1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penl podcast on Paul Swing You. 2 00:00:05,360 --> 00:00:07,760 Speaker 1: Along with my co host Lisa Brahmas, each day we 3 00:00:07,880 --> 00:00:10,399 Speaker 1: bring you the most noteworthy and useful interviews for you 4 00:00:10,520 --> 00:00:12,600 Speaker 1: and your money, whether at the grocery store or the 5 00:00:12,640 --> 00:00:15,960 Speaker 1: trading floor. Find a Bloomberg Penil podcast on Apple podcast 6 00:00:16,120 --> 00:00:18,040 Speaker 1: or wherever you listen to podcasts, as well as at 7 00:00:18,040 --> 00:00:21,240 Speaker 1: Bloomberg dot com. Well Leland Miller, a chief executive officer 8 00:00:21,239 --> 00:00:24,079 Speaker 1: of China beige Book International, has nailed at time and 9 00:00:24,079 --> 00:00:27,880 Speaker 1: again when it comes to looking at preliminary data coming 10 00:00:27,920 --> 00:00:32,639 Speaker 1: out of Chinese companies, nonofficial data and estimating the increase 11 00:00:32,720 --> 00:00:36,000 Speaker 1: or decrease in activity ahead of the official pm MY 12 00:00:36,120 --> 00:00:38,440 Speaker 1: data that we got out of China that was incredibly 13 00:00:38,560 --> 00:00:41,720 Speaker 1: ugly record weakness that we saw in the manufacturing sector. 14 00:00:42,000 --> 00:00:43,600 Speaker 1: Leland Miller was saying that that we were going to 15 00:00:43,640 --> 00:00:46,000 Speaker 1: see a contraction in the Chinese economy in the first quarter. 16 00:00:46,320 --> 00:00:49,600 Speaker 1: That seems almost to be an uncertainty. The question now 17 00:00:49,840 --> 00:00:53,360 Speaker 1: is going forward, how quickly can China ramp back up 18 00:00:53,400 --> 00:00:57,000 Speaker 1: production and get supply chains working again. Leland Miller joins 19 00:00:57,040 --> 00:00:59,480 Speaker 1: us here at our Interactive Broker Studios. So do you 20 00:00:59,520 --> 00:01:02,760 Speaker 1: have a set based on preliminary data luland of how 21 00:01:02,840 --> 00:01:06,920 Speaker 1: much we're seeing manufacturing come back online from China. Yeah, 22 00:01:06,959 --> 00:01:10,760 Speaker 1: we're we're seeing firms go back to work, we're seeing 23 00:01:10,800 --> 00:01:13,839 Speaker 1: workers show up. So we're seeing a trend towards firms opening. 24 00:01:13,840 --> 00:01:15,640 Speaker 1: But the question is how productive are they are they 25 00:01:15,640 --> 00:01:19,160 Speaker 1: actually being? Um, you know, there's a there's a real 26 00:01:19,240 --> 00:01:21,000 Speaker 1: question about this. You know, when we break down the 27 00:01:21,080 --> 00:01:22,720 Speaker 1: data to how many firms are open, to how many 28 00:01:22,720 --> 00:01:25,679 Speaker 1: are working in normal operations, the ratio is very low. 29 00:01:26,160 --> 00:01:28,160 Speaker 1: It's better than it was two weeks ago. Uh, And 30 00:01:28,200 --> 00:01:30,480 Speaker 1: we're and we're you know, we're tracking this data every 31 00:01:30,480 --> 00:01:33,200 Speaker 1: single day as it comes in, but this is China's 32 00:01:33,240 --> 00:01:35,120 Speaker 1: not back to work yet. What we do know is 33 00:01:35,160 --> 00:01:38,800 Speaker 1: that Beijing has given us their bad data that will 34 00:01:38,800 --> 00:01:41,040 Speaker 1: be the low no matter what happens. And asteroid could 35 00:01:41,080 --> 00:01:42,840 Speaker 1: hit Beijing at this point, and they're going to report 36 00:01:42,840 --> 00:01:45,440 Speaker 1: better data going forward. And so the question is how 37 00:01:45,520 --> 00:01:47,680 Speaker 1: much of this going back to work will be a 38 00:01:47,680 --> 00:01:50,440 Speaker 1: cover for rising p M s and A and a 39 00:01:50,480 --> 00:01:53,360 Speaker 1: better GDP number and better industrial production number when the 40 00:01:53,440 --> 00:01:56,840 Speaker 1: underlying reality doesn't doesn't reflect that. And I think we're 41 00:01:56,880 --> 00:01:58,920 Speaker 1: just waiting to see that because China is going back 42 00:01:58,960 --> 00:02:00,720 Speaker 1: to work, but we don't know whether they're going back 43 00:02:00,720 --> 00:02:03,480 Speaker 1: to growth. So is this literally, as I think about 44 00:02:03,600 --> 00:02:07,040 Speaker 1: China going back to work, is it literally moving millions 45 00:02:07,040 --> 00:02:10,200 Speaker 1: of people who are on their lunar holiday in their 46 00:02:10,280 --> 00:02:13,720 Speaker 1: villages back to the city's, back to the factories and 47 00:02:13,760 --> 00:02:15,400 Speaker 1: getting them working again. Is that kind of what we're 48 00:02:15,400 --> 00:02:17,280 Speaker 1: talking about. That's a big chunk of it. So what 49 00:02:17,320 --> 00:02:20,760 Speaker 1: we're seeing right now in some cases are buses being 50 00:02:20,880 --> 00:02:24,600 Speaker 1: filled with micro workers who are being driven with police 51 00:02:24,760 --> 00:02:29,079 Speaker 1: escorts from certain cities back to where they're needed. Uh. 52 00:02:29,240 --> 00:02:32,720 Speaker 1: Jent Paying wants growth back at all costs, and so 53 00:02:32,760 --> 00:02:35,680 Speaker 1: they are they are going to restart factories come hell 54 00:02:35,720 --> 00:02:38,120 Speaker 1: or high water. But the question is again is you know, 55 00:02:39,120 --> 00:02:41,280 Speaker 1: is this are we back? You know? Is this? Is 56 00:02:41,280 --> 00:02:43,160 Speaker 1: this going to stay this way? Are the firms gonna 57 00:02:43,160 --> 00:02:44,680 Speaker 1: be able to operate this way? Do they have the 58 00:02:44,720 --> 00:02:47,480 Speaker 1: inputs to be able to build going forward? And none 59 00:02:47,480 --> 00:02:49,360 Speaker 1: of this is clear at all yet. There was also 60 00:02:49,400 --> 00:02:52,280 Speaker 1: a story that caught my attention about the potential to 61 00:02:52,400 --> 00:02:58,679 Speaker 1: fudge data by having factories actually run electricity without necessarily 62 00:02:58,720 --> 00:03:02,160 Speaker 1: having the workers to do the work. Are you seeing anything? 63 00:03:02,160 --> 00:03:05,360 Speaker 1: I mean does that seem like a dominant type of 64 00:03:05,400 --> 00:03:08,799 Speaker 1: development or just sort of a one off example. It's 65 00:03:08,880 --> 00:03:13,880 Speaker 1: very Chinese. Look, the the Beijing has been doing things 66 00:03:13,919 --> 00:03:16,320 Speaker 1: like this for years. And the reality is, and we've 67 00:03:16,360 --> 00:03:19,960 Speaker 1: been warning people for years on this, electricity production is 68 00:03:20,000 --> 00:03:22,079 Speaker 1: not a gauge of the Chinese economy. There's a lot 69 00:03:22,080 --> 00:03:24,520 Speaker 1: of reasons for this, but the major reason is is 70 00:03:24,520 --> 00:03:26,000 Speaker 1: that as soon as you came out with the lead 71 00:03:26,040 --> 00:03:28,919 Speaker 1: Cut Young index, uh, you know, a number of years ago, 72 00:03:30,360 --> 00:03:32,680 Speaker 1: the Chinese understood people were using that as a barometer, 73 00:03:32,760 --> 00:03:34,880 Speaker 1: and they started manipulating the data. So what we've been 74 00:03:34,920 --> 00:03:36,560 Speaker 1: trying to explain is that if you're out there using 75 00:03:36,560 --> 00:03:38,480 Speaker 1: the lead Cut Young Index thinking you've got a brometer 76 00:03:38,520 --> 00:03:41,040 Speaker 1: on economy, you're just listening to the Chinese story like 77 00:03:41,080 --> 00:03:43,400 Speaker 1: any other piece of data. But this is actually really 78 00:03:43,440 --> 00:03:45,640 Speaker 1: important because a lot of people have turned to soft 79 00:03:45,720 --> 00:03:50,600 Speaker 1: data satellite images electricity production as a way to engauge 80 00:03:50,680 --> 00:03:53,600 Speaker 1: the activity levels in China because they don't trust the 81 00:03:53,680 --> 00:03:57,120 Speaker 1: official data. You're saying that this is also potentially fudged 82 00:03:57,320 --> 00:04:00,120 Speaker 1: or being manipulated. What do you look at them for 83 00:04:00,160 --> 00:04:03,080 Speaker 1: a reliable gauge? Well, look, we when we started trying 84 00:04:03,120 --> 00:04:05,800 Speaker 1: to figure out different ways of tracking the economy. We 85 00:04:05,840 --> 00:04:08,680 Speaker 1: went through all the different you know, obviously official data 86 00:04:08,720 --> 00:04:10,560 Speaker 1: is tainted, but then looking through all the sort of 87 00:04:11,040 --> 00:04:12,880 Speaker 1: private data sources, and what we found is that if 88 00:04:12,880 --> 00:04:16,120 Speaker 1: you don't collect the data yourself and it's being used 89 00:04:16,120 --> 00:04:18,320 Speaker 1: on a broad enough scale, the Chinese figure this out 90 00:04:18,400 --> 00:04:19,960 Speaker 1: and they start manipulating it. You know, this is not 91 00:04:20,000 --> 00:04:22,320 Speaker 1: some sort of conspiracy theory. It's very smart on the 92 00:04:22,480 --> 00:04:25,000 Speaker 1: on on Beijing's bath, they want to make sure they 93 00:04:25,040 --> 00:04:27,720 Speaker 1: control the narrative. So all these things, whether it's rare 94 00:04:27,920 --> 00:04:31,200 Speaker 1: rail cargo, whether it's electricity, whether it's whether it's other 95 00:04:31,240 --> 00:04:33,200 Speaker 1: bits of data. Uh that you know, they want to 96 00:04:33,240 --> 00:04:35,680 Speaker 1: control the narrative, which means they're going to control the data. 97 00:04:35,960 --> 00:04:39,040 Speaker 1: And that's why we just got around to collecting it ourselves, 98 00:04:39,080 --> 00:04:41,720 Speaker 1: because we figured out unless you take Beijing out as 99 00:04:41,720 --> 00:04:45,640 Speaker 1: the intermediary, you cannot trust the data, particularly in a crisis. 100 00:04:45,839 --> 00:04:50,160 Speaker 1: All right, so let's talk about China slowly getting back 101 00:04:50,240 --> 00:04:52,440 Speaker 1: to work. Give us a sense of how you think 102 00:04:52,480 --> 00:04:55,000 Speaker 1: this might ramp here on the mid first quarter into 103 00:04:55,040 --> 00:05:00,000 Speaker 1: second quarter and maybe the ultimate impact on for China. Right, Well, 104 00:05:00,080 --> 00:05:03,239 Speaker 1: so what the Chinese idea is to have everything bottom 105 00:05:03,240 --> 00:05:06,039 Speaker 1: out in February and to have more workers come back 106 00:05:06,040 --> 00:05:08,440 Speaker 1: in and be able to announce much better uh much 107 00:05:08,520 --> 00:05:10,920 Speaker 1: matter data in March and April, and then have if 108 00:05:11,160 --> 00:05:13,760 Speaker 1: not a v V recovery maybe but you know, just 109 00:05:13,960 --> 00:05:16,640 Speaker 1: a nice steady recovery that shows the competence of the party. 110 00:05:17,200 --> 00:05:20,000 Speaker 1: The problem is one, we don't know whether the outbreak 111 00:05:20,040 --> 00:05:22,120 Speaker 1: has actually been contained, so there are medical issues that 112 00:05:22,160 --> 00:05:24,760 Speaker 1: we can't we we can't understand yet. The second is 113 00:05:24,920 --> 00:05:27,240 Speaker 1: this is now spreading around the world and that hits demand, 114 00:05:27,560 --> 00:05:29,120 Speaker 1: So you have a lot you know, you have a 115 00:05:29,200 --> 00:05:31,240 Speaker 1: hit to demand domestically as well as it hit to 116 00:05:31,279 --> 00:05:33,279 Speaker 1: production domestically, and then you have a hit to global 117 00:05:33,320 --> 00:05:37,159 Speaker 1: demand is hitting tourism, this is hitting all kinds of 118 00:05:37,160 --> 00:05:42,520 Speaker 1: of of of companies that are normal buyers of Chinese goods, 119 00:05:42,560 --> 00:05:44,760 Speaker 1: and so the idea that they're going to have a 120 00:05:44,800 --> 00:05:46,919 Speaker 1: bounce back in demand, I know that's what the narrative is. 121 00:05:46,960 --> 00:05:49,760 Speaker 1: I know that's what they're aiming for. This now depends 122 00:05:50,200 --> 00:05:52,840 Speaker 1: as much on what's happening outside of China as what's 123 00:05:52,839 --> 00:05:58,719 Speaker 1: happening inside China. How low could growth go in China? Well, 124 00:05:58,880 --> 00:06:01,440 Speaker 1: what will they announce. I won't announce a number less 125 00:06:01,480 --> 00:06:03,800 Speaker 1: than say, you know, if we had a full on 126 00:06:03,880 --> 00:06:07,440 Speaker 1: global outbreak, they'll still announce four percent plus GDP. What 127 00:06:07,520 --> 00:06:09,880 Speaker 1: could it go? Look, I think that you could have 128 00:06:11,400 --> 00:06:15,280 Speaker 1: Q one contraction. You could have Q one barely positive growth, 129 00:06:15,400 --> 00:06:18,800 Speaker 1: and then you know you're back to your barely positive growth, 130 00:06:18,800 --> 00:06:22,000 Speaker 1: and then your normal numbers um are are probably around 131 00:06:22,120 --> 00:06:24,800 Speaker 1: three at a normal times. I mean, you could have 132 00:06:25,160 --> 00:06:27,600 Speaker 1: one or two percent growth for the year if things 133 00:06:27,600 --> 00:06:30,640 Speaker 1: were really bad. The Chinese would never announce that. But 134 00:06:31,000 --> 00:06:32,960 Speaker 1: the reality is if things got much worse, you could 135 00:06:32,960 --> 00:06:35,320 Speaker 1: see you could see growth under two percent. Certainly, How 136 00:06:35,360 --> 00:06:38,000 Speaker 1: much of a problem, if at all, is this crisis 137 00:06:38,040 --> 00:06:43,440 Speaker 1: for presidency? He's he's having a rough year or two. Yeah, 138 00:06:43,560 --> 00:06:46,760 Speaker 1: Like Hong Kong and trade war and and and coronavirus. Uh, 139 00:06:47,040 --> 00:06:48,920 Speaker 1: I think this is more dangerous than all of them, 140 00:06:48,960 --> 00:06:53,320 Speaker 1: because because this goes to vulnerabilities of the party. It 141 00:06:53,440 --> 00:06:56,160 Speaker 1: is not a mystery outside of China, but also inside 142 00:06:56,200 --> 00:06:58,200 Speaker 1: of China that the reason that spread like it did 143 00:06:58,520 --> 00:07:01,599 Speaker 1: is because officials lied in, covered it up, and and 144 00:07:01,680 --> 00:07:03,400 Speaker 1: did a bunch of things you're never supposed to do 145 00:07:03,520 --> 00:07:06,240 Speaker 1: when you've got an illness starting to spread. And this 146 00:07:06,320 --> 00:07:07,560 Speaker 1: is not a mystery. I mean, you see it on 147 00:07:07,600 --> 00:07:10,160 Speaker 1: we chat, you see it in domestic conversations. So the 148 00:07:10,240 --> 00:07:12,880 Speaker 1: question is, how can they throw enough junior people under 149 00:07:12,920 --> 00:07:16,680 Speaker 1: the bus, redeem the senior officials in terms of the 150 00:07:16,880 --> 00:07:20,400 Speaker 1: wonderful response, and and sort of redeem the party's role 151 00:07:20,440 --> 00:07:22,040 Speaker 1: in this. And one of the things you're seeing and 152 00:07:22,120 --> 00:07:24,800 Speaker 1: you're going to see going forward is China is already 153 00:07:24,840 --> 00:07:28,679 Speaker 1: starting to sell itself as the global authority on pandemic control. 154 00:07:28,960 --> 00:07:30,560 Speaker 1: You know, will help you out here. We don't need 155 00:07:30,560 --> 00:07:33,360 Speaker 1: any favorites United States, Iran, you want our help, it'llly 156 00:07:33,400 --> 00:07:35,400 Speaker 1: you want our help, We're here, we show you how 157 00:07:35,440 --> 00:07:38,120 Speaker 1: to do it right. It's a it's a clever narrative. 158 00:07:38,560 --> 00:07:41,560 Speaker 1: It's ridiculous, but it's a clever narrative narrative. Leland Miller, 159 00:07:41,640 --> 00:07:43,880 Speaker 1: as always, we appreciate your commentary. When it comes to 160 00:07:43,920 --> 00:07:46,240 Speaker 1: all things China, we learned so much. Leland Miller is 161 00:07:46,280 --> 00:07:48,840 Speaker 1: the chief executive officer of China based Book International. My 162 00:07:48,960 --> 00:07:51,800 Speaker 1: go to person for things on China, which is, uh, 163 00:07:51,840 --> 00:07:54,360 Speaker 1: you know, you have to really dig under the hood. 164 00:07:54,400 --> 00:08:02,760 Speaker 1: There a lot of questions surrounding the markets right now. 165 00:08:02,760 --> 00:08:06,040 Speaker 1: A key one is how long will the effect of 166 00:08:06,080 --> 00:08:09,600 Speaker 1: the shutdown that we saw in China effect manufacturers in 167 00:08:09,680 --> 00:08:12,800 Speaker 1: the United States will affect supply chains. There's no one 168 00:08:12,840 --> 00:08:15,680 Speaker 1: better to talk about that than Brooks Sutherland, Bloomberg opinion 169 00:08:15,680 --> 00:08:19,160 Speaker 1: columnist cover enjoining us here in our interactive Broker Studios. 170 00:08:19,360 --> 00:08:21,120 Speaker 1: I want to start with the data that we got 171 00:08:21,120 --> 00:08:25,040 Speaker 1: out today showing that manufacturing declined more than people expect 172 00:08:25,040 --> 00:08:28,200 Speaker 1: to the United States in the month of February. I'm 173 00:08:28,280 --> 00:08:32,600 Speaker 1: trying to understand as people game plan this out, do 174 00:08:32,640 --> 00:08:35,040 Speaker 1: we have a sense of how long it will take 175 00:08:35,480 --> 00:08:38,320 Speaker 1: for supply chains to get ramped up manufacturing to get 176 00:08:38,400 --> 00:08:41,480 Speaker 1: ramped up once we have a sense of stability here. 177 00:08:41,960 --> 00:08:43,920 Speaker 1: I do think with that I s M number, the 178 00:08:43,960 --> 00:08:46,679 Speaker 1: headline is somewhat of a misnumber there, because if you 179 00:08:46,720 --> 00:08:49,040 Speaker 1: look at what's bumping that number up, part of it 180 00:08:49,080 --> 00:08:51,840 Speaker 1: is a lengthening out of delivery times, and typically that's 181 00:08:51,840 --> 00:08:53,560 Speaker 1: supposed to be a good thing. It means demand is 182 00:08:53,600 --> 00:08:56,920 Speaker 1: so strong that suppliers are struggling to meet that. In 183 00:08:56,960 --> 00:08:59,160 Speaker 1: this case, it is likely an issue with people just 184 00:08:59,200 --> 00:09:01,480 Speaker 1: not having the parts that they need because they're not 185 00:09:01,520 --> 00:09:04,000 Speaker 1: able to get them from various different parts of the world. 186 00:09:04,320 --> 00:09:06,520 Speaker 1: So to me, this says that the worst is yet 187 00:09:06,559 --> 00:09:09,079 Speaker 1: to come for manufacturers, that you'll likely start to see 188 00:09:09,400 --> 00:09:12,200 Speaker 1: some of the aftershocks from the supply dick chain disruption 189 00:09:12,320 --> 00:09:14,480 Speaker 1: later on in the second quarter. So correct me if 190 00:09:14,480 --> 00:09:15,839 Speaker 1: I'm wrong, Brooke. But is I think back to the 191 00:09:15,920 --> 00:09:17,400 Speaker 1: list just a few weeks ago, when we were in 192 00:09:17,440 --> 00:09:20,440 Speaker 1: the thick of earnings, you know, other than Apple and 193 00:09:20,440 --> 00:09:22,240 Speaker 1: maybe a couple of the companies that were calling out 194 00:09:22,240 --> 00:09:25,760 Speaker 1: the coronavirus as a reason to change their auto we 195 00:09:25,760 --> 00:09:27,920 Speaker 1: didn't or did you, Did we hear much of anything 196 00:09:27,920 --> 00:09:30,000 Speaker 1: from your industrial companies that you come No, not really, 197 00:09:30,040 --> 00:09:32,400 Speaker 1: which is interesting because their earning season came a little 198 00:09:32,440 --> 00:09:34,280 Speaker 1: bit earlier, and so at that point in time, most 199 00:09:34,320 --> 00:09:37,880 Speaker 1: of the outlooks didn't really include any impact from the coronavirus. Now, 200 00:09:37,960 --> 00:09:40,560 Speaker 1: the exception was Emerson Electric, which did come out at 201 00:09:40,559 --> 00:09:42,520 Speaker 1: the end of last week and said they're increasing their 202 00:09:42,559 --> 00:09:45,960 Speaker 1: expectation of the revenue hit from coronavirus to as much 203 00:09:45,960 --> 00:09:48,400 Speaker 1: as a hundred and fifty million. It had been, you know, 204 00:09:48,800 --> 00:09:51,720 Speaker 1: significantly lower just a few days before when they had 205 00:09:51,760 --> 00:09:53,959 Speaker 1: held their investor day conference. So this sort of shows 206 00:09:54,000 --> 00:09:56,480 Speaker 1: you just how fast moving this is UM Now. I 207 00:09:56,520 --> 00:09:59,600 Speaker 1: do think you'll probably start to hear some guidance updates 208 00:09:59,600 --> 00:10:02,120 Speaker 1: from these companies in the coming weeks. Uh. You know, 209 00:10:02,200 --> 00:10:04,960 Speaker 1: g E is set to report its outlook on Wednesday, 210 00:10:05,000 --> 00:10:06,920 Speaker 1: and so certainly we'll be keeping an eye on that 211 00:10:07,000 --> 00:10:10,600 Speaker 1: for any guidance there, particularly around the coronavirus. But you know, 212 00:10:10,880 --> 00:10:13,920 Speaker 1: I think the key issue for the manufacturing side is 213 00:10:14,400 --> 00:10:16,800 Speaker 1: this supply chain disruption. But I do think you can 214 00:10:16,880 --> 00:10:18,720 Speaker 1: look at some of these other companies a sort of 215 00:10:18,720 --> 00:10:20,440 Speaker 1: a tell as to what we might see. I mean, 216 00:10:20,440 --> 00:10:22,440 Speaker 1: if you think about a company like three M. On 217 00:10:22,480 --> 00:10:24,720 Speaker 1: the one hand, they make face masks, which they're seeing 218 00:10:24,760 --> 00:10:27,199 Speaker 1: a huge spike in demand. On the other hand, they 219 00:10:27,200 --> 00:10:29,640 Speaker 1: make components for the electronics industry, and we did have 220 00:10:29,679 --> 00:10:32,480 Speaker 1: Microsoft come out and warn about supply chain disruptions for 221 00:10:32,520 --> 00:10:36,240 Speaker 1: its Windows PC unit. UM. Honeywell is another company that 222 00:10:36,320 --> 00:10:39,439 Speaker 1: makes personal protective Year, but it also supplies components to 223 00:10:39,559 --> 00:10:42,280 Speaker 1: the aerospace industry, and that is a much bigger, much 224 00:10:42,280 --> 00:10:45,160 Speaker 1: more profitable business for that company. And I do think 225 00:10:45,520 --> 00:10:49,480 Speaker 1: there's a risk of pretty significant downturn in aerospace when 226 00:10:49,520 --> 00:10:51,719 Speaker 1: you talk about supply chain. So just think about how 227 00:10:51,800 --> 00:10:55,080 Speaker 1: China is trying to get everybody back to factories and 228 00:10:55,160 --> 00:10:58,959 Speaker 1: demonstrate that they are ramping up production. How do we 229 00:10:59,000 --> 00:11:02,200 Speaker 1: have any precedent historically of how long it takes to 230 00:11:02,320 --> 00:11:05,400 Speaker 1: get things back up and running and supply chains working 231 00:11:05,400 --> 00:11:07,679 Speaker 1: as they had been. I don't know that we do, 232 00:11:07,760 --> 00:11:09,600 Speaker 1: because I think what we've seen is that the response 233 00:11:09,640 --> 00:11:11,680 Speaker 1: here has been so much more dramatic than what we 234 00:11:11,760 --> 00:11:14,040 Speaker 1: saw with Stars in two thousand and three. And part 235 00:11:14,080 --> 00:11:16,160 Speaker 1: of the reason for that is that China didn't account 236 00:11:16,200 --> 00:11:18,440 Speaker 1: for as much as the of the world's supply chain 237 00:11:18,480 --> 00:11:21,160 Speaker 1: at that point in time. But I think about Cafe Pacific, 238 00:11:21,480 --> 00:11:24,240 Speaker 1: so they've cut about seventy of their capacity. And I 239 00:11:24,280 --> 00:11:26,720 Speaker 1: saw one analyst report this morning saying during Stars that 240 00:11:26,840 --> 00:11:30,400 Speaker 1: was So that's a really significant shift as you think 241 00:11:30,440 --> 00:11:32,960 Speaker 1: about sort of the magnitudes of the response here and 242 00:11:33,000 --> 00:11:34,880 Speaker 1: how we come back from this. But it's not just 243 00:11:35,200 --> 00:11:38,199 Speaker 1: China anymore. Now we're dealing with Europe. Now, we're possibly 244 00:11:38,240 --> 00:11:41,600 Speaker 1: dealing with the U S and maybe even travel restrictions domestically. 245 00:11:41,600 --> 00:11:43,240 Speaker 1: I mean, we just don't know. And as if you 246 00:11:43,280 --> 00:11:45,839 Speaker 1: start thinking about how you get parts from point A 247 00:11:45,960 --> 00:11:47,920 Speaker 1: to point B, there's a lot of obstacles and a 248 00:11:47,960 --> 00:11:50,200 Speaker 1: lot of unknowns, and so I think this is going 249 00:11:50,240 --> 00:11:52,520 Speaker 1: to take a while for companies to bounce back from 250 00:11:52,679 --> 00:11:54,880 Speaker 1: So Brooke. While we have you here, um Boeing. I 251 00:11:54,920 --> 00:11:56,640 Speaker 1: saw a story that they're out there hiring a lot 252 00:11:56,679 --> 00:11:59,200 Speaker 1: of people for the seven thirty seven Max. Does that 253 00:11:59,400 --> 00:12:02,120 Speaker 1: suggect that that maybe they're close to getting this thing 254 00:12:02,200 --> 00:12:04,040 Speaker 1: back in the air, you know, I think they want 255 00:12:04,080 --> 00:12:07,480 Speaker 1: to be prepared because I think to shut down a 256 00:12:07,559 --> 00:12:12,320 Speaker 1: manufacturing line for an aircraft is a really significant step 257 00:12:12,640 --> 00:12:14,080 Speaker 1: for them to do that. I mean, they put that 258 00:12:14,120 --> 00:12:16,480 Speaker 1: off as long as they possibly could, and that a 259 00:12:16,520 --> 00:12:18,960 Speaker 1: big reason for that was a concern about having the 260 00:12:19,040 --> 00:12:21,920 Speaker 1: labor there to be able to manufacture the planes once 261 00:12:21,960 --> 00:12:24,320 Speaker 1: they do restart that. And there's also a lot of 262 00:12:24,360 --> 00:12:27,000 Speaker 1: steps involved here with once the Max is on grounded, 263 00:12:27,040 --> 00:12:29,480 Speaker 1: you have to get all of those planes ready to 264 00:12:29,520 --> 00:12:32,320 Speaker 1: fly again. We've already seen you know, potential issues with 265 00:12:32,360 --> 00:12:35,200 Speaker 1: that or bowing and said they've found you know, debris 266 00:12:35,320 --> 00:12:37,120 Speaker 1: and some of the fuel tanks, whether that be like 267 00:12:37,280 --> 00:12:39,800 Speaker 1: rags or you know, sort of leftover tools, and so 268 00:12:39,880 --> 00:12:41,760 Speaker 1: they have to make sure that all of that gets fixed. 269 00:12:42,000 --> 00:12:43,880 Speaker 1: And you have to bring these planes out of hibernation. 270 00:12:43,920 --> 00:12:46,520 Speaker 1: I mean that takes time, that takes people, that takes effort. 271 00:12:46,600 --> 00:12:49,720 Speaker 1: So look, I mean I think Boeing is progressing towards 272 00:12:49,760 --> 00:12:52,800 Speaker 1: getting this plane ready to fly, but there are niggling 273 00:12:52,880 --> 00:12:55,040 Speaker 1: issues that keep coming up and you know that may 274 00:12:55,080 --> 00:12:56,719 Speaker 1: take a little bit of time to work through. There 275 00:12:56,760 --> 00:12:58,720 Speaker 1: was a important the Seattle time not too long ago 276 00:12:58,760 --> 00:13:02,160 Speaker 1: about the risk of this timeline potentially slipping a little bit. 277 00:13:02,160 --> 00:13:04,040 Speaker 1: Now we're not talking about major shifts like we saw 278 00:13:04,280 --> 00:13:06,640 Speaker 1: the course of last year, but there is potentially a 279 00:13:06,760 --> 00:13:09,160 Speaker 1: risk there. What is the latest date? Do we have 280 00:13:09,240 --> 00:13:12,240 Speaker 1: a date for? Boeing is stuck with mid But what 281 00:13:13,360 --> 00:13:15,720 Speaker 1: means maybe there's some wiggle room there in terms of 282 00:13:15,720 --> 00:13:18,240 Speaker 1: your definition. So all right, thank you very much brook Sotheran, 283 00:13:18,280 --> 00:13:20,360 Speaker 1: and thanks so much for joining us. She covers all 284 00:13:20,440 --> 00:13:23,160 Speaker 1: things industrials for Bloomberg Opinion. You can read her work 285 00:13:23,320 --> 00:13:26,160 Speaker 1: excellent work on Bloomberg dot Com, Slash Opinion or if 286 00:13:26,200 --> 00:13:28,360 Speaker 1: you're on a terminal O P I N go for books, 287 00:13:28,360 --> 00:13:31,400 Speaker 1: work and all the other work from a Bloomberg Opinion. 288 00:13:31,880 --> 00:13:47,560 Speaker 1: She joins us here in our Bloomberg Interactive Broker Studio. Well, 289 00:13:47,600 --> 00:13:50,480 Speaker 1: despite the risk on field to the equity markets. Treasury 290 00:13:50,559 --> 00:13:53,120 Speaker 1: yields continue to grind lower. We got the two year 291 00:13:53,200 --> 00:13:57,240 Speaker 1: down about eleven basis points to zero point eight four percent, 292 00:13:57,360 --> 00:14:00,600 Speaker 1: just extraordinary levels on treasuries. To get a sense of 293 00:14:00,679 --> 00:14:03,760 Speaker 1: where yields could go. We welcome r J. Gallo. He's 294 00:14:03,760 --> 00:14:06,640 Speaker 1: a senior portfolio manager, head of the Missable Bond Investment 295 00:14:06,679 --> 00:14:09,760 Speaker 1: Group ahead of the Duration Committee for Federator Hermes. They 296 00:14:09,800 --> 00:14:13,760 Speaker 1: have about eleven point seven billion under management. They're based 297 00:14:13,800 --> 00:14:16,400 Speaker 1: in Pittsburgh. Of course, r J, thanks so much for 298 00:14:16,679 --> 00:14:20,080 Speaker 1: joining us once again. All right, so we the coronavirus 299 00:14:20,160 --> 00:14:23,920 Speaker 1: is there, it's spreading. Markets are trying to discount the impact. 300 00:14:24,200 --> 00:14:27,000 Speaker 1: I guess one of the next issues for the market 301 00:14:27,080 --> 00:14:29,440 Speaker 1: to really get a handle on is when will the 302 00:14:29,480 --> 00:14:31,880 Speaker 1: FED cut and how much will they cut? What are 303 00:14:31,920 --> 00:14:36,560 Speaker 1: your thoughts, well, I think it's pretty clear that this 304 00:14:36,760 --> 00:14:41,600 Speaker 1: central bank, under the leadership of Powell as well as 305 00:14:41,640 --> 00:14:46,560 Speaker 1: his most recent predecessors, have been eager to be proactive 306 00:14:46,760 --> 00:14:50,160 Speaker 1: in the when faced with crisis or challenge, Yelling put 307 00:14:50,200 --> 00:14:52,600 Speaker 1: off a plan tightening because markets got really volved all 308 00:14:52,600 --> 00:14:57,240 Speaker 1: the way back. I think it's BERNANKI certainly got very aggressive. 309 00:14:57,280 --> 00:15:01,320 Speaker 1: He's the one who sort of pioneered que all um 310 00:15:01,400 --> 00:15:04,480 Speaker 1: Inen tightened maybe more than the markets would have liked, 311 00:15:05,400 --> 00:15:07,640 Speaker 1: maybe more than was perhaps needed at the time, and 312 00:15:07,720 --> 00:15:11,720 Speaker 1: quickly reversed course. So I don't think they are inertial. 313 00:15:12,200 --> 00:15:14,360 Speaker 1: And I think the statement that came out last week 314 00:15:14,400 --> 00:15:17,480 Speaker 1: from Powell indicates that the FED will move. Um. I 315 00:15:17,520 --> 00:15:20,040 Speaker 1: don't know if in a textbook sense everybody agrees they 316 00:15:20,040 --> 00:15:23,440 Speaker 1: should move, but I don't think it hurts anything. Uh. 317 00:15:23,480 --> 00:15:26,640 Speaker 1: They can't cure the virus, they can't produce a vaccine, 318 00:15:27,000 --> 00:15:30,120 Speaker 1: but they can help cushion the blow economically by lowering 319 00:15:30,120 --> 00:15:32,640 Speaker 1: short term rates in such a way as to help 320 00:15:32,640 --> 00:15:37,640 Speaker 1: bolster somewhat interest rate sensitive sectors that otherwise wouldn't get 321 00:15:37,640 --> 00:15:39,680 Speaker 1: the boost from lower rates. So I think they are 322 00:15:39,680 --> 00:15:42,720 Speaker 1: going to ease the three eases almost four eases that 323 00:15:42,760 --> 00:15:46,600 Speaker 1: are on the work now seems extreme to me, but 324 00:15:46,720 --> 00:15:50,880 Speaker 1: I know some highly respected research firms and research areas 325 00:15:50,880 --> 00:15:53,840 Speaker 1: in the marketplace names everybody knows, UH suggests they're going 326 00:15:53,880 --> 00:15:55,880 Speaker 1: to cut hunter basis points. So there's you know, there's 327 00:15:55,920 --> 00:15:59,680 Speaker 1: your basis point eases. UM. I wouldn't be surprised if 328 00:15:59,720 --> 00:16:01,920 Speaker 1: it'll be less than that. So yeah, Deutsche Bank and 329 00:16:01,960 --> 00:16:05,000 Speaker 1: Coleman Sacks primarily among them, coming out with analysts saying 330 00:16:05,320 --> 00:16:07,520 Speaker 1: they expect for rate cuts or a hundred basis points 331 00:16:07,560 --> 00:16:10,280 Speaker 1: of cutting. I will just note that as you see 332 00:16:10,320 --> 00:16:14,120 Speaker 1: stocks rally, the number of expected rate cuts is coming 333 00:16:14,160 --> 00:16:18,720 Speaker 1: down precipitously. UH four year end now at just about 334 00:16:18,760 --> 00:16:21,840 Speaker 1: a little over three full rate cuts by the end 335 00:16:21,960 --> 00:16:24,400 Speaker 1: of January next year, so coming down. And I want 336 00:16:24,400 --> 00:16:26,960 Speaker 1: to talk about that. How much do you think this 337 00:16:27,080 --> 00:16:31,680 Speaker 1: erodes FED credibility if basically stock sell off and everyone 338 00:16:31,720 --> 00:16:34,400 Speaker 1: looks to them to just cut rates to prop up valuations. 339 00:16:34,400 --> 00:16:37,080 Speaker 1: I mean, is that the single data point that the 340 00:16:37,080 --> 00:16:41,280 Speaker 1: FED is looking at this point? I actually don't think 341 00:16:41,440 --> 00:16:43,960 Speaker 1: it is. I think that the FED cares very much 342 00:16:43,960 --> 00:16:48,920 Speaker 1: about financial conditions. You all provide the Financial Conditions Index. Uh, 343 00:16:48,960 --> 00:16:51,280 Speaker 1: it's on everybody's terminals. Have people have a terminal in 344 00:16:51,360 --> 00:16:54,840 Speaker 1: front of them. UM, it's now down uh negative one 345 00:16:54,880 --> 00:16:58,760 Speaker 1: standard deviation. UH. The FED wants markets to work. They 346 00:16:58,760 --> 00:17:02,000 Speaker 1: want capital to be provided at reasonable prices. UH. They 347 00:17:02,000 --> 00:17:05,440 Speaker 1: don't want gapping or volatile markets UH to to present 348 00:17:05,440 --> 00:17:08,760 Speaker 1: a headwind to economic expansion. And the Financial Conditions Index 349 00:17:08,960 --> 00:17:11,760 Speaker 1: sort of looks at volatility and valuation and tries to 350 00:17:12,320 --> 00:17:15,720 Speaker 1: um you know, quantify if you will, that tricky measure 351 00:17:15,760 --> 00:17:18,480 Speaker 1: of financial conditions, and they've clearly contracted with all that's 352 00:17:18,520 --> 00:17:21,359 Speaker 1: gone on so rapidly over the last couple of weeks. UM. 353 00:17:21,400 --> 00:17:24,040 Speaker 1: It's not just the stock market, the high yield corporate 354 00:17:24,040 --> 00:17:27,240 Speaker 1: markets UH certainly slowed down, and I think the deals 355 00:17:27,280 --> 00:17:29,960 Speaker 1: got pulled last week. There's no planned issuance at this point. 356 00:17:29,960 --> 00:17:33,040 Speaker 1: I don't think that's a challenge to the Federal reserves 357 00:17:33,040 --> 00:17:36,240 Speaker 1: overall framework that they want functioning of financial markets. So 358 00:17:36,480 --> 00:17:39,240 Speaker 1: the easy isn't just to target a stock price or 359 00:17:39,280 --> 00:17:42,040 Speaker 1: avoid a loss. I think it's to make sure that 360 00:17:42,080 --> 00:17:46,600 Speaker 1: the financial UH flows in the economy don't grind to 361 00:17:46,680 --> 00:17:49,800 Speaker 1: a halt. Twelve years ago when the financial crisis was 362 00:17:49,840 --> 00:17:52,960 Speaker 1: starting up, it's when those financial flows ground to a halt, 363 00:17:53,320 --> 00:17:55,920 Speaker 1: When when the provision of liquidity, when the transactions and 364 00:17:56,000 --> 00:17:58,720 Speaker 1: repo markets, when the issuance of bonds ground to a halt, 365 00:17:59,080 --> 00:18:03,000 Speaker 1: there was a clear sign of deeply challenging problems that 366 00:18:03,080 --> 00:18:04,960 Speaker 1: the Fed needed to act to. I don't think we're 367 00:18:05,000 --> 00:18:06,719 Speaker 1: there right now. I think that we have a more 368 00:18:06,800 --> 00:18:10,720 Speaker 1: robust financial UM system right now, much better capitalized banks, 369 00:18:11,320 --> 00:18:14,440 Speaker 1: sharp moves in markets are challenging for many, but financial 370 00:18:14,440 --> 00:18:18,240 Speaker 1: prices changing does not beget a financial crisis. Um. The 371 00:18:18,359 --> 00:18:21,240 Speaker 1: feds willingness to ease, on the other hand, is more 372 00:18:21,320 --> 00:18:24,040 Speaker 1: looking at how the financial markets are sending a signal 373 00:18:24,040 --> 00:18:26,200 Speaker 1: how the real economy will react in a public health 374 00:18:26,240 --> 00:18:29,280 Speaker 1: crisis of a magnitude we have not seen if this 375 00:18:29,359 --> 00:18:31,639 Speaker 1: gets as bad as people think it might. A highly 376 00:18:31,640 --> 00:18:36,600 Speaker 1: transmissible virus that has a mortality rate that's somewhere around 377 00:18:36,640 --> 00:18:39,080 Speaker 1: five to ten times the influenza which we did with 378 00:18:39,119 --> 00:18:42,440 Speaker 1: every year. Um, there are stark steps that are being taken. 379 00:18:42,480 --> 00:18:44,440 Speaker 1: Look what China did. They shut down cities worth fifty 380 00:18:44,480 --> 00:18:48,919 Speaker 1: million people. That real economic consequences are very profound. So 381 00:18:48,960 --> 00:18:51,600 Speaker 1: the Fed's easing isn't just to sort of blow the 382 00:18:51,600 --> 00:18:55,199 Speaker 1: stock market, uh back up. It's it's to try to 383 00:18:55,240 --> 00:18:57,840 Speaker 1: cushion the blow from an economic standpoint of all of 384 00:18:57,880 --> 00:19:00,760 Speaker 1: the measures that may emerge in the United States as 385 00:19:00,880 --> 00:19:03,240 Speaker 1: testing takes place. We're going to see many more cases 386 00:19:03,240 --> 00:19:06,160 Speaker 1: in this country, and you're gonna see school district shutting down, 387 00:19:06,400 --> 00:19:10,000 Speaker 1: you'll see less travel, you'll see events shutdown. That's what 388 00:19:10,040 --> 00:19:12,320 Speaker 1: the FEDS reacted to. R. J. Gallow thank you so 389 00:19:12,400 --> 00:19:14,440 Speaker 1: much for being with us. R J. Gallo, senior portfolio 390 00:19:14,480 --> 00:19:17,200 Speaker 1: manager and a head of the Unicipal Bond Investment Group 391 00:19:17,560 --> 00:19:25,760 Speaker 1: as well as the Duration Committee it federated. Hermes Let's 392 00:19:25,760 --> 00:19:28,560 Speaker 1: shaft gears a little bit talk politics. Former Vice President 393 00:19:28,880 --> 00:19:31,719 Speaker 1: Joe Biden had a landslide win in South Carolina over 394 00:19:31,720 --> 00:19:34,840 Speaker 1: the weekend, and of course tomorrow is Super Tuesday. To 395 00:19:35,080 --> 00:19:37,840 Speaker 1: put it all in a framework, we welcome Wendy Schiller. 396 00:19:37,920 --> 00:19:40,520 Speaker 1: She's a professor of political science and public policy at 397 00:19:40,520 --> 00:19:43,320 Speaker 1: Brown University in Providence, Rhode Island. Wendy, thanks so much 398 00:19:43,400 --> 00:19:47,280 Speaker 1: for joining us. Let's start with Saturday. What really changed 399 00:19:47,320 --> 00:19:51,480 Speaker 1: in the Democratic Party on Saturday? If anything? Well, I 400 00:19:51,520 --> 00:19:54,119 Speaker 1: think two things came out of South Carolina. One is 401 00:19:54,160 --> 00:19:57,439 Speaker 1: the you know, absolute importance of African American voters to 402 00:19:57,640 --> 00:20:00,920 Speaker 1: the Democratic Party's fate in November, but also to each 403 00:20:00,960 --> 00:20:04,600 Speaker 1: individual candidate running. I think that was really evident. And 404 00:20:04,640 --> 00:20:07,320 Speaker 1: the resurgence of Joe Biden. I mean, we saw him 405 00:20:07,359 --> 00:20:09,560 Speaker 1: a little bit better in the in the most recent debate, 406 00:20:09,960 --> 00:20:13,480 Speaker 1: and he won resounding. It didn't quite pass fifty. I 407 00:20:13,480 --> 00:20:16,200 Speaker 1: think that would have been really, you know, the striking victory, 408 00:20:16,240 --> 00:20:19,520 Speaker 1: but he you know, really trounced Bernie Sanders in that respect. 409 00:20:19,560 --> 00:20:21,680 Speaker 1: So the question is does that pattern hold going into 410 00:20:21,760 --> 00:20:24,639 Speaker 1: tomorrow's primaries well, And there also is the development of 411 00:20:24,640 --> 00:20:28,000 Speaker 1: Pete Budge dropping out mayor Pete dropping out of the 412 00:20:28,080 --> 00:20:31,240 Speaker 1: race and throwing his support behind Joe Biden, And I'm 413 00:20:31,240 --> 00:20:34,840 Speaker 1: wondering how much momentum you think that does give Biden 414 00:20:34,960 --> 00:20:38,800 Speaker 1: against the Bernie Sanders ticket. I'm not persuaded that this 415 00:20:38,920 --> 00:20:41,680 Speaker 1: is an automatic gift to Biden visa vis Sanders, because 416 00:20:41,680 --> 00:20:46,280 Speaker 1: Sanders did well in Nevada particularly it's a caucus state, granted, 417 00:20:46,280 --> 00:20:48,719 Speaker 1: not primary, but there are a lot of Latino voters 418 00:20:48,720 --> 00:20:51,080 Speaker 1: in the DEM Party in Nevada, and Sanders did well 419 00:20:51,119 --> 00:20:55,160 Speaker 1: with Latinos. So I'm looking at Texas. Obviously California Sanders 420 00:20:55,200 --> 00:20:57,520 Speaker 1: is polling pretty well, but Texas is also crucial. If 421 00:20:57,520 --> 00:21:01,000 Speaker 1: Bernie Sanders can show that he can get you fifty 422 00:21:01,080 --> 00:21:04,159 Speaker 1: six of the Latino voters tomorrow in some of these 423 00:21:04,240 --> 00:21:07,200 Speaker 1: key states, I think that puts him in the conversation 424 00:21:07,760 --> 00:21:12,000 Speaker 1: about leading this very diverse party to victory in November 425 00:21:12,160 --> 00:21:14,680 Speaker 1: and takes a little wind out of Biden's sales because 426 00:21:14,680 --> 00:21:16,920 Speaker 1: it's not just the African American vote. It's a higher 427 00:21:16,920 --> 00:21:19,520 Speaker 1: turnout among African Americans, but certainly there are a lot 428 00:21:19,520 --> 00:21:22,160 Speaker 1: of Latinos, and I think getting um, you know, Democrats 429 00:21:22,200 --> 00:21:25,119 Speaker 1: get about seventy percent Latinos. Getting that vote and getting 430 00:21:25,119 --> 00:21:28,640 Speaker 1: that vote up I think gives Bernie Sanderson bragging rights 431 00:21:28,680 --> 00:21:31,560 Speaker 1: if that's what happens tomorrow. So Whendy, Tomorrow is a 432 00:21:31,640 --> 00:21:35,280 Speaker 1: super Tuesday, a lot of delegates up for grabs. Who 433 00:21:35,359 --> 00:21:38,760 Speaker 1: is it make or break for tomorrow? I think the 434 00:21:39,000 --> 00:21:42,760 Speaker 1: obvious person is Amy Clobachar. So Amy Klobachar is leading 435 00:21:42,800 --> 00:21:46,000 Speaker 1: in Minnesota right now by sort of national agate poles, 436 00:21:46,040 --> 00:21:50,000 Speaker 1: but she's not trouncing Sanders right Sanders isn't within striking distance. 437 00:21:50,040 --> 00:21:53,959 Speaker 1: If for some reason Sanders wins Minnesota and she loses Minnesota, 438 00:21:54,040 --> 00:21:55,879 Speaker 1: I think there's just it's gonna be very hard for 439 00:21:55,920 --> 00:21:57,199 Speaker 1: her to stay in the race. If you can't win 440 00:21:57,240 --> 00:21:59,679 Speaker 1: your home state. Ask Al Gore Circuit two thousand when 441 00:21:59,680 --> 00:22:01,800 Speaker 1: he law to his home state in the general election. 442 00:22:01,920 --> 00:22:03,480 Speaker 1: You've got to win your home state. Same thing for 443 00:22:03,520 --> 00:22:06,720 Speaker 1: Elizabeth Warren. You can make an argument about Massachusetts proximity 444 00:22:06,760 --> 00:22:09,520 Speaker 1: to Vermont and Bernie Sanders popularity there, but she's got 445 00:22:09,520 --> 00:22:12,200 Speaker 1: to come really close to winning, if not outright winning 446 00:22:12,200 --> 00:22:14,960 Speaker 1: Massachusetts to really make a claim that you can, you know, 447 00:22:15,160 --> 00:22:18,080 Speaker 1: successfully compete at the national level for the presidency. Professor 448 00:22:18,119 --> 00:22:21,359 Speaker 1: Sheller had given your experience working with a variety of 449 00:22:21,359 --> 00:22:24,719 Speaker 1: politicians and particularly serving on the staffs of Senator Daniel 450 00:22:25,000 --> 00:22:28,400 Speaker 1: Patrick moynihan as well as Governor Mario Cuomo of New York, 451 00:22:28,440 --> 00:22:33,600 Speaker 1: I'm wondering from your perspective, whether the Democrats are consolidating 452 00:22:33,800 --> 00:22:37,600 Speaker 1: support enough early enough. In other words, what is sort 453 00:22:37,600 --> 00:22:39,560 Speaker 1: of the make it or break it time when we 454 00:22:39,600 --> 00:22:42,280 Speaker 1: have to see a certain degree of momentum emerging behind 455 00:22:42,359 --> 00:22:46,000 Speaker 1: one candidate. Well, I'm not convinced that that they have 456 00:22:46,080 --> 00:22:47,680 Speaker 1: to do that, because we look at what happened with 457 00:22:47,720 --> 00:22:50,760 Speaker 1: Trump in UH and you know, there wasn't a lot 458 00:22:50,800 --> 00:22:53,000 Speaker 1: of consensus there. He kept doing pretty well in terms 459 00:22:53,000 --> 00:22:55,240 Speaker 1: of the proportional representation states earlier in the in the 460 00:22:55,240 --> 00:22:57,800 Speaker 1: primaries for the Republicans and just emerged a somebody who 461 00:22:57,840 --> 00:22:59,480 Speaker 1: they weren't going to be able to beat. That could 462 00:22:59,600 --> 00:23:03,080 Speaker 1: very well happen with Bernie Sanders. So eventually, you know, 463 00:23:03,119 --> 00:23:06,119 Speaker 1: Republicans unify, even if they say they didn't want Trump 464 00:23:06,280 --> 00:23:08,280 Speaker 1: by election day, they got out the door and they 465 00:23:08,400 --> 00:23:11,399 Speaker 1: voted in a unified way for Trump. Democrats did not 466 00:23:11,480 --> 00:23:14,000 Speaker 1: do that for Hillary Clinton. So the D Day for 467 00:23:14,040 --> 00:23:16,439 Speaker 1: Democrats is always election day in the in the national 468 00:23:16,480 --> 00:23:19,320 Speaker 1: scope of things. But I just think, you know, Democrats 469 00:23:19,359 --> 00:23:22,200 Speaker 1: have to decide. If they don't unify, they can't win. 470 00:23:22,720 --> 00:23:26,080 Speaker 1: So this is just gonna be whoever it is. Bloomberg, Sanders, 471 00:23:26,119 --> 00:23:30,440 Speaker 1: Biden and Bloomberg also could benefit from Pete Bout dropping out. 472 00:23:30,480 --> 00:23:33,159 Speaker 1: If Amy Klobuchar drops out, then you know, creeping up 473 00:23:33,160 --> 00:23:35,879 Speaker 1: and sort of being competitive with Biden. If Bloomberg can 474 00:23:35,920 --> 00:23:38,800 Speaker 1: show that he can get some African American votes tomorrow 475 00:23:38,840 --> 00:23:41,680 Speaker 1: in addition to latinos, he becomes a viable alternative to 476 00:23:41,720 --> 00:23:45,000 Speaker 1: Bernie Sanders. So at some point Democrats are going to decide, 477 00:23:45,040 --> 00:23:48,080 Speaker 1: as Republicans always do, that they're just going to get 478 00:23:48,080 --> 00:23:51,040 Speaker 1: behind whoever the candidate is. And we should note that 479 00:23:51,160 --> 00:23:54,040 Speaker 1: Michael Bloomberg is the founder and principal owner of Bloomberg 480 00:23:54,160 --> 00:23:57,520 Speaker 1: LP and this radio station. So Wendy, let's talk about 481 00:23:58,119 --> 00:24:02,040 Speaker 1: Mr Sanders here. Bernie Sanders can he beat Trump? And 482 00:24:02,160 --> 00:24:04,520 Speaker 1: do you think do you agree with the concern that 483 00:24:04,560 --> 00:24:08,639 Speaker 1: maybe he could actually hurt Democrats down ballot. You know, 484 00:24:08,720 --> 00:24:12,240 Speaker 1: it's really sort of, you know, exploded all of our 485 00:24:12,280 --> 00:24:15,960 Speaker 1: ability to predict really the average voters inclination a to 486 00:24:15,960 --> 00:24:18,760 Speaker 1: get out the door to vote, which is something underestimated 487 00:24:18,800 --> 00:24:21,679 Speaker 1: in terms of Trump supporters. And that's the magic ticket 488 00:24:21,680 --> 00:24:24,520 Speaker 1: for Bernie Sanders. If he can win. He wins with 489 00:24:24,560 --> 00:24:26,639 Speaker 1: the same kind of strategy the Trump had, which is 490 00:24:26,800 --> 00:24:30,320 Speaker 1: tremendous enthusiasm among his supporters. So you know, people who 491 00:24:30,359 --> 00:24:32,199 Speaker 1: like Bernie are getting out the door and they're going 492 00:24:32,240 --> 00:24:34,119 Speaker 1: to make sure to vote. If he can actually, as 493 00:24:34,119 --> 00:24:35,959 Speaker 1: he says in the debates, if I can expand that 494 00:24:36,080 --> 00:24:39,000 Speaker 1: number of people who are really enthusiastic about me, he 495 00:24:39,040 --> 00:24:41,439 Speaker 1: can sort of pull a Trump like victory. I do 496 00:24:41,520 --> 00:24:44,760 Speaker 1: think there are challenges to that for him in particular areas, 497 00:24:44,760 --> 00:24:47,679 Speaker 1: in particular swing states, but I don't think it's impossible 498 00:24:47,720 --> 00:24:50,120 Speaker 1: to do if he follows that same playbook. And the 499 00:24:50,119 --> 00:24:53,159 Speaker 1: thing to watch is African American turnout turn out generally 500 00:24:53,160 --> 00:24:56,359 Speaker 1: in the primaries tomorrow among Democrats, but also African American 501 00:24:56,400 --> 00:24:59,280 Speaker 1: turnout in places like North Carolina. If turnout is high, 502 00:24:59,280 --> 00:25:01,200 Speaker 1: even if it's because bidens in the race or whatever reason, 503 00:25:01,240 --> 00:25:03,119 Speaker 1: you want to say, if people vote in the primary, 504 00:25:03,119 --> 00:25:05,280 Speaker 1: they're gonna vote in the general. That's usually what we see. 505 00:25:05,520 --> 00:25:08,440 Speaker 1: So if Bernie can generate high turnout in the primaries, 506 00:25:08,640 --> 00:25:10,880 Speaker 1: he's got an argument that those people will still come 507 00:25:10,880 --> 00:25:12,840 Speaker 1: back to the polls in November. So I don't think 508 00:25:12,880 --> 00:25:15,480 Speaker 1: anything should be you know, counted out as a possibility. 509 00:25:15,640 --> 00:25:17,600 Speaker 1: I think it's going to be harder for him to 510 00:25:17,640 --> 00:25:20,480 Speaker 1: explain how he'll pay for things that he's promised to do. 511 00:25:21,000 --> 00:25:24,480 Speaker 1: But enthusiasm is the number one, you know, a component 512 00:25:24,520 --> 00:25:27,520 Speaker 1: of turnout, and that's Bernie Sanders has that right now 513 00:25:27,560 --> 00:25:31,000 Speaker 1: amongst a decent size of the Democratic Party. Wendy Schiller, 514 00:25:31,040 --> 00:25:32,760 Speaker 1: thank you so much for being with us. Wendy Schiller, 515 00:25:32,800 --> 00:25:36,280 Speaker 1: Professor of political science and public Policy at Brown University 516 00:25:36,359 --> 00:25:39,520 Speaker 1: in a Providence, Rhode Island. Thanks for listening to the 517 00:25:39,560 --> 00:25:42,280 Speaker 1: Bloomberg pen L podcast. You can subscribe and listen to 518 00:25:42,280 --> 00:25:45,520 Speaker 1: interviews at Apple Podcasts or whatever podcast platform you prefer. 519 00:25:45,920 --> 00:25:48,680 Speaker 1: Paul Sweeney, I'm on Twitter at pt Sweeney. I'm Lisa 520 00:25:48,800 --> 00:25:51,360 Speaker 1: bram Woyds. I'm on Twitter at Lisa bramw wits one 521 00:25:51,560 --> 00:25:54,119 Speaker 1: before the podcast. You can always catch us worldwide on 522 00:25:54,200 --> 00:25:55,040 Speaker 1: Bloomberg Radio,