Latest / Bloomberg Intelligence / Pfizer Reversing Price Hikes After Trump Bullying Won’t Last

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Pfizer Reversing Price Hikes After Trump Bullying Won’t Last · Bloomberg Intelligence

0:05
Speaker 1: Welcome to the Bloomberg P and L Podcast. I'm Pim
0:08
Speaker 1: Fox along with my co host Lisa A. Brahmowitz. Each
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Speaker 1: day we bring you the most important, noteworthy, and useful
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0:32
Speaker 1: I want to shift your focus to the pharmaceutical industry.
0:35
Speaker 1: We've been talking a lot about when President Trump is
0:37
Speaker 1: going to shift his focus to lowering drug prices. It
0:41
Speaker 1: appears to be that the time is now and joining
0:43
Speaker 1: us as Max Neeson Biotech, pharma and healthcare columnists for
0:47
Speaker 1: Bloomberg Opinion, our oracle of the pharmaceutical industry and all
0:50
Speaker 1: things healthcare. Max, so just lay out what happened with
0:53
Speaker 1: Fiser and President Trump's involvement here. Well, as it always
0:57
Speaker 1: is with drug pricing, there there's more uh, and there
1:00
Speaker 1: appears to be on the surface so UM as it
1:03
Speaker 1: usually does kind of on a six month basis. Um
1:07
Speaker 1: Fightser raised drug prices on on a number of Medica
1:09
Speaker 1: a number of its medications. The President took to Twitter
1:13
Speaker 1: to criticize them for that on July nine, and then
1:17
Speaker 1: yesterday evening he announced that after speaking to the to
1:21
Speaker 1: Fightser CEO on the phone with the Health and Human
1:24
Speaker 1: Services sectary alex as R, they had agreed to roll
1:27
Speaker 1: back the price hikes they had planned to take, probably
1:30
Speaker 1: sometime in the next few weeks, but not permanently. It's
1:34
Speaker 1: either until January one or until the President's Drug Price
1:40
Speaker 1: Blueprint is enacted, though no difficient definition of enacted there so,
1:45
Speaker 1: UM it is a temporary rollback of prices opposed to
1:48
Speaker 1: something permanent or drastic max. Is this really what the
1:53
Speaker 1: pharmaceutical industry is looking for, which is an ad hoc
1:57
Speaker 1: kind of strategy on the part of the administration to
2:01
Speaker 1: deal with drug prices? Um? You know, I don't think
2:04
Speaker 1: this is how they really prefer to to operate. UM.
2:08
Speaker 1: Just kind of unilateral public negotiations UM in kind of
2:13
Speaker 1: the public sphere and then just kind of the President
2:16
Speaker 1: using the bully probed on an individual basis. I think
2:19
Speaker 1: that's what they've been scared up for a long time,
2:20
Speaker 1: which is probably why Fiser kind of chose to engage
2:23
Speaker 1: in this way. But I think they actually got a
2:25
Speaker 1: decent deal out of it. They kind of remove themselves
2:28
Speaker 1: from criticism without really giving up all that much. There.
2:32
Speaker 1: The reason I asked you is because maybe this is
2:35
Speaker 1: the way to do it. I mean, maybe this is
2:38
Speaker 1: the way to avoid having the back and forth of
2:41
Speaker 1: lobby interests in the Congress trying to manipulate or to
2:47
Speaker 1: massage the let potential legislation that would create some kind
2:51
Speaker 1: of consistent plan. And maybe this is the way that
2:55
Speaker 1: the President has decided to go at it because he
2:58
Speaker 1: doesn't want to have to do with the special interest
3:01
Speaker 1: groups or the pressure that's been previously applied to drug
3:05
Speaker 1: price that that actually makes a lot of sense in
3:07
Speaker 1: the sense you give the president kind of a big
3:09
Speaker 1: public victory. He gets to play um master negotiator, which
3:14
Speaker 1: is a favorite role of his, and and you know,
3:17
Speaker 1: have this sort of talking point like, look at me,
3:19
Speaker 1: I brought drug prices down, um, even though the actual
3:22
Speaker 1: impact on you know, fiser, on patients, on the drug
3:26
Speaker 1: pricing problem at all is actually quite minimal. Well, okay,
3:31
Speaker 1: so President Trump is one part of this, and fightser
3:35
Speaker 1: is certainly a specific story, but more broadly, there were
3:38
Speaker 1: a number of drug makers that lowered their prices in
3:40
Speaker 1: response to a new California law that aims to provide
3:43
Speaker 1: more transparency to the pharmaceutical industry. So even if President
3:48
Speaker 1: Trump is taking that out ad hoc approach, states are
3:51
Speaker 1: being more systematic in this case California absolutely, and um,
3:55
Speaker 1: you know, it's difficult to tell exactly how much of
3:58
Speaker 1: those price rollbacks are are ascribable to the law as
4:02
Speaker 1: opposed to whether we just happen to find out about them,
4:05
Speaker 1: because of the way that the laws of structure. Basically
4:08
Speaker 1: it requires drug makers to to kind of report and
4:10
Speaker 1: justify price increases that are of a certain magnitude. But
4:14
Speaker 1: it's pretty clear that the transparency has some effect. Having
4:18
Speaker 1: to let health plans know in advance, um, which gives
4:21
Speaker 1: them time to kind of push back, to react, and
4:23
Speaker 1: then having all that sort of in the public sphere
4:26
Speaker 1: clearly has an effect. And that's sort of um kind
4:28
Speaker 1: of a blueprinted other states or potential the government can follow,
4:32
Speaker 1: um if they actually want to have kind of a
4:34
Speaker 1: a sustained impact as opposed to this kind of one time,
4:38
Speaker 1: short duration sort of thing. Max. Has there been any
4:42
Speaker 1: discussion about the way in which healthcare is delivered? I
4:46
Speaker 1: don't mean drug prices, but the actual healthcare And the
4:49
Speaker 1: reason I ask is because yesterday we had a segment
4:52
Speaker 1: in which we focused on innovation in healthcare delivery having
4:57
Speaker 1: to do with hospitals. For example, where some hospitals would
5:01
Speaker 1: specialize in heart surgery, other hospitals would specialize in other
5:06
Speaker 1: kinds of surgical procedures or services. Right now, you have
5:10
Speaker 1: no idea how much they cost from hospital to hospital,
5:14
Speaker 1: so every hospital ends up almost duplicating the services and
5:18
Speaker 1: they compete with each other rather than delivering uh, what
5:21
Speaker 1: would be called efficient healthcare. So I think the lack
5:25
Speaker 1: of price transparency and the lack of UM really prices
5:29
Speaker 1: and healthcare that are just available or interpretable to the
5:33
Speaker 1: average consumer is really one of the most difficult things.
5:37
Speaker 1: It's it's basically impossible to comparison shop UM with any
5:41
Speaker 1: kind of like real pricing data or real data on
5:44
Speaker 1: outcomes on quality UM. The the data is bad. Hospitals
5:50
Speaker 1: usually for the most part, are interested in obfuscating that
5:53
Speaker 1: data about what something costs and why, which is why
5:56
Speaker 1: you hear about those bills where you have you know,
5:59
Speaker 1: thous and dollar charges for for aspirin, for for minor
6:03
Speaker 1: care UM just because you know they that's not the
6:06
Speaker 1: real price the one they negotiate with your insurance, the
6:08
Speaker 1: real price, but it's impossible to find the real price
6:10
Speaker 1: and compare it. So yeah, it's a miserable situation. Well,
6:13
Speaker 1: and and trying to to fix the entire healthcare system
6:17
Speaker 1: is a heavy one and one that we could spend
6:18
Speaker 1: hours on. Uh. There are some things that are going
6:21
Speaker 1: on right now though with respect to Obamacare, which is
6:24
Speaker 1: sort of heralded as a solution but has been uh
6:28
Speaker 1: really kind of tried to at least the attempt has
6:30
Speaker 1: been to try to pare it back in the recent
6:33
Speaker 1: few years, and the latest events have to do with
6:37
Speaker 1: reducing the payments to high risk pools as well as
6:43
Speaker 1: President Trump cutting some of the grants that help consumers
6:46
Speaker 1: get Obamacare. How significant are these developments in your view? Um,
6:51
Speaker 1: You know, for the most part, it depends on particularly
6:54
Speaker 1: the major one, which is the risk corridors or the sorry,
6:58
Speaker 1: the risk adjustments. Basically that UM ensures that have the
7:01
Speaker 1: sickest population UM they get paid back to a certain
7:05
Speaker 1: extent by insurers that have a healthier population UM. It
7:09
Speaker 1: helps them kind of stay in business and just adjust
7:11
Speaker 1: and and make basically ensuring those sacre patients more viable. Um,
7:16
Speaker 1: it's I bet like that it's likely that those payments
7:20
Speaker 1: will resume at some point. It was due to kind
7:22
Speaker 1: of just this weird, quirky New Mexico court case. But um,
7:26
Speaker 1: and even though that's going on just today or last night,
7:30
Speaker 1: rather we just got news that another insurer was expanding
7:33
Speaker 1: in a couple of A markets. So even though things
7:36
Speaker 1: are kind of still uncertain and and kind of prone
7:39
Speaker 1: to shake up and and prone to what many would
7:42
Speaker 1: call sabotage, um, there are still people interested in this market,
7:46
Speaker 1: as opposed to years past where everyone's just kind of fleeing. Well,
7:49
Speaker 1: but this is actually fascinating to me. And one thing
7:51
Speaker 1: that I'm wondering. As insures expand in a c A
7:53
Speaker 1: expand their Obamacare coverage, does that mean that people still
7:58
Speaker 1: like this program? Does that mean that the program is
8:02
Speaker 1: being made more lucrative for the health insurers? Um. I
8:06
Speaker 1: think it's a little bit of both. The in the
8:09
Speaker 1: sense that insurers are are a little bit more experienced
8:12
Speaker 1: with what it takes to be profitable in this market,
8:14
Speaker 1: even though it keeps changing and getting weird every year.
8:18
Speaker 1: But um, as for the consumer experience, it's very much
8:21
Speaker 1: bifurcated between people that get subsidies and people that don't. UM.
8:27
Speaker 1: For someone who gets a subsidy, you can get relatively
8:30
Speaker 1: affordable insurance without paying that much. But because of the
8:33
Speaker 1: fact that the law has been sort of systematically undermined
8:37
Speaker 1: um or at the very least not helped as in um.
8:40
Speaker 1: You know, things that could be done to improve it
8:42
Speaker 1: have have just not happened because of the administration Congress.
8:46
Speaker 1: Um premiums have gone up for people that have just
8:50
Speaker 1: aren't in that kind of income cut off the lots
8:52
Speaker 1: some good subsidies, so it's it's really terrible for them,
8:55
Speaker 1: but but still good for a good chunk of the market,
8:58
Speaker 1: which is more than that to its subsidies. Max. You know,
9:02
Speaker 1: one of the things that happens when you have the
9:04
Speaker 1: healthcare reform debate is always here about the cost of
9:09
Speaker 1: end of life care and how much that is outsized.
9:12
Speaker 1: That turns out to not necessarily be so. I mean,
9:15
Speaker 1: there's an estimate that between eleven to of total health
9:21
Speaker 1: care spending is on that end of life time for patients.
9:28
Speaker 1: Is is the focus should the focus then be on
9:31
Speaker 1: chronic long term conditions? Is that really where the bulk
9:37
Speaker 1: of the money goes. I mean, if if there's anywhere
9:39
Speaker 1: that you can move the dial just sort of in
9:41
Speaker 1: the largest possible population that requires, um the greatest amount
9:45
Speaker 1: of healthcare spending over the longer term and has the
9:47
Speaker 1: most benefit if you can kind of manage those conditions. Well, UM,
9:51
Speaker 1: it's definitely that population. And for the most part, it's
9:54
Speaker 1: something that's that's not done especially well unless you're lucky
9:58
Speaker 1: enough to have UM, you know, series of healthcare providers
10:01
Speaker 1: that are are really engaged or UM un employer that's
10:04
Speaker 1: kind of actively engaging and managing those costs. Otherwise you
10:08
Speaker 1: kind of just get left alone. And you know, it's, uh,
10:12
Speaker 1: it's not easy without kind of expert advice and input
10:16
Speaker 1: and monitoring and on all of that. And we're only
10:18
Speaker 1: just starting to get better than that. And uh that
10:21
Speaker 1: that's something where there's a lot of very for improvement.
10:23
Speaker 1: Just real quick. I do want to note that the
10:25
Speaker 1: SMP five Healthcare index has fallen nearly a percentage point
10:29
Speaker 1: today and that this a lot of people are attributing
10:32
Speaker 1: this to what happened with Visor. Do you expect President
10:37
Speaker 1: Trump to take a similar tap with other pharmacy companies
10:40
Speaker 1: in the near future. Um, you know, now now that
10:42
Speaker 1: he's gotten the sense that if he gets uh gets
10:45
Speaker 1: a CEO on on the phone and and uh jets
10:49
Speaker 1: them a while, that they might actually do something, he
10:51
Speaker 1: may very well give it, give it a shot again,
10:54
Speaker 1: especially because you know we're we're in this is drug
10:57
Speaker 1: price hike season middle of the year July one, so
11:00
Speaker 1: there are a number of other kind of prominent firms
11:02
Speaker 1: that have increased prices. He may give it a shot. Um,
11:05
Speaker 1: you know I would have even if it happens, even
11:07
Speaker 1: if the entire drug industry rolls back this round of
11:10
Speaker 1: drug price increases. You have to keep in mind that
11:13
Speaker 1: every single price hike that they've done for the past
11:15
Speaker 1: decade is still there. So this is really uh, at
11:19
Speaker 1: the end of the day. On the margins, Um, I'm
11:21
Speaker 1: hopeful that some something more materialized, but you know, this
11:26
Speaker 1: might stick shake stocks in the near term. I don't
11:29
Speaker 1: think it's going to be a wait for the long term,
11:32
Speaker 1: like a fig leaf, I guess you could describe it.
11:34
Speaker 1: Thanks very much, Max Neeson, Bloomberg Opinion columnists for all
11:38
Speaker 1: things related to healthcare. Of course, we appreciate your comments
11:43
Speaker 1: and your thoughts. You can follow Max on Twitter at
11:46
Speaker 1: Max Neeson. Our next guest is here in Reality. He
12:06
Speaker 1: is budget art. He is the co founder and president
12:09
Speaker 1: of hi A Technologies. They're based in Los Angeles. And
12:13
Speaker 1: the reason why I say object that you are here
12:15
Speaker 1: in reality is because you are focused on the world
12:19
Speaker 1: of artificial intelligence and avatars and creating the software and
12:24
Speaker 1: the platforms to actually have meaningful conversations with machines exactly.
12:31
Speaker 1: This is a technology that has been used through the
12:37
Speaker 1: the Institute of Creative Technologies at USC the un University
12:41
Speaker 1: of Southern California and the West Coast, and it was
12:44
Speaker 1: a military funded research. Forty million dollars went into it,
12:48
Speaker 1: and um, we're the first ones to commercialize this outside
12:52
Speaker 1: of the institute. They use it for military training and
12:56
Speaker 1: avatar interacting with humans to to test out certain situations
13:02
Speaker 1: with them and more specifically PTSD therapy Teumatic stress disorders therapy, right,
13:09
Speaker 1: so UM veterans with PTSD. It turns out respond to
13:13
Speaker 1: avatars much better in the in terms of opening up
13:18
Speaker 1: and revealing more about themselves, feeling more comfortable, taking more
13:22
Speaker 1: time to be interviewed than psychiatrists. So they had some
13:29
Speaker 1: famous papers published on this and it's been a couple
13:32
Speaker 1: of years, but now it's the technology has come to
13:34
Speaker 1: a point that it's cloud based, you know, client server,
13:38
Speaker 1: it's very easily transported to mobile devices, et cetera. So
13:42
Speaker 1: we decided to commercialize it. We have an exclusive license
13:45
Speaker 1: from USC and we're going to use it for HR
13:49
Speaker 1: and specifically in recruiting. We will conduct pre screening interviews
13:55
Speaker 1: for companies that hire large numbers of people and find
13:59
Speaker 1: itficult to do a good job in screening candidates and
14:03
Speaker 1: finding the right kind of people. Can we just talk
14:07
Speaker 1: a little bit about the concept of replicating a conversation
14:12
Speaker 1: in real time with a computer, Because when you have Alexa,
14:15
Speaker 1: for example, and you ask her a question, so give
14:19
Speaker 1: you a response based on an Internet search, but it's
14:22
Speaker 1: not carrying on a conversation. So how how does that work?
14:26
Speaker 1: Is that? Is that incredibly complicated to make happen? It
14:29
Speaker 1: is complicated, and it starts out with a lot of
14:33
Speaker 1: manual work. You have to script these conversations. But the
14:38
Speaker 1: magical thing behind it is the machine learning. It learns
14:42
Speaker 1: from its experiences and then it gets better and better
14:45
Speaker 1: over time. It gets better much quicker than humans get
14:48
Speaker 1: better in anything. So um, yes, it is complex, but UM,
14:53
Speaker 1: you know you you you have to start with a
14:56
Speaker 1: base product. For example, UM, in interviewing, we have these
15:01
Speaker 1: job modules. It's a question and answer module. So for
15:05
Speaker 1: a junior accountant position, there is a set of twenty
15:09
Speaker 1: questions that the company has decided to ask their potential employees.
15:14
Speaker 1: And uh, these are crafted by combination of our experts
15:20
Speaker 1: that we found and they're specific questions. So the questions
15:24
Speaker 1: are listed and then there's buckets of answers for each question.
15:28
Speaker 1: What we do is we listen to the answer. We
15:31
Speaker 1: assign what we heard to a particular bucket. Okay, can
15:36
Speaker 1: can avatars be funny? Yes? So there's an algorithm for
15:42
Speaker 1: for humor. Yes, And you have to understand we have
15:47
Speaker 1: to be very careful in applying that to situations like this.
15:50
Speaker 1: So we have actually tested that you know, uh, people
15:54
Speaker 1: UM do not take it lightly. And this is this
15:57
Speaker 1: happened in Syrie and Alexa as well. UM, the majority
16:02
Speaker 1: of the people do not think it's funny enough, or
16:07
Speaker 1: it's it's it's it's appropriate. So what we decided to do,
16:11
Speaker 1: literally in this particular case, since it's a an enterprise
16:15
Speaker 1: sale for us, we decided to stay on the safe
16:18
Speaker 1: side and not quite go there, and we just go
16:21
Speaker 1: very polite and very curious, and we just we just
16:25
Speaker 1: don't go there. But it's definitely possible. Tell us a
16:29
Speaker 1: little bit about how you got involved in this, because
16:31
Speaker 1: you have a wide ranging career in technology in Silicon Valley. Uh,
16:36
Speaker 1: Fabricate Labs for example of micro Fabrica is another one
16:41
Speaker 1: of the companies. I believe that you were uh involved
16:45
Speaker 1: with your You seem to have this sort of perspective
16:50
Speaker 1: of turning what is sort of almost mundane thing, you know,
16:56
Speaker 1: concepts into something uh precious and and and you know
17:00
Speaker 1: driven by technology. Yeah. Um, you know, pioneering brand new
17:05
Speaker 1: ideas um is my passion and uh that is a
17:12
Speaker 1: pattern in my background to some of those ideas. Some
17:15
Speaker 1: of the pioneering efforts have not been that successful, but
17:19
Speaker 1: it is what I like and changing paradigms, changing the
17:23
Speaker 1: way things are done today, um, disrupting the way things
17:27
Speaker 1: are done today, especially when it comes to making people
17:31
Speaker 1: more productive, um, and making people more accurate in the
17:36
Speaker 1: way they do things. Well what we do for example,
17:39
Speaker 1: let me say analogy is an Excel sheet. You know, Uh,
17:43
Speaker 1: we didn't Excel sheet did not dislodge accountants from their jobs.
17:49
Speaker 1: It's a tool and it doesn't you know, much like
17:52
Speaker 1: Ai is Budget. I could spend the next hour speaking
17:56
Speaker 1: with you, probably more. Thank you so much for being here.
17:58
Speaker 1: It was really great having you A have to have
18:00
Speaker 1: you back. Budget A rat is co founder and president
18:03
Speaker 1: of hi A Technologies in Los Angeles, creating technology that
18:07
Speaker 1: will soon replace me. When we talk about trade skirmishes
18:27
Speaker 1: between China and the US, many are quick to point
18:30
Speaker 1: out that China's imports from the US aren't large enough
18:33
Speaker 1: to match Trump's tariffs taller for dollar, meaning that they're
18:37
Speaker 1: unable to hit back really with the same force that
18:41
Speaker 1: the U s is. But is that true? Joining us now,
18:44
Speaker 1: Carl Weinberg, He's chief economist high Frequency Economics in New York. Carl,
18:49
Speaker 1: thank you so much for being here. So let's just
18:51
Speaker 1: start there. I mean, is it true that China really
18:54
Speaker 1: can't hit back dollar for dollar just due to the
18:57
Speaker 1: fact that isn't import enough from the US. High Lisa,
19:00
Speaker 1: good morning, Thanks for having me on your program. Um,
19:03
Speaker 1: China has a lot of weapons that can use that
19:05
Speaker 1: aren't strictly tariffs that could be engaged in the trade war.
19:09
Speaker 1: The most likely that we are that we are prone
19:12
Speaker 1: to see and perhaps have already started to see, are
19:15
Speaker 1: just boycotts against American branded goods. Um. You know, US
19:19
Speaker 1: automobile makers reported drop in sales in May of U
19:23
Speaker 1: S branded vehicles. That we've seen the Chinese do this before,
19:26
Speaker 1: boycotting brands from Japan and South Korea when tensions have
19:31
Speaker 1: risen on the political front against those nations. UM. The
19:35
Speaker 1: US companies have about a hundred billion dollars of direct
19:39
Speaker 1: investment in in China in projects to make goods for
19:44
Speaker 1: Chinese consumers in China, and every one of those companies
19:47
Speaker 1: is vulnerable. And there's some of our biggest corporate names,
19:50
Speaker 1: Carl Weinberg as an example. BMW says it will build
19:54
Speaker 1: more of its SUVs overseas and not in South Carolina
19:59
Speaker 1: be because of China's retaliation in the auto industry. Do
20:04
Speaker 1: you believe that? Sorry, go ahead exactly, Tim, And we
20:07
Speaker 1: just reported on Bloomberg the story yesterday of Tesla promising
20:11
Speaker 1: to build a plant there to build half a million
20:13
Speaker 1: vehicles per year in China. We don't know how real
20:16
Speaker 1: that is, but the intention is certainly real. And if
20:19
Speaker 1: Tesla can do it, others can do it GM right now.
20:22
Speaker 1: According to an article I read on Bloomberg a few
20:25
Speaker 1: weeks ago, produces more cars in China under ten joint
20:29
Speaker 1: ventures and two direct investments than it does in the
20:31
Speaker 1: United States. So big companies are vulnerable, and some companies
20:35
Speaker 1: get a great proportion of their profit, does not most
20:38
Speaker 1: of them from transactions in China. So, Carl, how much
20:42
Speaker 1: of this is being priced in that China will retaliate
20:44
Speaker 1: in the manner that you say, with sort of boycotting
20:47
Speaker 1: or discriminating against US companies they're doing business in China. Lisa,
20:52
Speaker 1: I wish I could give you an answer to that.
20:54
Speaker 1: There's no way to know. We've never really seen anything
20:56
Speaker 1: like this before. The only prior that we can point
21:00
Speaker 1: two is that when China has engaged in a spat
21:03
Speaker 1: with Japan, Japanese brands were boycotted. When they engaged in
21:07
Speaker 1: a spat with Korea, Korean brands were boycotted. And this
21:11
Speaker 1: can be a very very effective counter tool in any case.
21:16
Speaker 1: You know the name of the game here. The objective
21:19
Speaker 1: of the Trump tariffs is to try to short circuit
21:21
Speaker 1: China's Made in China program, and that's worth about a
21:26
Speaker 1: trillion dollars a year to China's economy forever once they
21:29
Speaker 1: succeeded it, and I think they will. And whatever pain
21:32
Speaker 1: that China feels on tariffs and on this trade war
21:36
Speaker 1: is peanuts compared to the potential gains from China, all right,
21:40
Speaker 1: So that is one way that China could hit back
21:43
Speaker 1: is through some of the measures that could take against
21:45
Speaker 1: US companies. What about its treasury holdings, I mean, do
21:48
Speaker 1: you expect that that to be on the table with
21:50
Speaker 1: China potentially liquidating it's holdings. Well, there's a risk of
21:55
Speaker 1: that at any time that China could decide to let go.
21:58
Speaker 1: Of course, they do have their own capital invested in
22:01
Speaker 1: those bonds, so that if they undermine the market, they
22:05
Speaker 1: do undermine the present value of their portfolio. But if
22:08
Speaker 1: they're planning on holding to maturity, then they can finesse
22:14
Speaker 1: the capital losses and they can probably make a profit
22:17
Speaker 1: on the bonds that they sell. So I would say
22:20
Speaker 1: that there is a risk, but I would say it's
22:23
Speaker 1: a tail risk right now, mainly because China sees itself
22:27
Speaker 1: as a world player and its future is involved in globalism,
22:31
Speaker 1: and to undermine the U S Treasury market would undermine
22:33
Speaker 1: the world economy, and that's not in China's interest. It
22:37
Speaker 1: has more focused tools at its disposal that it can use.
22:42
Speaker 1: Carl or about using currency as a weapon in this war, Well,
22:47
Speaker 1: it would seem, you know almost that they are. You know,
22:50
Speaker 1: we see the yuan getting cheaper, and um, you know
22:53
Speaker 1: that certainly is one way to offset the impact of tariffs.
22:57
Speaker 1: The thing is they don't really have to go that route.
23:01
Speaker 1: I'm writing tonight from our customers at High Frequency Economics,
23:04
Speaker 1: where our readers hear a story about trade diversion and
23:08
Speaker 1: alternative sources for goods, and um, China can can really
23:14
Speaker 1: escape through this tariff war with very little effect on
23:17
Speaker 1: its domestic economy. Um, the losses that they would face
23:21
Speaker 1: on sales to the US would be minimal, and the
23:24
Speaker 1: impact on their consumers of the tariffs the US is
23:27
Speaker 1: proposing would be I think negligible. Thank you very much
23:30
Speaker 1: for spending time with us. Carl Weinberg is the chief
23:33
Speaker 1: economist for High Frequency Economics. You can follow Carl on
23:38
Speaker 1: Twitter at c B Weinberg. The topic tariffs and President
23:43
Speaker 1: Donald Trump's trade war and retaliation from China. Fake accounts, Yes,
24:04
Speaker 1: fake accounts at Twitter, potentially fake accounts at Facebook, fake
24:08
Speaker 1: accounts almost everywhere. Here to tell us more about social
24:12
Speaker 1: media and advertising is David Garrity. He is the chief
24:16
Speaker 1: executive of g v A Research and you can of
24:19
Speaker 1: course follow David as we do on Twitter at a
24:22
Speaker 1: g v A Research. David always a pleasure, Thanks for
24:26
Speaker 1: coming into the studio. Uh, you're not a fake account.
24:31
Speaker 1: But how do we know that there isn't someone out
24:34
Speaker 1: there on social media impersonating David Garrity? Um, apart from
24:39
Speaker 1: the fact of you know, my own activity and those
24:42
Speaker 1: of people who basically host my social media activities, you know,
24:45
Speaker 1: trying to make sure that nobody's out there squatting. Uh.
24:48
Speaker 1: So there's a certain amount of self policing that takes place.
24:51
Speaker 1: But clearly we have a circumstance here with social media platforms,
24:56
Speaker 1: you know, not necessarily subscribing to the good business practices
25:00
Speaker 1: you know, traditional um news organizations and or other technology
25:05
Speaker 1: companies had subscribed to in terms of verifying users identities. Clearly,
25:10
Speaker 1: you know, we're seeing a belated response on the part
25:12
Speaker 1: of Twitter to suddenly go out and purge one out
25:15
Speaker 1: of every five of their user accounts. As at the
25:18
Speaker 1: end of March, I mean, the number of seventy million
25:20
Speaker 1: was somewhat staggering, especially when you consider that they have
25:23
Speaker 1: seventy million users in the US alone. Now, clearly we
25:27
Speaker 1: don't know what the geographic you know, dispersion was or
25:30
Speaker 1: distribution was of these seventy million accounts that were being
25:33
Speaker 1: acted by Twitter, but it would be very interesting to
25:36
Speaker 1: go through and see, you know, these accounts, what kind
25:39
Speaker 1: of social positions into or political positions were they espousing
25:43
Speaker 1: to what extent was that basically a very clear measure
25:46
Speaker 1: of manipulation of public opinion through Twitter, you know, And
25:50
Speaker 1: the question really is begged here if this is what
25:53
Speaker 1: they've done, now, what are they going to be going
25:56
Speaker 1: to do on an ongoing basis? What's Facebook going to
25:59
Speaker 1: be doing? You know, do we have a consensus potentially
26:03
Speaker 1: in Congress, or do we have a consensus overseas, say
26:06
Speaker 1: within the EU to make sure that these practices are
26:10
Speaker 1: being that the bars being raised. So what I'm trying
26:12
Speaker 1: to understand is also what are the consequences consequences from
26:16
Speaker 1: a corporate standpoint of some of these social media companies
26:20
Speaker 1: actually taking action? I mean, Twitter, yes, we know that
26:22
Speaker 1: they're going to be culling about one fifth of all
26:25
Speaker 1: of their active monthly users calling them fake bots are
26:29
Speaker 1: impersonating uh impersonating identities, but their shares are still up
26:34
Speaker 1: more than this here. No, I mean, certainly one could
26:37
Speaker 1: say on the flip side that they're gonna be able
26:39
Speaker 1: to come back to advertisers and say, look, okay, we've
26:42
Speaker 1: gone through, we've vetted our accounts. You're really dealing with
26:45
Speaker 1: real people here, and from that standpoint, we can justify
26:48
Speaker 1: our ad rates. And you know, we've we've you know,
26:50
Speaker 1: come to the altar, we've confessed our sins, you know,
26:54
Speaker 1: absolve us and let us go forward. And the question
26:57
Speaker 1: really boils down to, from a social and from a
26:59
Speaker 1: policy endpoint, is that good enough? My view would be no,
27:03
Speaker 1: because you know, what happened once clearly could happen again.
27:07
Speaker 1: I think that this might be an interesting opportunity to
27:09
Speaker 1: apply it a new technology, say blockchain, to verify user
27:14
Speaker 1: identity when it counts are opened, and also to update
27:17
Speaker 1: that record as new posts are being added. Hold on
27:21
Speaker 1: a second, I'm sorry, because people use blockchain and a
27:23
Speaker 1: lot of liberal ways and and they're sort of almost
27:25
Speaker 1: a joke in the newsroom that you know, if you
27:27
Speaker 1: have a problem, Just say blockchain and it will go away.
27:29
Speaker 1: Are you basically saying that everybody should have a digital
27:31
Speaker 1: fingerprint and that basically is used to sort of peg
27:35
Speaker 1: their social media presences? In reality? Is that that type
27:38
Speaker 1: of thing and that the blockchain technology will be used
27:41
Speaker 1: to give everyone that digital fingerprint? Or is it? My
27:43
Speaker 1: concept here would be say that for Twitter themselves, they
27:46
Speaker 1: could develop a utility token, which, you know, in which
27:49
Speaker 1: users would have to employ in order to access their platform.
27:53
Speaker 1: You know, if what Twitter wants to be able to
27:55
Speaker 1: put forward, absent the imposition of regulation and oversaw, if
28:00
Speaker 1: they wanted to adopt a solution that might allow a
28:03
Speaker 1: better tracking and verification, um, you know, around what activities
28:08
Speaker 1: are taking place on their site. Blockchain in this case
28:11
Speaker 1: actually is something of possible application and value. And I
28:15
Speaker 1: think it's something where you would have a distributed network
28:17
Speaker 1: because you have many people, many parties, who are actually
28:20
Speaker 1: interested in establishing and confirming and upholding the veracity of
28:25
Speaker 1: what's going across social media platforms. You know, this is
28:28
Speaker 1: possible for Twitter to consider a blockchain application. David Garty,
28:33
Speaker 1: I just want to bring in the concept of a
28:35
Speaker 1: middleman or middle person, right, and I understand that blockchain
28:40
Speaker 1: and bitcoin and a lot of cryptocurrencies, why we sometimes
28:45
Speaker 1: shouldn't conflate them. It is the goal to get rid
28:49
Speaker 1: of the costs, the friction cost that exists in the
28:53
Speaker 1: middle of transactions. Would that be accurate? No, entirely, okay,
28:58
Speaker 1: And until such time as we actually have technologies developed
29:01
Speaker 1: to support blockchain applications that have faster transaction times and
29:05
Speaker 1: lower transaction costs than existing centralized providers, you know, those
29:09
Speaker 1: are obstacles to blockchain adoption long term. Okay, let me
29:13
Speaker 1: just see if I can strike a blow for the
29:16
Speaker 1: middle person. You know, in the world of book selling,
29:20
Speaker 1: they used to be this concept that a publisher would
29:23
Speaker 1: ship a certain amount of books to a retail establishment.
29:27
Speaker 1: What the retail establishment didn't sell, they were allowed and
29:31
Speaker 1: then send back to the bookseller to the publisher. In
29:36
Speaker 1: another model, the book publisher sent books to the retailer
29:42
Speaker 1: and they didn't take anything back. When the New York
29:45
Speaker 1: Times went to look at best seller lists, they decided
29:49
Speaker 1: that it was more important to look at those organizations
29:52
Speaker 1: that could send the books back that were unsold, because
29:57
Speaker 1: they had no reason to fake the results. You had
30:02
Speaker 1: retailers who were faking results by saying, oh yeah, this
30:04
Speaker 1: was a best seller and it became a self fulfilling prophecy.
30:08
Speaker 1: So I'm wondering who would that middle person be in
30:12
Speaker 1: these kinds of transactions. In the middle person in case
30:15
Speaker 1: of this example might very well be a consortium that
30:19
Speaker 1: would be formed between the publishers and those retailers who
30:22
Speaker 1: would agree to participate. Um, you know, arguably, assuming that
30:26
Speaker 1: there is you know, frictionless application, you know, low cost
30:30
Speaker 1: or transactions or loss for processing, you know, you could
30:33
Speaker 1: potentially apply a blockchain tracker to each book that was
30:38
Speaker 1: going out and being sold, and then you could use
30:40
Speaker 1: you know, barcode readers that potentially update the related block
30:45
Speaker 1: chains and the distributed nodes that would be supporting the application.
30:49
Speaker 1: This blockchain would be operated by the consortium of these
30:52
Speaker 1: different organizations. Would that work for social media as well? Well? Potentially, yes,
30:58
Speaker 1: I think in the case here looking at it, or
31:00
Speaker 1: if one of the problems that we have is the
31:02
Speaker 1: ease with which these fake accounts can be opened. Impersonating myself,
31:06
Speaker 1: for impersonating you are God forbid impersonating Lisa exactly. But
31:11
Speaker 1: Lisa Brahma wits one. By the way, precisely, not too
31:15
Speaker 1: three or four exactly. But um, from that standpoint, you know,
31:20
Speaker 1: if we can find the platform that technology can be
31:23
Speaker 1: used to help to enable this kind of verification of
31:26
Speaker 1: identity and veracity of content. Arguably, given all that we
31:30
Speaker 1: have suffered, if you will, as a society because of
31:33
Speaker 1: the manipulation of social media, we would all benefit. David Garrity,
31:38
Speaker 1: the one and only, the non impersonatable David Garritty, the
31:41
Speaker 1: chief executive of g v A Research here in our
31:45
Speaker 1: eleven three oh studios. Thank you so much. Thanks for
31:53
Speaker 1: listening to the Bloomberg P and L podcast. You can
31:55
Speaker 1: subscribe and listen to interviews at Apple Podcasts, SoundCloud, or
31:59
Speaker 1: whatever podcast platform you prefer. I'm pim Fox. I'm on
32:03
Speaker 1: Twitter at pim Fox. I'm on Twitter at Lisa Abramo
32:06
Speaker 1: wits one. Before the podcast, you can always catch us
32:09
Speaker 1: worldwide on Bloomberg Radio.