01:13:54,120 --> 01:13:58,880
Speaker 2: real shortage is actually for what I call workforce housing

1265
01:13:59,000 --> 01:14:02,480
Speaker 2: rental and for homeers. Those are for kind of teachers

1266
01:14:02,680 --> 01:14:07,559
Speaker 2: and firemen and you know, kind of middle class people

1267
01:14:07,600 --> 01:14:10,760
Speaker 2: are making seventy five eighty K a year on a

1268
01:14:10,800 --> 01:14:14,800
Speaker 2: household basis, you know, nationwide, that's where the real shortage is.

1269
01:14:14,840 --> 01:14:19,760
Speaker 2: And so that's where policymakers really have not focused. They've

1270
01:14:19,760 --> 01:14:21,600
Speaker 2: been focused on the low end. They really need to

1271
01:14:21,640 --> 01:14:24,599
Speaker 2: focus on the middle part of the market. And there

1272
01:14:24,680 --> 01:14:27,120
Speaker 2: I would argue, if we had some tax subsidy like

1273
01:14:27,200 --> 01:14:29,759
Speaker 2: a LA tech for workforce rental, that would be very helpful.

1274
01:14:30,320 --> 01:14:34,840
Speaker 1: Is this so how sensitive is that issue by wealth

1275
01:14:34,880 --> 01:14:37,760
Speaker 1: of county. Right, so I take a look at like,

1276
01:14:37,920 --> 01:14:41,120
Speaker 1: you know, you go to around in and around San Jose, Frankly,

1277
01:14:41,240 --> 01:14:44,280
Speaker 1: in and around d C. Right, Montgomery County, Arlington County,

1278
01:14:44,320 --> 01:14:48,120
Speaker 1: where the service where the service industry folks, your teachers,

1279
01:14:48,160 --> 01:14:52,400
Speaker 1: your firefighters, your police officers can't necessarily afford to live

1280
01:14:52,439 --> 01:14:54,960
Speaker 1: in the county that they work in, right, because the

1281
01:14:55,080 --> 01:14:58,920
Speaker 1: cost of single family homes are so high. This is

1282
01:14:59,040 --> 01:15:01,960
Speaker 1: true in and around Valley, This is true in close

1283
01:15:02,040 --> 01:15:04,840
Speaker 1: in parts of LA and New York, et cetera. It

1284
01:15:04,920 --> 01:15:08,480
Speaker 1: seems like that's a unique that's a challenge that's very specific.

1285
01:15:09,200 --> 01:15:12,120
Speaker 1: But is this is this also an issue in and

1286
01:15:12,200 --> 01:15:14,400
Speaker 1: around Louisville, right in and around Wichita.

1287
01:15:15,080 --> 01:15:18,080
Speaker 2: Yeah, it's coast to coast and it's market to market.

1288
01:15:18,400 --> 01:15:22,400
Speaker 2: And even in those you know, very wealthy areas of

1289
01:15:22,479 --> 01:15:25,720
Speaker 2: the country, there are you can see there are you know,

1290
01:15:26,040 --> 01:15:31,160
Speaker 2: real pockets of problem of shortages in certain segments of

1291
01:15:31,200 --> 01:15:33,920
Speaker 2: the market. So it is coast to coast and it's

1292
01:15:34,040 --> 01:15:37,400
Speaker 2: very very local. You have, it's not that's one of

1293
01:15:37,400 --> 01:15:39,920
Speaker 2: the reasons why it's a hard thing for policymakers to address.

1294
01:15:40,320 --> 01:15:43,120
Speaker 2: It's not like I can do something at at federal

1295
01:15:43,160 --> 01:15:45,840
Speaker 2: government level, wave of magic wand and solve the problem.

1296
01:15:46,000 --> 01:15:48,799
Speaker 2: It's really a lot of you know, trying to understand

1297
01:15:48,920 --> 01:15:51,760
Speaker 2: individual markets at a local level and trying to figure

1298
01:15:51,760 --> 01:15:54,040
Speaker 2: out what the best strategy is to address those. And

1299
01:15:54,200 --> 01:15:57,880
Speaker 2: of course underlying all of this is zoning and permitting cours.

1300
01:15:57,960 --> 01:16:00,639
Speaker 2: Feral government has nothing to say about that and won't

1301
01:16:00,680 --> 01:16:04,280
Speaker 2: because the political you know, ramifications trying to address that

1302
01:16:04,479 --> 01:16:07,760
Speaker 2: would be you know, overwhelming. It's something as possible. So

1303
01:16:07,840 --> 01:16:10,920
Speaker 2: it makes it very difficult for government, federal government, for

1304
01:16:11,560 --> 01:16:13,800
Speaker 2: the federal government to really address this head on in

1305
01:16:13,920 --> 01:16:17,080
Speaker 2: a grand ways. It's got to be done, you know,

1306
01:16:17,400 --> 01:16:20,040
Speaker 2: helping local governments try to figure out, you know, what

1307
01:16:20,240 --> 01:16:22,200
Speaker 2: they need and where they need it and give them

1308
01:16:22,200 --> 01:16:23,519
Speaker 2: the resources to help them do it.

1309
01:16:23,800 --> 01:16:26,439
Speaker 1: So in some ways it's incentivizing local governments to change there.

1310
01:16:26,520 --> 01:16:29,120
Speaker 2: Yeah, yeah, again, I'd go back to you know, there's

1311
01:16:29,600 --> 01:16:33,439
Speaker 2: light tech is low income housing tax right, much maligned,

1312
01:16:33,560 --> 01:16:35,840
Speaker 2: no one really likes it, but it's tried and true,

1313
01:16:35,920 --> 01:16:39,680
Speaker 2: it's kind of works. Let's I take that and run

1314
01:16:39,720 --> 01:16:41,800
Speaker 2: with that and to just kind of tweak it and

1315
01:16:41,960 --> 01:16:43,360
Speaker 2: make it work for workforce rental.

1316
01:16:45,000 --> 01:16:47,080
Speaker 1: That gets me as something else that I think is

1317
01:16:47,640 --> 01:16:51,280
Speaker 1: is and maybe this is just a hallmark of the

1318
01:16:51,320 --> 01:16:55,280
Speaker 1: twenty first century, but how much would our economy benefit

1319
01:16:55,360 --> 01:16:59,640
Speaker 1: from domestic migration? You know, we we and is that

1320
01:17:00,080 --> 01:17:05,240
Speaker 1: it seems as if we move less domestically and we did.

1321
01:17:05,360 --> 01:17:07,479
Speaker 1: You know, Hey, if I can't find a job here,

1322
01:17:07,640 --> 01:17:09,760
Speaker 1: I'm going to travel to another state to go get work,

1323
01:17:09,960 --> 01:17:12,040
Speaker 1: or I'm gonna I can't afford a house here, I'm

1324
01:17:12,080 --> 01:17:14,680
Speaker 1: going to move somewhere else. And we've seen, you know,

1325
01:17:14,720 --> 01:17:17,760
Speaker 1: there was a little COVID migration. Obviously Florida experienced that

1326
01:17:18,240 --> 01:17:20,360
Speaker 1: Miami in particular, but that was kind of high end

1327
01:17:21,240 --> 01:17:24,759
Speaker 1: and it really is messed with inflation in Miami uniquely.

1328
01:17:26,120 --> 01:17:30,439
Speaker 1: But you know, I've always thought one of our one

1329
01:17:30,479 --> 01:17:33,519
Speaker 1: of our problems is that we and why we're we

1330
01:17:33,800 --> 01:17:36,679
Speaker 1: were so living in our silos, is that we don't

1331
01:17:36,720 --> 01:17:38,960
Speaker 1: have the domestic migration that we actually did have a

1332
01:17:39,040 --> 01:17:40,599
Speaker 1: lot of in the fifties or did have a lot

1333
01:17:40,680 --> 01:17:44,919
Speaker 1: of in the thirties. Is that measurable?

1334
01:17:45,680 --> 01:17:48,519
Speaker 2: Yeah, yeah, it's an excellent point. You know, we get

1335
01:17:49,400 --> 01:17:52,800
Speaker 2: had Moodies, all the credit files in country every month

1336
01:17:53,120 --> 01:17:56,360
Speaker 2: anonymized and we can see address changes, so I can

1337
01:17:56,400 --> 01:17:58,799
Speaker 2: tell you exactly how many people are moving from Chicago

1338
01:17:58,880 --> 01:18:03,720
Speaker 2: to Miami and act in a given month. And you're

1339
01:18:03,760 --> 01:18:07,559
Speaker 2: absolutely right. You know, over the last few decades we've

1340
01:18:07,600 --> 01:18:09,040
Speaker 2: become a much less mobile.

1341
01:18:09,200 --> 01:18:11,240
Speaker 1: I used the U haul thing. By the way, U

1342
01:18:11,320 --> 01:18:13,640
Speaker 1: haul light height always throws that out, and you know

1343
01:18:13,720 --> 01:18:16,120
Speaker 1: that's what a lay person like me, the U haul

1344
01:18:17,160 --> 01:18:19,120
Speaker 1: rental thing. It is interesting to me, and it does

1345
01:18:19,479 --> 01:18:20,360
Speaker 1: seem Yeah, I.

1346
01:18:20,360 --> 01:18:21,680
Speaker 2: Should go look at that. I can look at that

1347
01:18:21,720 --> 01:18:25,280
Speaker 2: in a while because I've been looking at this this crediphile.

1348
01:18:25,360 --> 01:18:26,679
Speaker 1: Do you have better data please?

1349
01:18:26,760 --> 01:18:29,120
Speaker 2: Kind of it's really good, you know, because I am

1350
01:18:29,200 --> 01:18:31,400
Speaker 2: kind of nerdy. I love looking at that data. And

1351
01:18:32,160 --> 01:18:34,559
Speaker 2: you know, one of the reasons why we're not moving

1352
01:18:34,600 --> 01:18:38,160
Speaker 2: as much is because just raging when you get older.

1353
01:18:38,200 --> 01:18:41,040
Speaker 2: You tend to move less when you're young, switching jobs.

1354
01:18:40,800 --> 01:18:42,599
Speaker 1: And so we're just an aging population.

1355
01:18:42,960 --> 01:18:46,800
Speaker 2: That's one explanation, yeah, And the other is I think

1356
01:18:47,080 --> 01:18:48,960
Speaker 2: goes back to the income and wealth distribution. If you're

1357
01:18:49,520 --> 01:18:53,439
Speaker 2: lower income, middle income and you live in parts of

1358
01:18:53,520 --> 01:18:56,760
Speaker 2: the country that got nailed with the loss of manufacturing,

1359
01:18:57,000 --> 01:18:59,599
Speaker 2: you know, the economy is just not very dynamic. House

1360
01:18:59,640 --> 01:19:03,160
Speaker 2: prices have not risen at all. They may have actually

1361
01:19:03,240 --> 01:19:06,280
Speaker 2: even declined in some of those communities. You just can't,

1362
01:19:06,760 --> 01:19:08,880
Speaker 2: you can't. And then you've seen the house prices rise.

1363
01:19:09,120 --> 01:19:12,120
Speaker 2: We're on the coast and say you can't afford to move,

1364
01:19:12,320 --> 01:19:15,360
Speaker 2: You literally can't, literally can't afford to move. There's just

1365
01:19:15,439 --> 01:19:17,120
Speaker 2: no possible way you're going to be able to do that.

1366
01:19:17,280 --> 01:19:19,280
Speaker 2: So you're kind of stuck. Even if you wanted to

1367
01:19:19,320 --> 01:19:21,360
Speaker 2: move to get that to that job that's sitting in

1368
01:19:21,479 --> 01:19:25,240
Speaker 2: Miami or wherever it is, you just can't do it.

1369
01:19:25,400 --> 01:19:27,880
Speaker 2: And and that's really cut down the mobility. I will

1370
01:19:27,960 --> 01:19:30,680
Speaker 2: say though, that's one of that has historically been one

1371
01:19:30,720 --> 01:19:34,360
Speaker 2: of the unique characteristics of the US economy compared to

1372
01:19:34,360 --> 01:19:37,280
Speaker 2: anywhere else in the world. You know, very few exceptions

1373
01:19:37,320 --> 01:19:40,200
Speaker 2: to that. And it's that mobility that has allowed the

1374
01:19:40,280 --> 01:19:42,960
Speaker 2: US economy to adjust to shocks, because, as you say,

1375
01:19:43,160 --> 01:19:44,720
Speaker 2: if you lose a job over here, you can pick

1376
01:19:44,800 --> 01:19:47,200
Speaker 2: up a move to take a job over there. But

1377
01:19:47,360 --> 01:19:50,240
Speaker 2: that that flexibility, it's still there. We're still much more

1378
01:19:50,320 --> 01:19:54,200
Speaker 2: flexible mobile than let's say Europe or you know, other

1379
01:19:54,240 --> 01:19:56,519
Speaker 2: parts of the Asia, other parts of the world, but

1380
01:19:56,760 --> 01:19:59,439
Speaker 2: much less so. So we're not you know, we don't

1381
01:19:59,439 --> 01:20:02,160
Speaker 2: benefit to the same degrees we did thirty forty fifty

1382
01:20:02,200 --> 01:20:02,559
Speaker 2: years ago.

1383
01:20:02,600 --> 01:20:05,160
Speaker 1: From that, from that mobility, All right, let me get

1384
01:20:05,200 --> 01:20:08,800
Speaker 1: you out of here on this, which is is our

1385
01:20:08,960 --> 01:20:13,759
Speaker 1: how much is our economy at risk due to domestic

1386
01:20:13,880 --> 01:20:18,040
Speaker 1: politics and how much of it is with more global forces?

1387
01:20:20,400 --> 01:20:24,680
Speaker 2: I'd say policy above, but you know.

1388
01:20:25,320 --> 01:20:28,360
Speaker 1: You know, I think it's clear or you can't really disentangle.

1389
01:20:28,720 --> 01:20:31,560
Speaker 2: Yeah, I mean, look, I think it's pretty clear that

1390
01:20:31,720 --> 01:20:35,639
Speaker 2: our politics are fractured, and you know, probably goes back.

1391
01:20:35,560 --> 01:20:40,640
Speaker 1: To was that worth a point of GDP. Probably a

1392
01:20:40,720 --> 01:20:45,200
Speaker 1: better politics or a more functional political system, we probably

1393
01:20:45,240 --> 01:20:47,599
Speaker 1: would have a healthier overall economy.

1394
01:20:47,840 --> 01:20:49,320
Speaker 2: How could it not be the case? I mean, just

1395
01:20:49,320 --> 01:20:51,599
Speaker 2: take a look at what's happening now with the government shutdown, right,

1396
01:20:51,680 --> 01:20:54,000
Speaker 2: I mean, yeah, there's no upside to that. There's nothing

1397
01:20:54,080 --> 01:20:56,040
Speaker 2: but downside, and it diminishes our.

1398
01:20:56,479 --> 01:20:58,800
Speaker 1: Large I have no there's nothing in the constitution that

1399
01:20:58,840 --> 01:21:01,360
Speaker 1: says government has to shut down if there's appropriations dispute.

1400
01:21:01,360 --> 01:21:04,520
Speaker 1: It tries to me crazy that we've just decided collectively

1401
01:21:04,600 --> 01:21:05,519
Speaker 1: this is how we should function.

1402
01:21:05,840 --> 01:21:08,800
Speaker 2: Yeah, there you go. And then you know, but of

1403
01:21:08,880 --> 01:21:12,200
Speaker 2: course that this goes to our ability to respond to

1404
01:21:13,400 --> 01:21:16,559
Speaker 2: the challenges that we face, and there are many challenges

1405
01:21:16,600 --> 01:21:20,360
Speaker 2: both domestic and you know globally, what's going on globally.

1406
01:21:20,400 --> 01:21:24,240
Speaker 2: There's a tremendous challenges there, and we can't address them

1407
01:21:24,920 --> 01:21:27,600
Speaker 2: if we're as politically fractured as we are. So I

1408
01:21:28,240 --> 01:21:31,720
Speaker 2: think that's you know, again, I want to say, it's

1409
01:21:31,760 --> 01:21:33,920
Speaker 2: not a cliff event. I kind of think of there

1410
01:21:33,960 --> 01:21:36,680
Speaker 2: are corrosives and there's cliff events. This is not a

1411
01:21:36,720 --> 01:21:38,439
Speaker 2: cliff event. It's not like we're going to go off

1412
01:21:38,560 --> 01:21:40,640
Speaker 2: the cliff here. But it's one of those things that

1413
01:21:40,920 --> 01:21:44,960
Speaker 2: kind of undermines the economy's ability to grow a longer run.

1414
01:21:45,640 --> 01:21:47,760
Speaker 2: And you know, you don't really feel it in a

1415
01:21:47,800 --> 01:21:49,719
Speaker 2: given year, but when you look back over a decade

1416
01:21:49,800 --> 01:21:52,200
Speaker 2: or two, you go, oh my gosh, you can see it.

1417
01:21:52,320 --> 01:21:53,720
Speaker 2: You can see it and you can feel it. Well.

1418
01:21:53,760 --> 01:21:56,080
Speaker 1: The reason I asked about the international versus the domestic.

1419
01:21:56,120 --> 01:21:58,280
Speaker 1: I mean, look, I think we all understand the domestic,

1420
01:21:58,320 --> 01:22:01,439
Speaker 1: but I look out of China. Is that a healthy

1421
01:22:01,520 --> 01:22:04,639
Speaker 1: economy or not? If you thought employment is near twenty percent,

1422
01:22:05,640 --> 01:22:06,799
Speaker 1: how's that a healthy economy?

1423
01:22:06,840 --> 01:22:08,519
Speaker 2: Now they got their we got their own problems.

1424
01:22:08,560 --> 01:22:11,840
Speaker 1: I mean, could that lead to contagion globally? I mean,

1425
01:22:11,960 --> 01:22:13,600
Speaker 1: there's such a big economy, how could it.

1426
01:22:13,640 --> 01:22:18,760
Speaker 2: Not well, I mean, I think it's one of those

1427
01:22:18,760 --> 01:22:21,520
Speaker 2: things where they can keep it together for an extended period.

1428
01:22:21,320 --> 01:22:23,759
Speaker 1: Right, I mean because of their system of government.

1429
01:22:23,800 --> 01:22:26,240
Speaker 2: Their system of government, I mean, it's very autocratic. I

1430
01:22:26,320 --> 01:22:31,320
Speaker 2: don't think it works well in terms of in terms

1431
01:22:31,360 --> 01:22:34,519
Speaker 2: of long term economic growth, but they can keep things

1432
01:22:34,560 --> 01:22:38,320
Speaker 2: going for a long time, and you know, paper over

1433
01:22:38,360 --> 01:22:40,320
Speaker 2: a lot of a lot of mistakes, and you know

1434
01:22:40,400 --> 01:22:43,160
Speaker 2: that's what they're doing right now. So you know, I'm

1435
01:22:43,200 --> 01:22:46,599
Speaker 2: not bullish on China long run, but I'm not bearish

1436
01:22:46,640 --> 01:22:48,479
Speaker 2: in the near term. I don't think that's something that's

1437
01:22:48,479 --> 01:22:49,800
Speaker 2: going to fall apart anytime soon.

1438
01:22:50,040 --> 01:22:51,840
Speaker 1: All right, So if I have you back here after

1439
01:22:51,880 --> 01:22:54,680
Speaker 1: the first of January, you think we're probably going to

1440
01:22:54,680 --> 01:22:57,760
Speaker 1: be in the same levels of risk more likely than not,

1441
01:22:58,080 --> 01:23:01,320
Speaker 1: just sort of sitting in this same sort of elevated

1442
01:23:01,479 --> 01:23:03,080
Speaker 1: but not there in a recession.

1443
01:23:03,520 --> 01:23:05,920
Speaker 2: Yeah, I think that that'll be the case, junk. I mean,

1444
01:23:06,000 --> 01:23:08,720
Speaker 2: I do think that if we look out a year

1445
01:23:08,800 --> 01:23:11,160
Speaker 2: from now and towards the second half of next year,

1446
01:23:11,439 --> 01:23:13,160
Speaker 2: you know, we might start to see a lift because

1447
01:23:13,160 --> 01:23:15,080
Speaker 2: at that point we're on the other side of the tariffs,

1448
01:23:15,160 --> 01:23:18,600
Speaker 2: the immigration policy, and you've got lower interest rates. The

1449
01:23:18,640 --> 01:23:20,479
Speaker 2: Fed is going to be cutting interest rates, and you

1450
01:23:20,560 --> 01:23:23,000
Speaker 2: know there's a lot of fiscal so called fiscal stimulus

1451
01:23:23,040 --> 01:23:25,600
Speaker 2: in that one big beautiful bill that got passed. You know,

1452
01:23:25,600 --> 01:23:27,640
Speaker 2: there's a lot of cutting, but that comes later, you know,

1453
01:23:27,800 --> 01:23:30,559
Speaker 2: next year, telling the tax cuts and so people are

1454
01:23:30,560 --> 01:23:31,960
Speaker 2: gonna get bigger refund checks.

1455
01:23:32,560 --> 01:23:35,680
Speaker 1: Good, So you think there could be another that in

1456
01:23:35,800 --> 01:23:38,160
Speaker 1: some ways we maybe we might have a leaky, hot

1457
01:23:38,200 --> 01:23:40,360
Speaker 1: air balloon, but there's gonna be more more air pumped

1458
01:23:40,400 --> 01:23:40,640
Speaker 1: into it.

1459
01:23:40,760 --> 01:23:42,720
Speaker 2: That's great what I think of putting it. Yeah, that's

1460
01:23:42,720 --> 01:23:44,680
Speaker 2: a great metaphor. It's exactly what's going to happen. So,

1461
01:23:44,960 --> 01:23:46,560
Speaker 2: you know, I think the economy is going to be

1462
01:23:46,600 --> 01:23:48,519
Speaker 2: most vulnerable in the next six to nine months. On

1463
01:23:48,640 --> 01:23:51,320
Speaker 2: the other side of that, then I think it it'll

1464
01:23:51,360 --> 01:23:53,920
Speaker 2: get some juice from the fiscal and monetary stimulus that's

1465
01:23:53,960 --> 01:23:54,519
Speaker 2: in train here.

1466
01:23:54,920 --> 01:23:57,600
Speaker 1: All right, Mark s Andy, Always great to hear from you.

1467
01:23:57,760 --> 01:23:59,840
Speaker 2: Yeah, thanks, Chuck thinks, thanks for all the wide ranging

1468
01:24:00,000 --> 01:24:01,080
Speaker 2: lisson is always appreciated.

1469
01:24:01,280 --> 01:24:03,920
Speaker 1: Well, I you know, you you humor me well and

1470
01:24:04,160 --> 01:24:06,519
Speaker 1: at the same time you're pretty good about putting this

1471
01:24:06,840 --> 01:24:08,000
Speaker 1: stuff in English, and I do.

1472
01:24:08,280 --> 01:24:12,559
Speaker 2: I mean, there you go, pretty good, pretty good, pretty good.

1473
01:24:14,360 --> 01:24:18,000
Speaker 1: Well, you know, you can't ever say great, right, but

1474
01:24:18,680 --> 01:24:21,200
Speaker 1: I never give five stars, right, I'm a four point

1475
01:24:21,320 --> 01:24:22,920
Speaker 1: nine guy. No, I hear you.

1476
01:24:23,800 --> 01:24:24,320
Speaker 2: Thanks Mark.

1477
01:24:24,920 --> 01:24:39,960
Speaker 1: It is Monday, which also means we're going to go

1478
01:24:40,040 --> 01:24:48,680
Speaker 1: back into the toodcast time Machine. Do I need to

1479
01:24:48,720 --> 01:24:53,720
Speaker 1: do it right? I don't know if you guys have

1480
01:24:54,320 --> 01:24:58,120
Speaker 1: you know, I hope you like our little music interlude

1481
01:24:58,160 --> 01:25:01,000
Speaker 1: on this you should. You should know that the inspiration

1482
01:25:01,080 --> 01:25:04,400
Speaker 1: I was looking for was sort of Huey Lewis meets

1483
01:25:05,320 --> 01:25:08,240
Speaker 1: you know, without you know, without having to pay Huey

1484
01:25:08,320 --> 01:25:13,080
Speaker 1: Lewis rights for you know, Huey Lewis adjacent to give

1485
01:25:13,120 --> 01:25:17,280
Speaker 1: you the vibe of back to the future. So the

1486
01:25:17,400 --> 01:25:20,639
Speaker 1: time podcast Time Machine has actually got a financial theme

1487
01:25:20,760 --> 01:25:24,240
Speaker 1: to it. I figured, you know, we're talking a lot

1488
01:25:24,280 --> 01:25:27,160
Speaker 1: of things having to do with money, the economy. Well,

1489
01:25:27,520 --> 01:25:31,960
Speaker 1: on October nineteenth, nineteen eighty seven, that's where we're going back.

1490
01:25:32,040 --> 01:25:34,680
Speaker 1: It's now called Black Monday. That was the day that

1491
01:25:34,760 --> 01:25:38,360
Speaker 1: the US stock market lost twenty two point six percent

1492
01:25:38,520 --> 01:25:40,920
Speaker 1: in a single trading day. It was one of the

1493
01:25:40,960 --> 01:25:45,559
Speaker 1: most sudden and alarming crashes and financial history and today

1494
01:25:45,640 --> 01:25:48,120
Speaker 1: as we move in October twenty twenty five, we're in

1495
01:25:48,160 --> 01:25:50,400
Speaker 1: the middle of it with a lot of people wondering

1496
01:25:50,840 --> 01:25:55,120
Speaker 1: as how bubblicious is this AI driven stock market? Right,

1497
01:25:55,360 --> 01:25:58,040
Speaker 1: it's worth re examining the moment and asking could history

1498
01:25:58,080 --> 01:26:02,400
Speaker 1: teach us anything relevant for this market and what risks

1499
01:26:02,640 --> 01:26:05,800
Speaker 1: lurk in twenty twenty five that echo nineteen eighty seven?

1500
01:26:06,560 --> 01:26:09,320
Speaker 1: And are there safeguards that are missing? I have to

1501
01:26:09,400 --> 01:26:11,360
Speaker 1: tell you this, we have a lot of safeguards today

1502
01:26:11,560 --> 01:26:14,519
Speaker 1: because of the nineteen eighty seven black market. But here's

1503
01:26:14,560 --> 01:26:16,600
Speaker 1: what you need to know about how it happened. And

1504
01:26:16,760 --> 01:26:23,000
Speaker 1: I'll just be honest it that eighty seven crash. I

1505
01:26:23,200 --> 01:26:28,000
Speaker 1: was fifteen. My dad would die thirty fourteen months later.

1506
01:26:30,360 --> 01:26:38,439
Speaker 1: He was a modestly successful financial advisor. Needless to say,

1507
01:26:38,439 --> 01:26:40,280
Speaker 1: all his clients lost a lot of money that day.

1508
01:26:41,840 --> 01:26:45,519
Speaker 1: Whatever savings my parents had were gone that day never

1509
01:26:45,600 --> 01:26:50,680
Speaker 1: recovered at that point and led to sort of So

1510
01:26:50,760 --> 01:26:54,680
Speaker 1: I've it has always been a it was sort of

1511
01:26:54,880 --> 01:26:57,200
Speaker 1: I've always pinpointed it, even though my dad had not

1512
01:26:57,320 --> 01:26:59,920
Speaker 1: been diagnosed yet, always have pinpointed it as sort of

1513
01:27:00,080 --> 01:27:03,680
Speaker 1: the beginning of the end for my father. So there

1514
01:27:03,760 --> 01:27:08,759
Speaker 1: is a for me. This is both personal and prepared

1515
01:27:08,800 --> 01:27:10,599
Speaker 1: and certainly had an impact on how I think about

1516
01:27:10,640 --> 01:27:12,640
Speaker 1: markets and how I think about the economy, and how

1517
01:27:12,640 --> 01:27:18,040
Speaker 1: I think about how you what you think of the

1518
01:27:18,080 --> 01:27:22,720
Speaker 1: stock market and how much you should react, underreact, overreact,

1519
01:27:22,840 --> 01:27:25,360
Speaker 1: et cetera. But let me give you sort of a

1520
01:27:25,479 --> 01:27:28,240
Speaker 1: larger look at what the economy was looking like back then.

1521
01:27:28,320 --> 01:27:31,840
Speaker 1: In mid eighty seven, market had already been running up

1522
01:27:32,040 --> 01:27:36,320
Speaker 1: big time. Valuations were stretched, growth was decelerating, while inflation

1523
01:27:36,479 --> 01:27:40,960
Speaker 1: and interest rates were starting to rise again. Yet international

1524
01:27:41,040 --> 01:27:43,200
Speaker 1: currency was a contributor to this one. The eighty five

1525
01:27:43,280 --> 01:27:46,599
Speaker 1: Plaza Accord, which sought to push the US dollar lower,

1526
01:27:47,520 --> 01:27:49,479
Speaker 1: that had a contribution there, and by eighty seven markets

1527
01:27:49,520 --> 01:27:54,160
Speaker 1: were uneasy about the coordination under a follow up accord

1528
01:27:54,280 --> 01:27:58,840
Speaker 1: called the Louver Accords. And what was interesting is that

1529
01:27:59,600 --> 01:28:02,360
Speaker 1: in the week leading up to the crash, it was

1530
01:28:02,840 --> 01:28:05,400
Speaker 1: a crash happened on a Monday. Markets had already been

1531
01:28:05,439 --> 01:28:08,960
Speaker 1: seeing some sharp, sharp decline, so there was definitely pressure

1532
01:28:09,080 --> 01:28:12,439
Speaker 1: to sell more and more we're thinking about selling. So

1533
01:28:12,920 --> 01:28:16,280
Speaker 1: when you look at you know, when you look back

1534
01:28:16,320 --> 01:28:19,280
Speaker 1: in history, the biggest structural culprit to the sort of

1535
01:28:19,400 --> 01:28:23,280
Speaker 1: near to this crash was something called portfolio insurance or

1536
01:28:23,400 --> 01:28:27,680
Speaker 1: dynamic hedging. This was sort of the first iteration of computerized,

1537
01:28:28,200 --> 01:28:33,760
Speaker 1: computer based programs that automatically triggered trades. So as prices fell,

1538
01:28:33,880 --> 01:28:37,800
Speaker 1: it automatically increased short positions i e. Futures that were

1539
01:28:38,000 --> 01:28:40,880
Speaker 1: then to hedge, and it effectively was selling into a

1540
01:28:40,960 --> 01:28:44,679
Speaker 1: weak market and it would sort of ballooned on itself.

1541
01:28:45,439 --> 01:28:48,799
Speaker 1: It triggered all sorts of horrible feedback loops, falling prices,

1542
01:28:49,320 --> 01:28:53,920
Speaker 1: more hedge, hedging, more selling, more downward pressure, more hedging, right,

1543
01:28:54,200 --> 01:28:56,560
Speaker 1: and it was it was sort of it was what

1544
01:28:56,960 --> 01:28:59,400
Speaker 1: it was. It was the first time we were warned

1545
01:28:59,439 --> 01:29:02,360
Speaker 1: of what happened when you start to attempt to automate

1546
01:29:02,479 --> 01:29:06,559
Speaker 1: certain trading decisions, right, you automatically buy if you see

1547
01:29:06,600 --> 01:29:08,560
Speaker 1: a number here, automatically do this if you see a

1548
01:29:08,640 --> 01:29:11,640
Speaker 1: number there. So, all of a sudden, quickly liquidity and

1549
01:29:12,840 --> 01:29:17,719
Speaker 1: got stressed immediately. Some stocks even open late, they were halted.

1550
01:29:17,840 --> 01:29:21,040
Speaker 1: Sometimes bids disappeared because remember some things were computerized, some

1551
01:29:21,160 --> 01:29:26,200
Speaker 1: things weren't, and then the structure of the market couldn't

1552
01:29:26,200 --> 01:29:30,720
Speaker 1: absorb all the orders. I mean it basically, if you

1553
01:29:30,800 --> 01:29:32,920
Speaker 1: think about what happened in October of eighty seven. And

1554
01:29:33,120 --> 01:29:35,760
Speaker 1: you know the movie Trading Places when they're having that

1555
01:29:35,960 --> 01:29:39,599
Speaker 1: when those guys are on the floor, when everything's panicking

1556
01:29:39,720 --> 01:29:42,000
Speaker 1: and they're having heart attacks, Sell, sell, and the whole

1557
01:29:42,040 --> 01:29:45,280
Speaker 1: frozen orange juice concentrate business. If you can imagine that,

1558
01:29:45,520 --> 01:29:48,200
Speaker 1: that's kind of how it looked there, and that's still

1559
01:29:48,240 --> 01:29:54,840
Speaker 1: the way trading was done on that floor, and it was.

1560
01:29:55,400 --> 01:29:58,240
Speaker 1: It certainly led to a lot of safeguards being put in.

1561
01:29:58,520 --> 01:30:01,400
Speaker 1: But the crash. Interesting about this crash is it wasn't

1562
01:30:01,479 --> 01:30:05,479
Speaker 1: rooted in sort of a singular catastrophic macro shock like

1563
01:30:05,600 --> 01:30:08,160
Speaker 1: the collapse of Layman Brothers right in the Great Recession.

1564
01:30:08,880 --> 01:30:11,320
Speaker 1: There was no war, there was no overnight dead crisis.

1565
01:30:12,080 --> 01:30:16,519
Speaker 1: The ferocity came simply from the markets of fragility, leverage,

1566
01:30:16,600 --> 01:30:19,879
Speaker 1: and mechanical strategies. Right. It was a bit over leverage.

1567
01:30:20,240 --> 01:30:23,360
Speaker 1: Trust me, as a kid, I knew. I knew that

1568
01:30:23,520 --> 01:30:26,560
Speaker 1: it was a tripping triple Witching Friday was something like

1569
01:30:26,600 --> 01:30:31,639
Speaker 1: when option Friday coincided with a report. I can't remember

1570
01:30:32,080 --> 01:30:34,600
Speaker 1: what all of that lingo meant, but I know it

1571
01:30:34,680 --> 01:30:38,280
Speaker 1: would make my father's mood either good or bad, depending

1572
01:30:38,520 --> 01:30:41,320
Speaker 1: on the situation. Let's just say he never had another

1573
01:30:41,400 --> 01:30:47,320
Speaker 1: good mood after that. Again, the good news about that

1574
01:30:47,479 --> 01:30:51,920
Speaker 1: crash is that, because it was essentially a mechanical crash,

1575
01:30:52,560 --> 01:30:55,240
Speaker 1: I guess the way to put it, it didn't provoke

1576
01:30:55,320 --> 01:30:57,760
Speaker 1: a broader banking crisis. Right. There wasn't a run on

1577
01:30:57,880 --> 01:31:00,479
Speaker 1: banks like we had during the Great Recession, and we

1578
01:31:00,560 --> 01:31:04,639
Speaker 1: didn't end up in a deep recession unlike two thousand

1579
01:31:04,640 --> 01:31:09,320
Speaker 1: and eight or even after nineteen twenty nine. Believe it

1580
01:31:09,439 --> 01:31:11,800
Speaker 1: or not, it took only two sessions after the crash

1581
01:31:11,880 --> 01:31:14,720
Speaker 1: for the Dow to claw back fifty seven percent of

1582
01:31:14,800 --> 01:31:17,840
Speaker 1: its drop. The market fully regained its prior high by

1583
01:31:17,880 --> 01:31:21,760
Speaker 1: early nineteen eighty nine, less than two years later, and

1584
01:31:21,800 --> 01:31:25,280
Speaker 1: then afterward regulators and exchanges added mechanisms like circuit breakers

1585
01:31:25,360 --> 01:31:29,800
Speaker 1: trading halts to slow panic in future crashes. Look, it

1586
01:31:30,560 --> 01:31:33,160
Speaker 1: was the first lesson I ever got, which was, hey,

1587
01:31:33,760 --> 01:31:37,880
Speaker 1: don't panic. You know, close your eyes. If you're younger,

1588
01:31:38,000 --> 01:31:40,920
Speaker 1: close your eyes. Eventually the market is going to come back,

1589
01:31:40,960 --> 01:31:44,519
Speaker 1: because the market always you can see it, right, there's

1590
01:31:44,560 --> 01:31:48,760
Speaker 1: always this upward trajectory, and in some ways many people

1591
01:31:48,840 --> 01:31:51,240
Speaker 1: behave that way. Anyway. Now the question is where are

1592
01:31:51,280 --> 01:31:54,240
Speaker 1: we sitting now, Right, Is this a bubble? Do we

1593
01:31:54,320 --> 01:31:56,320
Speaker 1: only have? Right? The S and P five hundred keeps

1594
01:31:56,360 --> 01:32:01,280
Speaker 1: going gangbusters, the Dow not so much. Right. There's all

1595
01:32:01,320 --> 01:32:03,800
Speaker 1: sorts of things that could be happening here that we're

1596
01:32:03,840 --> 01:32:06,640
Speaker 1: not quite one hundred percent sure of. Right. Why are

1597
01:32:06,680 --> 01:32:09,240
Speaker 1: the large stocks continue to go up? Is this all

1598
01:32:09,439 --> 01:32:12,280
Speaker 1: due to AI investment? How much of this is due

1599
01:32:12,280 --> 01:32:15,919
Speaker 1: to people who've gotten who are sort of heavy into crypto.

1600
01:32:16,800 --> 01:32:20,439
Speaker 1: It got essentially legalized by the government, and they've quickly

1601
01:32:20,520 --> 01:32:23,720
Speaker 1: got out of crypto and then bought Microsoft, Google, you know,

1602
01:32:23,800 --> 01:32:27,880
Speaker 1: all the large cap stocks in order to take this

1603
01:32:28,080 --> 01:32:32,000
Speaker 1: imagined money and turn it into a real asset. We

1604
01:32:32,120 --> 01:32:36,040
Speaker 1: shall see. But there's certainly a lot going on in

1605
01:32:36,120 --> 01:32:41,160
Speaker 1: this market that for those that are not experts in

1606
01:32:41,240 --> 01:32:43,960
Speaker 1: it are wondering, are you sure you're not missing something?

1607
01:32:44,040 --> 01:32:46,040
Speaker 1: Are we sure this isn't a bubble? Are we sure

1608
01:32:46,080 --> 01:32:48,320
Speaker 1: we're not going to end up in a situation like

1609
01:32:48,400 --> 01:32:49,760
Speaker 1: what we saw in two thousand and eight or what

1610
01:32:49,800 --> 01:32:55,040
Speaker 1: we saw in nineteen eighty seven. In twenty twenty five,

1611
01:32:55,200 --> 01:32:59,280
Speaker 1: so the question is, you know what parallels are out there? Well,

1612
01:32:59,320 --> 01:33:01,800
Speaker 1: we do have an algorithmic parallel, right that you could

1613
01:33:01,840 --> 01:33:05,120
Speaker 1: be their markets are even more dominated by algorithmic trading,

1614
01:33:05,800 --> 01:33:10,320
Speaker 1: quant strategies and AI and models, and it raises the

1615
01:33:10,560 --> 01:33:16,160
Speaker 1: risk of algorithmic collisions or systemic feedback loops. We supposedly

1616
01:33:16,240 --> 01:33:19,040
Speaker 1: are constantly looking to make sure this doesn't happen again,

1617
01:33:19,560 --> 01:33:22,240
Speaker 1: but so much is automated. Remember we had that flash

1618
01:33:22,280 --> 01:33:25,639
Speaker 1: crash this is probably about eight years ago now, which

1619
01:33:25,680 --> 01:33:28,679
Speaker 1: we had that thousand point drop out of nowhere because

1620
01:33:28,720 --> 01:33:32,560
Speaker 1: of a glitch in one of these automated things, And

1621
01:33:33,120 --> 01:33:36,840
Speaker 1: so you can't help but wonder. And then of course

1622
01:33:37,960 --> 01:33:42,559
Speaker 1: there's the fact that could a nefarious actor hack into

1623
01:33:42,680 --> 01:33:46,160
Speaker 1: one of these large private equity funds and sort of

1624
01:33:46,320 --> 01:33:51,880
Speaker 1: trigger trigger a flash crash of some sort, right, and

1625
01:33:52,000 --> 01:33:57,439
Speaker 1: trigger a market collapse essentially by redoing an algorithm. I

1626
01:33:57,479 --> 01:33:59,760
Speaker 1: think there's a lot of things here that we ought

1627
01:33:59,760 --> 01:34:03,599
Speaker 1: to be worried about. The other parallel is the sort

1628
01:34:03,640 --> 01:34:06,559
Speaker 1: of concentration risk right in twenty twenty. So far this year,

1629
01:34:06,600 --> 01:34:10,240
Speaker 1: valuations in certain sectors, particularly in tech, are under a

1630
01:34:10,360 --> 01:34:13,639
Speaker 1: ton of scrutiny. Central banks are worrying about overvaluations, structurally

1631
01:34:13,680 --> 01:34:17,960
Speaker 1: fragile markets. The equity markets are increasingly concentrated, meaning it's

1632
01:34:18,040 --> 01:34:23,000
Speaker 1: just a few big, mega tech names that carry outsized weight. Right,

1633
01:34:23,360 --> 01:34:29,439
Speaker 1: if Palenteer is in Navidia, are somehow you know, exposed

1634
01:34:29,479 --> 01:34:31,719
Speaker 1: to be something that they're not. And I'm not implying

1635
01:34:31,800 --> 01:34:35,080
Speaker 1: that they are, right, but if they somehow were the

1636
01:34:35,200 --> 01:34:39,400
Speaker 1: contagion of something like that, right, it would impact your Microsoft's,

1637
01:34:39,439 --> 01:34:42,160
Speaker 1: it would impact Google, it would impact Amazon. I mean,

1638
01:34:42,760 --> 01:34:45,640
Speaker 1: the contagion effect of this is something that you do

1639
01:34:45,840 --> 01:34:50,200
Speaker 1: have a lot of people worried about. And then, of

1640
01:34:50,320 --> 01:34:53,320
Speaker 1: course the other part of this is something we didn't

1641
01:34:53,360 --> 01:34:55,799
Speaker 1: have in eighty seven that we do have today, concerned

1642
01:34:55,800 --> 01:35:00,320
Speaker 1: about the politicizing of the FED, which can manipulate mark gets,

1643
01:35:01,320 --> 01:35:06,160
Speaker 1: which in turn could cause a trash, cause a crash. Now,

1644
01:35:06,280 --> 01:35:08,439
Speaker 1: some of the differences, right, y eighty seven is not

1645
01:35:08,920 --> 01:35:12,800
Speaker 1: really a corollary to twenty twenty five. Market infrastructure is

1646
01:35:12,800 --> 01:35:15,519
Speaker 1: a lot more mature. We have a lot more exchanges

1647
01:35:15,520 --> 01:35:18,439
Speaker 1: that are resilient. There are more circuit breakers in case

1648
01:35:18,520 --> 01:35:20,400
Speaker 1: there are halts that are baked in in case we

1649
01:35:20,600 --> 01:35:23,120
Speaker 1: do have a flash crash, in case an algorithm does

1650
01:35:23,200 --> 01:35:26,519
Speaker 1: go haywire. Information is a lot more transparent, it's a

1651
01:35:26,560 --> 01:35:30,479
Speaker 1: lot more real time. Every investor has more tools at

1652
01:35:30,520 --> 01:35:34,320
Speaker 1: their own disposal. You know, that's both good and bad.

1653
01:35:34,360 --> 01:35:36,200
Speaker 1: It means everybody could make their own run on a bank.

1654
01:35:36,200 --> 01:35:37,560
Speaker 1: You don't have to go find a trader to do

1655
01:35:37,640 --> 01:35:43,080
Speaker 1: it for you. And in some ways, because the markets

1656
01:35:43,080 --> 01:35:46,479
Speaker 1: are so global and so interconnected that in many ways,

1657
01:35:46,560 --> 01:35:49,519
Speaker 1: we all either rise and fall together. Right, it's not

1658
01:35:49,680 --> 01:35:51,680
Speaker 1: as if this would be an American problem, and it

1659
01:35:51,680 --> 01:35:55,519
Speaker 1: wouldn't be a problem everywhere else. In a weird way,

1660
01:35:55,800 --> 01:35:57,960
Speaker 1: if we're all in it together, is that a good thing?

1661
01:35:58,880 --> 01:36:02,040
Speaker 1: Or we'll we somehow take the blame if we somehow

1662
01:36:02,120 --> 01:36:07,120
Speaker 1: bring down the world, the world economy. But either way,

1663
01:36:07,439 --> 01:36:12,240
Speaker 1: that's the way back machine. Nineteen eighty seven, Black Monday.

1664
01:36:13,400 --> 01:36:18,400
Speaker 1: It has a particular resonance for me because it was

1665
01:36:18,760 --> 01:36:20,400
Speaker 1: it was for me sort of the beginning of the

1666
01:36:20,560 --> 01:36:23,240
Speaker 1: end for my father and for a variety of reasons.

1667
01:36:26,439 --> 01:36:29,360
Speaker 1: But it also taught me some lessons about the market.

1668
01:36:30,760 --> 01:36:32,400
Speaker 1: And you know, there are people that were close to

1669
01:36:32,479 --> 01:36:34,840
Speaker 1: my father were very angry about how the market acted

1670
01:36:34,880 --> 01:36:38,880
Speaker 1: that day and not paying attention to the fact that

1671
01:36:39,000 --> 01:36:44,680
Speaker 1: if they had just taken a breath, they'd have been

1672
01:36:44,720 --> 01:36:47,920
Speaker 1: in a better place two years later than they were

1673
01:36:48,000 --> 01:36:51,559
Speaker 1: on the day of the crash, and it's something I've

1674
01:36:51,640 --> 01:36:55,920
Speaker 1: learned over the years. Never panic right away when it comes.

1675
01:36:55,960 --> 01:36:59,680
Speaker 1: If you're investing money is don't invest money you need

1676
01:36:59,760 --> 01:37:03,640
Speaker 1: right way. If you're investing money, it's just that let it,

1677
01:37:04,280 --> 01:37:08,040
Speaker 1: let it do its work, and you know the long

1678
01:37:08,160 --> 01:37:11,599
Speaker 1: term rise. There's always going to be volatility in the middle,

1679
01:37:12,800 --> 01:37:15,360
Speaker 1: and you've got to if you have us, if you're

1680
01:37:15,479 --> 01:37:21,839
Speaker 1: invested soundly, the volatility should should be in some ways minimized.

1681
01:37:21,880 --> 01:37:25,360
Speaker 1: Sometimes the worst thing we have these days is, uh,

1682
01:37:25,840 --> 01:37:29,280
Speaker 1: it's too easy to follow all of this right. So

1683
01:37:29,400 --> 01:37:31,360
Speaker 1: there's your history lesson for the day. So with that,

1684
01:37:31,560 --> 01:37:38,599
Speaker 1: let me turn to a few questions ask Chuck. Question.

1685
01:37:39,040 --> 01:37:42,040
Speaker 1: First question comes from Brian Chuck. I really enjoy listening

1686
01:37:42,040 --> 01:37:43,599
Speaker 1: to your show. For some reason, all of our local,

1687
01:37:43,680 --> 01:37:46,280
Speaker 1: state and even city political parties all seem to be

1688
01:37:46,320 --> 01:37:49,639
Speaker 1: affiliated with the two national parties. You've had independent candidates

1689
01:37:49,920 --> 01:37:51,960
Speaker 1: running for governor in certain states that say they can't

1690
01:37:52,000 --> 01:37:54,360
Speaker 1: be a Democrat or Republican because that brand name is

1691
01:37:54,439 --> 01:37:56,920
Speaker 1: toxic in that state. Here's my question, would it make

1692
01:37:57,000 --> 01:37:59,200
Speaker 1: more sense for the Democratic Party of Idaho or the

1693
01:37:59,280 --> 01:38:03,040
Speaker 1: Republican Party Massachusetts and similar situations to change their name

1694
01:38:03,080 --> 01:38:05,560
Speaker 1: to something different than the Democrat or Republican, or to

1695
01:38:05,640 --> 01:38:08,559
Speaker 1: carve off the state political party from the national political

1696
01:38:08,600 --> 01:38:13,120
Speaker 1: party names and run state candidates for legislature for governor

1697
01:38:13,240 --> 01:38:16,000
Speaker 1: under a different name. Regards Bryant, Well, actually that's the

1698
01:38:16,080 --> 01:38:19,400
Speaker 1: state of Minnesota. It's the Democratic Farm Labor Party and

1699
01:38:19,439 --> 01:38:21,640
Speaker 1: the Republican Party until recently used to be known as

1700
01:38:21,680 --> 01:38:25,599
Speaker 1: the Independent Republican Party. Those two state parties, and in fact,

1701
01:38:25,640 --> 01:38:28,800
Speaker 1: there were two parties at one time in Minnesota that

1702
01:38:29,160 --> 01:38:32,120
Speaker 1: make up the Democrat and Farm DFL. It was known

1703
01:38:32,160 --> 01:38:36,679
Speaker 1: as Democratic Farm Labor Party. I have often wondered why

1704
01:38:37,240 --> 01:38:42,280
Speaker 1: parties haven't done this, and that actually, to me, isn't

1705
01:38:42,960 --> 01:38:46,720
Speaker 1: such a crazy notion to this day. You know, look,

1706
01:38:46,760 --> 01:38:52,679
Speaker 1: the word independent is totally I can create a halo effect.

1707
01:38:53,400 --> 01:38:55,720
Speaker 1: And I remember, look, Minnesota always had a different type

1708
01:38:55,720 --> 01:38:58,240
Speaker 1: of Republican that could win because they were a member

1709
01:38:58,280 --> 01:39:01,639
Speaker 1: of the Independent. They were I are Independent Republican Party

1710
01:39:01,680 --> 01:39:05,840
Speaker 1: of Minnesota, and you had guys like Dave Durnberger Rudy

1711
01:39:05,920 --> 01:39:08,559
Speaker 1: Boschwitz that could win in Minnesota probably couldn't have won

1712
01:39:08,600 --> 01:39:12,599
Speaker 1: in many other places as a Republican. But I think

1713
01:39:12,680 --> 01:39:16,479
Speaker 1: if I think this would make sense, I think it

1714
01:39:16,520 --> 01:39:21,200
Speaker 1: would make a ton of sense because, again, especially if

1715
01:39:21,200 --> 01:39:23,760
Speaker 1: you want to believe all politics is local. Unfortunately all

1716
01:39:23,800 --> 01:39:28,160
Speaker 1: politics has become national. But all politics should be localized again,

1717
01:39:28,600 --> 01:39:30,280
Speaker 1: and one of the better ways to do it is

1718
01:39:30,400 --> 01:39:32,720
Speaker 1: to in some ways be your own brand. Say, look,

1719
01:39:33,000 --> 01:39:37,960
Speaker 1: we're affiliating for fundraising purposes with the National Democrats or

1720
01:39:38,040 --> 01:39:42,800
Speaker 1: with the National Republicans, but we're kind of an independent organization.

1721
01:39:43,280 --> 01:39:47,400
Speaker 1: And you know, now maybe the national parties are you know,

1722
01:39:47,560 --> 01:39:51,800
Speaker 1: don't want their state chapters having that kind of independence,

1723
01:39:53,240 --> 01:39:55,440
Speaker 1: or maybe it's a way to sort of test splintering

1724
01:39:55,560 --> 01:39:58,600
Speaker 1: off and see how it goes on that front. But

1725
01:39:58,720 --> 01:40:02,840
Speaker 1: I think it's an app salute worthy experiment. If you're

1726
01:40:03,120 --> 01:40:07,400
Speaker 1: the Democratic Party in South Dakota, the Republican Party in Delaware.

1727
01:40:08,520 --> 01:40:13,919
Speaker 1: And here's the thing, you can it's a cheap experiment,

1728
01:40:15,320 --> 01:40:18,360
Speaker 1: you know, because you can experiment in these smaller states,

1729
01:40:19,000 --> 01:40:23,000
Speaker 1: you know, these smaller sort of one party states, and

1730
01:40:23,160 --> 01:40:25,080
Speaker 1: see if it does have an impact, See if you're

1731
01:40:25,080 --> 01:40:28,160
Speaker 1: able to sort of recruit a different type of candidate.

1732
01:40:28,840 --> 01:40:32,080
Speaker 1: Suddenly you might win more local elections, and ultimately, the

1733
01:40:32,160 --> 01:40:34,960
Speaker 1: more local elections you win, the more credibility you might

1734
01:40:35,040 --> 01:40:37,920
Speaker 1: get in statewide elections. And to me, if you really

1735
01:40:37,960 --> 01:40:39,600
Speaker 1: want to grow your state party, the goal is to

1736
01:40:39,640 --> 01:40:41,960
Speaker 1: win the governorship. The goal isn't to win Senate seats.

1737
01:40:42,000 --> 01:40:44,680
Speaker 1: The goal is win. Once you prove you can win

1738
01:40:44,840 --> 01:40:48,800
Speaker 1: races locally in the state legislature and governor, everything else

1739
01:40:48,840 --> 01:40:52,719
Speaker 1: will take care of itself in the state. So, Brian,

1740
01:40:52,760 --> 01:40:55,960
Speaker 1: I think this is a great idea, and again it's

1741
01:40:56,000 --> 01:40:59,280
Speaker 1: actually been done before. The Minnesota was sort of the

1742
01:40:59,360 --> 01:41:04,160
Speaker 1: prime exam in the twentieth century. Both I think now

1743
01:41:04,240 --> 01:41:07,200
Speaker 1: they're both have gotten rid of those older names, but

1744
01:41:07,280 --> 01:41:10,479
Speaker 1: they were. They had their own distinct brand and they

1745
01:41:10,600 --> 01:41:15,400
Speaker 1: prided themselves. You know, you'd have politicians in Minnesota. I'm

1746
01:41:15,400 --> 01:41:17,719
Speaker 1: not a Democrat. I'm a member of the Democratic Farm

1747
01:41:17,800 --> 01:41:20,479
Speaker 1: Labor Party, and that was a point of pride. No, no, no, no,

1748
01:41:20,680 --> 01:41:22,240
Speaker 1: I'm not a National Republican. I'm a member of the

1749
01:41:22,280 --> 01:41:27,639
Speaker 1: Independent Republican Party in Minnesota. That branding helped both parties.

1750
01:41:28,600 --> 01:41:31,360
Speaker 1: Both helped candidates in both parties in that state. And

1751
01:41:31,920 --> 01:41:34,400
Speaker 1: Minnesota is no small state, right and they're kind of

1752
01:41:34,920 --> 01:41:37,160
Speaker 1: swing ish, you know, could be a swing states, not

1753
01:41:37,240 --> 01:41:41,520
Speaker 1: quite there. I think a non Donald Trump led Republican

1754
01:41:41,560 --> 01:41:45,240
Speaker 1: party could make Minnesota a bit more competitive, and de

1755
01:41:45,400 --> 01:41:48,040
Speaker 1: versus are. For what it's worth, I think trump is

1756
01:41:48,680 --> 01:41:51,080
Speaker 1: is just a hard sell in the suburbs of Minnesota

1757
01:41:51,120 --> 01:41:55,240
Speaker 1: for people. But anyway, I think it's a again. It's

1758
01:41:55,280 --> 01:41:58,920
Speaker 1: been tried and it probably should be tried again. Great suggestion, Brian.

1759
01:41:59,400 --> 01:42:02,400
Speaker 1: Next question, I'm from Jason with a Y from California.

1760
01:42:03,439 --> 01:42:05,360
Speaker 1: Hi Chuck. Hearing your take on the two party system

1761
01:42:05,400 --> 01:42:07,120
Speaker 1: and how big these tents can get makes me wonder

1762
01:42:07,320 --> 01:42:09,840
Speaker 1: why more small parties are independents haven't emerged you and

1763
01:42:09,960 --> 01:42:13,559
Speaker 1: me both brother huge overlooked reason seems to be battle access.

1764
01:42:13,640 --> 01:42:15,560
Speaker 1: Oh yeah, I don't think it's an overlooked reason. I

1765
01:42:15,600 --> 01:42:20,120
Speaker 1: think it is the reason. But battle access is costly

1766
01:42:20,160 --> 01:42:22,120
Speaker 1: and time consuming, so only candidates backed by a major

1767
01:42:22,160 --> 01:42:24,599
Speaker 1: party usually make it. Getting on the ballot. We're easier.

1768
01:42:24,640 --> 01:42:27,880
Speaker 1: We'd likely see more options and less polarization. It's California.

1769
01:42:28,439 --> 01:42:30,559
Speaker 1: I am weary of a race with one hundred plus candidates.

1770
01:42:30,600 --> 01:42:34,960
Speaker 1: Hello twenty ozho three recall election. Ah, yes, remember we

1771
01:42:35,080 --> 01:42:41,120
Speaker 1: had Gary Coleman Arianna Huffington. I think there was at

1772
01:42:41,240 --> 01:42:45,559
Speaker 1: least one prostitute in that race as well. Some might

1773
01:42:45,680 --> 01:42:49,559
Speaker 1: argue that if you're elected official, you've already prostituted yourself.

1774
01:42:49,560 --> 01:42:52,519
Speaker 1: But I will leave that there. Anyway, I keep injecting

1775
01:42:52,720 --> 01:42:55,920
Speaker 1: my own commentary into Jason's question. My apologies there. Back

1776
01:42:55,960 --> 01:42:58,559
Speaker 1: to Jason's question, but our system right now, where parties

1777
01:42:58,600 --> 01:43:00,840
Speaker 1: serve as king makers and create rules that block other

1778
01:43:00,880 --> 01:43:03,559
Speaker 1: parties from gaining access or individuals from getting on the ballot,

1779
01:43:03,760 --> 01:43:07,320
Speaker 1: seems like an understated cause for increasing polarization. What best

1780
01:43:07,400 --> 01:43:09,800
Speaker 1: practices would use suggest to reform ballot access and open

1781
01:43:09,840 --> 01:43:12,920
Speaker 1: the field? Thanks is from California. Well, look, I'd like

1782
01:43:13,000 --> 01:43:15,720
Speaker 1: to try some better legal strategies. I think that there's

1783
01:43:15,760 --> 01:43:22,200
Speaker 1: an equal protection argument, and that it is if you

1784
01:43:22,400 --> 01:43:25,640
Speaker 1: can't you know the fact that there that that a

1785
01:43:25,720 --> 01:43:28,000
Speaker 1: third party doesn't have an equal shot at making the

1786
01:43:28,080 --> 01:43:32,800
Speaker 1: ballot as the two major parties doesn't. There's no there's

1787
01:43:32,800 --> 01:43:36,320
Speaker 1: no mention of a political party in the constitution. I

1788
01:43:36,439 --> 01:43:43,360
Speaker 1: also think taxpayer funded partisan primaries are likely unconstitutional because

1789
01:43:43,400 --> 01:43:48,840
Speaker 1: they they leave out they intentionally leave people out from

1790
01:43:49,280 --> 01:43:53,920
Speaker 1: participating unless you're a member of this private club known

1791
01:43:53,960 --> 01:43:57,240
Speaker 1: as either the Republican Party or the Democratic Party. So

1792
01:43:58,080 --> 01:44:00,920
Speaker 1: I look, I think there are legal arguments to make.

1793
01:44:00,960 --> 01:44:02,840
Speaker 1: But here's here's the problem, right, you want to talk

1794
01:44:02,840 --> 01:44:06,080
Speaker 1: about a system that's rigged. Even the judiciary is rigged

1795
01:44:06,120 --> 01:44:09,760
Speaker 1: by the two party system. Why they're all appointed by

1796
01:44:09,840 --> 01:44:16,240
Speaker 1: members of the two parties. But I do think a

1797
01:44:16,479 --> 01:44:22,519
Speaker 1: high profile effort to make this argument. I think banning

1798
01:44:22,600 --> 01:44:25,599
Speaker 1: partisan primaries is probably if you could ask me, what's

1799
01:44:25,760 --> 01:44:30,000
Speaker 1: one thing we could do to chip away at polarization

1800
01:44:30,120 --> 01:44:34,720
Speaker 1: in America? Banning partisan primaries, pure and simple, having none

1801
01:44:34,760 --> 01:44:36,160
Speaker 1: of it. I mean, I go back to what David

1802
01:44:36,200 --> 01:44:41,360
Speaker 1: Holt said. I'm guessing you guys devoured that entire episode

1803
01:44:41,439 --> 01:44:46,800
Speaker 1: with the mayor of Oklahoma City. The least polarizing executive

1804
01:44:47,120 --> 01:44:49,599
Speaker 1: elected officials in the country are mayors, and it's because

1805
01:44:49,640 --> 01:44:52,240
Speaker 1: of how mayors are elected. They're not Most of them

1806
01:44:52,280 --> 01:44:54,760
Speaker 1: are not elected in partisan primaries. They're elected in all

1807
01:44:54,840 --> 01:44:57,479
Speaker 1: party primaries. They don't run with a party I D

1808
01:44:57,640 --> 01:45:00,880
Speaker 1: next to their name. Yes, people know who's liberal or conservative,

1809
01:45:01,120 --> 01:45:03,160
Speaker 1: but they don't run with a party, ID, etceter name,

1810
01:45:03,479 --> 01:45:06,880
Speaker 1: and they don't end up governing as polarizing as now

1811
01:45:07,240 --> 01:45:11,240
Speaker 1: partisan governors do or partisan presidents. And here we are,

1812
01:45:11,479 --> 01:45:16,320
Speaker 1: so partisan primaries is the virus. It's a big one,

1813
01:45:17,080 --> 01:45:20,280
Speaker 1: and we need to it's one of those things. There's

1814
01:45:20,320 --> 01:45:21,760
Speaker 1: a lot of things I'd like to do to open

1815
01:45:21,840 --> 01:45:24,840
Speaker 1: up the ballot, but you know, in some ways, let's

1816
01:45:24,920 --> 01:45:29,880
Speaker 1: singularly focus on what would help in the very very

1817
01:45:30,200 --> 01:45:35,280
Speaker 1: very near term banning partisan primaries. So let's start there.

1818
01:45:36,880 --> 01:45:40,679
Speaker 1: Chris K from South Carolina Rights, is it un American

1819
01:45:40,720 --> 01:45:42,800
Speaker 1: to feel that control of TikTok may be less risky

1820
01:45:42,800 --> 01:45:44,280
Speaker 1: in the hands of China than in the hands a

1821
01:45:44,320 --> 01:45:47,040
Speaker 1: few powerful of a few powerful Americans. Eke, I know

1822
01:45:47,080 --> 01:45:50,000
Speaker 1: where you're going here. The current risk is unregulated propaganda

1823
01:45:50,040 --> 01:45:52,599
Speaker 1: and data harvesting. Than I am not sure Corporate America

1824
01:45:52,680 --> 01:45:55,720
Speaker 1: has made the case they would be better actors to

1825
01:45:55,880 --> 01:45:59,880
Speaker 1: shay to add to the turmoil. Fourteen billion dollars sounds shady,

1826
01:46:00,400 --> 01:46:02,920
Speaker 1: by the way, Go hawks, Do we know who is

1827
01:46:03,000 --> 01:46:05,479
Speaker 1: good yet? Maybe? Or oh this is a separate question,

1828
01:46:06,880 --> 01:46:09,880
Speaker 1: and he has a separate question, do you know who's

1829
01:46:09,880 --> 01:46:14,479
Speaker 1: good at yet? On college football? I'm gonna get to

1830
01:46:14,560 --> 01:46:16,240
Speaker 1: college football in a minute, So it was a two

1831
01:46:16,280 --> 01:46:19,120
Speaker 1: part question. Thank you, Chris. I appreciate that, But look

1832
01:46:19,200 --> 01:46:19,960
Speaker 1: the TikTok thing.

1833
01:46:20,120 --> 01:46:20,479
Speaker 2: I I.

1834
01:46:22,680 --> 01:46:27,960
Speaker 1: Don't understand why TikTok's legal Congress passed the law, and

1835
01:46:29,240 --> 01:46:33,879
Speaker 1: somehow Donald Trump is going to agree to an ownership

1836
01:46:33,920 --> 01:46:38,000
Speaker 1: structure for TikTok. That doesn't solve the initial problem, which

1837
01:46:38,080 --> 01:46:42,479
Speaker 1: is China controls the algorithm, hard stop. China controls the

1838
01:46:42,520 --> 01:46:46,640
Speaker 1: algorithm concentrated. Look, we're now going to have the Ellisons

1839
01:46:47,240 --> 01:46:52,280
Speaker 1: owning CBS News, perhaps CNN and TikTok. That's a pretty

1840
01:46:52,720 --> 01:46:59,240
Speaker 1: large chunk of the news. I mean, the public information

1841
01:46:59,439 --> 01:47:04,120
Speaker 1: systems shouldn't be owned by a select few people. And

1842
01:47:04,280 --> 01:47:08,560
Speaker 1: yet the concentration of power in our in the in

1843
01:47:08,800 --> 01:47:12,880
Speaker 1: the ownership of platforms, right, I mean, look at we

1844
01:47:12,960 --> 01:47:16,160
Speaker 1: talk about independent media. Most of us though, are basically

1845
01:47:16,280 --> 01:47:21,800
Speaker 1: on two platforms, Google owned YouTube or substack. Right, there's

1846
01:47:21,920 --> 01:47:26,240
Speaker 1: there's not a diversity per se of platform there are

1847
01:47:26,360 --> 01:47:29,400
Speaker 1: you know, we probably need to diversify. There's no doubt

1848
01:47:29,520 --> 01:47:35,200
Speaker 1: there is too much monopolizing of the distribution system, let

1849
01:47:35,280 --> 01:47:39,320
Speaker 1: alone on the content side. We're starting to see consolidation,

1850
01:47:40,240 --> 01:47:43,639
Speaker 1: and it's quite a bit of consolidation on the content side.

1851
01:47:43,640 --> 01:47:45,439
Speaker 1: So I think both of them ought to concern us.

1852
01:47:46,080 --> 01:47:49,120
Speaker 1: And with TikTok, it is you're right, it's the but

1853
01:47:49,320 --> 01:47:52,679
Speaker 1: I mean that's always what made the It was really

1854
01:47:52,720 --> 01:47:55,639
Speaker 1: frustrating to hear many members of Congress correctly point out

1855
01:47:56,240 --> 01:48:05,320
Speaker 1: the propaganda of TikTok, and frankly the propaganda accomplishment of TikTok. Right,

1856
01:48:05,439 --> 01:48:08,240
Speaker 1: you know, you know if you somehow point out what

1857
01:48:08,400 --> 01:48:12,120
Speaker 1: the Chinese do with the wigers, you know, nobody ever

1858
01:48:12,200 --> 01:48:17,680
Speaker 1: sees that the fact that it seems to the algorithm

1859
01:48:17,840 --> 01:48:24,720
Speaker 1: rewards anti Israel messaging just automatically, no matter what it is.

1860
01:48:25,479 --> 01:48:27,200
Speaker 1: How do I know this? We did our own polling

1861
01:48:27,280 --> 01:48:30,720
Speaker 1: on this, where TikTok users between eight and eighteen and

1862
01:48:30,840 --> 01:48:34,800
Speaker 1: thirty had a unfavorable rating of Israel. Israel that was

1863
01:48:34,840 --> 01:48:38,639
Speaker 1: twenty points higher than if you didn't regularly use TikTok.

1864
01:48:39,320 --> 01:48:42,960
Speaker 1: So this was already and so I think what was

1865
01:48:43,040 --> 01:48:46,040
Speaker 1: so frustrating hear you're worried about TikTok, but you're doing

1866
01:48:46,160 --> 01:48:54,599
Speaker 1: nothing about X or YouTube or Instagram or anything meta owns, right,

1867
01:48:55,160 --> 01:48:58,519
Speaker 1: And I think that that was why there was plenty

1868
01:48:58,600 --> 01:49:02,759
Speaker 1: of TikTok users are going, well, geez, I mean Amazon

1869
01:49:02,840 --> 01:49:06,840
Speaker 1: and Google take my data and sell it. I'm certainly

1870
01:49:06,920 --> 01:49:09,920
Speaker 1: not crazy about that, But how is that any more

1871
01:49:10,000 --> 01:49:12,360
Speaker 1: or less nefarious than what the Chinese government is doing

1872
01:49:14,200 --> 01:49:16,600
Speaker 1: at least that was the user experience. So look, I

1873
01:49:16,640 --> 01:49:18,439
Speaker 1: think you bring up a lot of important points. But

1874
01:49:18,479 --> 01:49:24,040
Speaker 1: I also think that we've that this is another thing

1875
01:49:24,120 --> 01:49:27,000
Speaker 1: that you have elected Republicans who were the biggest drivers

1876
01:49:27,040 --> 01:49:31,120
Speaker 1: of this, who are suddenly looking the other way. Even

1877
01:49:31,120 --> 01:49:36,679
Speaker 1: though Donald Trump is literally ignoring the rationale for why

1878
01:49:36,840 --> 01:49:39,719
Speaker 1: the TikTok ban was put in in the first place,

1879
01:49:40,960 --> 01:49:43,439
Speaker 1: which was control of that algorithm. We still don't know

1880
01:49:43,520 --> 01:49:46,200
Speaker 1: anything about it. Then Ellison's are not going to hear

1881
01:49:46,600 --> 01:49:49,439
Speaker 1: know anything about it there apparently is just going to

1882
01:49:49,479 --> 01:49:52,519
Speaker 1: be the data will be housed here. It's not about

1883
01:49:52,560 --> 01:49:56,280
Speaker 1: the data to me, it's about the propaganda and about

1884
01:49:56,320 --> 01:49:59,560
Speaker 1: that algorithm and how it's used to dial up or

1885
01:49:59,600 --> 01:50:03,000
Speaker 1: dial that what China cares about when it comes to

1886
01:50:03,080 --> 01:50:07,439
Speaker 1: public opinion. All right, I'll do one more question here.

1887
01:50:07,520 --> 01:50:09,120
Speaker 1: The next one comes from Warren. Hey, I haven't heard

1888
01:50:09,120 --> 01:50:12,000
Speaker 1: any status about infrastructure projects that were started before the

1889
01:50:12,040 --> 01:50:14,400
Speaker 1: current administration where they defunded as part of BBB or

1890
01:50:14,439 --> 01:50:17,240
Speaker 1: are they still in progress? Thank you well, Warren. Some

1891
01:50:17,400 --> 01:50:21,840
Speaker 1: of them have been sort of interrupted, you know, a

1892
01:50:21,920 --> 01:50:24,120
Speaker 1: lot of it the Biden administration try to move a

1893
01:50:24,120 --> 01:50:26,559
Speaker 1: whole bunch of money out the door before January twentieth,

1894
01:50:27,320 --> 01:50:30,400
Speaker 1: but some of it has been cut via the recisions,

1895
01:50:31,000 --> 01:50:34,120
Speaker 1: which is arguably a part that has triggered the real

1896
01:50:34,160 --> 01:50:37,400
Speaker 1: shutdown showdown between Democrats and Republicans here. So that's one.

1897
01:50:37,880 --> 01:50:42,320
Speaker 1: The second is you've had some of the money the

1898
01:50:42,360 --> 01:50:46,880
Speaker 1: Trump administration has enough authority over that they've essentially redirected

1899
01:50:46,960 --> 01:50:50,600
Speaker 1: it to projects that they would prefer as opposed to

1900
01:50:50,680 --> 01:50:53,519
Speaker 1: some of it is, for instance, going to be I

1901
01:50:53,560 --> 01:50:55,479
Speaker 1: think some of these projects pushed to building some of

1902
01:50:55,520 --> 01:50:57,840
Speaker 1: these data centers and things like that. And then some

1903
01:50:58,000 --> 01:51:03,400
Speaker 1: of it is is projects that the Trump administration is

1904
01:51:03,479 --> 01:51:06,680
Speaker 1: claiming are their ideas and they actually come from from

1905
01:51:06,760 --> 01:51:09,680
Speaker 1: what was passed by the Biden administration in the Bipartisan

1906
01:51:10,080 --> 01:51:12,920
Speaker 1: Infrastructure Act. But for the most part, a lot of

1907
01:51:12,960 --> 01:51:15,840
Speaker 1: particularly the energy projects in particular, this is what Russell

1908
01:51:15,880 --> 01:51:19,640
Speaker 1: Voight's been targeting. This is the goes back to my

1909
01:51:19,960 --> 01:51:22,840
Speaker 1: introduction in this in the in the full episode here today,

1910
01:51:23,360 --> 01:51:28,679
Speaker 1: the political targeting, you know, using what was legally passed

1911
01:51:29,240 --> 01:51:35,200
Speaker 1: legislation and essentially only trying to cut off Democratic funds.

1912
01:51:35,920 --> 01:51:40,040
Speaker 1: I guess right. And you know he pulled funding of

1913
01:51:40,120 --> 01:51:44,639
Speaker 1: certain clean energy projects from any state that was carried

1914
01:51:44,640 --> 01:51:48,240
Speaker 1: by Kamala Harris, sort of ignoring the fact that there

1915
01:51:48,280 --> 01:51:51,080
Speaker 1: were a lot of Republicans in those states. You know,

1916
01:51:51,240 --> 01:51:54,240
Speaker 1: more people. I think more people voted for Donald Trump

1917
01:51:54,280 --> 01:51:56,639
Speaker 1: in La County than I think in all of Idaho

1918
01:51:57,920 --> 01:52:00,720
Speaker 1: or certainly all of Wyoming and if other states like that.

1919
01:52:00,960 --> 01:52:05,600
Speaker 1: So it is not very smart how they do this,

1920
01:52:06,400 --> 01:52:09,240
Speaker 1: but it is all about getting the headline and owning

1921
01:52:09,360 --> 01:52:12,600
Speaker 1: the Libs and feeding the MAGA base. Who thinks this

1922
01:52:12,800 --> 01:52:17,000
Speaker 1: kind of weaponization of the democracy is somehow healthy and

1923
01:52:17,040 --> 01:52:19,439
Speaker 1: the right thing to do because they have convinced themselves

1924
01:52:19,479 --> 01:52:24,759
Speaker 1: that the Democrats have governed this way. And again, it's

1925
01:52:25,520 --> 01:52:29,599
Speaker 1: just because your feedback loops says they did this, doesn't

1926
01:52:29,640 --> 01:52:33,599
Speaker 1: mean the facts actually match your feedback loop. But either way,

1927
01:52:34,080 --> 01:52:37,479
Speaker 1: if what you think the Biden administration did was wrong,

1928
01:52:38,800 --> 01:52:41,519
Speaker 1: why are you cheerleading the same behavior on the right.

1929
01:52:56,720 --> 01:53:02,960
Speaker 1: I will pivot to my little rants of the weekend

1930
01:53:03,000 --> 01:53:05,360
Speaker 1: in college football. It was sort of a relaxed weekend

1931
01:53:05,479 --> 01:53:09,400
Speaker 1: for me personally or Miami Hurricanes were idle. But here's

1932
01:53:09,400 --> 01:53:12,400
Speaker 1: my favorite stat of the week when it comes to

1933
01:53:12,760 --> 01:53:15,880
Speaker 1: college football. Nine of the top seventeen teams in the

1934
01:53:15,920 --> 01:53:20,640
Speaker 1: preseason AP pole are unranked this week? How about that

1935
01:53:21,120 --> 01:53:25,439
Speaker 1: nine essentially the more than half of the top seventeen teams.

1936
01:53:26,800 --> 01:53:29,439
Speaker 1: So of course your first reaction may be, well, why

1937
01:53:29,479 --> 01:53:31,360
Speaker 1: do they bother with a preseason AP pole. Well, if

1938
01:53:31,360 --> 01:53:32,840
Speaker 1: AP didn't do it, somebody else would do it, and

1939
01:53:32,840 --> 01:53:35,680
Speaker 1: there'd always be somebody trying to do preseason polls. And

1940
01:53:35,760 --> 01:53:38,280
Speaker 1: if nobody was doing a shoot, I'd be doing it, right.

1941
01:53:38,320 --> 01:53:39,760
Speaker 1: We'd all want to do it. We all think we're

1942
01:53:40,520 --> 01:53:43,479
Speaker 1: we all think we're we follow this stuff enough. By

1943
01:53:43,479 --> 01:53:46,920
Speaker 1: the way, I have a correction from my Thursday podcast

1944
01:53:48,080 --> 01:53:50,599
Speaker 1: courtesy of my son I kept talking about. I said, hey,

1945
01:53:50,640 --> 01:53:53,080
Speaker 1: you should make a bet on Justin saying for the Heisman.

1946
01:53:53,320 --> 01:53:57,679
Speaker 1: And I'm guessing that you couldn't find a Justin saying

1947
01:53:57,760 --> 01:54:00,600
Speaker 1: to make a bet on for the Heisman because his

1948
01:54:00,680 --> 01:54:03,360
Speaker 1: name's Julian. And those of you that knew his name

1949
01:54:03,439 --> 01:54:05,200
Speaker 1: was Julian when I was saying it, we're probably going

1950
01:54:05,320 --> 01:54:07,600
Speaker 1: you dumb and that or how do you not know

1951
01:54:07,720 --> 01:54:11,280
Speaker 1: it's Julian not just In, etcetera, etcetera. Well, just so

1952
01:54:11,439 --> 01:54:13,439
Speaker 1: you know, my son was on the case, So thank

1953
01:54:13,479 --> 01:54:17,559
Speaker 1: you Harrison for that correction. I said I would give

1954
01:54:17,640 --> 01:54:20,479
Speaker 1: him credit for that correction. But here's where where we

1955
01:54:20,560 --> 01:54:25,760
Speaker 1: are in college football. When you have essentially fifty programs

1956
01:54:25,800 --> 01:54:28,720
Speaker 1: spending somewhere between fifteen and twenty five million dollars for

1957
01:54:28,840 --> 01:54:33,600
Speaker 1: roster construction, you are now professional league right among this

1958
01:54:33,800 --> 01:54:37,360
Speaker 1: top forty. So among those sort of seventeen, you know,

1959
01:54:37,400 --> 01:54:40,520
Speaker 1: among the top twenty five, pretty much everybody. Indiana spends

1960
01:54:40,600 --> 01:54:43,520
Speaker 1: money on roster construction. Okay, maybe they don't spend as

1961
01:54:43,600 --> 01:54:45,960
Speaker 1: much money yet as Oregon or Penn State, but they're

1962
01:54:46,000 --> 01:54:48,440
Speaker 1: spending a lot of money. I know, Miami spends a

1963
01:54:48,480 --> 01:54:50,520
Speaker 1: lot of money. Florida spends a lot of money, Clemson

1964
01:54:50,560 --> 01:54:52,800
Speaker 1: spends a lot of You get the drift, the rules

1965
01:54:52,840 --> 01:54:59,120
Speaker 1: of change, but in some ways, everybody's spending. And so

1966
01:54:59,280 --> 01:55:01,560
Speaker 1: the first couple of years, not everybody spent, and it

1967
01:55:01,680 --> 01:55:05,320
Speaker 1: allowed your TCUs to sort of come from nowhere and

1968
01:55:05,560 --> 01:55:08,600
Speaker 1: jump up right and bite everybody. And then they immediately

1969
01:55:08,680 --> 01:55:13,320
Speaker 1: disappeared because suddenly more people, more entities, started spending. And

1970
01:55:13,440 --> 01:55:16,760
Speaker 1: now now we're sort of almost already at at at

1971
01:55:16,800 --> 01:55:21,840
Speaker 1: a major power parody in spending. And so what that

1972
01:55:22,080 --> 01:55:26,840
Speaker 1: means is just like it's just like the NFL, which

1973
01:55:26,960 --> 01:55:30,360
Speaker 1: which is a year to year league, and you know

1974
01:55:30,520 --> 01:55:34,000
Speaker 1: everybody's spending about the same amount of money. It is

1975
01:55:34,120 --> 01:55:37,480
Speaker 1: really hard. Yes, you have two or three or four franchises,

1976
01:55:38,000 --> 01:55:42,480
Speaker 1: are you know, can can can be in the can

1977
01:55:42,600 --> 01:55:44,640
Speaker 1: be in the top tier of the league for four

1978
01:55:44,760 --> 01:55:47,920
Speaker 1: or five years at a time. But you're going to

1979
01:55:48,000 --> 01:55:51,440
Speaker 1: have teams go in and go out, and you're also

1980
01:55:51,520 --> 01:55:54,800
Speaker 1: going to have sort of chapters to your seasons. Like

1981
01:55:54,880 --> 01:55:56,720
Speaker 1: I also think it's a little early for us to

1982
01:55:57,440 --> 01:56:02,440
Speaker 1: assume we know that two loss teams now are terrible

1983
01:56:02,920 --> 01:56:05,560
Speaker 1: and that the undefeated teams now are going to be

1984
01:56:05,600 --> 01:56:08,600
Speaker 1: the ones that make the playoff, right, You now have

1985
01:56:08,680 --> 01:56:10,920
Speaker 1: a situation where you're gonna have ebbs and flows right

1986
01:56:11,000 --> 01:56:13,880
Speaker 1: and one and you can you know, teams may lose. Look,

1987
01:56:14,240 --> 01:56:16,240
Speaker 1: Florida State's lost three in a row. Penn States lost

1988
01:56:16,280 --> 01:56:19,760
Speaker 1: three in a row. I didn't see it coming. With

1989
01:56:19,840 --> 01:56:21,640
Speaker 1: Florida State, by the way, that has not been very

1990
01:56:21,680 --> 01:56:24,080
Speaker 1: popular in my household, as some of you may be aware.

1991
01:56:25,960 --> 01:56:29,720
Speaker 1: But they also certainly had some holes in their roster construction,

1992
01:56:29,840 --> 01:56:32,720
Speaker 1: and nobody should have expected them to go from a

1993
01:56:32,800 --> 01:56:35,800
Speaker 1: two and ten season to playoff contention right away. But

1994
01:56:35,840 --> 01:56:38,000
Speaker 1: they pull an early upset and so everybody sort of

1995
01:56:38,120 --> 01:56:41,800
Speaker 1: got over enthused, kind of like you know what happens

1996
01:56:41,840 --> 01:56:43,480
Speaker 1: to a two and oh team, You're like, oh wow,

1997
01:56:43,640 --> 01:56:45,400
Speaker 1: Like last year the New Orleans Saints for two and oh,

1998
01:56:46,320 --> 01:56:51,400
Speaker 1: they suddenly were terrible. Right, So, just like in the NFL,

1999
01:56:51,440 --> 01:56:53,760
Speaker 1: you don't know who's good early, right. Are the Chargers

2000
01:56:53,920 --> 01:56:56,680
Speaker 1: a good team or not? I'm not sure. They almost

2001
01:56:56,720 --> 01:56:59,160
Speaker 1: lost to the Dolphins today. They did lose last week,

2002
01:57:00,040 --> 01:57:01,800
Speaker 1: but they started off to and Ow and looked amazing.

2003
01:57:01,960 --> 01:57:04,680
Speaker 1: My Packers looked amazing the first two weeks. Then they

2004
01:57:04,720 --> 01:57:07,480
Speaker 1: lost a game to Cleveland ty Dallas. We'll find out

2005
01:57:07,520 --> 01:57:11,880
Speaker 1: how they do the rest of the season. So I

2006
01:57:12,000 --> 01:57:15,800
Speaker 1: do think that college football now is going to look

2007
01:57:15,880 --> 01:57:19,200
Speaker 1: more and more like the NFL. There's more parody. So

2008
01:57:19,320 --> 01:57:22,440
Speaker 1: you're going to have a year where a couple of

2009
01:57:22,520 --> 01:57:25,760
Speaker 1: years where in Indiana is contending and then they may,

2010
01:57:26,120 --> 01:57:28,560
Speaker 1: you know, fall short on their ability to find the

2011
01:57:28,680 --> 01:57:31,640
Speaker 1: right defensive lineman and offensive linemen they need to sort

2012
01:57:31,680 --> 01:57:35,480
Speaker 1: of keep in the top tier and so they may

2013
01:57:35,560 --> 01:57:37,840
Speaker 1: slip back. Right, That's what happened to Florida State, That's

2014
01:57:37,840 --> 01:57:40,400
Speaker 1: what's happened in to a Clemson. You know, I've got

2015
01:57:40,440 --> 01:57:42,840
Speaker 1: to sort of prepare for that with Miami. And I

2016
01:57:42,880 --> 01:57:45,200
Speaker 1: think this idea that you can expect your team in

2017
01:57:45,280 --> 01:57:48,880
Speaker 1: college football to win ten games or more five, six,

2018
01:57:49,000 --> 01:57:52,880
Speaker 1: seven years in a row is totally unrealistic because nobody

2019
01:57:52,960 --> 01:57:56,560
Speaker 1: has depth anymore. Right, Georgia and Alabama, Miami and it's heyday,

2020
01:57:57,240 --> 01:58:00,840
Speaker 1: they could stock bile talent. The greatest college football team

2021
01:58:00,880 --> 01:58:02,680
Speaker 1: of all time might be the two thousand and one

2022
01:58:02,720 --> 01:58:05,800
Speaker 1: Miami Hurricane National championship team. I say, might I accept

2023
01:58:06,280 --> 01:58:10,280
Speaker 1: the twenty nineteen LSU team as a contender for that spot? Right?

2024
01:58:11,320 --> 01:58:14,320
Speaker 1: Miami had a third string running back named Frank Gore

2025
01:58:14,400 --> 01:58:17,480
Speaker 1: on that team. Right. The first string running back was

2026
01:58:17,720 --> 01:58:20,720
Speaker 1: Clinton Portis, his backup was a guy named Willis mcgahey,

2027
01:58:21,560 --> 01:58:23,640
Speaker 1: and the third string one was Frank Gore, who's going

2028
01:58:23,680 --> 01:58:25,440
Speaker 1: to be in the NFL Hall of Fame. So the

2029
01:58:25,520 --> 01:58:28,760
Speaker 1: point is is that in this day and age of nil,

2030
01:58:29,200 --> 01:58:32,200
Speaker 1: Frank Gore doesn't stit at Miami for two years waiting

2031
01:58:32,280 --> 01:58:36,760
Speaker 1: his turn. He's probably in another roster. And I think

2032
01:58:36,840 --> 01:58:40,360
Speaker 1: that's what you're going to see with college football, and

2033
01:58:40,480 --> 01:58:45,320
Speaker 1: that's probably why we're seeing where because you cannot, you know,

2034
01:58:45,600 --> 01:58:48,760
Speaker 1: you don't have the depth and it's really now a

2035
01:58:48,840 --> 01:58:52,120
Speaker 1: war of attrition. The teams that can stay the healthiest

2036
01:58:52,240 --> 01:58:53,920
Speaker 1: or the ones that are going to be there, and

2037
01:58:54,040 --> 01:58:56,919
Speaker 1: the teams that sort of end up with some injuries

2038
01:58:57,080 --> 01:59:00,880
Speaker 1: or bad luck or the wrong You know, turns out

2039
01:59:01,040 --> 01:59:03,720
Speaker 1: somebody just wasn't as good of a quarterback as they

2040
01:59:03,760 --> 01:59:05,720
Speaker 1: thought they were going to be, or wasn't as good

2041
01:59:05,720 --> 01:59:07,360
Speaker 1: of a receiver as you thought they were going to be.

2042
01:59:09,000 --> 01:59:11,880
Speaker 1: There goes your season because there isn't a guy waiting

2043
01:59:11,960 --> 01:59:15,040
Speaker 1: in the wings that you could just tap into. And

2044
01:59:15,120 --> 01:59:17,959
Speaker 1: I think in some ways that's what we should be realizing,

2045
01:59:18,120 --> 01:59:21,640
Speaker 1: is that that college now that college football has been professionalized,

2046
01:59:22,080 --> 01:59:25,880
Speaker 1: it's going to resemble the quirks of the NFL. And

2047
01:59:26,000 --> 01:59:29,120
Speaker 1: in many ways I would argue that college football in

2048
01:59:29,200 --> 01:59:32,240
Speaker 1: the sort of the top forty programs looks a heck

2049
01:59:32,280 --> 01:59:34,960
Speaker 1: of a lot like the NFL, more like the NFL

2050
01:59:35,360 --> 01:59:38,920
Speaker 1: than it does what college football look like even six, seven,

2051
01:59:39,880 --> 01:59:45,720
Speaker 1: eight years ago. As for who's good, I think everybody

2052
01:59:45,760 --> 01:59:47,880
Speaker 1: agrees that Ohio State and Miami seemed to be good.

2053
01:59:48,160 --> 01:59:52,520
Speaker 1: They look good statistically, and they've looked good on the field.

2054
01:59:53,840 --> 01:59:55,720
Speaker 1: I could make an argument, if I really if I

2055
01:59:55,880 --> 01:59:57,800
Speaker 1: really want I don't want Miami to be ranked number one.

2056
01:59:58,280 --> 02:00:00,520
Speaker 1: I don't like the statistic that's out there already that

2057
02:00:00,560 --> 02:00:04,080
Speaker 1: says Miami is the best chance of finishing undefeated. Look,

2058
02:00:04,240 --> 02:00:09,160
Speaker 1: I am well aware despite what the SEC thinks, everybody's

2059
02:00:09,280 --> 02:00:12,120
Speaker 1: conference road games are hard. It's not just in the

2060
02:00:12,280 --> 02:00:16,800
Speaker 1: SEC conference. Road games mean more in every conference and

2061
02:00:16,920 --> 02:00:20,560
Speaker 1: they're very difficult. And Miami has only had to play

2062
02:00:20,640 --> 02:00:24,040
Speaker 1: one road game so far. So I am fully on

2063
02:00:24,840 --> 02:00:28,000
Speaker 1: upset alert for the rest of the season. If we

2064
02:00:28,040 --> 02:00:30,640
Speaker 1: can just get through the season with one loss, we'll

2065
02:00:30,680 --> 02:00:33,920
Speaker 1: be fine, thankfully. That's how the college football playoff system

2066
02:00:34,320 --> 02:00:36,400
Speaker 1: has now made it where you don't have to be

2067
02:00:36,640 --> 02:00:40,560
Speaker 1: perfect if you're not a member of the SEC like

2068
02:00:40,640 --> 02:00:42,400
Speaker 1: you were even when we were our top four, right,

2069
02:00:42,480 --> 02:00:45,560
Speaker 1: And sometimes perfection only doesn't work if you lose your

2070
02:00:45,600 --> 02:00:50,320
Speaker 1: starting quarterback, as Florida State found out. Because the ESPN

2071
02:00:50,360 --> 02:00:53,960
Speaker 1: Invitational is just that, it is an invitational, and even

2072
02:00:54,000 --> 02:00:57,760
Speaker 1: at twelve teams, it's still an invitational, and clearly what

2073
02:00:57,920 --> 02:01:01,480
Speaker 1: the matchups are, etc. Are going to have the networks

2074
02:01:01,520 --> 02:01:05,400
Speaker 1: are going to have to say on all that. But

2075
02:01:05,480 --> 02:01:08,920
Speaker 1: I think we know this much. We know Ohio State's good,

2076
02:01:08,960 --> 02:01:12,440
Speaker 1: we know Miami's good. Is Indiana in that top three

2077
02:01:12,520 --> 02:01:15,880
Speaker 1: or not? Right you start doing the you know, I

2078
02:01:15,920 --> 02:01:18,600
Speaker 1: think Indiana has looked impressive. I think they do. I

2079
02:01:18,720 --> 02:01:20,240
Speaker 1: think they're part of it. But if you want to

2080
02:01:20,320 --> 02:01:23,200
Speaker 1: question Indiana by saying, well, Oregon beat a Penn State

2081
02:01:23,240 --> 02:01:26,440
Speaker 1: team that turned out to be terrible, are they terrible?

2082
02:01:26,640 --> 02:01:30,120
Speaker 1: Are they just missing Tyler Warren? I do think that's

2083
02:01:30,200 --> 02:01:33,160
Speaker 1: something we have to realize, right, Tyler Warren was so

2084
02:01:33,480 --> 02:01:38,960
Speaker 1: good at Penn State, and without him there, it's it

2085
02:01:39,160 --> 02:01:41,960
Speaker 1: is set Drew allerback. Obviously, now he's injured, so he's

2086
02:01:42,040 --> 02:01:43,960
Speaker 1: totally set back for the season. But even before he

2087
02:01:43,960 --> 02:01:47,520
Speaker 1: got injured, he didn't look like the same quarterback. Tyler

2088
02:01:47,600 --> 02:01:53,080
Speaker 1: Warren made every made that team, made that offense incredibly

2089
02:01:53,120 --> 02:01:56,720
Speaker 1: hard to stop. He was a unicorn. How good is he?

2090
02:01:57,360 --> 02:02:00,520
Speaker 1: He's turned He's helped turn the Indianapolis Colts into a

2091
02:02:00,600 --> 02:02:03,640
Speaker 1: top tier NFL team this year. So clearly they miss

2092
02:02:03,760 --> 02:02:07,200
Speaker 1: him and miss him a lot. But I think those

2093
02:02:07,240 --> 02:02:08,840
Speaker 1: are the you know, you look at those three teams

2094
02:02:08,880 --> 02:02:11,760
Speaker 1: and then after that, Ole miss almost lost to Washington State,

2095
02:02:12,120 --> 02:02:14,840
Speaker 1: a group of five team. You know, I guess there's

2096
02:02:14,840 --> 02:02:17,800
Speaker 1: still you can say they're still technically member of the

2097
02:02:17,880 --> 02:02:20,760
Speaker 1: PAC two right now, but this is a team that

2098
02:02:20,840 --> 02:02:23,800
Speaker 1: has just been devastated by the portal. Right They've lost

2099
02:02:23,800 --> 02:02:26,320
Speaker 1: their last two starting quarterbacks, cam Ward to Miami, John

2100
02:02:26,360 --> 02:02:30,480
Speaker 1: Mitteer to Oklahoma, and they lost their coaching staff. They're there,

2101
02:02:30,520 --> 02:02:33,560
Speaker 1: they're great offensive coordinator to Oklahoma as well with Matier,

2102
02:02:34,480 --> 02:02:37,200
Speaker 1: and yet they went into Oxford and almost beat Ole Miss.

2103
02:02:38,920 --> 02:02:41,040
Speaker 1: I guess the good news is, if you're a long

2104
02:02:41,120 --> 02:02:44,840
Speaker 1: time Lane Kiffin watcher, you could argue the way I

2105
02:02:45,040 --> 02:02:49,280
Speaker 1: argue so far with Mario, which is, hey, Lane Kiffin

2106
02:02:49,280 --> 02:02:52,440
Speaker 1: blows that game two years ago. At least he didn't

2107
02:02:52,480 --> 02:02:56,040
Speaker 1: blow it this time. And that's kind of the way

2108
02:02:56,080 --> 02:02:57,560
Speaker 1: I look at it. I still think Old Miss is

2109
02:02:57,600 --> 02:02:59,600
Speaker 1: going to be there at the end, and I think

2110
02:02:59,640 --> 02:03:01,560
Speaker 1: Texa and m is the best team in the SEC.

2111
02:03:01,840 --> 02:03:04,160
Speaker 1: And I think they're better than Ole missed by a

2112
02:03:04,520 --> 02:03:07,040
Speaker 1: by a little bit more than than than the than

2113
02:03:07,080 --> 02:03:11,640
Speaker 1: The rankings indicate Alabama is certainly vulnerable. They're not. They're not.

2114
02:03:12,640 --> 02:03:17,000
Speaker 1: And and can I just say this, Georgia only won

2115
02:03:17,080 --> 02:03:19,720
Speaker 1: because of the officials in that Auburn Georgia game that

2116
02:03:19,880 --> 02:03:28,080
Speaker 1: was an atrociously officiated game. And you know, normally, normally

2117
02:03:28,360 --> 02:03:32,000
Speaker 1: most games where fans complain about any officiating, myself included,

2118
02:03:32,680 --> 02:03:36,280
Speaker 1: you know, you're only seeing the calls that go against you.

2119
02:03:36,520 --> 02:03:39,400
Speaker 1: You're not really processing the calls that go for you

2120
02:03:39,680 --> 02:03:41,960
Speaker 1: or the calls that go against the opponent. You don't

2121
02:03:42,160 --> 02:03:44,960
Speaker 1: really sort of have the same emotional And I do

2122
02:03:45,080 --> 02:03:47,680
Speaker 1: think it's sort of like, you know, those that judge

2123
02:03:47,720 --> 02:03:51,280
Speaker 1: officiating as fans are like partisans trying to claim they

2124
02:03:51,280 --> 02:03:55,080
Speaker 1: can identify media bias. Right, no partisan. I always laugh

2125
02:03:55,160 --> 02:03:58,360
Speaker 1: at people that accuse me of bias. It's always somebody

2126
02:03:58,440 --> 02:04:01,160
Speaker 1: from the from hard lefter hard right, And I'm like,

2127
02:04:01,320 --> 02:04:03,800
Speaker 1: how do you guys know what bias looks like? Right?

2128
02:04:03,920 --> 02:04:07,200
Speaker 1: You're upset if people aren't biased in your direction. That's

2129
02:04:07,240 --> 02:04:11,160
Speaker 1: what you view as political bias. Like those that clowns

2130
02:04:11,200 --> 02:04:14,360
Speaker 1: show that the Bozell family that has turned into a

2131
02:04:14,440 --> 02:04:19,000
Speaker 1: family grift some sort of grifting business, that that thing

2132
02:04:19,360 --> 02:04:21,840
Speaker 1: in the entire Bozell family makes money off of this

2133
02:04:22,640 --> 02:04:26,440
Speaker 1: off this group that claims there's somehow left wing bias

2134
02:04:26,560 --> 02:04:31,160
Speaker 1: hidden everywhere in America, and a whole bunch of right

2135
02:04:31,240 --> 02:04:34,440
Speaker 1: wingers like Bozell who thought Nixon didn't commit crimes. The

2136
02:04:34,760 --> 02:04:41,320
Speaker 1: old Man is somehow an arbiter of neutrality anyway. I'm

2137
02:04:41,360 --> 02:04:44,640
Speaker 1: not saying there's not biased in different places. I'm saying

2138
02:04:44,680 --> 02:04:48,680
Speaker 1: the Bozells don't have the qualifications to identify it. And

2139
02:04:48,760 --> 02:04:50,680
Speaker 1: it's that way with many fans. We don't have the

2140
02:04:50,760 --> 02:04:55,000
Speaker 1: qualifications to identify. I didn't really have a I didn't

2141
02:04:55,000 --> 02:04:58,040
Speaker 1: really have a rooting interest in Georgia Auburn. I've got

2142
02:04:58,040 --> 02:04:59,520
Speaker 1: a lot of in laws that are Auburn fans, so

2143
02:04:59,560 --> 02:05:01,680
Speaker 1: I want to see Auburn do well. But I hate

2144
02:05:01,760 --> 02:05:04,720
Speaker 1: Hugh Freeze. I don't like that guy, I'll admit. So

2145
02:05:04,840 --> 02:05:07,920
Speaker 1: I struggle with you know, with my with my in

2146
02:05:08,000 --> 02:05:10,640
Speaker 1: laws on that. I'm like, yeah, okay, but why Hugh Freeze.

2147
02:05:10,680 --> 02:05:14,120
Speaker 1: But you know what, ask any Auburn fan and they

2148
02:05:14,240 --> 02:05:19,000
Speaker 1: sort of like, yeah, you Freeze. They're not they know it, right,

2149
02:05:19,840 --> 02:05:23,480
Speaker 1: But those were just some terrible calls, and I, you know,

2150
02:05:24,480 --> 02:05:28,440
Speaker 1: Georgia gets I certainly hope the following isn't happening that

2151
02:05:28,560 --> 02:05:31,800
Speaker 1: somehow SEC officials, because this is not a great year

2152
02:05:31,840 --> 02:05:35,840
Speaker 1: for the SEC. It doesn't appear they have four or

2153
02:05:35,920 --> 02:05:38,640
Speaker 1: five great teams. Appeers, they might have one great team

2154
02:05:38,680 --> 02:05:41,120
Speaker 1: in Texas A and M and a couple of good teams.

2155
02:05:41,240 --> 02:05:43,320
Speaker 1: No different than the Big Ten, no different than the ACC,

2156
02:05:43,520 --> 02:05:45,680
Speaker 1: no different than the Big twelve. They just look like

2157
02:05:45,800 --> 02:05:49,480
Speaker 1: another conference this year. They don't look like the SEC. Right,

2158
02:05:51,720 --> 02:05:54,040
Speaker 1: But how badly does the SEC want to protect its

2159
02:05:54,040 --> 02:05:57,000
Speaker 1: big brands? Right our Alabama and Georgia are going to

2160
02:05:57,040 --> 02:05:59,000
Speaker 1: continue to get calls for the rest of the year

2161
02:06:00,360 --> 02:06:03,080
Speaker 1: like this. You know in is Texas and Oklahoma sort

2162
02:06:03,120 --> 02:06:05,520
Speaker 1: of in that same category where those teams will get

2163
02:06:05,600 --> 02:06:09,240
Speaker 1: calls more likely, right, Oklahoma got it against Auburn. Now Auburn,

2164
02:06:09,400 --> 02:06:12,800
Speaker 1: you know, didn't get a call against Georgia. I hesitate

2165
02:06:12,880 --> 02:06:15,480
Speaker 1: to see how the refereeing looks when Auburn has to

2166
02:06:15,480 --> 02:06:20,440
Speaker 1: play Alabama. But my goodness, the refs decided that game

2167
02:06:20,640 --> 02:06:23,200
Speaker 1: when they didn't award that touchdown to Jackson Arnold and

2168
02:06:23,240 --> 02:06:26,919
Speaker 1: they gave it a turnover that it flipped the game completely.

2169
02:06:27,000 --> 02:06:29,720
Speaker 1: Instead of seventeen to nothing at halftime, it was ten

2170
02:06:29,800 --> 02:06:36,240
Speaker 1: to three. And that was a massive, massive swing by

2171
02:06:36,320 --> 02:06:41,160
Speaker 1: what was again? I mean you break the plane period,

2172
02:06:42,160 --> 02:06:45,800
Speaker 1: right it is? And by the way, guys, in this

2173
02:06:46,000 --> 02:06:50,080
Speaker 1: day and age, can we please create some sort of

2174
02:06:50,240 --> 02:06:54,680
Speaker 1: new barrier right where and a chip in the ball

2175
02:06:55,600 --> 02:06:58,480
Speaker 1: so that the second it crosses that goal lines, you

2176
02:06:58,560 --> 02:07:01,680
Speaker 1: know right that you know what you see it. You

2177
02:07:01,800 --> 02:07:03,760
Speaker 1: can't tell me we don't have the technology to be

2178
02:07:03,800 --> 02:07:08,280
Speaker 1: able to do that rather than having all of these days.

2179
02:07:08,320 --> 02:07:10,680
Speaker 1: Because here's the other thing you have is that not

2180
02:07:10,840 --> 02:07:13,840
Speaker 1: every every NFL game has every camera angle that you

2181
02:07:13,880 --> 02:07:16,840
Speaker 1: would want for replay, but not every college game has that.

2182
02:07:17,200 --> 02:07:20,120
Speaker 1: The big time college games, right that are going to

2183
02:07:20,160 --> 02:07:23,560
Speaker 1: get covered in primetime by your Fox, your NBC, your NBC,

2184
02:07:23,680 --> 02:07:28,600
Speaker 1: and your Fox at CBS and ESPN, there's about six

2185
02:07:28,720 --> 02:07:32,560
Speaker 1: or seven games that'll have seventeen eighteen different cameras, But

2186
02:07:32,880 --> 02:07:35,160
Speaker 1: most of the other games don't have that many cameras

2187
02:07:35,240 --> 02:07:36,920
Speaker 1: because the networks are want to spend that kind of

2188
02:07:37,000 --> 02:07:41,080
Speaker 1: money for what might be a streaming game or what

2189
02:07:41,200 --> 02:07:43,960
Speaker 1: might be an ESPN two or CBO Sports Network or

2190
02:07:44,000 --> 02:07:48,600
Speaker 1: if this one peacock you get it right. So, like

2191
02:07:48,680 --> 02:07:50,960
Speaker 1: I was watching the Florida State pit game, they didn't

2192
02:07:51,080 --> 02:07:55,400
Speaker 1: have a camera angle right down the goal line, so

2193
02:07:55,480 --> 02:07:57,680
Speaker 1: they couldn't tell for sure. They did a review of

2194
02:07:57,760 --> 02:08:00,360
Speaker 1: a touchdown that I'm pretty sure was a touchdown, but

2195
02:08:00,480 --> 02:08:02,840
Speaker 1: they didn't it's because they didn't have a camera angle

2196
02:08:03,320 --> 02:08:06,600
Speaker 1: to dispute it, even if you wanted to dispute it.

2197
02:08:08,320 --> 02:08:12,040
Speaker 1: That seems like, look, if you're gonna do replay and

2198
02:08:12,200 --> 02:08:15,040
Speaker 1: we have the ability, my god, we can put GoPros everywhere.

2199
02:08:15,160 --> 02:08:19,760
Speaker 1: Now this is not a high cost the way it

2200
02:08:19,840 --> 02:08:22,640
Speaker 1: even was just five or six years ago. If you

2201
02:08:22,760 --> 02:08:24,600
Speaker 1: do care about the outcomes of these games and you

2202
02:08:24,680 --> 02:08:26,840
Speaker 1: want to make sure we always get it right, let's

2203
02:08:27,040 --> 02:08:29,600
Speaker 1: make sure we have all the equipment at all the

2204
02:08:29,720 --> 02:08:32,920
Speaker 1: games that are getting televised and that are going to

2205
02:08:33,120 --> 02:08:36,400
Speaker 1: use replay. You can't just sort of be glad that,

2206
02:08:36,720 --> 02:08:39,640
Speaker 1: oh well, hey, because believe it or not, I don't

2207
02:08:39,720 --> 02:08:42,280
Speaker 1: know if we would have had that camera angle that

2208
02:08:42,400 --> 02:08:46,800
Speaker 1: Georgia Auburn had which showed Arnold the ball crossing the

2209
02:08:46,800 --> 02:08:49,520
Speaker 1: goal line before it was punched out. I don't know

2210
02:08:49,520 --> 02:08:51,920
Speaker 1: if you would have had that at the UMass Can

2211
02:08:52,040 --> 02:08:55,920
Speaker 1: State game. Then again, maybe we didn't need any replay

2212
02:08:56,000 --> 02:08:59,040
Speaker 1: officials for the U mass Can Stay game. All right,

2213
02:08:59,160 --> 02:09:01,800
Speaker 1: there's my college foot all rant for the week. So

2214
02:09:01,920 --> 02:09:04,120
Speaker 1: there you go. Appreciate it. Appreciate you here. I hope

2215
02:09:04,160 --> 02:09:06,240
Speaker 1: you enjoy If you have a holiday today, I hope

2216
02:09:06,240 --> 02:09:09,080
Speaker 1: you're enjoying it. For those that are nervous about getting

2217
02:09:09,080 --> 02:09:13,040
Speaker 1: their paycheck due to the government shutdown. I'm sorry. I

2218
02:09:13,120 --> 02:09:15,920
Speaker 1: hope this podcast and the attention that we give to

2219
02:09:16,040 --> 02:09:19,520
Speaker 1: it serves as at least something that can be done

2220
02:09:19,560 --> 02:09:23,560
Speaker 1: there and maybe at worst or at best, my podcast

2221
02:09:23,680 --> 02:09:25,760
Speaker 1: is a distraction for the day. So with that, thank

2222
02:09:25,800 --> 02:09:28,360
Speaker 1: you for listening, thank you for liking and subscribing, thank

2223
02:09:28,400 --> 02:09:31,000
Speaker 1: you for all those five star reviews, And with that,

2224
02:09:31,200 --> 02:09:32,320
Speaker 1: I'll see in forty eight hours.