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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the

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Speaker 1: Bloomberg Balance of Power podcast. Catch us live weekdays at

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Speaker 1: noon Eastern on Applecarplay and then Roun Auto with the

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Speaker 1: Bloomberg Business App. Listen on demand wherever you get your podcasts,

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Speaker 1: or watch us live on YouTube.

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Speaker 2: Welcome to the Friday edition of Balance of Power. Welcome

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Speaker 2: to November, the first of November. I forgot to say

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Speaker 2: rabbit rabbit this morning. I just realized it. As we

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Speaker 2: join you live from World Headquarters in New York on

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Speaker 2: Bloomberg Radio, on the satellite radio and on YouTube search

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Speaker 2: Bloomberg Business News Live. If you want to come on in.

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Speaker 2: We've got the camera set up as always. It's great

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Speaker 2: to be back here as we settle in for the

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Speaker 2: long haul. We're not here by accident. We are moving

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Speaker 2: into World Headquarters for the duration of this election. We're

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Speaker 2: not going back home till they call it. Kayleie's on

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Speaker 2: her way. She'll be joining us with special coverage full

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Speaker 2: Smash Tuesday night right here Onloomberg Radio as you would expect.

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Speaker 2: That goes for YouTube as well. By the way, you

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Speaker 2: want the best free coverage in the world, keep both

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Speaker 2: of these options in mind. It's all about Wisconsin today.

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Speaker 2: Kamala Harris leaving Las Vegas to Wisconsin. She's in several

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Speaker 2: locations there. How about the Isley Brothers. That's pretty cool,

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Speaker 2: by the way, plan together, big concert tonight with many

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Speaker 2: more contemporary artists. But as Gwen Moore reminded us yesterday,

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Speaker 2: the Isisley Brothers are still together. Donald Trump and Warren

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Speaker 2: Michigan back to Milwaukee again. Yeah, it's all Wisconsin, It's

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Speaker 2: all Michigan. And we have new numbers out in the

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Speaker 2: swing states. Marist right now finds a two point race

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Speaker 2: in Pennsylvania, Harris up by two, Harris up by three

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Speaker 2: in Michigan, Harris up by two in Wisconsin. But I

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Speaker 2: can find polls that say that they're tied or that

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Speaker 2: Donald Trump is in charge. And Politico put this together

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Speaker 2: pretty well for us before we bring in Joe Wisenthal.

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Speaker 2: Just imagine you want to know how chaotic all of

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Speaker 2: this is. Five point thirty eight forecast Trump fifty three

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Speaker 2: times out of one hundred New York Times polling average,

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Speaker 2: Harris by one point. Nate Silver's model Trump fifty five

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Speaker 2: cent of the time s and P five hundred Harris,

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Speaker 2: polymarket Trump voter enthusiasm Harris by a whisker according to

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Speaker 2: Gallop right track, wrong track, Trump that favorability rating Harris.

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Speaker 2: No one has a clue, although Wall Street again seems

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Speaker 2: to think that this is Trump's race to lose. And

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Speaker 2: that's where we get into it with half of odd

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Speaker 2: Lot's the stalwart Joe Wisenthal. It's the first phone call

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Speaker 2: we make whenever we leave Washington and come to New York.

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Speaker 2: It's great to see you.

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Speaker 3: Thank you.

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Speaker 2: Time down to see me.

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Speaker 4: Great to see you, thank you.

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Speaker 2: I just want to get in your head for a

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Speaker 2: little bit. Yeah, because Wall Street thinks it has this

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Speaker 2: figured out, and I want to know why.

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Speaker 4: It's interesting about a week ago. I don't think it

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Speaker 4: was just Wall Street. About a week ago, everyone I

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Speaker 4: was talking to, They're like, yeah, I think Trump's can you.

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Speaker 2: Walk up one Monday morning?

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Speaker 4: Yeah, it is like about a week or so ago,

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Speaker 4: and like I realized that everyone around me just sort

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Speaker 4: of thought Trump was gonna win. And I, you know,

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Speaker 4: I have no opinion. I'm just a journalist yet it

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Speaker 4: but uh uh, but then you know it's like, oh,

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Speaker 4: this is really like locked in is convent Wisdom but

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Speaker 4: the thing was, like, there's no poll, there's no prediction market,

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Speaker 4: there's no model like the Nate Silver model that has

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Speaker 4: ever said Trump is a lock to win, even it's

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Speaker 4: sixty percent, or see even sixty five percent in the

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Speaker 4: prediction markets, which was around is high. It's not a lock.

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Speaker 4: I mean one in three odds come in all the time. Well,

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Speaker 4: I guess they come in about one in three. Like,

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Speaker 4: that's not a lock at all. And so it's been

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Speaker 4: interesting a to see this tightening in some of the

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Speaker 4: a little bit of movement in the prediction markets, and

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Speaker 4: then some of these Trump trade some of these stocks

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Speaker 4: like start to waver a little bit in the last week.

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Speaker 4: It feels like to some extent, people have woken up

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Speaker 4: to the fact, no, this looks like a very close

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Speaker 4: race based on almost any any metric you can see.

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Speaker 2: So, with all of that said, what are we setting

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Speaker 2: ourselves up for if this is going to take days?

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Speaker 3: We wake up?

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Speaker 2: Yesty, nobody knows this market primed for volatility.

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Speaker 4: I think there's two things. I think there's two things.

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Speaker 4: I mean, certainty people would probably just like to know,

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Speaker 4: And then I think that there's the question of like

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Speaker 4: how much will it be contested through the legal system,

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Speaker 4: and that creates its own uncertainty because it pushes back

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Speaker 4: the date. But I think then there's this other element

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Speaker 4: that it's not very good for the country to have

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Speaker 4: so much distrust about the results. Right, so even like

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Speaker 4: sitting let's say, okay to let's say we're to take

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Speaker 4: two weeks or something like that, because there's a lot

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Speaker 4: of close races and some ambiguity in some states. But

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Speaker 4: then we get some sort of resolution. Okay, that's uncertainty.

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Speaker 4: But then there's like, what does it mean that every

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Speaker 4: election now is presumed to be fought over courts and

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Speaker 4: technicalities rather than the votes. And then I think this

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Speaker 4: is where there's sort of like deeper anxiety comes in

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Speaker 4: about like you know, you think about treasuries, you think

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Speaker 4: about the US dollar, you think about what makes American

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Speaker 4: companies great. It's not great for American companies or enterprise

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Speaker 4: and economics if there's huge chunks of the population that

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Speaker 4: it feels like will simply not trust the results whichever

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Speaker 4: way it goes.

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Speaker 2: Is that why the VIX is creeping up on twenty

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Speaker 2: two here today or is that.

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Speaker 4: I think there's a lot I mean, look, I think

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Speaker 4: there's a lot going on. I think once again today's

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Speaker 4: jobs report. You know, we sort of in our collectively,

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Speaker 4: I think, blacked out the economy over the last month.

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Speaker 4: They're like, we're just not going to talk that much

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Speaker 4: about the economy. You know, you haven't heard much. There's

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Speaker 4: a FED meeting next week too. No one's really talking

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Speaker 4: about that. I mean, I guess at twenty five basis

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Speaker 4: points a lot. But like now, there's a fair amount

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Speaker 4: of economic ambiguity after today's job's report, and once again

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Speaker 4: a lot of uncertainty. And you then you see some

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Speaker 4: of this other stuff with rates rising in the UK

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Speaker 4: and rates rising in Australia hitting their highest levels since

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Speaker 4: last November. What's going on there? So the other thing

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Speaker 4: that's going to happen is we're going to have to

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Speaker 4: refocus and figure out what's happening in the US economic conditions,

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Speaker 4: which are ambiguous.

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Speaker 2: So let's talk about that jobs report, because I thought

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Speaker 2: I saw you tweeting about it earlier. And this clearly

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Speaker 2: this is not just noisy. This is an aberration. We

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Speaker 2: had hurricanes, we had strikes, that's right, and people are

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Speaker 2: wondering how to interpret this. Donald Trump, by the way,

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Speaker 2: is blaming the Harris policy.

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Speaker 4: Or as one does in an election.

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Speaker 1: Yes, exactly.

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Speaker 2: But the fact of the matter is the response rate,

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Speaker 2: as you point out to the Establishment survey, was just

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Speaker 2: over forty seven percent, way below last month sixty two percent,

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Speaker 2: lowest since January ninety one.

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Speaker 4: Oh, Mayor Sharif, who I have to give a big

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Speaker 4: shout out to. He has a little shop called Inflation Insights,

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Speaker 4: and he knows the data better than anyone else. And

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Speaker 4: I saw this in one of his email blasts that

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Speaker 4: he sent out right after the report. Again, so there's

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Speaker 4: so many levels of noise here because you had the hurricane.

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Speaker 4: Everyone knew the hurricane was going to have an effect,

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Speaker 4: which is why there was already a big step down

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Speaker 4: sequentially in the expectations. That's why economists at one hundred k.

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Speaker 4: So everyone knew that. Everyone knew the Boeing strike it happened.

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Speaker 4: I hadn't seen as much talk about that specifically as

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Speaker 4: a factor, but that was obviously something that people could

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Speaker 4: have anticipated. I would say two things. A. The number

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Speaker 4: was still weak. B The revisions were negative, and this

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Speaker 4: is really important because we've had negative revisions to prior

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Speaker 4: jobs report throughout the year. Yes, then last month we

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Speaker 4: got upward revisions, and that sort of I think was

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Speaker 4: taken as a signal, oh, maybe like this wasn't a blip,

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Speaker 4: there's like is actually sustained. To see those get revised

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Speaker 4: down again, I think creates a lot of maybe more

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Speaker 4: confidence that there's something there is a weakening. We also

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Speaker 4: got the Jolts report this week that showed an ongoing

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Speaker 4: decline in the quits rate, an ongoing decline in the

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Speaker 4: number of job openings. That reminds people that the job

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Speaker 4: market is weak. But yeah, to this point about the

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Speaker 4: non response rate sort of just another reason to scratch

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Speaker 4: our heads and say, we don't really know what's going

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Speaker 4: on right now.

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Speaker 2: But then you poked the bear. She was chalking it

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Speaker 2: all up to the hurricane and strikes. Yeah, is that

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Speaker 2: every economist to put out a number on the Bloomberg

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Speaker 2: save a survey, knew there were hurricanes and strike.

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Speaker 4: By the way, I ha. We have to give a

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Speaker 4: big shout out to our colleague Anna Wong, who she

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Speaker 4: had a negative ten k, which was far and away

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Speaker 4: the closest a.

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Speaker 2: Venue she would have won on the prices.

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Speaker 4: She would have definitely won on the prices, right, So

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Speaker 4: there's really impressive because some people had like, you know,

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Speaker 4: well over one hundred k. So there are some people

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Speaker 4: that were taking this. But again, the fact that we

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Speaker 4: knew about the hurricane, the fact that the Boeing strike

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Speaker 4: has been in the news, it's a reason to simply think, like, well,

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Speaker 4: you can't just dismiss this number, because these all get

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Speaker 4: baked in when the professional forecasters put in that forecast.

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Speaker 2: Right, it's a funny business.

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Speaker 1: Yeah.

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Speaker 2: Where do you think about this whole polymarket story or does.

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Speaker 1: It bore you?

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Speaker 5: No?

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Speaker 4: I mean I think it's really interesting because I think

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Speaker 4: a couple of things. One is that it seems like

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Speaker 4: now there's a lot, you know, it seems like now

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Speaker 4: that prediction markets are here to stay and they'll always

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Speaker 4: be a coverage. There'll always be an aspect in how

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Speaker 4: we analyze big events. Two, I don't think it's crazy

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Speaker 4: to think that like these numbers aren't as good in

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Speaker 4: the sense as like other markets that are out there,

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Speaker 4: like the US Treasury market. They really are thin markets.

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Speaker 4: Something I a friend of mine pointed out to me

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Speaker 4: yesterday is if you want to sell two million contracts

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Speaker 4: on Trump, Let's say you want to get your long

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Speaker 4: Trump and you want to get out of your position.

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Speaker 4: The poly market headline prices is around sixty one or

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Speaker 4: sixty two. To sell two million, drops the price to

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Speaker 4: below fifty seven. The order book is really thin on

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Speaker 4: these markets. Another thing to note is that if you

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Speaker 4: look at other if you look at the regulated US

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Speaker 4: prediction market Kelshi, which only got the green light to

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Speaker 4: do this a few couple weeks ago, their prices are

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Speaker 4: meaningfully different than the poly market prices. It remains a

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Speaker 4: bit of a mystery why traders can't arbitrage the gap

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Speaker 4: between the two. So I would say, a these markets

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Speaker 4: are here to stay. They're going to be part of

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Speaker 4: how we consume information going into elections for the time being,

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Speaker 4: for a long time. But the degree to which they're

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Speaker 4: really clear signals maybe just because they're young, because there

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Speaker 4: isn't a lot of money behind them, because they're regulatory

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Speaker 4: constraints and all kinds of I mean, it's not legal

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Speaker 4: for us to citizens do polymarket. We all know they

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Speaker 4: do it because they use VPNs to disguise where their

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Speaker 4: computers coming from. Well it's not legal.

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Speaker 6: And so like.

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Speaker 4: When these markets have sufficient depth so that we could say, okay,

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Speaker 4: there is real money here, we can really find a

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Speaker 4: correlation between say, what treasuries are doing, what bitcoin is doing,

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Speaker 4: what polymarket is saying. Like, we're not there yet.

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Speaker 2: Let me ask you this. I don't I have like

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Speaker 2: a minute left that I'll show your mind. But look

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Speaker 2: at the rules on some of these contracts. Yeah, yes, polymarket.

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Speaker 2: Resolution source for this market is the associated press Fox

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Speaker 2: NBC calling the race Robinhood will pay out January after

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Speaker 2: the results are certified by the Congress on January sixth.

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Speaker 2: Is part of this being driven by conspiracy thinking the

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Speaker 2: House will solve the election.

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Speaker 4: I'll say this people who are inte bedding and take

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Speaker 4: these markets really seriously. One of the things they're talking

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Speaker 4: about is the possibility that Kamala Harris wins. But like

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Speaker 4: let's say Wednesday, it's clear. I don't know if it

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Speaker 4: will be, but let's just say Wednesday, we're clear, but

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Speaker 4: we know. But there is a belief that there is

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Speaker 4: a contingent of Trump traders who wouldn't bid it, who

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Speaker 4: will buy his odds even at two or three percent. Yeah,

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Speaker 4: because they're convinced that some sort of data sex mocking

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Speaker 4: that will happen in the House. So it may not

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Speaker 4: even go to one hundred percent. Even after everyone's called,

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Speaker 4: you think of all the inputs, Yes, so many impacts.

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Speaker 2: Do you watch the election results like it's a game

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Speaker 2: Tuesday night? Or you just wake up the next day

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Speaker 2: and tell me what happened.

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Speaker 4: Of course I'm going to be on line.

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Speaker 2: I'll be why I got to be the first grateful

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Speaker 2: dead show a shirt in the history of Balance of

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Speaker 2: Power Paging Wiley Nickel, Joe Wisenthal on Bloomberg.

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Speaker 1: You're listening to the Bloomberg Balance of Power podcast kens

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Speaker 1: just live weekdays at noon Eastern on Applecarplay and enroun

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Speaker 1: Oo with the Bloomberg Business app. You can also listen

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Speaker 1: live on Amazon Alexa from our flagship New York station,

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Speaker 1: Just say Alexa play Bloomberg eleven thirty.

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Speaker 2: We made it to New York. We're live at World

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Speaker 2: Headquarters in Manhattan, here at the Mothership for the duration

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Speaker 2: the Big Show Tuesday Night special coverage, and of course

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Speaker 2: we're all you know, we're looking at this as election

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Speaker 2: day or Election week really, because nobody thinks this is

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Speaker 2: finished by Wednesday or Thursday, depending on who you ask.

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Speaker 2: I've had a couple of people come in here lately.

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Speaker 2: I don't know if they're just projecting aspirations that we

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Speaker 2: might get an earlier call than we did four years ago.

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Speaker 2: But of course, so much of the conversation in the

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Speaker 2: closing moments here, where we're four days out. Can you

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Speaker 2: believe it has just devolved around garbage. Literally, we're talking

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Speaker 2: about garbage and Donald Trump, as we'll get in to

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Speaker 2: a little bit later, gets a fourth day out of

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Speaker 2: this with a stenographer highlighting the changing of the way

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Speaker 2: they recorded this call with Joe Biden. Let's say we'll

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Speaker 2: do another garbage stop at some point here. But the

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Speaker 2: comments about this Cheney are resonating today as well. You

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Speaker 2: just can't even keep up with the news flow at

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Speaker 2: this stage. It'll be like this all weekend, early next

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Speaker 2: week into election day. As Donald Trump spent some time

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Speaker 2: with Tucker Carlson, it was a Halloween special and actually

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Speaker 2: quite scary. I suspect if you are Liz Cheney watching this,

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Speaker 2: some saw it as a threat to her life. Listen

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Speaker 2: to what Donald Trump said last night.

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Speaker 5: She's a radical warhawk. Let's put her with a rifle

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Speaker 5: standing there with nine barrel, shooting at her. Okay, let's

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Speaker 5: see how she feels about it, you know, when the

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Speaker 5: guns are trained on her face. You know, there are

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Speaker 5: warhawks when they're sitting in Washington in a nice building, saying, oh,

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Speaker 5: g you will, let's send Let's send ten thousand troops

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Speaker 5: right into the mouth of the enemy.

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Speaker 1: You have it.

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Speaker 2: There's a smattering of applause there. Let's see how she

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Speaker 2: feels about it when the guns are trained on her face,

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Speaker 2: he said. Timothy O'Brien is executive director of Bloomberg Opinion,

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Speaker 2: senior executive director, and he's the man who wrote the

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Speaker 2: book on Trump, and we wanted to spend some time

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Speaker 2: with him since we're back here in New York. Tim,

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Speaker 2: it's great to see you. Thanks for spending some time

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Speaker 2: with us here. Surely you were watching this. You can't

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Speaker 2: hide from it. This was at the Desert Diamond Arena

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Speaker 2: in Glendale, Arizona. How is that for a closing argument.

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Speaker 2: Some folks are, in fact suggesting that this might have

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Speaker 2: put Liz Cheney in danger, that it was a threat

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Speaker 2: on her life. Of course, the Trump campaign is not

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Speaker 2: going to see it like that, and we've already heard

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Speaker 2: from them. But how did you interpret that remark?

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Speaker 7: Well, I think the Trump campaign's not going to see

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Speaker 7: it like that because they want to, as every campaign does,

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Speaker 7: cast their candidate in the best light. The reality of

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Speaker 7: it is he made a statement about Liz Cheney being soft.

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Speaker 3: On war and that she needed to know what.

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Speaker 7: The experience of war was like in order to be

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Speaker 7: more sensitive to it. However, the way he said it

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Speaker 7: invoked violence against her, pure and simple. There's been a

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Speaker 7: debate about the specifics of what that violence might have

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Speaker 7: been based on what he said, But the reality is

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Speaker 7: he's a former president of the United States. He is

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Speaker 7: on a stage and he is talking about violence against

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Speaker 7: one of his most high profile critics, a member of

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Speaker 7: the Republican Party, and he's putting her in harm's way,

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Speaker 7: pure and simple.

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Speaker 3: And he's done this for years.

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Speaker 7: He's done at his rallies, not just about Liz Cheney,

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Speaker 7: but about people he regards as his critics or his opponents.

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Speaker 7: And it's not an accident. He revels in violence. He's

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Speaker 7: called for it in the past. So it's irresponsible and

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Speaker 7: it's uncivilized. And I don't think that that's an ideological

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Speaker 7: or partisan viewpoint. It's just about I think civility and

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Speaker 7: a call to be better in the way that we

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Speaker 7: speak about our differences and not have it devolve into violence.

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Speaker 3: But that's not who he is.

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Speaker 2: Liz Cheney responded, you might have seen, quote, this is

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Speaker 2: how dictates destroy free nations. They threaten those who speak

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Speaker 2: against them with death unquote. She retweeted the video of

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Speaker 2: him delivering those words sitting down with Tucker Carlson. So

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Speaker 2: bring me.

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Speaker 7: I know you can't, can I just wanted a quick thought, Joe, Yes,

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Speaker 7: you know recently, you know his His chief of staff

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Speaker 7: John Kelly, said he believed that Trump had fascist tendencies.

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Speaker 7: Another general, General Millet, has criticized Trump. Millie, a senior

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Speaker 7: member the military, said he felt physically threatened in the

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Speaker 7: wake of speaking out publicly about Trump, and he went

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Speaker 7: home and he putting, you know, bulletproof.

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Speaker 3: Windows in his home.

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Speaker 7: So these aren't just light fantastical fears that these people

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Speaker 7: have once they get in the in the radar.

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Speaker 2: Can you imagine the threats that Liz Janey is dealing

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Speaker 2: with that we never hear about. But I guess my

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Speaker 2: question for you is what's Donald Trump's motivation here? This

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Speaker 2: is how it goes in the final throes. Now, this

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Speaker 2: is the third cycle we've seen, and then that last

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Speaker 2: week while things are said to your point, not all

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Speaker 2: of them are new, but you get this concentrated version

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Speaker 2: and he's clearly flooding the zone. And we're talking about

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Speaker 2: him all day every day. Is that the point here

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Speaker 2: or he just can't help but to say some of

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Speaker 2: these things.

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Speaker 3: I mean, I just think it's who he is, you know.

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Speaker 7: I think one of Donald Trump's one of the reasons

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Speaker 7: his base finds him attractive and feels an allegiance to

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Speaker 7: uman is that he's authentic and that he does speak

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Speaker 7: I think in a very visceral way about what he

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Speaker 7: cares about. And what we found out at Madison Square

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Speaker 7: Garden is he cares about race and misogyny and hostility,

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Speaker 7: and what you found out last night is violence.

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Speaker 3: And I think that.

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Speaker 7: He's just in the home stretch and he's speaking around

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Speaker 7: the themes that he has used for a long time.

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Speaker 7: I think they're obviously becoming part of our public debates

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Speaker 7: because we're close.

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Speaker 3: To election day.

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Speaker 7: But it isn't This is obviously not standard political fair

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Speaker 7: and I think that people are thinking about this and

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Speaker 7: what to do about it as voters should talk about

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Speaker 7: the public dialogues they want to have around the economy

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Speaker 7: and policy and foreign affairs and the things that we

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Speaker 7: should care about as a community as opposed to I

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Speaker 7: think some of these cultural and personal issues.

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Speaker 3: That divide us.

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Speaker 2: In the closing hours of this campaign, a Trump supporter,

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Speaker 2: a real Trump supporter who actually knows the policy proposals

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Speaker 2: and is familiar with his first term say the same thing,

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Speaker 2: no new Wars, good economy, I don't care about the rest.

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Speaker 2: Those are my priorities, which is a pretty strong message

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Speaker 2: in the closing hours of this campaign. How does Kamala

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Speaker 2: Harris answer it?

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Speaker 7: Well, she's been I mean, I think she's been trying

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Speaker 7: to lay out policy issues she spoke.

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Speaker 2: Has she effectively answered that, I think she has. I

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Speaker 2: thought this no New Wars thing that resonates with a

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Speaker 2: lot of Trump supporters.

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Speaker 3: Well, I think that.

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Speaker 7: I think that the United States has citiside with amy

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Speaker 7: when they what we mean when we say no new Wars.

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Speaker 7: I think people feel we have an obligation to Israel.

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Speaker 7: People feel that we have an out. Some people feel

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Speaker 7: an allegation to Ukraine. Some people feel we have an

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Speaker 7: obligation to Taiwan.

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Speaker 2: And he would tell you none of those would have

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Speaker 2: happened if he.

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Speaker 7: Was president, right, But in fact, you know, there were

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Speaker 7: multiple aggressions while he was president. And the issue here

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Speaker 7: is what's our in the world in terms of securing

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Speaker 7: global security so we can have a strong economy in

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Speaker 7: a safe world. Those are I think also nonpartisan issues

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Speaker 7: that we should think long and heart about.

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Speaker 2: So give me Timothy O'Brien's election night. I want to

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Speaker 2: know what you're watching, what you care about, how you

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Speaker 2: take it in.

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Speaker 7: Well, like everybody else, Joe, I'm watching the swing states.

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Speaker 3: You know there is tight as ever.

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Speaker 2: Are you of the mind like so many people, this

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Speaker 2: call happens earlier than I'm not.

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Speaker 6: Four years ago?

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Speaker 3: No, I'm not. You're in for the long home.

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Speaker 7: Yeah, I mean, remember like four years ago we were

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Speaker 7: waiting on Pennsylvania till Friday or Saturday. And I don't

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Speaker 7: know if it'll be Pennsylvania this time.

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Speaker 3: It could be Michigan. You know, it might be Georgia

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Speaker 3: or North Carolina. Those those three seem to me like

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Speaker 3: the iffier ones.

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Speaker 7: And it's going to come down to you know, I

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Speaker 7: think probably what happens in half of the swing states, Yes,

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Speaker 7: in terms of who gets into the White.

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Speaker 2: House, how concerned. Are you about reports of poll watchers

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Speaker 2: intimidating people, the many lawsuits that we see continued to

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Speaker 2: be filed in real time, challenging results in pennsylvani You

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Speaker 2: again and in other states. What's this going to feel

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Speaker 2: like my next Wednesday or Thursday?

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Speaker 7: Well, I think we're I think people are already drained

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Speaker 7: by it now. I think this will just be another

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Speaker 7: turn of the screw, But we we have to go

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Speaker 7: through this. I think voting is important again for nonpartisan

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Speaker 7: and non ideological reasons, and we should think of polling

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Speaker 7: places as safe haven's, not places where you're worried about

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Speaker 7: getting beaten up. Yeah, and uh, and you know, our

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Speaker 7: elections are not fixed in the you know, in the

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Speaker 7: in the troubled elections.

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Speaker 3: Around the entire planet.

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Speaker 7: The United States is a pretty good job of having

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Speaker 7: clean and fair elections.

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Speaker 2: There's a lot of stop to steal tweet and going

439
00:20:34,760 --> 00:20:38,360
Speaker 2: on out there already. Marjorie Taylor Green. Donald Trump himself

440
00:20:38,440 --> 00:20:42,119
Speaker 2: talking about massive, widespread fraud, and I was talking about

441
00:20:42,119 --> 00:20:44,919
Speaker 2: this yesterday. He talks about the weave. We call this

442
00:20:45,040 --> 00:20:48,520
Speaker 2: the blur. Every day five headlines like this and people

443
00:20:48,560 --> 00:20:51,440
Speaker 2: start to just kind of step back and say, yeah,

444
00:20:51,440 --> 00:20:52,359
Speaker 2: this whole thing's broken.

445
00:20:52,400 --> 00:20:53,120
Speaker 6: It's crazy.

446
00:20:53,160 --> 00:20:56,000
Speaker 7: I can't trust anything right. And it's not just about

447
00:20:56,080 --> 00:20:59,480
Speaker 7: vot effect. It's about war or immigration or the economy,

448
00:20:59,640 --> 00:21:03,440
Speaker 7: you know, you name the issue, and it is designed

449
00:21:03,480 --> 00:21:05,719
Speaker 7: to keep us from focusing on the facts and from

450
00:21:05,800 --> 00:21:08,280
Speaker 7: having a healthy conversation about how to think about the facts.

451
00:21:08,320 --> 00:21:12,800
Speaker 2: Sure, so Wednesday, Thursday, more lawsuits are filed and so forth.

452
00:21:14,400 --> 00:21:17,200
Speaker 2: Is this the nine week slog that Bruce Melman was

453
00:21:17,200 --> 00:21:19,440
Speaker 2: writing about, where we really actually don't have this settled

454
00:21:19,520 --> 00:21:21,320
Speaker 2: until January sixth on certification.

455
00:21:21,440 --> 00:21:24,040
Speaker 7: I think it depends on the margin of victory, okay,

456
00:21:24,080 --> 00:21:26,480
Speaker 7: And then I think it depends on how the alacrity

457
00:21:26,560 --> 00:21:29,840
Speaker 7: with the judges who preside over these in courtrooms across

458
00:21:29,840 --> 00:21:32,639
Speaker 7: the United States respond. They've already been pretty aggressive in

459
00:21:32,680 --> 00:21:35,879
Speaker 7: this cycle about batting back the more ridiculous ones in

460
00:21:35,920 --> 00:21:38,360
Speaker 7: a way they weren't in twenty twenty, and the judges

461
00:21:38,400 --> 00:21:39,639
Speaker 7: comported themselves.

462
00:21:39,320 --> 00:21:40,720
Speaker 3: Well, I think in twenty twenty.

463
00:21:40,720 --> 00:21:43,159
Speaker 7: But you know, that's sort of a nice edge to

464
00:21:43,240 --> 00:21:45,120
Speaker 7: keep an election result balanced upon.

465
00:21:45,359 --> 00:21:47,920
Speaker 2: Does he declare victory at ten o'clock at night on Tuesday?

466
00:21:47,960 --> 00:21:52,160
Speaker 7: No matter what, Donald Trump never loses. Joe his gravestone

467
00:21:52,200 --> 00:21:56,320
Speaker 7: will say I won, so yes, yeah, I think he'll

468
00:21:56,359 --> 00:21:58,119
Speaker 7: declare victory for the next So we've.

469
00:21:58,000 --> 00:22:00,520
Speaker 2: Been through this a couple of times already. So does

470
00:22:00,560 --> 00:22:01,480
Speaker 2: it land differently?

471
00:22:03,119 --> 00:22:04,679
Speaker 7: That's a great question, I think, you know, because at

472
00:22:04,720 --> 00:22:06,800
Speaker 7: the end of the day, voters are the thing that

473
00:22:06,840 --> 00:22:10,359
Speaker 7: we'll preserve and say us, not journalists, not lawyers, not

474
00:22:10,400 --> 00:22:12,959
Speaker 7: the federal government, but voters. And I think voters are

475
00:22:12,960 --> 00:22:15,160
Speaker 7: the ones who have to keep you know, their eyes

476
00:22:15,200 --> 00:22:16,080
Speaker 7: on the prize and all of this.

477
00:22:16,240 --> 00:22:18,280
Speaker 2: Well, I suspect that that is something that a lot

478
00:22:18,320 --> 00:22:20,919
Speaker 2: of news organizations are prepared for. And I wonder what

479
00:22:20,920 --> 00:22:23,160
Speaker 2: this is going to mean later this hour or later

480
00:22:23,200 --> 00:22:24,760
Speaker 2: in the program, I should say, we're going to talk

481
00:22:24,760 --> 00:22:28,159
Speaker 2: to Julie Pace from the Associated Press, who's tasked with

482
00:22:28,320 --> 00:22:32,600
Speaker 2: making the call. It's a different equation against the backdrop

483
00:22:32,640 --> 00:22:34,040
Speaker 2: of all of this noise, isn't it. Do you think

484
00:22:34,080 --> 00:22:37,520
Speaker 2: the Associated Press is compelled to maybe slow the role

485
00:22:37,880 --> 00:22:39,400
Speaker 2: a little bit more in twenty twenty four.

486
00:22:39,800 --> 00:22:40,879
Speaker 3: They've been around the block.

487
00:22:41,000 --> 00:22:43,640
Speaker 7: I think they've always been an extremely valuable and judicious

488
00:22:43,680 --> 00:22:46,200
Speaker 7: news organization for that reason, and I think they'll call

489
00:22:46,240 --> 00:22:46,959
Speaker 7: it as they see it.

490
00:22:47,359 --> 00:22:49,919
Speaker 2: Well, there are a lot of inputs this time. You know,

491
00:22:49,920 --> 00:22:51,360
Speaker 2: when you're looking at a district and you know there's

492
00:22:51,359 --> 00:22:53,600
Speaker 2: a potential for a recount or a multiple lawsuits, do

493
00:22:53,640 --> 00:22:58,680
Speaker 2: you factor that in or should this be truly a numbers.

494
00:22:58,480 --> 00:22:59,960
Speaker 3: I think they have to call it based on the numbers.

495
00:23:00,119 --> 00:23:00,400
Speaker 3: I see.

496
00:23:00,520 --> 00:23:04,000
Speaker 7: Yeah, and if there's if those numbers are contested later, fine,

497
00:23:04,520 --> 00:23:06,280
Speaker 7: But but they have to call the numbers. Is the

498
00:23:06,440 --> 00:23:09,560
Speaker 7: you know, the pulling data shows.

499
00:23:09,480 --> 00:23:11,680
Speaker 2: It's the Associated Press will be the gold standard. We'll

500
00:23:11,680 --> 00:23:13,760
Speaker 2: be watching a lot of other networks as well. But

501
00:23:13,800 --> 00:23:17,280
Speaker 2: when you hear us talking about these races next Tuesday, Wednesday, Thursday,

502
00:23:17,800 --> 00:23:21,080
Speaker 2: uh and beyond that will be the number that we're

503
00:23:21,080 --> 00:23:23,720
Speaker 2: looking for. Do we get a call on the Senate earlier?

504
00:23:24,240 --> 00:23:24,920
Speaker 2: We'll have a sense?

505
00:23:25,119 --> 00:23:27,000
Speaker 3: I think so. I think, you know, the Senate.

506
00:23:27,160 --> 00:23:29,560
Speaker 7: I think the republic the Republicans are in a very

507
00:23:29,600 --> 00:23:33,400
Speaker 7: advantageous place with Visa VI the Senate and very competitive

508
00:23:33,440 --> 00:23:36,679
Speaker 7: in the House. And I don't think the kind of

509
00:23:37,080 --> 00:23:41,359
Speaker 7: you know, propaganda swhirls around congressional races that swirl around

510
00:23:41,400 --> 00:23:42,280
Speaker 7: the presidential race.

511
00:23:42,400 --> 00:23:44,040
Speaker 2: I'll get a bunch of tweets for this, But Philip

512
00:23:44,040 --> 00:23:45,720
Speaker 2: Bump is writing we's step a minute left in the

513
00:23:45,760 --> 00:23:49,080
Speaker 2: Washington Post about how Donald Trump talks about groceries and

514
00:23:49,119 --> 00:23:51,640
Speaker 2: he constantly goes back to the b lt Bacon, let

515
00:23:51,680 --> 00:23:54,359
Speaker 2: us Tomato in his stump speech, right, because he's maybe

516
00:23:54,400 --> 00:23:56,680
Speaker 2: never gone grocery shopping before. Is that true?

517
00:23:56,840 --> 00:23:59,880
Speaker 7: Yes, I mean maybe at the beach we went into

518
00:23:59,880 --> 00:24:02,680
Speaker 7: a package store to get, you know, a sandwich.

519
00:24:02,720 --> 00:24:03,280
Speaker 3: But no, you.

520
00:24:03,240 --> 00:24:06,160
Speaker 2: Remember George Bush with the gallon of milk, with the scanner.

521
00:24:06,280 --> 00:24:08,440
Speaker 3: That's the scanner. One could lose an election.

522
00:24:08,119 --> 00:24:08,840
Speaker 2: Over that back then.

523
00:24:09,040 --> 00:24:11,680
Speaker 7: I mean, he definitely has a shop for his only groceries.

524
00:24:11,680 --> 00:24:15,879
Speaker 7: He's had you know, maids and cooks and staff for

525
00:24:15,960 --> 00:24:17,200
Speaker 7: his entire existence.

526
00:24:17,359 --> 00:24:20,360
Speaker 2: Bacon let us Tomato. It's great to see you. I'm

527
00:24:20,359 --> 00:24:22,800
Speaker 2: here all week. Let's do it again, Timothy O'Brien find

528
00:24:22,840 --> 00:24:26,760
Speaker 2: him on the terminal of course, OPI n go Bloomberg Opinion.

529
00:24:30,480 --> 00:24:34,000
Speaker 1: You're listening to the Bloomberg Balance of Power podcast. Catch

530
00:24:34,080 --> 00:24:36,880
Speaker 1: us live weekdays at noon Eastern on Apple car Play

531
00:24:36,920 --> 00:24:39,760
Speaker 1: and then Roudoto with the Bloomberg Business app. Listen on

532
00:24:39,800 --> 00:24:43,000
Speaker 1: demand wherever you get your podcasts, or watch us live

533
00:24:43,119 --> 00:24:48,840
Speaker 1: on YouTube.

534
00:24:46,440 --> 00:24:49,080
Speaker 2: Today as we work our way into the final weekend

535
00:24:49,520 --> 00:24:53,800
Speaker 2: before this election cycle. Promising special coverage full smash here

536
00:24:53,840 --> 00:24:58,880
Speaker 2: on Bloomberg TV and Radio Tuesday night that'll start at

537
00:24:58,880 --> 00:25:01,520
Speaker 2: seven pm East. In time, We're going to have a

538
00:25:01,520 --> 00:25:04,480
Speaker 2: lot more to talk about with regard to this election

539
00:25:04,600 --> 00:25:07,000
Speaker 2: and the final throes of this cycle, with some pretty

540
00:25:07,000 --> 00:25:09,840
Speaker 2: wild rhetoric that we were hearing just last night on

541
00:25:09,960 --> 00:25:13,560
Speaker 2: Halloween from Donald Trump. We're following the Harris campaign. They're

542
00:25:13,600 --> 00:25:15,880
Speaker 2: both back in the swing states in the Midwest. Today

543
00:25:15,880 --> 00:25:18,399
Speaker 2: it's all about Wisconsin for some reason, and we do

544
00:25:18,440 --> 00:25:21,159
Speaker 2: have some new numbers from the states as well. On

545
00:25:21,200 --> 00:25:23,399
Speaker 2: what is of course, also at Jobs Day, Amy Morris

546
00:25:23,480 --> 00:25:25,119
Speaker 2: is looking at the markets for us through the guys

547
00:25:25,160 --> 00:25:27,920
Speaker 2: of today's jobs report, all the data out now, this

548
00:25:27,960 --> 00:25:30,199
Speaker 2: is all we're going to get between now and the

549
00:25:30,240 --> 00:25:33,920
Speaker 2: election and the Fed meeting. Of course, payrolls increase by

550
00:25:34,040 --> 00:25:35,440
Speaker 2: just twelve thousand.

551
00:25:35,560 --> 00:25:36,040
Speaker 1: What is this?

552
00:25:36,160 --> 00:25:39,520
Speaker 2: You say, not what we expected, that's what. But if

553
00:25:39,560 --> 00:25:41,760
Speaker 2: you look at the markets today, it certainly doesn't seem

554
00:25:41,800 --> 00:25:43,520
Speaker 2: to be a problem, and everyone seems to know what

555
00:25:43,560 --> 00:25:46,800
Speaker 2: went on here. The impact of the hurricanes, the impact

556
00:25:46,800 --> 00:25:49,520
Speaker 2: of the strikes, blew the number out here, and it's

557
00:25:49,560 --> 00:25:52,920
Speaker 2: basically an aberration. Hiring advancing at the slowest pay since

558
00:25:52,960 --> 00:25:55,359
Speaker 2: twenty twenty. As I read from Molly Smith, who's going

559
00:25:55,400 --> 00:25:57,640
Speaker 2: to join us after we talk to the chairman. He's

560
00:25:57,640 --> 00:25:59,160
Speaker 2: with us from the North Lawn at the White House

561
00:25:59,240 --> 00:26:01,399
Speaker 2: right now, Jared Burr and steamchair of the White House

562
00:26:01,640 --> 00:26:04,520
Speaker 2: Council of Economic Advisors. Mister Chairman, it's great to see you.

563
00:26:04,920 --> 00:26:08,160
Speaker 2: Welcome as always to Bloomberg TV and Radio. I'm wondering

564
00:26:08,200 --> 00:26:10,159
Speaker 2: what was in your head? What would this report have

565
00:26:10,240 --> 00:26:12,480
Speaker 2: looked like if it were not for the storms.

566
00:26:14,080 --> 00:26:16,199
Speaker 8: Well, the storms and the strikes. I mean, one of

567
00:26:16,200 --> 00:26:18,800
Speaker 8: the things we went into this report knowing, because the

568
00:26:18,840 --> 00:26:22,040
Speaker 8: Bureau of Labor Statistics told us, was that the strike

569
00:26:22,200 --> 00:26:26,239
Speaker 8: was going to subtract more than forty thousand workers, and

570
00:26:26,280 --> 00:26:30,440
Speaker 8: we saw more than that in the manufacturing of transportation

571
00:26:30,520 --> 00:26:33,679
Speaker 8: equipment that was down about forty four K. Now we

572
00:26:33,800 --> 00:26:36,439
Speaker 8: know that there's upstream workers. I think some of the

573
00:26:36,480 --> 00:26:41,159
Speaker 8: decline in temp workers, upstream workers in manufacturing from probably

574
00:26:41,160 --> 00:26:44,560
Speaker 8: Boeing supply chains. I would probably assign another ten k

575
00:26:44,760 --> 00:26:48,360
Speaker 8: negative on that. And then you get over to the hurricanes.

576
00:26:48,840 --> 00:26:52,800
Speaker 8: That's much more uncertain, much much harder to estimate. But

577
00:26:52,840 --> 00:26:55,720
Speaker 8: the Bureau itself which they don't often do. The Bureau

578
00:26:55,760 --> 00:26:59,440
Speaker 8: itself said that the hurricanes very likely played a role here.

579
00:26:59,560 --> 00:27:01,960
Speaker 8: So the way set it up is exactly right. The

580
00:27:02,080 --> 00:27:05,720
Speaker 8: underlying strength of the American economy, the American labor force,

581
00:27:06,359 --> 00:27:09,040
Speaker 8: is ongoing. We have a full spate of reports from

582
00:27:09,080 --> 00:27:11,480
Speaker 8: this week that show that to be the case. And

583
00:27:11,560 --> 00:27:14,280
Speaker 8: if you look at the unemployment rate, which is far

584
00:27:14,359 --> 00:27:17,360
Speaker 8: less affected by strikes and hurricanes, that held a four

585
00:27:17,400 --> 00:27:20,840
Speaker 8: point one percent and historically low rate. So you have

586
00:27:20,880 --> 00:27:22,960
Speaker 8: to block out the noise, try to find the signal,

587
00:27:23,200 --> 00:27:25,480
Speaker 8: and if you do so, you see the US economy

588
00:27:25,480 --> 00:27:28,480
Speaker 8: continues to move ahead with momentum.

589
00:27:28,520 --> 00:27:32,040
Speaker 2: The response rate to the Establishment Survey Jared was just

590
00:27:32,160 --> 00:27:36,240
Speaker 2: forty seven point four percent, the lowest since January of

591
00:27:36,320 --> 00:27:39,560
Speaker 2: nineteen ninety one, well below last month sixty two percent.

592
00:27:40,240 --> 00:27:41,439
Speaker 2: What do you make of that number?

593
00:27:42,800 --> 00:27:45,760
Speaker 8: There were four hundred and sixty thousand people, according to

594
00:27:45,760 --> 00:27:48,520
Speaker 8: the Bureau this morning, that couldn't get to work because

595
00:27:48,520 --> 00:27:51,840
Speaker 8: of the weather. Not every one of those persons got

596
00:27:51,840 --> 00:27:54,919
Speaker 8: taken off payrolls. If they were paid over the relevant period,

597
00:27:54,920 --> 00:27:59,320
Speaker 8: they'd be counted, But obviously many of them were taken

598
00:27:59,600 --> 00:28:03,000
Speaker 8: off pay as were strikers. Strikers don't get counted on payrolls,

599
00:28:03,320 --> 00:28:05,800
Speaker 8: but the strikers do get counted as being employed in

600
00:28:05,840 --> 00:28:08,560
Speaker 8: the other survey, in the household survey. And that's why,

601
00:28:08,640 --> 00:28:11,560
Speaker 8: if you want to think of it, simply take some signal.

602
00:28:12,160 --> 00:28:14,320
Speaker 8: You never want to overtrqu on one month, and this

603
00:28:14,359 --> 00:28:17,280
Speaker 8: month especially, you want to be mindful of the noise.

604
00:28:17,480 --> 00:28:20,240
Speaker 8: But take some signal from the unemployment rate which held

605
00:28:20,240 --> 00:28:22,680
Speaker 8: steady at four to one, and you got to write

606
00:28:22,720 --> 00:28:26,040
Speaker 8: off the payroll number as largely noise due to strikes

607
00:28:26,080 --> 00:28:26,720
Speaker 8: and hurricanes.

608
00:28:26,840 --> 00:28:29,600
Speaker 2: For one, I believe is the lowest pre election unemployment

609
00:28:29,680 --> 00:28:31,600
Speaker 2: rate in twenty four years. Jared, you can correct me

610
00:28:31,640 --> 00:28:33,520
Speaker 2: if I'm wrong on that, and I guess I would

611
00:28:33,640 --> 00:28:36,239
Speaker 2: ask you big picture then, for the sake of our

612
00:28:36,320 --> 00:28:39,480
Speaker 2: viewers and listeners today, how would you describe the market

613
00:28:39,560 --> 00:28:42,200
Speaker 2: if it weren't for these aberrations? How would you describe

614
00:28:42,200 --> 00:28:44,760
Speaker 2: the job market days before this election.

615
00:28:46,800 --> 00:28:51,440
Speaker 8: Growing at a solid pace, generating enough jobs to hold

616
00:28:51,440 --> 00:28:54,160
Speaker 8: the unemployment rate where it is so hitting what economists

617
00:28:54,200 --> 00:28:58,080
Speaker 8: call the breake even level, meaning enough employment to absorb

618
00:28:58,120 --> 00:29:01,680
Speaker 8: people coming into the labor force, give people good job

619
00:29:01,680 --> 00:29:04,920
Speaker 8: opportunities to upgrade even though vacancies have come down, we

620
00:29:04,960 --> 00:29:08,480
Speaker 8: still have significant openings, and I think the main thing

621
00:29:08,680 --> 00:29:12,440
Speaker 8: from the perspective of American working households is that this

622
00:29:12,560 --> 00:29:17,280
Speaker 8: job support, including in October, is generating real wage gains

623
00:29:17,560 --> 00:29:20,800
Speaker 8: wages world four percent year over year. Now, we don't

624
00:29:20,840 --> 00:29:24,080
Speaker 8: have the CPI yet for October, but for September it

625
00:29:24,120 --> 00:29:27,640
Speaker 8: was two point four percent, and expectations are that it's

626
00:29:27,640 --> 00:29:30,800
Speaker 8: somewhere in that ballpark, which means yet another growth, yet

627
00:29:30,840 --> 00:29:33,880
Speaker 8: another month of real wage growth. Earlier this week in

628
00:29:35,000 --> 00:29:39,760
Speaker 8: the Consumer Spending Report, we learned that disposable income real

629
00:29:39,880 --> 00:29:42,960
Speaker 8: after tax income also up, and in fact, since this

630
00:29:43,080 --> 00:29:47,280
Speaker 8: president took office up four thousand dollars, real buying power

631
00:29:47,480 --> 00:29:51,440
Speaker 8: up for working households. Now, our work is not done, Joe.

632
00:29:51,440 --> 00:29:53,920
Speaker 8: We've talked about this a lot. We have to continue

633
00:29:53,960 --> 00:29:57,720
Speaker 8: our cost cutting agenda in housing, in childcare, in healthcare,

634
00:29:57,760 --> 00:30:01,440
Speaker 8: in prescription drugs, and we have to defend that agenda

635
00:30:01,760 --> 00:30:04,880
Speaker 8: against those who would repeal it, pushing prices in exactly

636
00:30:04,880 --> 00:30:05,680
Speaker 8: the wrong direction.

637
00:30:05,960 --> 00:30:09,479
Speaker 2: We heard from the Donald Trump campaign or response to

638
00:30:09,520 --> 00:30:12,320
Speaker 2: the job market this morning, Jared. It does not make

639
00:30:12,400 --> 00:30:15,600
Speaker 2: mention of hurricanes, but it says in a single month

640
00:30:15,960 --> 00:30:19,960
Speaker 2: Kamala's failed economic agenda wiped out nearly thirty thousand private

641
00:30:20,040 --> 00:30:25,240
Speaker 2: sector jobs, nearly fifty thousand manufacturing jobs. Working families that

642
00:30:25,280 --> 00:30:27,400
Speaker 2: goes on to say, are being ripped off by the

643
00:30:27,440 --> 00:30:32,560
Speaker 2: Harris Biden economic agenda. Kamala broke the economy. You can

644
00:30:32,600 --> 00:30:36,120
Speaker 2: respond to that as you will, But I wonder if

645
00:30:36,400 --> 00:30:39,720
Speaker 2: the Harris Biden economic agenda includes the weather.

646
00:30:42,360 --> 00:30:44,680
Speaker 8: I don't do electoral politics. I need to stay out

647
00:30:44,720 --> 00:30:48,480
Speaker 8: of that. I will say the following. If you're commenting on,

648
00:30:48,800 --> 00:30:53,720
Speaker 8: or analyzing, or putting forth an interpretation of today's payroll

649
00:30:53,840 --> 00:30:58,120
Speaker 8: number that ignores hurricanes and ignores strikes, you are not

650
00:30:58,400 --> 00:31:01,719
Speaker 8: engaged in good faith and alloy. You are engaged in

651
00:31:02,120 --> 00:31:05,680
Speaker 8: political manipulation, and you should be summarily ignored.

652
00:31:06,240 --> 00:31:10,520
Speaker 2: That said, no hurricanes, and potentially, as we're reading today

653
00:31:10,560 --> 00:31:13,200
Speaker 2: progress in the Boeing strike, Jared would make next Yes,

654
00:31:13,360 --> 00:31:14,480
Speaker 2: Job's report looked like.

655
00:31:14,440 --> 00:31:17,680
Speaker 8: What Yeah, it's a great point. So we know we

656
00:31:17,800 --> 00:31:23,960
Speaker 8: have an agreement between the machinists and the machinists, I

657
00:31:23,960 --> 00:31:27,400
Speaker 8: should say, the union leadership and the management for a

658
00:31:27,520 --> 00:31:30,440
Speaker 8: vote on Monday. It is of course up to the

659
00:31:30,480 --> 00:31:33,720
Speaker 8: rank and file to decide whether they approve that new contract.

660
00:31:34,480 --> 00:31:38,520
Speaker 8: But that is a good news of progress in that area.

661
00:31:39,000 --> 00:31:41,720
Speaker 8: One of the things we showed today, you guys would

662
00:31:41,760 --> 00:31:44,200
Speaker 8: love this, so you should go check it out on

663
00:31:45,080 --> 00:31:48,840
Speaker 8: my Twitter feed, which is econ Jared forty six is

664
00:31:49,440 --> 00:31:54,040
Speaker 8: the if you look at the movement in unemployment claims.

665
00:31:54,400 --> 00:31:56,760
Speaker 8: This is responsive to your question about what to expect

666
00:31:57,160 --> 00:32:01,719
Speaker 8: next month. The unemployment claims really spiked, as they should

667
00:32:02,160 --> 00:32:05,680
Speaker 8: in the areas that were affected by hurricanes, devastated by hurricanes.

668
00:32:06,040 --> 00:32:11,160
Speaker 8: As those areas rebuild and get back on track, and

669
00:32:11,200 --> 00:32:13,960
Speaker 8: there's still a long way to go. They were devastated

670
00:32:14,000 --> 00:32:15,760
Speaker 8: and we're gonna help them every step of the way.

671
00:32:16,320 --> 00:32:19,400
Speaker 8: You see claims coming back down. That spike has really

672
00:32:19,440 --> 00:32:22,720
Speaker 8: done a pretty significant round trip. And by the way,

673
00:32:22,760 --> 00:32:25,840
Speaker 8: we contrast that to areas where there was no hurricane,

674
00:32:25,880 --> 00:32:28,400
Speaker 8: and there you see claims were pretty flat. So if

675
00:32:28,440 --> 00:32:30,840
Speaker 8: you look at claims response to the hurricane, they went up,

676
00:32:30,840 --> 00:32:33,360
Speaker 8: they came down, and when they went up was the

677
00:32:33,400 --> 00:32:37,240
Speaker 8: reference period for the payroll survey. It explains the noise

678
00:32:37,280 --> 00:32:40,440
Speaker 8: in the payroll survey today. But yes, it looks like

679
00:32:41,280 --> 00:32:44,400
Speaker 8: we should be getting back on track for next month's reports.

680
00:32:44,440 --> 00:32:46,440
Speaker 2: Okay, I'm not allowed to ask you about the FED

681
00:32:47,080 --> 00:32:48,880
Speaker 2: because I know you're going to talk to me about

682
00:32:48,920 --> 00:32:51,440
Speaker 2: FED independence, mister chairman, I guess i'd ask you with

683
00:32:51,560 --> 00:32:53,960
Speaker 2: the data we've seen. Here's a big data week leading

684
00:32:53,960 --> 00:32:57,600
Speaker 2: into this election, and this FED meeting just happens to

685
00:32:57,640 --> 00:32:59,719
Speaker 2: be one next week. You probably didn't hear about it.

686
00:32:59,880 --> 00:33:03,080
Speaker 2: I wonder if the data change your view when it

687
00:33:03,080 --> 00:33:05,680
Speaker 2: comes to the trajectory of interest rates, if only in

688
00:33:05,720 --> 00:33:06,400
Speaker 2: the bond market.

689
00:33:09,280 --> 00:33:13,800
Speaker 8: Well, we've seen rates in the bond market be somewhat elevated.

690
00:33:13,840 --> 00:33:17,160
Speaker 8: We've certainly see the mortgage rate go up, and you know,

691
00:33:17,240 --> 00:33:20,920
Speaker 8: part of that has to do with the stronger economy.

692
00:33:21,200 --> 00:33:24,160
Speaker 8: So look under President Biden. You know, we got the

693
00:33:24,160 --> 00:33:28,160
Speaker 8: GDP report this week. Under President Biden, the annualized growth

694
00:33:28,240 --> 00:33:31,160
Speaker 8: rate for GDP has been slightly north of three percent.

695
00:33:31,640 --> 00:33:34,760
Speaker 8: That is a very strong, very much above trend growth rate.

696
00:33:34,960 --> 00:33:39,200
Speaker 8: So strong growth, solid labor market, easing prices, real wage

697
00:33:39,200 --> 00:33:42,440
Speaker 8: and income gains, certainly putting some operate pressure there. But

698
00:33:42,520 --> 00:33:47,320
Speaker 8: I also think there's a policy element going on in

699
00:33:47,360 --> 00:33:49,880
Speaker 8: that spread, in that interest rate, and I think it

700
00:33:49,920 --> 00:33:51,800
Speaker 8: has to do with the idea that one of the

701
00:33:52,480 --> 00:33:56,640
Speaker 8: candidates is talking about massive tariffs acting as a sales

702
00:33:56,680 --> 00:34:00,880
Speaker 8: tax on the middle class, massive deportation, this terrible idea

703
00:34:00,920 --> 00:34:04,680
Speaker 8: for the labor market, and compromising fed independence that may

704
00:34:04,800 --> 00:34:07,520
Speaker 8: also be putting some upward pressure on rates. And I

705
00:34:07,520 --> 00:34:11,840
Speaker 8: think that's just a sign of some of those destructive ideas.

706
00:34:11,920 --> 00:34:13,760
Speaker 2: Wow analysis from the chairman.

707
00:34:13,920 --> 00:34:14,439
Speaker 1: What a treat.

708
00:34:14,520 --> 00:34:16,320
Speaker 2: Jared Bernstein. Great to see us her, chair of the

709
00:34:16,360 --> 00:34:20,080
Speaker 2: White House Council of Economic Advisors. From a sunny North lawn.

710
00:34:23,160 --> 00:34:26,440
Speaker 1: You're listening to the Bloomberg Balance of Power podcast Ken

711
00:34:26,640 --> 00:34:30,200
Speaker 1: just live weekdays at noon Eastern on Applecarplay and Enrounoo

712
00:34:30,320 --> 00:34:33,080
Speaker 1: with a Bloomberg Business app. You can also listen live

713
00:34:33,200 --> 00:34:36,400
Speaker 1: on Amazon Alexa from our flagship New York station, Just

714
00:34:36,440 --> 00:34:42,000
Speaker 1: Say Alexa Play Bloomberg eleven thirty.

715
00:34:41,200 --> 00:34:43,560
Speaker 2: At World Headquarters in New York. Thanks for joining us

716
00:34:43,640 --> 00:34:46,320
Speaker 2: on Balance of Power here on Bloomberg TV and Radio.

717
00:34:46,360 --> 00:34:51,120
Speaker 2: It's the Friday edition and the stenography office is calling.

718
00:34:52,120 --> 00:34:55,480
Speaker 2: Producer James is calling this apostrophe gate, and I wonder

719
00:34:56,120 --> 00:34:58,520
Speaker 2: if this starts to take on some momentum here. If

720
00:34:58,520 --> 00:35:00,919
Speaker 2: you've not heard about this, we're getting a fourth day,

721
00:35:02,000 --> 00:35:05,080
Speaker 2: I mean, guess it's five. Actually it's Friday. We've been

722
00:35:05,120 --> 00:35:08,719
Speaker 2: doing this since Madison Square Garden. A fifth day of

723
00:35:08,800 --> 00:35:13,200
Speaker 2: the garbage story, as the Associated Press reports that White

724
00:35:13,200 --> 00:35:17,000
Speaker 2: House officials altered the official transcript of President Biden's garbage

725
00:35:17,040 --> 00:35:23,200
Speaker 2: remark despite some concern by the stenographers at the White House.

726
00:35:23,280 --> 00:35:27,200
Speaker 2: They actually managed to obtain an internal email from yes,

727
00:35:27,200 --> 00:35:30,239
Speaker 2: the White House Stenography Office and called the Press offices

728
00:35:30,320 --> 00:35:37,680
Speaker 2: intervention quote a breach of protocol and spoiliation of transcript

729
00:35:37,719 --> 00:35:42,919
Speaker 2: integrity between the stenography and press offices. This of course

730
00:35:42,960 --> 00:35:45,680
Speaker 2: goes back to the whole garbage remark, right. President Biden

731
00:35:45,760 --> 00:35:49,600
Speaker 2: was on this Voto Latino call when he responded to

732
00:35:49,680 --> 00:35:54,399
Speaker 2: the joke at Madison Square Garden not very funny one

733
00:35:55,080 --> 00:35:58,000
Speaker 2: that referred to Puerto Rico as an island of floating

734
00:35:58,080 --> 00:36:02,919
Speaker 2: garbage course was turned into a meme, a living meme

735
00:36:03,000 --> 00:36:05,240
Speaker 2: by Donald Trump as he dressed up like a garbage

736
00:36:05,239 --> 00:36:08,640
Speaker 2: man and got into a garbage truck. Got a third

737
00:36:08,719 --> 00:36:11,399
Speaker 2: day out of that. Now we're a fifth day here

738
00:36:11,520 --> 00:36:14,120
Speaker 2: because of the Stenography Office, And it really just has

739
00:36:14,160 --> 00:36:20,360
Speaker 2: to do with not only showing exactly on the record

740
00:36:20,520 --> 00:36:25,080
Speaker 2: what the President said, but the integrity of the messaging

741
00:36:25,120 --> 00:36:27,440
Speaker 2: coming out of the White House in this administration. That's

742
00:36:27,440 --> 00:36:29,480
Speaker 2: where we start with our panel this hour, Rick Davis

743
00:36:29,480 --> 00:36:32,640
Speaker 2: and Jeanie Shanzeno or with U Bloomberg Politics contributors. He

744
00:36:32,719 --> 00:36:36,080
Speaker 2: is partner at stone Court Capital, republican strategist. She is

745
00:36:36,200 --> 00:36:41,000
Speaker 2: a political science professor at Iona University and democratic analyst. Genie,

746
00:36:41,000 --> 00:36:44,840
Speaker 2: what's your thought on this? When the Stenography Office gets upset,

747
00:36:44,880 --> 00:36:48,120
Speaker 2: it's not too often they show up in the headlines here.

748
00:36:48,320 --> 00:36:49,360
Speaker 2: Do we have a problem.

749
00:36:51,120 --> 00:36:53,400
Speaker 9: Yeah, I mean I think it would be far bigger

750
00:36:53,440 --> 00:36:55,400
Speaker 9: problem if Joe Biden was still at the top of

751
00:36:55,440 --> 00:36:58,040
Speaker 9: the ticket. But this is serious. You know, these are

752
00:36:58,280 --> 00:37:02,120
Speaker 9: non partisan civil servants. They take their duty very seriously,

753
00:37:02,239 --> 00:37:05,719
Speaker 9: as do I. Because this goes to the National Archives.

754
00:37:05,800 --> 00:37:09,560
Speaker 9: These are records for historians fifty one hundred years from

755
00:37:09,600 --> 00:37:12,440
Speaker 9: now to know what had happened and what was said.

756
00:37:13,239 --> 00:37:15,239
Speaker 9: It's an example of the cover up being worse than

757
00:37:15,239 --> 00:37:18,640
Speaker 9: the crime. Because Joe Biden made a mistake when he

758
00:37:18,760 --> 00:37:22,279
Speaker 9: was speaking, the White House Press Office or whoever went

759
00:37:22,360 --> 00:37:25,479
Speaker 9: and tried to strong arm these stenographers should have left

760
00:37:25,520 --> 00:37:28,440
Speaker 9: it that way. Instead, they tried to get involved and

761
00:37:28,600 --> 00:37:32,160
Speaker 9: change and I guess they did successfully change what had

762
00:37:32,200 --> 00:37:34,799
Speaker 9: been said. And that is problematic. Do I think it's

763
00:37:34,840 --> 00:37:37,719
Speaker 9: going to impact the election. No, But for all of

764
00:37:37,800 --> 00:37:40,319
Speaker 9: us who care about a record of American history and

765
00:37:40,360 --> 00:37:44,359
Speaker 9: our archives, this is unacceptable and the White House should

766
00:37:44,440 --> 00:37:47,840
Speaker 9: change it back to the way the professional, nonpartisan stenographers

767
00:37:48,120 --> 00:37:49,120
Speaker 9: had its place.

768
00:37:49,280 --> 00:37:51,120
Speaker 2: I had a feeling as an academic that you might

769
00:37:51,160 --> 00:37:53,960
Speaker 2: feel that way, Rick. The actual change here, Literally, it's

770
00:37:53,960 --> 00:37:57,640
Speaker 2: an apostrophe, Joe Biden said on the call, quote The

771
00:37:57,640 --> 00:37:59,960
Speaker 2: only garbage I see floating out there is his support.

772
00:38:00,320 --> 00:38:04,440
Speaker 2: His demonization of Latinos is unconscionable, and that's un American.

773
00:38:04,600 --> 00:38:05,160
Speaker 1: Unquote.

774
00:38:05,400 --> 00:38:09,000
Speaker 2: The transcript released by the Press Office, as I read

775
00:38:09,120 --> 00:38:12,080
Speaker 2: in the pages of the Associated Press, rendered the quote

776
00:38:12,080 --> 00:38:18,520
Speaker 2: with an apostrophe, reading supporters possessive rather than supporters plural.

777
00:38:19,880 --> 00:38:22,160
Speaker 2: Is this just silly splitting of hairs or is this

778
00:38:22,239 --> 00:38:22,720
Speaker 2: a problem?

779
00:38:22,800 --> 00:38:22,960
Speaker 1: Rick?

780
00:38:24,400 --> 00:38:26,759
Speaker 6: I think by now all the methane is out of

781
00:38:26,800 --> 00:38:29,520
Speaker 6: this trashy. I mean, really, do we have to talk

782
00:38:29,520 --> 00:38:32,600
Speaker 6: about the garbage comments anymore? I mean, like four days

783
00:38:32,640 --> 00:38:34,239
Speaker 6: into this thing, five days, But this.

784
00:38:34,200 --> 00:38:37,439
Speaker 2: Is about the White House when the Stenographer's office called.

785
00:38:38,719 --> 00:38:41,160
Speaker 6: But my guess is nobody's been fighting over comments and

786
00:38:41,200 --> 00:38:46,040
Speaker 6: apostrophes other than on politically sensitive remarks like these. And look,

787
00:38:46,560 --> 00:38:48,719
Speaker 6: Joe Biden made a mistake. He should have never weighed

788
00:38:48,760 --> 00:38:51,000
Speaker 6: in on this thing. And they want to just let

789
00:38:51,080 --> 00:38:53,319
Speaker 6: the stographers in the White House do their job. I mean,

790
00:38:53,360 --> 00:38:56,080
Speaker 6: nobody is going to think history has changed. If someone

791
00:38:56,080 --> 00:38:59,120
Speaker 6: wants to look this up, they're going to see reams

792
00:38:59,280 --> 00:39:02,919
Speaker 6: of porting on this that it's not about what he said,

793
00:39:02,960 --> 00:39:05,040
Speaker 6: it's about how it was taken. I think all the

794
00:39:05,120 --> 00:39:07,960
Speaker 6: damage that was done, if there was any damage, has

795
00:39:08,000 --> 00:39:10,160
Speaker 6: already been done. This is not going to be an

796
00:39:10,160 --> 00:39:15,239
Speaker 6: election weekend story. And I think apostrophe Gate will go

797
00:39:15,280 --> 00:39:17,920
Speaker 6: along with all the other gates that we've had, which is,

798
00:39:18,400 --> 00:39:20,680
Speaker 6: you know, more smoke than fire.

799
00:39:21,400 --> 00:39:24,279
Speaker 2: Rick Davis and Genie Shanzino on apostrophe Gate, as we

800
00:39:24,360 --> 00:39:27,880
Speaker 2: bring you back, So the Tucker Crosson Live Tour show

801
00:39:28,200 --> 00:39:32,120
Speaker 2: in Glendale, Arizona. They occupied the Desert Diamond Arena for

802
00:39:32,200 --> 00:39:35,399
Speaker 2: Big rally last night. Rick and Geenie Donald Trump sat

803
00:39:35,440 --> 00:39:37,640
Speaker 2: down with Tucker Carlson and he said some things about

804
00:39:37,719 --> 00:39:41,000
Speaker 2: Liz Cheney that are also driving headlines. Now, again, we

805
00:39:41,080 --> 00:39:43,720
Speaker 2: haven't touched policy yet in this segment, because no one's

806
00:39:43,760 --> 00:39:47,200
Speaker 2: talking policy with the noise and the rhetoric coming out

807
00:39:47,239 --> 00:39:50,480
Speaker 2: of well, I guess everywhere at this point, listen to

808
00:39:50,480 --> 00:39:53,240
Speaker 2: what Donald Trump said about Liz Cheney. We'll get your reaction.

809
00:39:54,120 --> 00:39:57,920
Speaker 5: She's a radical warhawk. Let's put her with a rifle,

810
00:39:57,960 --> 00:40:01,200
Speaker 5: standing there with nine barrel shooting. Okay, let's see how

811
00:40:01,239 --> 00:40:03,719
Speaker 5: she feels about it. You know, when the guns are

812
00:40:03,719 --> 00:40:07,640
Speaker 5: trained in her face. You know there are warhawks when

813
00:40:07,640 --> 00:40:10,520
Speaker 5: they're sitting in Washington in a nice building saying, oh, gee,

814
00:40:10,600 --> 00:40:14,799
Speaker 5: will let's send let's send ten thousand troops right into

815
00:40:14,880 --> 00:40:15,960
Speaker 5: the mouth of the enemy.

816
00:40:16,880 --> 00:40:18,719
Speaker 2: Now, Genie, I don't know what he meant by that.

817
00:40:18,760 --> 00:40:21,920
Speaker 2: People are interpreting this as a threat. Let's put her

818
00:40:21,960 --> 00:40:24,680
Speaker 2: with a rifle, right, he's got her, put a rifle

819
00:40:24,680 --> 00:40:27,719
Speaker 2: in her hand, standing there, nine barrels shooting at her.

820
00:40:27,840 --> 00:40:30,480
Speaker 2: I guess he's implying, let's put her in a battlefield

821
00:40:31,239 --> 00:40:34,920
Speaker 2: as someone who calls us. He says for forever wars

822
00:40:34,960 --> 00:40:37,200
Speaker 2: you refer to as a warhawk. Did he mean that

823
00:40:37,719 --> 00:40:39,360
Speaker 2: or was he implying something different?

824
00:40:40,600 --> 00:40:43,399
Speaker 9: You know, to listen to the campaign. Not surprisingly they

825
00:40:43,440 --> 00:40:45,880
Speaker 9: say we are all taking it out of context. But

826
00:40:46,000 --> 00:40:49,719
Speaker 9: you just played the piece and you can hear in

827
00:40:49,760 --> 00:40:53,720
Speaker 9: there what he was saying. He is talking about putting

828
00:40:53,760 --> 00:40:57,680
Speaker 9: guns in the face of somebody who politically opposes him,

829
00:40:58,080 --> 00:41:03,320
Speaker 9: and seeing how she likes it, the imagery alone is unconscionable.

830
00:41:03,640 --> 00:41:07,879
Speaker 9: And this is vintage Donald Trump and Liz Cheney. When

831
00:41:07,920 --> 00:41:10,800
Speaker 9: you look at her tweet and her response, she says,

832
00:41:10,840 --> 00:41:14,319
Speaker 9: and I think rightly so, he is not fit from

833
00:41:14,400 --> 00:41:17,799
Speaker 9: a character perspective to be president. That is what the

834
00:41:17,840 --> 00:41:21,799
Speaker 9: people have worked closely with him have said. And that

835
00:41:21,840 --> 00:41:24,680
Speaker 9: she also then ties this into the fact that women

836
00:41:25,120 --> 00:41:28,560
Speaker 9: should not forget that we don't have to stand for this.

837
00:41:29,480 --> 00:41:31,920
Speaker 9: You know, it is there is no way around the

838
00:41:31,960 --> 00:41:36,200
Speaker 9: fact that he is doing himself a disservice with this rhetoric,

839
00:41:36,640 --> 00:41:39,919
Speaker 9: and that it is something that can potentially and should,

840
00:41:40,000 --> 00:41:42,719
Speaker 9: in my mind, cost him the election. You don't talk

841
00:41:43,040 --> 00:41:46,360
Speaker 9: about shooting your opponents. That is the thing of dictators.

842
00:41:46,640 --> 00:41:48,000
Speaker 2: Is this another media narrative?

843
00:41:48,080 --> 00:41:48,239
Speaker 5: Rick?

844
00:41:48,280 --> 00:41:49,040
Speaker 2: How did you hear it?

845
00:41:50,560 --> 00:41:50,759
Speaker 8: You know?

846
00:41:50,880 --> 00:41:53,560
Speaker 6: Look, I mean, you can parsis sing all you want.

847
00:41:53,680 --> 00:41:58,399
Speaker 6: It was super inappropriate, you know, And regardless of how

848
00:41:58,440 --> 00:42:01,319
Speaker 6: he meant it to be, you you cannot say that

849
00:42:01,400 --> 00:42:04,280
Speaker 6: you're going to shoot someone in or have someone shot

850
00:42:04,320 --> 00:42:09,000
Speaker 6: in the face. I mean it's just the insensitivity that

851
00:42:09,040 --> 00:42:14,439
Speaker 6: goes along with that remark is you know, clear right.

852
00:42:14,480 --> 00:42:16,400
Speaker 6: I mean, like nobody who hears that is going to

853
00:42:16,480 --> 00:42:19,719
Speaker 6: think anything other than that's inappropriate. There's no way to

854
00:42:19,800 --> 00:42:21,799
Speaker 6: explain it around. And I would say this has been

855
00:42:21,840 --> 00:42:25,080
Speaker 6: consistent with Donald Trump through the latter half of October.

856
00:42:25,120 --> 00:42:29,440
Speaker 6: He's done everything he could to kind of put obstacles

857
00:42:29,440 --> 00:42:30,920
Speaker 6: in his way. He didn't have to have this kind

858
00:42:30,960 --> 00:42:33,160
Speaker 6: of a day. He could have been talking about other

859
00:42:33,239 --> 00:42:36,480
Speaker 6: issues like garbage and things like that. But the reality

860
00:42:36,600 --> 00:42:39,320
Speaker 6: is that he's his own worst enemy. I mean, honestly,

861
00:42:39,360 --> 00:42:42,080
Speaker 6: I think that there have been very few attacks by

862
00:42:43,880 --> 00:42:46,600
Speaker 6: Kamala Harrison the waiting days of the campaign here that

863
00:42:46,680 --> 00:42:51,120
Speaker 6: have done more damage than Donald Trump's own statements. Even

864
00:42:51,160 --> 00:42:54,600
Speaker 6: the idea of talking about the election, you know, is

865
00:42:54,680 --> 00:42:58,320
Speaker 6: already being flawed. I mean, it just reminds voters, especially

866
00:42:58,360 --> 00:43:00,680
Speaker 6: in places like Pennsylvania that had to go through a

867
00:43:00,760 --> 00:43:06,160
Speaker 6: lot of lawsuits last time post election, that this is

868
00:43:06,200 --> 00:43:07,960
Speaker 6: the kind of chaos that he brings to the table.

869
00:43:08,000 --> 00:43:10,240
Speaker 6: It doesn't really matter whether he means it, it doesn't

870
00:43:10,239 --> 00:43:13,480
Speaker 6: really matter. It's chaos. And I do think that is

871
00:43:13,520 --> 00:43:16,600
Speaker 6: a factor. I mean, like if people have voters who

872
00:43:16,680 --> 00:43:19,840
Speaker 6: have yet to vote think that they're entering into another

873
00:43:20,840 --> 00:43:26,040
Speaker 6: four years of chaotic name calling and inappropriate remarks, that

874
00:43:26,120 --> 00:43:28,520
Speaker 6: might be enough for them to actually change their vote

875
00:43:28,560 --> 00:43:32,120
Speaker 6: and vote for Hair. So I do think the campaign

876
00:43:32,120 --> 00:43:34,680
Speaker 6: needs to worry about this, regardless of how they spin it.

877
00:43:34,760 --> 00:43:37,439
Speaker 2: Well, that answers I guess part of my question, which

878
00:43:37,480 --> 00:43:40,239
Speaker 2: is whether there's a strategy to this flooding the zone.

879
00:43:40,280 --> 00:43:43,239
Speaker 2: Having us talk about Donald Trump all day, whether it's

880
00:43:43,280 --> 00:43:46,960
Speaker 2: garbage or rifles aimed at Liz Cheney or whatever the

881
00:43:47,040 --> 00:43:50,440
Speaker 2: rhetoric that day might be. We're not talking about Kamala

882
00:43:50,520 --> 00:43:55,280
Speaker 2: Harris or things that she is proposing. Genie, I wonder

883
00:43:55,320 --> 00:43:57,319
Speaker 2: your thoughts on that, or is it in fact a

884
00:43:57,400 --> 00:44:00,879
Speaker 2: danger when it comes to gathering news to sit down

885
00:44:00,880 --> 00:44:03,520
Speaker 2: with Tucker Crasson on Halloween and let it rip.

886
00:44:05,120 --> 00:44:08,239
Speaker 9: I think it is incredible danger for the campaign. You know,

887
00:44:08,360 --> 00:44:11,320
Speaker 9: Donald Trump has always been of the sort of Andy

888
00:44:11,360 --> 00:44:15,200
Speaker 9: Warhol view that any publicity is good publicity, Get out there,

889
00:44:15,360 --> 00:44:20,000
Speaker 9: keep talking. The reality is, whoever this election ends up

890
00:44:20,040 --> 00:44:23,480
Speaker 9: being a referendum on, is likely to lose. And at

891
00:44:23,560 --> 00:44:26,960
Speaker 9: this point, to Rick's point, we don't hear much from

892
00:44:27,040 --> 00:44:29,799
Speaker 9: Kamala Harris. I mean, she's out there, she's talking, but

893
00:44:30,000 --> 00:44:33,560
Speaker 9: not in this incendiary language that is catching fire. It

894
00:44:33,680 --> 00:44:37,320
Speaker 9: is all about Donald Trump, all about garbage, all about

895
00:44:37,320 --> 00:44:40,759
Speaker 9: shooting people in the face, all about reminding us of

896
00:44:40,800 --> 00:44:44,880
Speaker 9: the chaos that was his administration. And that is the

897
00:44:45,040 --> 00:44:48,520
Speaker 9: death knell for the campaign. Think about it from another perspective.

898
00:44:48,760 --> 00:44:51,799
Speaker 9: He could get out there today and say, look at

899
00:44:51,840 --> 00:44:55,160
Speaker 9: those job numbers, twelve thousand, that is horrible. I will

900
00:44:55,160 --> 00:44:57,920
Speaker 9: create twelve million jobs or whatever number he wants to

901
00:44:57,920 --> 00:45:01,200
Speaker 9: give and focus on the economy. That's what people are

902
00:45:01,280 --> 00:45:04,520
Speaker 9: upset about, and they're upset about Joe Biden. Instead, he

903
00:45:04,560 --> 00:45:08,279
Speaker 9: does everything but talk about the issues that will move

904
00:45:08,360 --> 00:45:12,280
Speaker 9: those undecided voters to his lane. A big problem. Yeah,

905
00:45:12,320 --> 00:45:14,920
Speaker 9: Andy Warhol's theory works if you are you know, I

906
00:45:14,920 --> 00:45:17,560
Speaker 9: don't know, a comedian or an actor. He is running

907
00:45:17,680 --> 00:45:19,640
Speaker 9: for president of the United States.

908
00:45:19,719 --> 00:45:22,000
Speaker 2: Yeah, ask Kinchcliffe about that. We did hear from Liz

909
00:45:22,080 --> 00:45:25,400
Speaker 2: Cheney rick quote this is how dictators destroy free dations.

910
00:45:25,719 --> 00:45:28,920
Speaker 2: She actually retweeted the video they threaten she writes, those

911
00:45:28,960 --> 00:45:32,680
Speaker 2: who speak against them with death unquote. Is that pushing

912
00:45:32,680 --> 00:45:35,000
Speaker 2: it a little far? Or should that, in fact be

913
00:45:35,040 --> 00:45:37,760
Speaker 2: the response he's effectively a surrogate for the Kamala Harris

914
00:45:37,800 --> 00:45:38,399
Speaker 2: campaign here.

915
00:45:39,280 --> 00:45:41,480
Speaker 6: Yeah, I don't think you can really just judge it

916
00:45:41,520 --> 00:45:44,040
Speaker 6: on one comment. I mean, the reality is there's a

917
00:45:44,040 --> 00:45:47,040
Speaker 6: lot of reporting on a lot of Republicans who were

918
00:45:47,080 --> 00:45:50,120
Speaker 6: threatened within his own administration, like General Millie, who was

919
00:45:50,200 --> 00:45:52,360
Speaker 6: his chairman of the Joint Chiefs of Staff, the highest

920
00:45:52,400 --> 00:45:55,880
Speaker 6: ranking military officer in the country, who served at the

921
00:45:55,920 --> 00:45:58,479
Speaker 6: pleasure of the President of the United States, and he's

922
00:45:58,520 --> 00:46:01,600
Speaker 6: had to, you know, basically fortify his home and hire

923
00:46:01,680 --> 00:46:05,480
Speaker 6: lawyers and be prepared for a nonslaught of retribution from

924
00:46:05,520 --> 00:46:08,680
Speaker 6: Donald Trump. Now this is not an isolated example. If

925
00:46:08,680 --> 00:46:11,560
Speaker 6: it were, we'd have a conversation about it and probably

926
00:46:11,560 --> 00:46:14,520
Speaker 6: wouldn't affect much. But the reality is, you know, Donald

927
00:46:14,520 --> 00:46:16,600
Speaker 6: Trump has flooded the zone, but he's flooded the zone

928
00:46:16,640 --> 00:46:19,520
Speaker 6: with this kind of sort of you know, retribution to

929
00:46:19,560 --> 00:46:21,360
Speaker 6: her again, and this is what held him back in

930
00:46:21,400 --> 00:46:24,600
Speaker 6: the summer before the convention, and he seems to be

931
00:46:24,719 --> 00:46:29,760
Speaker 6: re introducing that into the campaign, going after people settling scores.

932
00:46:30,200 --> 00:46:32,440
Speaker 6: This is not what his own voters want to hear.

933
00:46:32,560 --> 00:46:34,960
Speaker 6: His own voters want to hear, you know, changing the

934
00:46:34,960 --> 00:46:37,960
Speaker 6: administration and fixing the problems that we're incumbent in the

935
00:46:38,080 --> 00:46:38,920
Speaker 6: Biden administration.

936
00:46:39,000 --> 00:46:41,280
Speaker 2: You know, it's pretty incredible to see the Harris campaign

937
00:46:41,360 --> 00:46:44,600
Speaker 2: flood TikTok with the Access Hollywood tape all over again

938
00:46:44,680 --> 00:46:48,319
Speaker 2: for young people who weren't there to witness it the

939
00:46:48,360 --> 00:46:51,239
Speaker 2: first time around. You wonder what the cumulative effect will be.

940
00:46:51,960 --> 00:46:55,360
Speaker 2: Didn't matter the first time. Rick Davis and Genie Shanzano

941
00:46:55,400 --> 00:46:57,120
Speaker 2: see you on the late edition to Balance of Power

942
00:46:57,160 --> 00:47:02,719
Speaker 2: five pm Eastern right here on Bloomberg TV and Radio.

943
00:47:03,600 --> 00:47:07,160
Speaker 1: You're listening to the Bloomberg Balance of Power podcast. Catch

944
00:47:07,239 --> 00:47:10,279
Speaker 1: Just Live weekdays at noon Eastern on Apocarplay and then

945
00:47:10,400 --> 00:47:13,800
Speaker 1: Rouno with the Bloomberg Business app. Listen on demand wherever

946
00:47:13,880 --> 00:47:20,000
Speaker 1: you get your podcasts, or watch us live on YouTube.

947
00:47:19,719 --> 00:47:21,919
Speaker 2: In New York. Thanks for joining us on Balance of Power,

948
00:47:21,960 --> 00:47:25,400
Speaker 2: the fastest show in politics, here on Bloomberg TV and Radio.

949
00:47:25,560 --> 00:47:27,720
Speaker 2: As we prepare it to spend some time with Julie

950
00:47:27,760 --> 00:47:31,960
Speaker 2: Pace at the Associated Press, who will be overseeing the

951
00:47:32,000 --> 00:47:34,479
Speaker 2: calling of races next week. When you hear us say

952
00:47:34,480 --> 00:47:38,439
Speaker 2: the Associated Press has called this state or has called

953
00:47:38,480 --> 00:47:41,880
Speaker 2: this Senate race, it's going to be Julie Pace and

954
00:47:41,920 --> 00:47:46,799
Speaker 2: her team making that known. As we find the op

955
00:47:46,960 --> 00:47:49,160
Speaker 2: ed in the Associated Press today from Julie Pace, the

956
00:47:49,200 --> 00:47:52,440
Speaker 2: headline for the US election, The AP performs the world's

957
00:47:52,480 --> 00:47:58,920
Speaker 2: single largest act of journalism, consider as she writes, the

958
00:47:59,000 --> 00:48:01,279
Speaker 2: important work is being done against the backdrop of an

959
00:48:01,320 --> 00:48:05,719
Speaker 2: electorate that has become increasingly skeptical of election results. An

960
00:48:05,760 --> 00:48:09,560
Speaker 2: APRC pull from twenty twenty three showed only forty four

961
00:48:09,600 --> 00:48:12,560
Speaker 2: percent of Americans say they are highly confident the votes

962
00:48:12,600 --> 00:48:16,440
Speaker 2: in this presidential election twenty twenty four will be counted accurately.

963
00:48:17,200 --> 00:48:21,000
Speaker 2: Bloomberg Politics contributor Republican strategist Rick Davis is with US

964
00:48:21,040 --> 00:48:23,560
Speaker 2: partner at Stone Court Capital as we prepare to talk

965
00:48:23,600 --> 00:48:26,920
Speaker 2: to Julie Pace. Rick, you've run campaigns. You know what

966
00:48:26,960 --> 00:48:30,040
Speaker 2: it's like to be waiting to hear from the Associated Press.

967
00:48:30,040 --> 00:48:34,520
Speaker 2: This has become a riskier journalistic endeavor compared to years past,

968
00:48:34,560 --> 00:48:34,920
Speaker 2: isn't it.

969
00:48:36,120 --> 00:48:41,680
Speaker 6: Yeah, there's so much information available and frankly, more and

970
00:48:41,800 --> 00:48:44,680
Speaker 6: more skepticism on the part of voters, So you know

971
00:48:44,719 --> 00:48:47,040
Speaker 6: you want to get it right. I remember one night

972
00:48:47,840 --> 00:48:51,120
Speaker 6: and during the South Carolina primary in two thousand and eight,

973
00:48:51,280 --> 00:48:54,319
Speaker 6: we lost the South Carolina primary in two thousand ended

974
00:48:54,320 --> 00:48:57,799
Speaker 6: the campaign basically, so it was really important. I get

975
00:48:57,840 --> 00:49:00,680
Speaker 6: a call I'm with the mccains and and you know,

976
00:49:00,719 --> 00:49:04,480
Speaker 6: it's AP saying, okay, ten minutes we're going to announce

977
00:49:04,520 --> 00:49:07,640
Speaker 6: that you've won the South Carolina primary. Be ready, And

978
00:49:07,680 --> 00:49:11,000
Speaker 6: of course you've got one speech. It says, you know,

979
00:49:11,200 --> 00:49:14,480
Speaker 6: concession another victory. Which one are you going to prep for? Right?

980
00:49:15,000 --> 00:49:17,200
Speaker 6: So we go into the bedroom. We're prepping for that

981
00:49:17,320 --> 00:49:20,480
Speaker 6: victory speech. And I get a call back about five

982
00:49:20,520 --> 00:49:24,520
Speaker 6: minutes later saying, hold off, we got to rerun the model.

983
00:49:24,880 --> 00:49:27,319
Speaker 6: I mean, something doesn't look right here. I'm like, what

984
00:49:27,320 --> 00:49:30,759
Speaker 6: do you mean? You just said? I want so Look,

985
00:49:30,800 --> 00:49:33,600
Speaker 6: it's not a perfect scientist science, but it has gotten

986
00:49:33,719 --> 00:49:36,759
Speaker 6: so much better. And you know, they prepare months and

987
00:49:36,800 --> 00:49:39,680
Speaker 6: months in advance with their models and their information that

988
00:49:39,760 --> 00:49:43,640
Speaker 6: they have available that literally can predict an outcome based

989
00:49:43,680 --> 00:49:49,000
Speaker 6: on early vote that's been incredibly accurate, and I think,

990
00:49:49,120 --> 00:49:51,160
Speaker 6: you know, voters can rely upon it.

991
00:49:51,640 --> 00:49:55,200
Speaker 2: That's, of course, not to be confused with broadcast networks

992
00:49:56,080 --> 00:49:58,839
Speaker 2: other news outlets. Everyone's got a website now. I used

993
00:49:58,880 --> 00:50:01,359
Speaker 2: to call them newspapers, but not anymore. Rick They're all

994
00:50:01,360 --> 00:50:03,160
Speaker 2: going to make their own calls, They have their own

995
00:50:03,160 --> 00:50:07,680
Speaker 2: decision desks, and they all work independently of the Associated Press,

996
00:50:07,719 --> 00:50:10,200
Speaker 2: even though they're members of that consortium. Can you explain

997
00:50:10,280 --> 00:50:11,920
Speaker 2: that to our listeners and viewers that we're going to

998
00:50:12,000 --> 00:50:14,920
Speaker 2: hear multiple calls from different places at different times.

999
00:50:15,920 --> 00:50:20,279
Speaker 6: That's right. Starting at about six thirties coast time data

1000
00:50:20,320 --> 00:50:23,360
Speaker 6: is flowing into these models, and you're right. Each network

1001
00:50:23,400 --> 00:50:26,279
Speaker 6: now has its own quote decision desk, right, and they

1002
00:50:27,000 --> 00:50:29,800
Speaker 6: like to make decisions on their own. They don't coordinate

1003
00:50:29,880 --> 00:50:33,279
Speaker 6: with others, they don't coordinate with the AP, and they

1004
00:50:33,320 --> 00:50:35,520
Speaker 6: have their own models. Every one of them has different

1005
00:50:35,560 --> 00:50:39,919
Speaker 6: polling data that will be instrumental and making a judgment call,

1006
00:50:40,920 --> 00:50:43,759
Speaker 6: and their own political instincts. Right. In some cases, there's

1007
00:50:43,760 --> 00:50:46,440
Speaker 6: a gut check that's involved, and they have to delay

1008
00:50:46,640 --> 00:50:49,880
Speaker 6: an announcement unless they have really total confidence they know

1009
00:50:49,920 --> 00:50:51,799
Speaker 6: what the outcome is going to be. And so you

1010
00:50:51,880 --> 00:50:55,879
Speaker 6: could have competing outcomes. You could have competing calls where

1011
00:50:55,880 --> 00:50:59,440
Speaker 6: one network calls it for one candidate and another calls

1012
00:50:59,440 --> 00:51:05,240
Speaker 6: it for someone else, or withdraws the announcement that somebody

1013
00:51:05,280 --> 00:51:09,600
Speaker 6: has won, based like what happened in two thousand with

1014
00:51:09,719 --> 00:51:14,280
Speaker 6: Florida so the reality is there is a good chance

1015
00:51:14,280 --> 00:51:18,120
Speaker 6: of confusion. But I must say, as a campaign professional,

1016
00:51:18,560 --> 00:51:21,200
Speaker 6: we never acted upon anything that didn't come from the AP.

1017
00:51:21,920 --> 00:51:24,319
Speaker 2: It's quite the setup for Julie Pace, Rick Davis, thank

1018
00:51:24,320 --> 00:51:27,000
Speaker 2: you as always for being with us on balance of power.

1019
00:51:27,080 --> 00:51:29,479
Speaker 2: She is executive editor of the Associated Press and joins

1020
00:51:29,560 --> 00:51:34,400
Speaker 2: us from Washington with a massive responsibility ahead next week. Julie,

1021
00:51:34,400 --> 00:51:36,200
Speaker 2: it's great to have you and I appreciate your time.

1022
00:51:36,239 --> 00:51:39,640
Speaker 2: As you right, the AP performs the world's single largest

1023
00:51:40,000 --> 00:51:43,280
Speaker 2: act of journalism, and I was looking at your website

1024
00:51:43,320 --> 00:51:45,680
Speaker 2: a little while ago. You talk about your decision team

1025
00:51:45,719 --> 00:51:50,120
Speaker 2: here driven entirely by facts. Calls made by other organizations.

1026
00:51:50,160 --> 00:51:51,880
Speaker 2: As we were just discussing with Rick, who I know

1027
00:51:51,920 --> 00:51:55,160
Speaker 2: you've worked with, have no bearing on when the Associated

1028
00:51:55,200 --> 00:51:58,560
Speaker 2: Press declares a candidate the winner. I would love for

1029
00:51:58,600 --> 00:52:01,480
Speaker 2: you to walk us through. This is an opportunity to

1030
00:52:01,520 --> 00:52:04,080
Speaker 2: go to school with Julie Pace for our listeners and viewers.

1031
00:52:04,120 --> 00:52:06,680
Speaker 2: How big is your decision team and what is the

1032
00:52:06,719 --> 00:52:08,640
Speaker 2: methodology that goes into calling a race?

1033
00:52:09,080 --> 00:52:09,360
Speaker 6: Sure?

1034
00:52:09,440 --> 00:52:11,799
Speaker 10: Well, thank you first of all for having me. You know,

1035
00:52:11,840 --> 00:52:14,360
Speaker 10: really one of our primary focuses in the lead up

1036
00:52:14,400 --> 00:52:16,440
Speaker 10: to the election, and then certainly as we're calling races,

1037
00:52:16,520 --> 00:52:19,319
Speaker 10: is going to be transparency, making sure that people really

1038
00:52:19,400 --> 00:52:22,880
Speaker 10: understand all of the effort, the work, the preparation that

1039
00:52:22,880 --> 00:52:25,279
Speaker 10: goes into these race calls, and then making sure that

1040
00:52:25,280 --> 00:52:28,080
Speaker 10: we're being transparent about how we make the calls when

1041
00:52:28,080 --> 00:52:30,080
Speaker 10: they come through. I think the biggest thing that I

1042
00:52:30,120 --> 00:52:32,040
Speaker 10: would emphasize is, you know, we've been doing this at

1043
00:52:32,040 --> 00:52:35,000
Speaker 10: the AP for more than one hundred and seventy five years,

1044
00:52:35,440 --> 00:52:38,640
Speaker 10: and this is a full time operation for us. This

1045
00:52:38,719 --> 00:52:41,440
Speaker 10: isn't just something that we stand up in an election year.

1046
00:52:41,480 --> 00:52:45,880
Speaker 10: So our teams are really spending their full time understanding

1047
00:52:46,360 --> 00:52:50,680
Speaker 10: rule changes in states, methodology of voting in states, the

1048
00:52:51,160 --> 00:52:55,280
Speaker 10: rhythm of the counting and the vote tabulations in these states.

1049
00:52:55,480 --> 00:52:58,680
Speaker 10: And at the core of our effort is four thousand

1050
00:52:58,880 --> 00:53:01,120
Speaker 10: vote count reporters who are going to be all across

1051
00:53:01,200 --> 00:53:04,600
Speaker 10: the country physically in counties, which is where admin where

1052
00:53:04,640 --> 00:53:06,919
Speaker 10: elections in the United States are administered, and they are

1053
00:53:07,200 --> 00:53:10,120
Speaker 10: really our ultimate system of checks and balances, making sure

1054
00:53:10,160 --> 00:53:12,640
Speaker 10: that they are matching up the vote count numbers with

1055
00:53:12,719 --> 00:53:15,200
Speaker 10: the numbers that counties may be putting and states may

1056
00:53:15,200 --> 00:53:18,520
Speaker 10: be putting in their databases and that's really where this

1057
00:53:18,560 --> 00:53:22,640
Speaker 10: whole operation starts. That that data is fed up through

1058
00:53:22,719 --> 00:53:25,279
Speaker 10: the models and into our race analysts and ultimately our

1059
00:53:25,320 --> 00:53:29,839
Speaker 10: decision desk. They have an exceptional accuracy rate, and we're

1060
00:53:29,840 --> 00:53:32,040
Speaker 10: really confident that we're going to be able to deliver

1061
00:53:32,239 --> 00:53:35,680
Speaker 10: on that accuracy but also be able to transparently explain

1062
00:53:35,719 --> 00:53:38,280
Speaker 10: to the public what we're doing. Come come Tuesday and beyond.

1063
00:53:38,400 --> 00:53:42,080
Speaker 2: Fascinating how much human involvement is involved in the moment

1064
00:53:42,120 --> 00:53:46,839
Speaker 2: of making the call versus having criteria in advance that

1065
00:53:46,920 --> 00:53:49,000
Speaker 2: a computer could tell you when you reach that point

1066
00:53:49,000 --> 00:53:53,040
Speaker 2: when certain votes are cast in certain areas of a district,

1067
00:53:53,040 --> 00:53:55,879
Speaker 2: for instance, are you in a room with your team

1068
00:53:55,960 --> 00:53:57,719
Speaker 2: looking at each other in the eye saying are we

1069
00:53:57,760 --> 00:53:58,560
Speaker 2: going for this or not?

1070
00:53:59,200 --> 00:53:59,399
Speaker 8: Yeah?

1071
00:53:59,480 --> 00:54:03,080
Speaker 10: Ultimately, you know, the final decision makers on race calls

1072
00:54:03,160 --> 00:54:05,920
Speaker 10: are human journalists at the Associated Press. You know, our

1073
00:54:06,360 --> 00:54:08,520
Speaker 10: team is the one. Humans are the one that make

1074
00:54:08,600 --> 00:54:13,399
Speaker 10: those final decisions. But obviously we're aided by statistical analysis

1075
00:54:13,480 --> 00:54:16,560
Speaker 10: and modeling and the actual raw data that's coming in.

1076
00:54:16,600 --> 00:54:19,359
Speaker 10: You know, the the closer the race is in a

1077
00:54:19,400 --> 00:54:23,000
Speaker 10: particular state, the more you need actual vote count. You know,

1078
00:54:23,040 --> 00:54:25,480
Speaker 10: the more the model is one of the tools in

1079
00:54:25,480 --> 00:54:27,800
Speaker 10: your toolkit, but you're really just looking at the actual

1080
00:54:27,920 --> 00:54:30,560
Speaker 10: vote with the raw vote count that's that's coming in here.

1081
00:54:30,560 --> 00:54:32,879
Speaker 10: But this is always going to be a situation where

1082
00:54:32,880 --> 00:54:36,120
Speaker 10: we've got a humans who's an expert in their state

1083
00:54:37,080 --> 00:54:40,319
Speaker 10: or in their race potentially depending on the way you

1084
00:54:40,320 --> 00:54:43,000
Speaker 10: know that we've divided things up that year, and they're

1085
00:54:43,040 --> 00:54:45,279
Speaker 10: the ones that are really helping us make that final call.

1086
00:54:45,480 --> 00:54:50,080
Speaker 2: How local do you need to get in congressional districts

1087
00:54:50,080 --> 00:54:52,560
Speaker 2: in certain states? You talked about the long history of

1088
00:54:52,560 --> 00:54:55,920
Speaker 2: the associated press here that allows you to understand the

1089
00:54:56,000 --> 00:54:59,319
Speaker 2: nuances of each area that you're calling a race in.

1090
00:54:59,360 --> 00:55:00,480
Speaker 2: How different are are they all?

1091
00:55:00,880 --> 00:55:03,719
Speaker 10: Yeah, so we are down to the county level because again,

1092
00:55:03,760 --> 00:55:05,919
Speaker 10: I think one of the interesting and unique things about

1093
00:55:05,920 --> 00:55:08,400
Speaker 10: the American system of elections is that there is no

1094
00:55:08,600 --> 00:55:14,000
Speaker 10: federal elections office. There is no federal agency that administers elections,

1095
00:55:14,160 --> 00:55:16,320
Speaker 10: so you don't have a one size fits all approach,

1096
00:55:16,360 --> 00:55:18,719
Speaker 10: and as a result, you actually have elections that are

1097
00:55:18,840 --> 00:55:23,160
Speaker 10: run within states in multiple different ways. And so that's

1098
00:55:23,160 --> 00:55:26,279
Speaker 10: why that team of four thousand vote count reporters is

1099
00:55:26,320 --> 00:55:29,080
Speaker 10: absolutely essential because they need to be focused on what's

1100
00:55:29,080 --> 00:55:31,840
Speaker 10: happening in the county that they're in. That's the only

1101
00:55:31,880 --> 00:55:33,920
Speaker 10: thing that they're focused on in that moment is the

1102
00:55:33,960 --> 00:55:36,160
Speaker 10: way that the election is administered down at.

1103
00:55:36,040 --> 00:55:36,960
Speaker 6: That local level.

1104
00:55:37,239 --> 00:55:39,279
Speaker 10: And we need that level of nuance because of the

1105
00:55:39,320 --> 00:55:40,360
Speaker 10: complexity of these.

1106
00:55:40,239 --> 00:55:43,040
Speaker 2: Elections coming off of what we saw in twenty twenty

1107
00:55:43,880 --> 00:55:49,000
Speaker 2: and the expectation for contested races, certainly on the presidential

1108
00:55:49,080 --> 00:55:52,520
Speaker 2: level this year. Is there a lawyer involved in making

1109
00:55:52,560 --> 00:55:55,880
Speaker 2: these calls? Do you look at lawsuits or potential recounts

1110
00:55:55,920 --> 00:55:57,279
Speaker 2: in the district before you call it?

1111
00:55:57,840 --> 00:56:00,560
Speaker 10: So there's no lawyer involved in our act of actually

1112
00:56:00,560 --> 00:56:02,799
Speaker 10: calling the races. But we look at a range of

1113
00:56:02,800 --> 00:56:05,680
Speaker 10: factors when we're making the decision to call a race,

1114
00:56:05,880 --> 00:56:08,160
Speaker 10: and one of the things that we look at is

1115
00:56:08,160 --> 00:56:11,360
Speaker 10: is there an automatic recount in a state. Some states

1116
00:56:11,360 --> 00:56:14,399
Speaker 10: have a tiny margin where if the race is within

1117
00:56:14,440 --> 00:56:17,279
Speaker 10: that margin, then it goes to an automatic recount. We

1118
00:56:17,320 --> 00:56:19,560
Speaker 10: want to make sure that the ap race call is

1119
00:56:19,640 --> 00:56:24,120
Speaker 10: not brought up as part of a legitimate legal process.

1120
00:56:24,480 --> 00:56:26,279
Speaker 10: We want to make sure that our race call can

1121
00:56:26,360 --> 00:56:30,560
Speaker 10: stand and withstand any other external factors. So certainly those

1122
00:56:30,560 --> 00:56:33,200
Speaker 10: are factors that we look at, but really ultimately this

1123
00:56:33,280 --> 00:56:36,560
Speaker 10: comes down to a simple question, which is does the

1124
00:56:36,640 --> 00:56:39,880
Speaker 10: trailing candidate have a way to catch up? And if

1125
00:56:39,920 --> 00:56:42,319
Speaker 10: the answer to that is no, then we decide that

1126
00:56:42,320 --> 00:56:44,000
Speaker 10: we're ready to move forward with that race call.

1127
00:56:44,120 --> 00:56:48,120
Speaker 2: That's fascinating. What about reports is we've seen recently of

1128
00:56:48,960 --> 00:56:53,279
Speaker 2: ballot boxes being set on fire, ballots being destroyed. If

1129
00:56:53,320 --> 00:56:56,640
Speaker 2: you have cases like that, if there's damage to ballots,

1130
00:56:56,680 --> 00:56:59,040
Speaker 2: if you have protests around a precinct, do you have

1131
00:56:59,120 --> 00:57:02,000
Speaker 2: to put things on whold or does that not impact

1132
00:57:02,040 --> 00:57:04,080
Speaker 2: your model because you're looking at a different sample of

1133
00:57:04,080 --> 00:57:04,640
Speaker 2: the electorate.

1134
00:57:05,160 --> 00:57:06,839
Speaker 10: Yeah, it's a good question. Look, I would say that

1135
00:57:06,920 --> 00:57:10,600
Speaker 10: every one of those potential situations is unique and different,

1136
00:57:10,719 --> 00:57:12,960
Speaker 10: and so it's hard to give a one size fits

1137
00:57:13,000 --> 00:57:15,600
Speaker 10: all answer to that. What we're always looking at in

1138
00:57:15,640 --> 00:57:17,640
Speaker 10: the situation like that is how many ballots are we

1139
00:57:17,680 --> 00:57:19,960
Speaker 10: talking about? You know, are we talking about ten ballots?

1140
00:57:20,000 --> 00:57:21,919
Speaker 10: Are we talking about a thousand ballots? Are we talking

1141
00:57:21,920 --> 00:57:26,560
Speaker 10: about ten thousand ballots? Historically, elections in the United States are,

1142
00:57:27,160 --> 00:57:32,680
Speaker 10: while quite complex, exceptionally well run, and the incidents of

1143
00:57:33,080 --> 00:57:38,160
Speaker 10: true voter fraud or moments where large numbers of votes

1144
00:57:38,240 --> 00:57:41,480
Speaker 10: that cannot be counted for some reason in numbers that

1145
00:57:41,480 --> 00:57:44,400
Speaker 10: could actually sway the outcome of the election that just

1146
00:57:44,440 --> 00:57:46,760
Speaker 10: doesn't exist. You know, we looked back at twenty twenty

1147
00:57:46,800 --> 00:57:50,400
Speaker 10: to find the number of incidents of true voter fraud,

1148
00:57:50,640 --> 00:57:53,200
Speaker 10: and it was a couple of hundred incidents, and that

1149
00:57:53,280 --> 00:57:55,520
Speaker 10: was a race that was obviously decided by far more

1150
00:57:55,600 --> 00:57:58,400
Speaker 10: So we watched these things, but really this does come

1151
00:57:58,480 --> 00:58:00,600
Speaker 10: down to the size and the number of votes that

1152
00:58:00,600 --> 00:58:02,120
Speaker 10: we could potentially be talking about.

1153
00:58:02,320 --> 00:58:05,520
Speaker 2: As I read on the how we call Races page,

1154
00:58:05,520 --> 00:58:07,600
Speaker 2: I would encourage everybody go to AP dot org to

1155
00:58:07,640 --> 00:58:07,960
Speaker 2: read this.

1156
00:58:08,200 --> 00:58:09,040
Speaker 3: Who calls them?

1157
00:58:09,280 --> 00:58:11,200
Speaker 2: When does the AP call a race? Where can I

1158
00:58:11,200 --> 00:58:14,000
Speaker 2: find AP race calls? There's a lot of interesting information here,

1159
00:58:14,040 --> 00:58:16,040
Speaker 2: But you point out that a lot of races are

1160
00:58:16,040 --> 00:58:18,720
Speaker 2: won on election night, but not uncommon for it to

1161
00:58:18,760 --> 00:58:23,320
Speaker 2: take a few days, maybe even weeks to reach that point. Julie,

1162
00:58:23,320 --> 00:58:25,840
Speaker 2: everybody's got an office pool going on when the presidential

1163
00:58:25,920 --> 00:58:28,160
Speaker 2: race is going to be called, and we only have

1164
00:58:28,640 --> 00:58:30,880
Speaker 2: the last election really to base this on. It took

1165
00:58:30,960 --> 00:58:33,400
Speaker 2: us until Saturday. What's the Associated Press prepared for?

1166
00:58:33,960 --> 00:58:37,360
Speaker 10: Look, we're prepared for any scenario here. It's impossible to

1167
00:58:37,360 --> 00:58:41,000
Speaker 10: predict when we'll call the race for the presidency. I

1168
00:58:41,000 --> 00:58:43,800
Speaker 10: would say that at the presidential level, twenty twenty was

1169
00:58:43,880 --> 00:58:46,480
Speaker 10: an anomaly. If you look back from sort of twenty

1170
00:58:46,960 --> 00:58:50,280
Speaker 10: two thousand and four, you know, through twenty twenty, most

1171
00:58:50,280 --> 00:58:53,400
Speaker 10: of those presidential races have been called either on Tuesday night,

1172
00:58:53,440 --> 00:58:56,720
Speaker 10: on election night, or early on Wednesday. Sometimes house races,

1173
00:58:56,760 --> 00:58:58,920
Speaker 10: senate races can go on much longer, but we're prepared

1174
00:58:58,920 --> 00:59:02,040
Speaker 10: for any scenario if there is a longer wait for

1175
00:59:02,080 --> 00:59:03,880
Speaker 10: a call, you know, our real focus is going to

1176
00:59:03,920 --> 00:59:07,280
Speaker 10: be on being transparent, explaining why that's the case, and

1177
00:59:07,320 --> 00:59:09,520
Speaker 10: making sure that the public is informed about everything that

1178
00:59:09,560 --> 00:59:12,640
Speaker 10: we're looking at so they know, you know, what's accurate

1179
00:59:12,680 --> 00:59:15,160
Speaker 10: information that's out there about the race call, the and

1180
00:59:15,240 --> 00:59:16,680
Speaker 10: the process of getting to a winner.

1181
00:59:16,760 --> 00:59:18,040
Speaker 2: We just want to know when we're going to see

1182
00:59:18,040 --> 00:59:20,240
Speaker 2: our families again, Julie, if you have any reporting on.

1183
00:59:20,200 --> 00:59:22,240
Speaker 10: That, that would I wish I knew when I was

1184
00:59:22,240 --> 00:59:24,800
Speaker 10: going to see my family again too, So if anybody

1185
00:59:24,800 --> 00:59:26,040
Speaker 10: has any information, let me know.

1186
00:59:26,240 --> 00:59:28,120
Speaker 2: I bet that's true. We've only got a minute or

1187
00:59:28,200 --> 00:59:30,800
Speaker 2: so left. Does this not come This job that you

1188
00:59:30,840 --> 00:59:33,440
Speaker 2: call the most important act in journalism come with an

1189
00:59:33,560 --> 00:59:36,520
Speaker 2: enormous amount of added stress after what we experienced four

1190
00:59:36,600 --> 00:59:37,120
Speaker 2: years ago.

1191
00:59:37,960 --> 00:59:40,960
Speaker 10: Look, it's certainly not something that's easy, and you know,

1192
00:59:41,000 --> 00:59:43,440
Speaker 10: we often say to ourselves here, you know, if it

1193
00:59:43,520 --> 00:59:45,720
Speaker 10: was easy, everybody would do this. You know, we've been

1194
00:59:45,720 --> 00:59:47,840
Speaker 10: doing this for one hundred and seventy five years because

1195
00:59:48,080 --> 00:59:50,040
Speaker 10: we think it's an enormous public service and that's what

1196
00:59:50,080 --> 00:59:52,920
Speaker 10: the Associated Press is about. We're about public service journalism.

1197
00:59:52,960 --> 00:59:56,320
Speaker 10: And without that Federal Elections Agency, it was really into

1198
00:59:56,400 --> 00:59:59,160
Speaker 10: that void that the AP really at the founding of

1199
00:59:59,200 --> 01:00:02,040
Speaker 10: our organization, really stepped in and we've been doing this,

1200
01:00:02,120 --> 01:00:04,560
Speaker 10: carrying this mission out ever since. And I hope you know,

1201
01:00:04,600 --> 01:00:07,400
Speaker 10: what the public understands is that that same AP that

1202
01:00:07,440 --> 01:00:10,400
Speaker 10: has been calling these races all these years, that people

1203
01:00:10,440 --> 01:00:13,080
Speaker 10: have relied on and trusted and believed in, it's the

1204
01:00:13,120 --> 01:00:16,280
Speaker 10: same organization making those calls this time around. And I

1205
01:00:16,320 --> 01:00:19,760
Speaker 10: hope that that long history and that long record of accuracy,

1206
01:00:19,920 --> 01:00:22,160
Speaker 10: you know, will matter when people are making their decisions

1207
01:00:22,200 --> 01:00:24,000
Speaker 10: about what information to trust.

1208
01:00:24,160 --> 01:00:26,080
Speaker 2: We actually got to put a face on it here,

1209
01:00:26,400 --> 01:00:29,000
Speaker 2: Remember Julie Pace when you hear these calls being made

1210
01:00:29,080 --> 01:00:32,400
Speaker 2: next week, A world class journalist and executive editor the

1211
01:00:32,440 --> 01:00:35,680
Speaker 2: Associated Press. Julie, thank you so much for the seminar

1212
01:00:35,840 --> 01:00:38,520
Speaker 2: on how the AP calls races. The Decision Team, by

1213
01:00:38,520 --> 01:00:41,240
Speaker 2: the way, will declare at least six eight hundred and

1214
01:00:41,320 --> 01:00:45,840
Speaker 2: twenty three winners federal, state, and local races next week,

1215
01:00:46,160 --> 01:00:50,280
Speaker 2: with special coverage here on Tuesday on Bloomberg TV and radio.

1216
01:00:52,560 --> 01:00:55,760
Speaker 2: Thanks for listening to the Balance of Power podcast. Make

1217
01:00:55,800 --> 01:00:58,880
Speaker 2: sure to subscribe if you haven't already, Apple, Spotify, or

1218
01:00:58,920 --> 01:01:01,600
Speaker 2: wherever you get your podcasts, and you can find us

1219
01:01:01,640 --> 01:01:05,160
Speaker 2: live every weekday from Washington, DC at noontime Eastern at

1220
01:01:05,200 --> 01:01:06,720
Speaker 2: Bloomberg dot com.