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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg

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Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern

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Speaker 1: on Apple car Play or Android Auto with the Bloomberg

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

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Speaker 1: or watch us live on YouTube for this from.

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Speaker 2: Blackrock Wailey in studio. Thrilled to have you here, with

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Speaker 2: immense respect for your profound accomplishments as a kid. And

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Speaker 2: you were in China and then you went to Singapore,

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Speaker 2: right it's somewhere. Did you go through the H one

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Speaker 2: B visa process years ago?

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Speaker 3: I didn't because I'm working. I'm based in London right now,

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Speaker 3: I have a l one A. I think I need

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Speaker 3: to remember that as against custom every time.

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Speaker 2: What are your thoughts on this? You know it's the

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Speaker 2: bar charts are India with a huge impact and then

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Speaker 2: China is an impact away from the politics of it.

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Speaker 2: What are your thoughts on it?

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Speaker 3: I think that represents near tom uncertainty, especially facing I

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Speaker 3: guess smaller companies. I think this is another example why

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Speaker 3: we have to focus on fundamentals and pricing power of

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Speaker 3: large companies as we think about being selective the zechist.

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Speaker 2: This weekend, You're wonderful on LinkedIn pushing back against it

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Speaker 2: is worry, worry AI, worry more worry, worry, worry AI.

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Speaker 2: That's normal in a bull market.

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Speaker 4: Isn't it. I think so.

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Speaker 3: I think so, and I think it's worth remembering that

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Speaker 3: bull markets do not die from valuation. And even if

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Speaker 3: there is more focus around valuations right now, our study

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Speaker 3: shows that it's not really as stretched as you would

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Speaker 3: have expected looking at price appreciation. You look at magnificent

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Speaker 3: seven right now, at thirty two times, PE is actually

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Speaker 3: lower than the level at the beginning of the year

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Speaker 3: because of the very strong earnings delivery and earnings upgrade,

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Speaker 3: so we think that there is more to go.

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Speaker 5: Our study shows that for US Tech.

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Speaker 3: More broadly, if they deliver earning in the region from

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Speaker 3: fifteen percent to twenty percent, their current multiple is maybe

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Speaker 3: even higher than that can be very well supported. And

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Speaker 3: now you may ask, you know, fifteen twenty that sounds

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Speaker 3: like a lot, but looking back thirty years, a quarter

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Speaker 3: of those period actually have seen US Tech growing earnings

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Speaker 3: that strongly, right, so you know it's doable.

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Speaker 4: That's doable.

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Speaker 6: I think that the AI believers are firm believers in

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Speaker 6: AI how about the rest of the world, the four

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Speaker 6: hundred and ninety three other stocks in the S and

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Speaker 6: P five hundred, how do you guys approach those names?

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Speaker 3: You know, right now we're in this let's quite lucky

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Speaker 3: juncture where we have the FED restarting raycut cycle and

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Speaker 3: the labor market is supporting that rate cut direction of

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Speaker 3: travel without it then becoming a big political debate in

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Speaker 3: terms of fat independence, but also then what it means

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Speaker 3: for long end of the curve and term premiere. So

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Speaker 3: right now, the FAT is starting restarting fat rate cuts

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Speaker 3: and growth is holding up. Okay, we're looking at one

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Speaker 3: point five percent for your economy this year. It's very

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Speaker 3: far from recession. Earnings a strong so it's a good

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Speaker 3: mix that can continue to support risk assets. Now the

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Speaker 3: question is just for how long this lucky combination will last.

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Speaker 3: So we're very much paying attention to you know, if

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Speaker 3: labor market deterioration is a precursor of something worse to

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Speaker 3: come on a growth front, it's not our expectation, but

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Speaker 3: you know, lots of uncertainty.

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Speaker 6: You say you're staying risk on, how does that apply

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Speaker 6: to the fixed income market? Are you are you staying

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Speaker 6: with it in the treasury market where you can get more,

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Speaker 6: you can get four percent for change on a tenure,

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Speaker 6: or do it take some credit risk our credit.

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Speaker 3: We have had the preference for credit over long duration

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Speaker 3: for a while, and you look at how ig spread

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Speaker 3: is at close to multi decades low will actually add

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Speaker 3: multi decay load. That has been a good call. But

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Speaker 3: at this juncture, at this particular juncture, we do think

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Speaker 3: that there is room to extend out duration exposure a

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Speaker 3: little bit because we see this lucky mix of labor

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Speaker 3: market supporting fact cuts and just generally markets are focusing

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Speaker 3: on that. So we want to lock in some of

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Speaker 3: the attractive long duration radios in the US.

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Speaker 2: In the technology juggernaut that you've let on, where is

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Speaker 2: use of cash? Obviously they're doing a capex. Does Blackrock

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Speaker 2: see evidence of a return and invest in capital from

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Speaker 2: this capex balloon or does that wait?

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Speaker 3: We have seen significant growth in our cash business because

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Speaker 3: there is a huge amount of cash on the sizeline

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Speaker 3: from an investment portfolio perspective. But to your point about

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Speaker 3: return on investment for copex deployment, that's actually one thing

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Speaker 3: that we're paying close attention to to understand if momentum

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Speaker 3: of the AI trade could potentially shift, you know, as

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Speaker 3: we think about sectors outside of technology also kind of

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Speaker 3: getting very focused around AI adoption as we go from

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Speaker 3: capital lights to capital intensive kind of deployment. It has

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Speaker 3: significant impact on return on equity. So we're paying attention

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Speaker 3: to return on all this copex spend, but it would

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Speaker 3: take time, and right now, what exes look like the

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Speaker 3: axis axis is twenty seven nine. You mean intensive return

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Speaker 3: on investment?

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Speaker 2: When are we going to find out why Facebook is

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Speaker 2: spending all that jillions? And it's going to be an

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Speaker 2: ability to do an excess spreadsheet at black Rock to

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Speaker 2: figure out what the return is.

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Speaker 3: I would say that actually it's remarkably hard to get

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Speaker 3: present a number you've written an investment for these capex

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Speaker 3: because it's quite well hidden and they're not obligated to

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Speaker 3: report them in a very precise form. But I would

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Speaker 3: make the general observation that markets are letting them off

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Speaker 3: the hook right now because it's really an existential build

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Speaker 3: out race. You're either spending and overspending to stay in

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Speaker 3: the game and stay on the table, or you will

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Speaker 3: be viewed as well. You won't be part of the

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Speaker 3: future mix, right so I think markets are giving the

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Speaker 3: tech companies some leeway to spend and overspend. We pay

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Speaker 3: attention to free cash flow as a percentage of free

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Speaker 3: cash flow. It's gone up quite a bit in terms

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Speaker 3: of the kapex SU spent, but not to a level

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Speaker 3: that they can't afford, not to mention, they can always

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Speaker 3: tap into funding market public and private to raise additional

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Speaker 3: cash to spend. Right So, you know, like right now,

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Speaker 3: it's still early in this journey and we see all

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Speaker 3: systems go when it comes to AI build out.

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Speaker 6: How do you, guys as chief investment strategies, what screens

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Speaker 6: well for you these days? Are you screening on industries, factors?

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Speaker 6: How are you kind of looking at markets and opportunities

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Speaker 6: these days broadly?

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Speaker 3: Well, we have liked we have like growthy type of

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Speaker 3: names because we want to focus on companies that can

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Speaker 3: really give exposure to exponential growth opportunities related to AI.

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Speaker 3: But we also just think broader market given the lucky

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Speaker 3: combination of fact cuts growth holding up. Okay, earnings are

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Speaker 3: reasonably well delivered so far as opposed to broader market. Yeah,

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Speaker 3: we focus on the TAG and the EI complex, but

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Speaker 3: generally we have an overweight to the broader US acquity

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Speaker 3: market that includes the smaller caps compared to the mega

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Speaker 3: tech companies in the international market. We're more selective, right, Like,

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Speaker 3: so you're in Europe, we like defense, we like we

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Speaker 3: like financials, we like industrials as a sector pick rather

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Speaker 3: than across the across the board. Do you look to

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Speaker 3: the emergent market? You know, like being selective would have

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Speaker 3: paid off well so far this year as well. You know,

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Speaker 3: the hands and healthcare indexes up more than one hundred percent.

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Speaker 2: Are you flying into Heathrow today.

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Speaker 3: On Thursday or maybe even over the weekend?

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Speaker 2: Traffic congestion or something? So some software went down.

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Speaker 4: I came you over the weekend.

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Speaker 3: It was actually quite smooth.

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Speaker 2: We'll see mischic think you just go, Larry, can I

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Speaker 2: get the golf stream.

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Speaker 5: When you ask?

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Speaker 3: On my behalf greatly?

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Speaker 2: Thank you so much. It is with Blackrock. Can't say

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Speaker 2: enough about her contribution to the zeitgeist on LinkedIn. She

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Speaker 2: had a beautiful Bard shirt piecing together showing this huge

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Speaker 2: technology investment. Uh that's out there and you know it's

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Speaker 2: interesting to see, Uh, to say the least. Stay with us.

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Speaker 2: More from Bloomberg Surveillance coming up after.

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Speaker 1: This you're listening to the Bloomberg Surveillance Podcast. Catch us

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Speaker 1: live weekday afternoons from seven to ten am Eastern Listen

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Speaker 1: on Applecarplay and Android Otto with the Bloomberg Business app,

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Speaker 1: or watch us live on YouTube.

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Speaker 2: A good time now with Yen's Nordvig of ACCENTI data

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Speaker 2: all of his experience, including with Namur and goldn Sachs

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Speaker 2: over the years, and it can be on foreign exchange.

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Speaker 2: But you know, folks, of the one hundred and forty

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Speaker 2: two books that came out out of the crisis, they

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Speaker 2: are like five or six that had traction. Shout out

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Speaker 2: Andrew ros Serkin's book of seven I thought was really good,

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Speaker 2: as he launches a new one here. The follow of

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Speaker 2: the euro reinventing the Euros on YenS Nordvig was absolutely

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Speaker 2: I called it a primal scream. It was just it

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Speaker 2: was so visceral. You have to be from Denmark to

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Speaker 2: do that. If you're from America, you're too polite. It

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Speaker 2: was so visceral. If you were to rewrite a book

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Speaker 2: in the euro now, what would you title it?

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Speaker 5: The challenges are still there. This challenge is still there.

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Speaker 2: Zurosclerousa is still in place.

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Speaker 5: We still have a weak growth done and we've had

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Speaker 5: we've had a wake up call this year. Right, So

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Speaker 5: we've had deflationary forces in Europe for the last ten years,

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Speaker 5: as we spoke about, and then we had the COVID

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Speaker 5: shock and all of that change, so that's gone. And

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Speaker 5: then Germany have done something pretty dramatic right in terms

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Speaker 5: of escaping the fiscal rules, so that was triggered by

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Speaker 5: triggered by the US. Pauls have changed as well.

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Speaker 6: So it seems like Europe is trying to spend its

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Speaker 6: way out of its malaise, whether it's induced by the

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Speaker 6: US change in policy. But I think there's questions about,

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Speaker 6: all right, maybe Germany can get it done, maybe even

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Speaker 6: Poland can get it done, because I point the right

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Speaker 6: in the backyard of Russia it's in their best interest, But.

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Speaker 4: How about everybody else?

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Speaker 2: What's the rest of you are.

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Speaker 6: Going to do in terms of trying to lift their

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Speaker 6: they're spending levels.

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Speaker 5: Yeah, Like the fundamental issue is that we used to

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Speaker 5: in Europe for many decades to always have like the

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Speaker 5: center of the politics was driving what was happening. So

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Speaker 5: you had social democratic parties like a little bit to

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Speaker 5: the left of center, and and then you had another

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Speaker 5: centrist party a little bit to the right of the center,

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Speaker 5: but they more or less did the same type of

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Speaker 5: policies and they agreed on most things. And now you

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Speaker 5: don't have that anymore. You can see in France like

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Speaker 5: the center has like been annihilated, right, mess, Yeah, and

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Speaker 5: it's in many different countries.

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Speaker 2: Is it just another mess or is there something original

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Speaker 2: this time about more protesting?

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Speaker 5: I think we'll we're waiting for an election result where

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Speaker 5: there's actually going to be one of these far right,

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Speaker 5: far left parties coming to power. Like at the moment,

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Speaker 5: the center is getting small and smaller, but still staying

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Speaker 5: in power and almost all countries, right, So the real

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Speaker 5: test this will be when these non centrist forties actually

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Speaker 5: get into power and they have to decide what they

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Speaker 5: what they do. And I think in relation to your

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Speaker 5: question right about military spending, right, so it's clearly going

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Speaker 5: up across the whole of the EU, Germany leading, and

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Speaker 5: the fear of Russia is driving that, but it's not

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Speaker 5: every country like Spain is not doing much like so

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Speaker 5: so if you average it out, it's certainly not as

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Speaker 5: dramatic as if you just look at Germany alone the

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Speaker 5: US dollar.

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Speaker 6: We had the FX annals from City City in your

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Speaker 6: street just probably a half hour ago saying he's polished

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Speaker 6: on the US dollar and he feels pretty empty alone

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Speaker 6: out there, pretty lonely out there. What's your view of

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Speaker 6: the dollar? He does not bounce back like everything else

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Speaker 6: seems to bounce back.

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Speaker 5: Yeah. So there's a huge debate going on at the

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Speaker 5: moment about, Okay, what's happening with dollar hedging? Right? So

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Speaker 5: on our data platform, we have a whole section that's

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Speaker 5: dedicated to this specifically, right, because you can track it

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Speaker 5: in many ways. There's been a lot of writing, including

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Speaker 5: on Bloomberg in the last couple of weeks, about oh,

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Speaker 5: if you look at the ETF flows, they show a

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Speaker 5: lot of people are buying US acid but with a

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Speaker 5: hedge on top. I think that's it's very tricky to

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Speaker 5: just use the ETFs because a lot of institutional flow

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Speaker 5: don't happen in ETF space, right, So you can have

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Speaker 5: pension funds that do big changes and you will not

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Speaker 5: see anything in ETF. So I think the big picture

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Speaker 5: is the following. We've been through, you know, three phases

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Speaker 5: in terms of like dollar flows, where we came into

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Speaker 5: this year, people still believed in US exceptionalism, still bought

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Speaker 5: US stocks. Tech was the dominant theme. Then we had

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Speaker 5: all the policy uncertainty, reciprocal tariffs. We also had the

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Speaker 5: German fiscal stimulus that people saw, okay, maybe there's an alternative, right,

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Speaker 5: And we had a period where actually inflows into the

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Speaker 5: US where smaller than inflows into other international competitors. And

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Speaker 5: then in the last couple of months it's like kind

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Speaker 5: of like a gray song. We're not back to US exceptionalism,

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Speaker 5: but the US is recovering. There is a bit more

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Speaker 5: flow coming in, so it's it's sort of a gray song.

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Speaker 5: So in my forecast for the dollar, I now put

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Speaker 5: less weight on sort of very negative flows as a

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Speaker 5: drive of the dollar. I put more weight on the FED. Again,

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Speaker 5: so since my company specialized in the flow, maybe I'm

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Speaker 5: being kind of like under budding. But we also do

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Speaker 5: some FED analysis and and that's really been the key.

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Speaker 5: You can see it in the correlations like the dollar

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Speaker 5: and US interest rates super highly correlated. Again, there was

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Speaker 5: no correlation at all in April May.

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Speaker 2: Okay, I got I gotta get quickly because i'mnna do

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Speaker 2: an audible. What's your what's your euro call? Here?

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Speaker 5: At twelve months, I think we're going to be grinding higher.

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Speaker 5: I think we're going to be stronger. I think the

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Speaker 5: euro can be grinding high differ.

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Speaker 2: Yeah, it's great, Okay, we're doing audio against Nordvik with

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Speaker 2: us right now. And again his book was just absolutely fabulous.

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Speaker 2: I learned this the hard way. Patrick O'Brien wrote a

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Speaker 2: book called The Surgeon's Mate. In America, most people study

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Speaker 2: the Baltic Sea for two days in ninth grade, and

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Speaker 2: that's a combined knowledge. We don't have any understanding of

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Speaker 2: the world. You grew up in Copenhagen by boat, sixteen

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Speaker 2: hundred miles from Russia, Saint Petersburg, the Baltic States. We've

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Speaker 2: got testing of Russian planes in Estonia right now. It

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Speaker 2: bare barely moves the needle here in America. I want

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Speaker 2: you to explain to our American audience here that this

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Speaker 2: ginormous brackish Baltic Sea with Denmark at the isthmus of it,

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Speaker 2: where you come out the importance of that to the

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Speaker 2: Western Alliance.

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Speaker 5: Well, maybe i'll give you a one minute.

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Speaker 4: History lesson, please, So all the.

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Speaker 5: Traffic that comes by ship from Russia, Poland Baltic nations,

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Speaker 5: so for what have to go through a tiny little

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Speaker 5: gap between Sweden and Denmark. The reason why Copenhagen used

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Speaker 5: to be a very wealthy city was that they collected

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Speaker 5: taxi taxes from all those ships and they had a

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Speaker 5: cannon in place, so if they didn't pay the tax,

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Speaker 5: they would just shoot this ship down. And that's literally

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Speaker 5: the reason why Copenhagen was a wealthy city very early on.

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Speaker 5: And obviously now we have tension in the Baltic Sea

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Speaker 5: right because we have you knowlitary military aircraft doing things

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Speaker 5: they're not supposed to do, so there's a lot of

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Speaker 5: tension in that area. Like one card that Western nations

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Speaker 5: could play was to actually control if they really wanted

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Speaker 5: to control that waters, like logistically they used to do

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Speaker 5: with one cannon, so it could be done. I think

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Speaker 5: part of the problem we have in the EU in

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Speaker 5: relation to Russia is that the EU and the European

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Speaker 5: are so afraid to escalate, right that those cards that

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Speaker 5: they actually have that could be very powerful cards are

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Speaker 5: just not not they're not being played, but they're not

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Speaker 5: even being talked about. So that was a that was

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Speaker 5: a more than one minute, but they gave you a

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Speaker 5: little bit of because we got there.

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Speaker 2: We got the Greenland distraction. Who's winning in Greenland today

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Speaker 2: is the US or Denmark? I mean, you've got this

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Speaker 2: whole Greenland distraction. Meanwhile, we have jets over NATO countries.

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Speaker 2: I mean it is bizarre. Right now, Denmark is building

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Speaker 2: up their military capabilities, right.

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Speaker 5: That's right, that's just an investment into air defense system,

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Speaker 5: like multimillion investments, right. And the interesting part about that

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Speaker 5: was that it was announced as an investment that also

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Speaker 5: had offensive capability, right, because the Prime Minister essentially said, like,

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Speaker 5: there's no point in only having If you only have defenses,

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Speaker 5: then how you're going to scare the aggressive on that.

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Speaker 2: Line with the technology of Stockholm and you know no

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Speaker 2: key years ago in that. Are you a believer that

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Speaker 2: Europe can get their technology act together?

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Speaker 5: I think you're seeing some signs of hope in countries

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Speaker 5: like Germany, where there's actually a bunch of AI startups

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Speaker 5: in robotics, AI robotics some people call the real world AI, right,

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Speaker 5: not just in a digital domain. So I think the

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Speaker 5: resource that Europe still has is that we have an

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Speaker 5: education system that still delivers a lot of well educated engineers,

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Speaker 5: computer sciences and so forth, so the human resource materials there,

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Speaker 5: maybe it will matter a few of those people go

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Speaker 5: to the United States and get an age one bbs. Right,

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Speaker 5: So there's all these different things happening right now where

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Speaker 5: the sort of relative force of the different labor market

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Speaker 5: is shifting.

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Speaker 2: Did you have an H and B visa when you

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Speaker 2: first came here?

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Speaker 5: I did not know.

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Speaker 2: I did.

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Speaker 5: I was with Goldvin Sacks in London and I did

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Speaker 5: a transfer with Goldman Sachs, So that's a different visus.

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Speaker 2: Excuse me, the embassy of Goldman Sachs picks up a.

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Speaker 4: Phone and it's done.

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Speaker 2: Yes, talk to us.

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Speaker 4: From when you're talking to your clients globally.

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Speaker 6: What's the level of concern, if any, about the independence

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Speaker 6: of the US fedter Reserve these days?

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Speaker 5: Well, very very elevated concern. I have a lot of

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Speaker 5: clients around the world right that invest in macro assets

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Speaker 5: on a very broad basis, including emergen market assets, and

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Speaker 5: those investors have a lot of experience and a lot

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Speaker 5: of you know, lessons that they drawn from being involved

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Speaker 5: in countries where central bank independence was a real problem

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Speaker 5: and it caused massive, massive asm moves when when essentially

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Speaker 5: the government took over the central bank or forced the

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Speaker 5: central bank to do certain things. We've seen that in Turkey, right,

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Speaker 5: where the government has pushed through certain to easy monetary policy, right,

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Speaker 5: and the currency has seen disastrous depreciation. So people have

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Speaker 5: those lessons in the back of the head, right, And

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Speaker 5: then it's a matter of Okay, what degree are we

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Speaker 5: going down? There's a path. We've certainly already taken a

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Speaker 5: step down this path.

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Speaker 2: Right.

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Speaker 5: You can see it in the dot plot. Right, you

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Speaker 5: had you had a new governor, right that had a

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Speaker 5: dot that was totally out of whack with all the

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Speaker 5: other dots. Right. So it's it's very clear that we're

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Speaker 5: going in that direction. But the question is whether it's

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Speaker 5: really dry policy.

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Speaker 2: Right.

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Speaker 5: You also saw that we only had one descent. So

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Speaker 5: it's all almost like the voting members of the f

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Speaker 5: m C decided mostly to say, Okay, we're actually going

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Speaker 5: to try to show a degree of consensus. There's one

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Speaker 5: dot we cannot do anything about, but we're trying to

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Speaker 5: do a degree of consensus about that audible.

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Speaker 2: We got to get this in before we go to

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Speaker 2: Michael Byron. One quick question, bestent of the Treasuries out

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Speaker 2: with a wide set of headlines. US is ready to

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Speaker 2: do what's needed to support Argentina. In a tweet, the

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Speaker 2: Secretary said, they want to make Argentina great again. Okay,

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Speaker 2: are you lying the Argentinian paeso because we're going to

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Speaker 2: bail out Argentina.

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Speaker 5: This is really interesting. We have a situation right where

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Speaker 5: the United States kind of has a fight with Brazil,

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Speaker 5: including terror, very elevated channel from Brazil that are mostly

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Speaker 5: based on a political tension with what is haptable scenarow right,

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Speaker 5: and now we have a situation where Argentina potentially might

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Speaker 5: get very favorable toreat and something that really has potentially

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Speaker 5: not happened since the Clinton bailout of Mexico, so very rare,

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Speaker 5: and it's happening because they like the leadership in Argentina playoffs,

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Speaker 5: So it's it becomes a situation where it's the relationships

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Speaker 5: at the highest level in government, including internationally, that might

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Speaker 5: determine really who gets tariffed, who gets support. And this

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Speaker 5: is a new regime we're in. This would have not

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Speaker 5: happen like this a couple of months ago, what should

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Speaker 5: we say, seven months ago? So new, new, new regime.

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Speaker 2: Don't be strange. He has Nord. Thank you so much.

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Speaker 2: Excity Data can't see enough of out his book of

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Speaker 2: a decade ago plus in the euro We looked for

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Speaker 2: another one out here. If missus Nordvigil to write volume four,

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Speaker 2: whatever it is, stay with us. More from Bloomberg Surveillance

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Speaker 2: coming up after this.

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Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday

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00:23:18,520 --> 00:23:21,919
Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto

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00:23:21,960 --> 00:23:24,920
Speaker 1: with the Bloomberg Business app. You can also listen live

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00:23:25,000 --> 00:23:28,560
Speaker 1: on Amazon Alexa from our flagship New York station, Just

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00:23:28,600 --> 00:23:31,159
Speaker 1: say Alexa Play Bloomberg eleven thirty.

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Speaker 2: Michelle Meyer with us the master Card. It's a first

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Speaker 2: look at the holiday season. I'm going to round up

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Speaker 2: the numbers because it's Monday. Online shopping up eight percent,

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Speaker 2: store shopping up two percent. Is that because the technology

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Speaker 2: and we like our Amazon boxes or is there a

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Speaker 2: backstory to that at MasterCard?

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Speaker 7: I mean, I think the technology and the digitalization of

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Speaker 7: the retail space has been happening for years and that

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Speaker 7: has been driving e commerce to see.

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Speaker 4: Faster growth rate to the last years.

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Speaker 7: But I do think there also is a specific story

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Speaker 7: this year which is around tariffs, and they need to

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Speaker 7: have even greater price discovery for consumers that are facing

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Speaker 7: varied prices depending on that sensitivity to tariffs, they're going

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Speaker 7: to want to be able to get the best deal

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Speaker 7: that's out there and find that value. And you can

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Speaker 7: do a lot more of that online.

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Speaker 6: So how is the consumer here? We had some retail

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Speaker 6: sales that look pretty darn solid.

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Speaker 4: So how do you feel the consumer these days?

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Speaker 7: I mean, I think the data is speaking really loudly

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Speaker 7: right now, which is that consumers are still engaged in spending.

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Speaker 7: You see it, as you just noted in the.

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Speaker 5: Censuspure of retail sales reports the last.

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Speaker 7: Few months showing some real healthy spend trends, and we

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Speaker 7: see it in our own insights as well with our

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Speaker 7: spending pool data that showed acceleration throughout the summer. So yes,

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Speaker 7: consumers are making choices in how they're using their purchasing power,

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Speaker 7: and I think a lot of that has to do

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Speaker 7: with where, again, they find the most value. They're trying

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Speaker 7: to navigate the tariff environment to the best of their ability,

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Speaker 7: and the sales numbers that we're looking at are of

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Speaker 7: course nominal sales, and we are still to see a

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Speaker 7: little bit higher goods inflation than certainly we saw this

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Speaker 7: time last year.

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Speaker 2: Will you break it down in your special MasterCard report

440
00:25:07,760 --> 00:25:11,119
Speaker 2: with smiling people on the cover because they're happy to

441
00:25:11,240 --> 00:25:16,040
Speaker 2: start shopping in September. Artificial Christmas trees, the tariff is

442
00:25:16,040 --> 00:25:19,720
Speaker 2: twenty seven yea percent. You're like the budget lab at Yale,

443
00:25:19,760 --> 00:25:23,439
Speaker 2: I mean, what is the calculation of tariff impact right now?

444
00:25:24,040 --> 00:25:26,520
Speaker 7: Absolutely, so we looked at just the data that the

445
00:25:26,560 --> 00:25:30,400
Speaker 7: Census Bear reports in terms of the teriff freight by

446
00:25:30,800 --> 00:25:33,320
Speaker 7: really granular category, because that's what we like to do.

447
00:25:33,359 --> 00:25:35,720
Speaker 7: We like to go really deep in terms of understanding

448
00:25:36,000 --> 00:25:39,679
Speaker 7: consumer spending by different categories. And certainly you are seeing

449
00:25:39,760 --> 00:25:43,000
Speaker 7: some like artificial trees stood out as one where tariffs

450
00:25:43,000 --> 00:25:45,679
Speaker 7: are significantly high than this time last year. So consumers

451
00:25:45,720 --> 00:25:49,240
Speaker 7: have to make decisions if they do indeed see some

452
00:25:49,280 --> 00:25:52,760
Speaker 7: of those tariff increases passed on to them, and that's

453
00:25:52,760 --> 00:25:55,119
Speaker 7: a question of if. Because retailers are also trying to

454
00:25:55,200 --> 00:25:57,960
Speaker 7: navigate this, then they'll have to decide if they want

455
00:25:58,000 --> 00:26:00,640
Speaker 7: to allocate more of their dollars to get that Christmas

456
00:26:00,640 --> 00:26:03,080
Speaker 7: tree or do something different. So there's going to be

457
00:26:03,080 --> 00:26:05,920
Speaker 7: a certain amount of substitution, where, when and where it's

458
00:26:05,960 --> 00:26:08,480
Speaker 7: possible to do that based off of where tariffs are

459
00:26:08,560 --> 00:26:10,080
Speaker 7: kicking it and showing up in the data.

460
00:26:10,160 --> 00:26:12,720
Speaker 6: So your forecast, how do you think the holiday season

461
00:26:12,760 --> 00:26:13,320
Speaker 6: will shape up?

462
00:26:13,320 --> 00:26:14,800
Speaker 4: How do you think spending will be this holiday?

463
00:26:14,920 --> 00:26:17,959
Speaker 7: So Tom gave the breakdown between e commerce and in store,

464
00:26:18,040 --> 00:26:20,160
Speaker 7: but to give the overall numbers, we're looking for three

465
00:26:20,200 --> 00:26:24,200
Speaker 7: point six percent retail sales ex autos, which is measured

466
00:26:24,359 --> 00:26:27,480
Speaker 7: good from Yeah, it's November first, the December twenty fourth,

467
00:26:27,560 --> 00:26:30,560
Speaker 7: knowing that, of course the holiday season starts even earlier.

468
00:26:30,640 --> 00:26:33,080
Speaker 7: We think it's kicking off now, but it just.

469
00:26:33,040 --> 00:26:36,600
Speaker 2: For scraz You should start Friday after Thanksgiving.

470
00:26:36,720 --> 00:26:42,200
Speaker 5: Yes, things have changed, that's still a big day.

471
00:26:42,240 --> 00:26:44,800
Speaker 7: Of course, Black Friday period is super important and we'll

472
00:26:44,840 --> 00:26:47,159
Speaker 7: be monitoring it really closely to understand the trends for

473
00:26:47,200 --> 00:26:47,639
Speaker 7: the season.

474
00:26:48,240 --> 00:26:50,080
Speaker 4: All right, Michelle, thank you so much. Appreciate that.

475
00:26:50,160 --> 00:26:53,720
Speaker 6: Michelle mayor joining us here in our studio. Michelle Mayer's

476
00:26:53,720 --> 00:26:57,120
Speaker 6: a chief economist North America for Massacart Economics Institute.

477
00:26:57,200 --> 00:26:58,880
Speaker 4: Well, if they don't get up, if they don't have a.

478
00:26:58,800 --> 00:27:01,240
Speaker 6: Finger on the pulse of spending on who doesn't I

479
00:27:01,240 --> 00:27:03,080
Speaker 6: mean I'll be throwing down the carton.

480
00:27:03,240 --> 00:27:05,520
Speaker 2: Do you get to go to Formula one? Like McLaren,

481
00:27:05,520 --> 00:27:08,399
Speaker 2: do you get to go like? Are you going to Austin?

482
00:27:08,480 --> 00:27:09,280
Speaker 4: I went to Vegas?

483
00:27:09,320 --> 00:27:10,240
Speaker 2: You're going to Austin?

484
00:27:10,280 --> 00:27:11,080
Speaker 4: You are kidding here?

485
00:27:11,359 --> 00:27:17,840
Speaker 2: No McLaren, Lando and Oscar? Yes, yes, yes? Who do

486
00:27:17,880 --> 00:27:18,480
Speaker 2: you root for?

487
00:27:19,080 --> 00:27:19,520
Speaker 5: All of these?

488
00:27:19,800 --> 00:27:24,640
Speaker 2: Scott? Who do you root for? Sharaison is Gaga over Oscar?

489
00:27:24,840 --> 00:27:27,440
Speaker 2: Come on, Oscar Orlando? We need to know.

490
00:27:29,200 --> 00:27:31,960
Speaker 7: Maybe Lando a little bit more, but Oscar's great to

491
00:27:32,080 --> 00:27:35,000
Speaker 7: I don't want to you know anybody wearing THO McLaren

492
00:27:35,040 --> 00:27:35,439
Speaker 7: colors on the.

493
00:27:35,600 --> 00:27:41,000
Speaker 2: Bottle it Michelle Meyer, Orlando crush. That's what I learned

494
00:27:41,040 --> 00:27:46,480
Speaker 2: today is the chief ecotomist. I'll carry your bags, the

495
00:27:46,560 --> 00:27:50,560
Speaker 2: Lewis Street luggage. You've got to Austin. I'll carry your bags.

496
00:27:50,840 --> 00:27:53,760
Speaker 2: Michell Meyer, Thank you so much. Stay with us. More

497
00:27:53,880 --> 00:28:04,199
Speaker 2: from Bloomberg Surveillance coming up after this.

498
00:28:04,200 --> 00:28:08,080
Speaker 1: This is the Bloomberg Surveillance podcast. Listen live each weekday

499
00:28:08,160 --> 00:28:11,159
Speaker 1: starting at seven am Eastern on Apple, Coarplay, and Android

500
00:28:11,200 --> 00:28:14,160
Speaker 1: Auto with the Bloomberg Business app. You can also watch

501
00:28:14,280 --> 00:28:17,199
Speaker 1: us live every weekday on YouTube and always on the

502
00:28:17,240 --> 00:28:18,280
Speaker 1: Bloomberg terminal.

503
00:28:18,440 --> 00:28:21,119
Speaker 2: What a great set of conversations today in this H

504
00:28:21,160 --> 00:28:24,199
Speaker 2: one V up forth. Thank you Josh Wingrove and our

505
00:28:24,240 --> 00:28:27,600
Speaker 2: team in Washington who broke that story. Huge impact by

506
00:28:27,600 --> 00:28:32,000
Speaker 2: Bloomberg News in our White House correspondence over the weekend.

507
00:28:32,119 --> 00:28:34,800
Speaker 2: We continue strong with god A mcinda joining us from

508
00:28:34,800 --> 00:28:38,680
Speaker 2: Bloomberg Opinion and also Yale School of Management. Okay, you

509
00:28:38,720 --> 00:28:41,280
Speaker 2: grew up in America, but you know the entire H

510
00:28:41,320 --> 00:28:45,960
Speaker 2: one B Malsterman in all that one hundred and fifty

511
00:28:46,040 --> 00:28:51,000
Speaker 2: thousand engineering graduates in America ten times, at eight times,

512
00:28:51,040 --> 00:28:55,520
Speaker 2: at whatever in India. I get the people that want

513
00:28:55,560 --> 00:28:59,760
Speaker 2: Americans to have jobs. But in your study, is there

514
00:28:59,800 --> 00:29:06,440
Speaker 2: anyway American engineering talent can make what percent of the

515
00:29:06,520 --> 00:29:08,280
Speaker 2: present H one B pool?

516
00:29:08,880 --> 00:29:10,120
Speaker 4: So it's not even close.

517
00:29:10,200 --> 00:29:12,640
Speaker 8: So H one b's are a huge supplement, and because

518
00:29:12,680 --> 00:29:15,719
Speaker 8: they're so hard to get, they're particularly sort of value added.

519
00:29:16,000 --> 00:29:16,160
Speaker 2: Right.

520
00:29:16,200 --> 00:29:18,479
Speaker 8: Well, what we actually see from H one b's is

521
00:29:18,520 --> 00:29:21,959
Speaker 8: they create jobs for American engineers because of right, because

522
00:29:22,200 --> 00:29:23,960
Speaker 8: that makes it easier to create companies, It makes it

523
00:29:24,000 --> 00:29:26,320
Speaker 8: easier to dumb it to lead in high skilled industries,

524
00:29:26,560 --> 00:29:28,480
Speaker 8: and so it's not a zero sum game. They don't

525
00:29:28,520 --> 00:29:29,680
Speaker 8: push out American engineers.

526
00:29:29,800 --> 00:29:33,360
Speaker 2: Okay, but help our audience. If there's one hundred jobs created,

527
00:29:33,920 --> 00:29:38,120
Speaker 2: how many can be people from Georgia Tech, Texas A

528
00:29:38,240 --> 00:29:42,120
Speaker 2: and m cal Tech. Is it like twenty thirty? Is

529
00:29:42,160 --> 00:29:44,560
Speaker 2: it eighty nine out of one hundred?

530
00:29:44,120 --> 00:29:48,000
Speaker 4: So in the US, So your thing as the proportion

531
00:29:48,080 --> 00:29:49,240
Speaker 4: of the h one d's.

532
00:29:49,080 --> 00:29:51,440
Speaker 2: If we eliminate H one B, how many of those

533
00:29:51,480 --> 00:29:54,000
Speaker 2: one hundred h one B jobs are going to be

534
00:29:54,040 --> 00:29:55,560
Speaker 2: taken by American engineers?

535
00:29:56,040 --> 00:29:58,600
Speaker 8: Oh so till we run out of engineers? Yes, so

536
00:29:58,640 --> 00:30:00,400
Speaker 8: it's one as we've run out of engineers. So the

537
00:30:00,440 --> 00:30:02,720
Speaker 8: problem isn't just that, it's that, you know, maybe twenty

538
00:30:02,760 --> 00:30:04,720
Speaker 8: or thirty of those were taken. It's that twenty or thirty,

539
00:30:04,840 --> 00:30:08,160
Speaker 8: But then we would lose fifty or sixty other American

540
00:30:08,200 --> 00:30:12,040
Speaker 8: engineering jobs from companies that aren't created, that don't grow

541
00:30:12,160 --> 00:30:14,160
Speaker 8: because they don't have access to this engineering count. The

542
00:30:14,160 --> 00:30:17,200
Speaker 8: total number of engineering of the total employment for American

543
00:30:17,240 --> 00:30:20,440
Speaker 8: engineers in the United States will go down, not up,

544
00:30:20,480 --> 00:30:20,960
Speaker 8: because of this.

545
00:30:21,640 --> 00:30:24,840
Speaker 6: Presumably the tech industry is one of the ones, if

546
00:30:24,880 --> 00:30:27,640
Speaker 6: not the most impacted here. Yet I don't hear much

547
00:30:27,680 --> 00:30:30,480
Speaker 6: from technology leaders. In fact, I see them accompanying the

548
00:30:30,480 --> 00:30:35,440
Speaker 6: President at various events, including over in London last week for.

549
00:30:35,400 --> 00:30:36,240
Speaker 4: His state visit.

550
00:30:37,280 --> 00:30:39,680
Speaker 6: Are you surprised that we haven't seen pushback from maybe

551
00:30:39,680 --> 00:30:42,880
Speaker 6: some corporate leadership or just some other business entities.

552
00:30:43,080 --> 00:30:44,000
Speaker 4: No, for two reasons.

553
00:30:44,080 --> 00:30:46,760
Speaker 8: The first is fear, right, Like, if you talk to

554
00:30:46,800 --> 00:30:49,040
Speaker 8: corporate leaders and you'll start starting to see people that

555
00:30:49,160 --> 00:30:51,280
Speaker 8: was the l CEO Sunit recently, where this was just

556
00:30:51,360 --> 00:30:52,320
Speaker 8: the consensus.

557
00:30:51,920 --> 00:30:53,080
Speaker 4: In the room.

558
00:30:53,280 --> 00:30:55,960
Speaker 8: Everybody is unhappy and no one wants to see say

559
00:30:55,960 --> 00:30:58,080
Speaker 8: anything about it because they think the president will come

560
00:30:58,080 --> 00:30:58,720
Speaker 8: after them if they do.

561
00:30:58,840 --> 00:30:58,920
Speaker 3: So.

562
00:30:59,080 --> 00:31:01,920
Speaker 8: Fear is a real company here. But the second is

563
00:31:02,440 --> 00:31:05,080
Speaker 8: the way this is structured is interesting in the way

564
00:31:05,120 --> 00:31:06,840
Speaker 8: it's done right. So there's this one hundred thousand dollars

565
00:31:06,840 --> 00:31:10,400
Speaker 8: fee which can be waived at the president's discretion for

566
00:31:10,480 --> 00:31:11,200
Speaker 8: any reason.

567
00:31:11,840 --> 00:31:13,160
Speaker 4: So in a real sense.

568
00:31:12,960 --> 00:31:15,920
Speaker 8: What this does is just create a huge, you know,

569
00:31:15,960 --> 00:31:18,880
Speaker 8: a huge incentive to cultivate the president. And it also

570
00:31:18,960 --> 00:31:22,080
Speaker 8: really helps sort of big incumbent companies over small scrappy ones.

571
00:31:22,400 --> 00:31:22,920
Speaker 4: Both of those.

572
00:31:22,960 --> 00:31:25,040
Speaker 8: If you're a major CEO leader, you might decide your

573
00:31:25,040 --> 00:31:27,840
Speaker 8: interests are go along tariffs.

574
00:31:28,080 --> 00:31:30,880
Speaker 6: I'm not sure where we are. I think the courts

575
00:31:30,960 --> 00:31:33,920
Speaker 6: are taking a look at these things. What's your view

576
00:31:33,960 --> 00:31:35,400
Speaker 6: of kind of where we are here, because I think

577
00:31:35,440 --> 00:31:37,360
Speaker 6: the Supreme Court's going to have some type of say here.

578
00:31:37,520 --> 00:31:39,640
Speaker 4: It's absolutely going to have some type of say.

579
00:31:39,680 --> 00:31:42,320
Speaker 8: And the Supreme Court has sort of to an unprecedented

580
00:31:42,360 --> 00:31:45,120
Speaker 8: extent and given deference to the Trump administration a way

581
00:31:45,120 --> 00:31:48,200
Speaker 8: that we just haven't seen this before in the modern era,

582
00:31:48,280 --> 00:31:50,840
Speaker 8: in ways that are pretty surprising that even other judges

583
00:31:50,840 --> 00:31:54,240
Speaker 8: are starving to call out as this is inappropriate. So

584
00:31:54,720 --> 00:31:58,120
Speaker 8: we don't know what they will do, and anyone's guess

585
00:31:58,520 --> 00:32:00,800
Speaker 8: has good on that. I think the law, most legal

586
00:32:00,960 --> 00:32:03,200
Speaker 8: analysts think that the law says that these terrors are

587
00:32:03,200 --> 00:32:05,320
Speaker 8: going to be overturned, but we don't know. But even

588
00:32:05,360 --> 00:32:08,800
Speaker 8: if they are, the Trump administration has ways to reimpose them.

589
00:32:09,000 --> 00:32:12,320
Speaker 8: So unfortunately, the Court is actually increasing the level of

590
00:32:12,400 --> 00:32:14,200
Speaker 8: uncertainty that's attached to the terrorist's not decreasing.

591
00:32:14,440 --> 00:32:17,800
Speaker 2: Gotta macunda with this Yale University a great set of

592
00:32:17,800 --> 00:32:22,240
Speaker 2: books out in presidential politics. Here on our talent, I

593
00:32:22,400 --> 00:32:27,920
Speaker 2: take immense umbrage about a huge body of Americans don't

594
00:32:28,000 --> 00:32:32,360
Speaker 2: understand the engineering heritage of many of our schools. How

595
00:32:32,400 --> 00:32:37,080
Speaker 2: many people actually know there's Yale engineering with all of

596
00:32:37,120 --> 00:32:41,080
Speaker 2: that nineteenth century heritage. So if I'm taking physics for

597
00:32:41,320 --> 00:32:46,880
Speaker 2: twenty thermodynamics and statistical mechanics, this is not an easy a,

598
00:32:47,160 --> 00:32:51,240
Speaker 2: is it? No? It's not? Okay? Fine, So if I'm

599
00:32:51,240 --> 00:32:56,120
Speaker 2: doing entropy at Yale, is the Indian education superior and

600
00:32:56,200 --> 00:32:59,840
Speaker 2: more rigorous than across America engineering?

601
00:33:00,120 --> 00:33:03,360
Speaker 8: So the median Indian education isn't. But there are a

602
00:33:03,400 --> 00:33:06,040
Speaker 8: lot of Indians. There are one point four billion of them.

603
00:33:06,280 --> 00:33:07,960
Speaker 8: If you're talking about the people who are going to

604
00:33:08,000 --> 00:33:10,840
Speaker 8: the its and places like that. My mother was both

605
00:33:10,880 --> 00:33:11,920
Speaker 8: her undergrad and her PhD.

606
00:33:12,000 --> 00:33:13,040
Speaker 4: It was from it compore.

607
00:33:13,840 --> 00:33:15,240
Speaker 2: Did she come here in an H one B?

608
00:33:16,000 --> 00:33:17,400
Speaker 4: She came here. She did not come here on an

609
00:33:17,480 --> 00:33:20,560
Speaker 4: H one B. She came here in the early seventies Maria.

610
00:33:20,480 --> 00:33:23,560
Speaker 2: But she got off an airplane somewhere. Did she take

611
00:33:23,600 --> 00:33:25,520
Speaker 2: an American job when she came here?

612
00:33:25,600 --> 00:33:27,880
Speaker 8: So she took a job in the United States, But

613
00:33:27,960 --> 00:33:30,200
Speaker 8: she did not take an American job because her skill

614
00:33:30,240 --> 00:33:32,720
Speaker 8: set was such that she was essentially the only person

615
00:33:32,760 --> 00:33:34,280
Speaker 8: in the world who was able to do the work

616
00:33:34,280 --> 00:33:37,920
Speaker 8: that she did for NASA, And so every single program,

617
00:33:38,000 --> 00:33:41,080
Speaker 8: every single American spacecraft that involved nuclear power and space

618
00:33:41,440 --> 00:33:43,400
Speaker 8: went through her at some point over the course of

619
00:33:43,400 --> 00:33:44,280
Speaker 8: her forty year career.

620
00:33:44,600 --> 00:33:48,360
Speaker 2: It literally, did she think we could use nuclear propulsion

621
00:33:48,400 --> 00:33:50,800
Speaker 2: to go to Mars? This was a raging dinner table.

622
00:33:50,880 --> 00:33:56,560
Speaker 2: Copper like buns and rolls were thrown over. This is

623
00:33:56,600 --> 00:33:59,240
Speaker 2: it her fault that we were supposed to develop nuclear

624
00:33:59,320 --> 00:34:01,520
Speaker 2: miss or rocketry rather to go to March.

625
00:34:01,680 --> 00:34:03,280
Speaker 4: It's not. It's actually a treaty problem.

626
00:34:03,320 --> 00:34:06,040
Speaker 8: But I will say when The Martian came out, exactly

627
00:34:06,160 --> 00:34:07,720
Speaker 8: one of the probes in the Martian is actually the

628
00:34:07,800 --> 00:34:10,719
Speaker 8: last mission she helped design. And so when she saw it,

629
00:34:10,760 --> 00:34:13,360
Speaker 8: I got a four page technical analysis of the movie

630
00:34:13,400 --> 00:34:13,839
Speaker 8: from her.

631
00:34:15,960 --> 00:34:17,120
Speaker 2: Read it. I loved it.

632
00:34:17,160 --> 00:34:19,439
Speaker 4: I thought it was great, Bud, thanks for setting this

633
00:34:19,440 --> 00:34:19,680
Speaker 4: to it.

634
00:34:20,200 --> 00:34:22,600
Speaker 8: But this is actually a key thing, right, This is

635
00:34:22,680 --> 00:34:25,799
Speaker 8: taking a skill set from India. Right, So, India, at

636
00:34:25,800 --> 00:34:29,080
Speaker 8: the time, one of the world's poorest countries, at ruinous expense,

637
00:34:29,640 --> 00:34:33,479
Speaker 8: educated America's finest scientist and engineers and let's sent them here.

638
00:34:33,960 --> 00:34:36,239
Speaker 8: This is a phenomenal deal for the United States. The

639
00:34:36,280 --> 00:34:39,400
Speaker 8: idea of every country in the world would kill to

640
00:34:39,440 --> 00:34:41,719
Speaker 8: get the best graduates of the Iets there that right,

641
00:34:41,800 --> 00:34:44,960
Speaker 8: like that is an asset of uncalculable value, and in

642
00:34:45,000 --> 00:34:47,640
Speaker 8: staid we seem to be throwing it away. It is

643
00:34:47,680 --> 00:34:50,600
Speaker 8: a decision that makes no sense on any level of

644
00:34:50,600 --> 00:34:51,440
Speaker 8: the national interest.

645
00:34:52,160 --> 00:34:53,759
Speaker 6: So what do you think, How do you think this

646
00:34:53,800 --> 00:34:54,960
Speaker 6: is going to play out? I mean, I'm sure it's

647
00:34:54,960 --> 00:34:57,680
Speaker 6: a topic of conversation at Yale, at Harvard and all

648
00:34:57,680 --> 00:34:58,759
Speaker 6: the places you hang your head.

649
00:34:59,120 --> 00:35:00,520
Speaker 4: How do you think this is going to play So.

650
00:35:00,480 --> 00:35:01,800
Speaker 8: One is there's going to be a lot of pushback.

651
00:35:01,800 --> 00:35:04,640
Speaker 8: For example, a lot of these people are like surgical residents.

652
00:35:05,040 --> 00:35:05,920
Speaker 8: We already have a.

653
00:35:05,960 --> 00:35:07,280
Speaker 4: Doctor's shortage in the United States.

654
00:35:07,320 --> 00:35:09,120
Speaker 8: People don't know this, but the United States has fewer

655
00:35:09,160 --> 00:35:11,800
Speaker 8: doctors per capita than any other industrial We got.

656
00:35:11,680 --> 00:35:13,040
Speaker 2: To cut to thee This is brilliant.

657
00:35:13,280 --> 00:35:13,400
Speaker 3: You know.

658
00:35:13,480 --> 00:35:15,920
Speaker 2: I have to have you back again. Got them just

659
00:35:16,280 --> 00:35:20,120
Speaker 2: on this. If the president does this, how does it

660
00:35:20,239 --> 00:35:25,120
Speaker 2: change in American's life at Georgia Tech Engineering or el Engineering.

661
00:35:25,640 --> 00:35:28,919
Speaker 8: So one is these schools will these schools become less

662
00:35:28,920 --> 00:35:31,440
Speaker 8: attractive to foreign students because a lot of them come

663
00:35:31,440 --> 00:35:32,920
Speaker 8: in in the expectation they will be able to stay

664
00:35:32,960 --> 00:35:34,919
Speaker 8: in the United States with an H one BBS, which

665
00:35:35,320 --> 00:35:38,760
Speaker 8: they find an incredibly attractive prospect. So first American schools,

666
00:35:38,800 --> 00:35:41,880
Speaker 8: which have historically gotten the best talent in the world,

667
00:35:42,080 --> 00:35:44,480
Speaker 8: are going to find it harder to do that. And

668
00:35:44,680 --> 00:35:47,040
Speaker 8: that's a big problem because those schools are the ones

669
00:35:47,040 --> 00:35:49,239
Speaker 8: that produce the new technologies that are the foundation for

670
00:35:49,400 --> 00:35:52,399
Speaker 8: new for new industries and new companies. So you want

671
00:35:52,400 --> 00:35:53,880
Speaker 8: them to keep spilling out that. You want them to

672
00:35:53,920 --> 00:35:57,560
Speaker 8: have the best global talent. So second, companies are going

673
00:35:57,600 --> 00:35:59,960
Speaker 8: to be more likely, not less likely, they're going to

674
00:35:59,960 --> 00:36:04,120
Speaker 8: be more likely to outsource American technology jobs outside of

675
00:36:04,120 --> 00:36:06,160
Speaker 8: the United States, because if they can't get the labor here,

676
00:36:06,640 --> 00:36:09,080
Speaker 8: they can get it in India. So you're going to

677
00:36:09,120 --> 00:36:12,160
Speaker 8: see more outsourcing and more offshoring for the sorts of

678
00:36:12,280 --> 00:36:14,280
Speaker 8: jobs that we actually desperately want.

679
00:36:14,160 --> 00:36:17,120
Speaker 2: For Microsoft setting up more in the United Kingdom with

680
00:36:17,280 --> 00:36:20,600
Speaker 2: that's the president's visit. Yeah, this is brilliant gun, Thank

681
00:36:20,640 --> 00:36:23,239
Speaker 2: you so much. With the Yale University. Can't say enough

682
00:36:23,239 --> 00:36:25,640
Speaker 2: about it. We'll do this, We'll do this again. That's

683
00:36:25,640 --> 00:36:26,440
Speaker 2: a nerd fest.

684
00:36:27,640 --> 00:36:29,800
Speaker 4: Did you watch some Marsha Yeah, awesome.

685
00:36:30,120 --> 00:36:35,520
Speaker 2: My mother said my father was literally crying during the movie. Yep,

686
00:36:35,680 --> 00:36:37,120
Speaker 2: they got so many things right.

687
00:36:37,920 --> 00:36:42,799
Speaker 1: This is the Bloomberg Surveillance podcast available on Apple, Spotify,

688
00:36:42,920 --> 00:36:47,200
Speaker 1: and anywhere else you get your podcasts. Listen live each weekday,

689
00:36:47,320 --> 00:36:50,839
Speaker 1: seven to ten am Eastern on Bloomberg dot Com, the

690
00:36:50,880 --> 00:36:54,920
Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You

691
00:36:54,920 --> 00:36:58,319
Speaker 1: can also watch us live every weekday on YouTube and

692
00:36:58,480 --> 00:37:00,120
Speaker 1: always on the Bloomberg term no

693
00:37:07,239 --> 00:37:07,439
Speaker 6: Yeh