1 00:00:01,400 --> 00:00:04,120 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney. Along 2 00:00:04,120 --> 00:00:06,200 Speaker 1: with my co host of Bonnie Quinn. Every business day 3 00:00:06,240 --> 00:00:10,360 Speaker 1: we bring you interviews from ceo, market pros, and Bloomberg experts, 4 00:00:10,400 --> 00:00:13,600 Speaker 1: along with essential market moving news. Find the Bloomberg Markets 5 00:00:13,600 --> 00:00:17,000 Speaker 1: Podcast on Apple podcast or wherever you listen to podcasts, 6 00:00:17,000 --> 00:00:20,759 Speaker 1: and on Bloomberg dot com. Let's bring in our next guest. 7 00:00:20,760 --> 00:00:23,320 Speaker 1: Now going to be a fascinating conversation with Jim Anderson, 8 00:00:23,320 --> 00:00:26,920 Speaker 1: who is CEO of Social Flow and in full disclosure, 9 00:00:27,000 --> 00:00:29,200 Speaker 1: social Floe as a platform that is used by Bloomberg 10 00:00:29,240 --> 00:00:33,839 Speaker 1: for social media purposes, used by many many companies. Jim, Welcome. 11 00:00:34,000 --> 00:00:35,519 Speaker 1: We brought you on because we want to talk to 12 00:00:35,560 --> 00:00:37,160 Speaker 1: you a little bit about what happened at that also 13 00:00:37,280 --> 00:00:41,720 Speaker 1: rally over the weekend and how K pop Zoomers and 14 00:00:42,680 --> 00:00:46,680 Speaker 1: those who stand with them, if you like, managed to 15 00:00:47,280 --> 00:00:51,040 Speaker 1: reserve tickets for this rally and then of course they 16 00:00:51,040 --> 00:00:53,920 Speaker 1: didn't turn up. They weren't interested in doing that. They 17 00:00:53,960 --> 00:00:55,880 Speaker 1: how did it work to talk to us about TikTok 18 00:00:55,920 --> 00:01:01,160 Speaker 1: and the power of sort of amplification. Yeah, funny, Jail, 19 00:01:01,160 --> 00:01:02,680 Speaker 1: thanks for having me. This is this is a great 20 00:01:02,720 --> 00:01:05,920 Speaker 1: story in terms of just illustrating the power of viral 21 00:01:06,200 --> 00:01:08,480 Speaker 1: distribution on social networks, right, I mean that's not a 22 00:01:08,480 --> 00:01:11,480 Speaker 1: new concept. Facebook's weren't been around for more than a decade, 23 00:01:11,480 --> 00:01:15,000 Speaker 1: Twitter and others. And so what we saw is TikTok, 24 00:01:15,000 --> 00:01:17,840 Speaker 1: which is an application typically is for like to dance 25 00:01:17,959 --> 00:01:21,600 Speaker 1: videos being harnessed in a really new and different way. 26 00:01:21,640 --> 00:01:24,199 Speaker 1: But the same algorithms that pow are those dance videos 27 00:01:24,200 --> 00:01:26,080 Speaker 1: and make them show up in your feet also power 28 00:01:26,200 --> 00:01:31,280 Speaker 1: the teenage activists efforts and interestingly, they're they're disappearing messages. Right. 29 00:01:31,280 --> 00:01:33,640 Speaker 1: One of the things about TikTok is the messages disappear 30 00:01:33,720 --> 00:01:35,800 Speaker 1: after some period of time. So not only did their 31 00:01:35,800 --> 00:01:37,880 Speaker 1: parents not know what was going on, because parents, I 32 00:01:37,920 --> 00:01:39,880 Speaker 1: have a teenage daughter, it's awfully difficult to know what's 33 00:01:39,880 --> 00:01:43,000 Speaker 1: going on with your teenager, but the messages themselves disappeared. 34 00:01:43,040 --> 00:01:45,360 Speaker 1: So it's sort of teenage tradecraft at work in a 35 00:01:45,440 --> 00:01:48,240 Speaker 1: in a social media world. So, Jim, do we have 36 00:01:48,360 --> 00:01:52,560 Speaker 1: hard data that shows that this is what really happened, 37 00:01:52,560 --> 00:01:55,440 Speaker 1: that there was, in fact, I guess quote unquote bogus 38 00:01:55,480 --> 00:02:00,400 Speaker 1: requests for tickets that were never fulfilled or picked up. Well, 39 00:02:00,400 --> 00:02:02,600 Speaker 1: we don't, and there's really no way for us to know. 40 00:02:02,720 --> 00:02:04,720 Speaker 1: I can I can bet you that the campaign, the 41 00:02:04,760 --> 00:02:07,200 Speaker 1: Trump campaign, has that data, but it's certainly not going 42 00:02:07,240 --> 00:02:09,360 Speaker 1: to be in their interests to sort of give this 43 00:02:09,400 --> 00:02:12,600 Speaker 1: story any oxygen and to admit that that happened. And 44 00:02:12,639 --> 00:02:15,080 Speaker 1: I do want to make one really important point, because 45 00:02:15,080 --> 00:02:17,760 Speaker 1: this this issue officers gets dislated. The activities of the 46 00:02:17,760 --> 00:02:20,360 Speaker 1: teenagers didn't keep people from showing up to the rally. 47 00:02:20,440 --> 00:02:21,840 Speaker 1: I think the fact that we're in the midst of 48 00:02:21,840 --> 00:02:25,760 Speaker 1: a global pandemic. The rally was in Tulsa, Oklahoma. That 49 00:02:25,840 --> 00:02:28,720 Speaker 1: population of Tulsa's four hundred thousand. You know, you're asking 50 00:02:28,919 --> 00:02:31,720 Speaker 1: to fill an eighteen or nineteen thousand feet arena plus 51 00:02:31,760 --> 00:02:35,240 Speaker 1: forty thousand feet of of overflow from the outdoor stage. 52 00:02:35,280 --> 00:02:38,040 Speaker 1: I think what they did, though, is they created the expectation, 53 00:02:38,120 --> 00:02:40,120 Speaker 1: oh my goodness, this thing is out of control. The 54 00:02:40,160 --> 00:02:43,280 Speaker 1: campaign wanted to believe that there was sort of this 55 00:02:43,440 --> 00:02:46,240 Speaker 1: giant pent up demand, and so then they started talking 56 00:02:46,240 --> 00:02:48,480 Speaker 1: about it. They wanted to believe it was true, and 57 00:02:48,520 --> 00:02:50,959 Speaker 1: then they got set up just for a big, giant, 58 00:02:51,000 --> 00:02:54,120 Speaker 1: sort of deflation of expectations. That's what the thieves managed 59 00:02:54,120 --> 00:02:55,679 Speaker 1: to see exactly. So, on the one hand, there was 60 00:02:55,680 --> 00:02:57,680 Speaker 1: a little bit of hubris. They were boasting about how 61 00:02:57,680 --> 00:03:01,120 Speaker 1: many people are coming, they were creating out door overflow spaces. 62 00:03:01,120 --> 00:03:03,560 Speaker 1: On the other hand, there was complacency. They didn't sort 63 00:03:03,560 --> 00:03:07,920 Speaker 1: of call to arms the base, which may have been 64 00:03:07,919 --> 00:03:12,079 Speaker 1: a good thing given the coronavirus has definitely knock gone away. 65 00:03:12,160 --> 00:03:16,000 Speaker 1: What's the power that you know, a group of fans 66 00:03:16,160 --> 00:03:18,639 Speaker 1: like K pop fans and zoomers and so on can 67 00:03:18,760 --> 00:03:21,960 Speaker 1: leverage on TikTok Beyond this is there is there something 68 00:03:22,080 --> 00:03:24,639 Speaker 1: a little more political in terms of getting out the 69 00:03:24,720 --> 00:03:29,440 Speaker 1: vote or in terms of you know, um, convincing people 70 00:03:29,840 --> 00:03:34,400 Speaker 1: to participate in democracy more. Yeah, I think there definitely 71 00:03:34,440 --> 00:03:36,320 Speaker 1: are a lot of things and and you know, many 72 00:03:36,320 --> 00:03:38,120 Speaker 1: people are excited that. Wow, that's is sort of the 73 00:03:38,160 --> 00:03:41,600 Speaker 1: type of a much larger sphere as uh teenagers come 74 00:03:41,600 --> 00:03:44,240 Speaker 1: of age, come of voting age. Specifically, I saw speciftic 75 00:03:44,320 --> 00:03:47,040 Speaker 1: this morning that one of an eligible voters will be 76 00:03:47,120 --> 00:03:50,480 Speaker 1: gen z uh and the upcoming presidential election. So you know, 77 00:03:50,520 --> 00:03:53,040 Speaker 1: they they're starting to find their voice. And I'll go 78 00:03:53,080 --> 00:03:55,680 Speaker 1: back to these algorithms. I mean, it's now very specky 79 00:03:55,760 --> 00:03:58,320 Speaker 1: and not very accessible to talk about algorithms, but largely 80 00:03:58,360 --> 00:04:03,720 Speaker 1: algorithms are a political right. They can spread content on left, right, middle, 81 00:04:03,880 --> 00:04:06,920 Speaker 1: updown that they generally are not political. I know people's 82 00:04:06,960 --> 00:04:09,920 Speaker 1: criticisms of them are significant and they feel like their 83 00:04:09,960 --> 00:04:13,200 Speaker 1: side is being discriminated against. But if the teenagers are 84 00:04:13,200 --> 00:04:15,640 Speaker 1: excited and are spreading it and are paying attention, the 85 00:04:15,680 --> 00:04:18,279 Speaker 1: algorithms noticed that, and then they contribute to that. And 86 00:04:18,320 --> 00:04:22,560 Speaker 1: I've sent viral distribution of of content is and and 87 00:04:22,600 --> 00:04:25,479 Speaker 1: that's exactly what TikTok is doing. So jim I, I 88 00:04:25,520 --> 00:04:28,560 Speaker 1: know that TikTok is a Chinese company. I can imagine 89 00:04:28,600 --> 00:04:32,479 Speaker 1: the Trump administration that Trump campaign knows this as well. 90 00:04:32,520 --> 00:04:35,600 Speaker 1: Should we expect a torrent of tweets coming out of 91 00:04:35,880 --> 00:04:39,320 Speaker 1: President Trump, you know, saying that Chinese China is interfering 92 00:04:39,360 --> 00:04:42,640 Speaker 1: with the election of the campaign. Well, I would always 93 00:04:42,680 --> 00:04:44,640 Speaker 1: hesitate to predict what the president is going to do 94 00:04:44,640 --> 00:04:47,120 Speaker 1: on Twitter for all the obvious reasons. But I will 95 00:04:47,120 --> 00:04:49,760 Speaker 1: say that there was bound to be some really uncomfortable 96 00:04:49,800 --> 00:04:53,480 Speaker 1: conversations and probably uncomfortable Sunday at TikTok. When you're owned 97 00:04:53,520 --> 00:04:56,440 Speaker 1: by a Chinese company, They've gone to great efforts, including 98 00:04:56,520 --> 00:04:59,159 Speaker 1: hiring a very senior executive from Disney to try to 99 00:04:59,240 --> 00:05:02,279 Speaker 1: sort of build their brand as not a Chinese own brand. 100 00:05:02,600 --> 00:05:04,520 Speaker 1: That's probably the last thing they want to say. And 101 00:05:04,640 --> 00:05:07,600 Speaker 1: to be clear, TikTok. TikTok really had nothing to do 102 00:05:07,640 --> 00:05:10,720 Speaker 1: with this from a company standpoint. They just provided the platform. 103 00:05:11,040 --> 00:05:14,080 Speaker 1: The K pop users or other teenagers provided the excitement 104 00:05:14,120 --> 00:05:16,839 Speaker 1: and the energy, and they used the platform in some 105 00:05:16,960 --> 00:05:19,200 Speaker 1: ways as the platform was designed to be used, which 106 00:05:19,240 --> 00:05:22,000 Speaker 1: is to distribute you know, viral videos, um. But but 107 00:05:22,080 --> 00:05:24,039 Speaker 1: in other ways, you know, sort of the use case 108 00:05:24,240 --> 00:05:27,640 Speaker 1: in and around politics is certainly not what TikTok likely 109 00:05:27,680 --> 00:05:30,800 Speaker 1: had in mind. Jim Anderson, thank you so much for 110 00:05:31,160 --> 00:05:34,840 Speaker 1: joining us. Fascinating kind of story here that I'm sure 111 00:05:35,279 --> 00:05:37,360 Speaker 1: is going to continue to develop and will continue to follow. 112 00:05:37,440 --> 00:05:42,200 Speaker 1: Jim Anderson, CEO of Social Flow, based in New York City, Fannie, 113 00:05:42,240 --> 00:05:44,480 Speaker 1: that's just interesting. You think about social media and the 114 00:05:44,520 --> 00:05:47,840 Speaker 1: impact that's having obviously across all of our lives over 115 00:05:47,880 --> 00:05:50,280 Speaker 1: the past ten years or so, but certainly the political 116 00:05:50,720 --> 00:05:52,640 Speaker 1: sphere as well. And we thought it was really limited 117 00:05:52,680 --> 00:05:54,720 Speaker 1: to a kind of a Facebook, a Twitter kind of thing, 118 00:05:54,760 --> 00:05:58,400 Speaker 1: but here comes TikTok, and each one of these platforms 119 00:05:58,440 --> 00:06:00,840 Speaker 1: has a different way of connecting with the audience. And 120 00:06:00,880 --> 00:06:03,120 Speaker 1: it may be the same audience and maybe different audiences, 121 00:06:03,120 --> 00:06:06,880 Speaker 1: but TikTok content needs to be very different from Twitter 122 00:06:06,920 --> 00:06:10,000 Speaker 1: content or Facebook content. And just as a as a 123 00:06:10,080 --> 00:06:13,040 Speaker 1: sort of a separate example, you look at Sarah Cooper, 124 00:06:13,279 --> 00:06:17,760 Speaker 1: who's the impersonator of Trump. She made her debut really 125 00:06:17,760 --> 00:06:19,920 Speaker 1: on TikTok, even though she had been on the other platforms. 126 00:06:19,920 --> 00:06:22,080 Speaker 1: It was on TikTok that you really took off and 127 00:06:22,120 --> 00:06:24,840 Speaker 1: then transferred to Twitter. Yeah, and as Jim mentioned, TikTok 128 00:06:25,000 --> 00:06:27,800 Speaker 1: obviously really popular with the really the the younger demos. 129 00:06:27,839 --> 00:06:32,640 Speaker 1: And that's certainly interesting from a political perspective. And it 130 00:06:32,720 --> 00:06:35,400 Speaker 1: is time checken with Bloomberg Opinion or Joy Now by 131 00:06:35,440 --> 00:06:39,000 Speaker 1: Bloomberg Opinion columnist Neil Ferguson. He's also Senior Fellow at 132 00:06:39,000 --> 00:06:42,719 Speaker 1: the Hoover Institution at Stanford University. Noted historian of course, 133 00:06:42,960 --> 00:06:45,400 Speaker 1: and author of many many books, from The Ascent of 134 00:06:45,440 --> 00:06:48,640 Speaker 1: Money to the House of Rothschild, Too Much much More. Neil, 135 00:06:48,800 --> 00:06:51,760 Speaker 1: thanks for joining your latest column. America is on the road, 136 00:06:52,120 --> 00:06:54,640 Speaker 1: but whether it's on the road to relapse or recovery 137 00:06:54,880 --> 00:07:01,000 Speaker 1: is the question. What say you? Well, maybe both. That's 138 00:07:01,080 --> 00:07:04,960 Speaker 1: the same. We can see really to rapid recovery, not 139 00:07:05,080 --> 00:07:09,320 Speaker 1: only in some of the obvious nuns like the unemployment 140 00:07:09,400 --> 00:07:13,360 Speaker 1: rate or retail sales, but actually mobility data, which is 141 00:07:13,400 --> 00:07:16,840 Speaker 1: a great higher frequency tracker of what's happening in the country. 142 00:07:16,840 --> 00:07:19,240 Speaker 1: And you can see that just looking at say the 143 00:07:19,320 --> 00:07:25,360 Speaker 1: Google data on trips to retail and recreation destination. They're 144 00:07:25,400 --> 00:07:28,880 Speaker 1: on track to be back normal by around July ten 145 00:07:29,080 --> 00:07:32,120 Speaker 1: or eleventh. And at the same time, what we're seeing 146 00:07:32,800 --> 00:07:38,400 Speaker 1: is significant increases in case numbers, not nationwide, but in 147 00:07:38,520 --> 00:07:42,720 Speaker 1: particular regions the South, for example, some Western states, and 148 00:07:42,760 --> 00:07:48,600 Speaker 1: so we've got both relatively rapid it's not v shaped recovery. Also, 149 00:07:48,760 --> 00:07:51,720 Speaker 1: and of course there's a relationship. You're getting this increase 150 00:07:51,800 --> 00:07:55,480 Speaker 1: in in case numbers, positive tests and hospitalizations, especially in 151 00:07:55,560 --> 00:07:59,280 Speaker 1: states like Aaron Zone, Florida and texass to look like 152 00:07:59,440 --> 00:08:02,400 Speaker 1: you've got got a second wave of COVID ninetine in 153 00:08:02,400 --> 00:08:05,800 Speaker 1: those states, and that that's the problem that we're seeing 154 00:08:05,800 --> 00:08:10,040 Speaker 1: in the US today. Were rapidly retuble economically, but without 155 00:08:10,080 --> 00:08:14,880 Speaker 1: social distending, without masks wearing, people are being somewhat reckless. 156 00:08:14,920 --> 00:08:18,520 Speaker 1: By comparison with the europe pensive part. And that's driving 157 00:08:18,800 --> 00:08:22,600 Speaker 1: in case numbers back up neil to what extent as 158 00:08:22,760 --> 00:08:26,200 Speaker 1: the I guess the COVID virus and a response to 159 00:08:26,280 --> 00:08:29,800 Speaker 1: it at the state level and the reopening strategies at 160 00:08:29,800 --> 00:08:32,240 Speaker 1: the state level, how was that to what extent has 161 00:08:32,280 --> 00:08:36,880 Speaker 1: that become politicized? I e. The more conservative UH states 162 00:08:36,880 --> 00:08:40,400 Speaker 1: and regions of the country perhaps taken a less stringent 163 00:08:40,960 --> 00:08:44,640 Speaker 1: uh COVID response than maybe some of the more democratic 164 00:08:44,720 --> 00:08:50,600 Speaker 1: or liberal regions of the country. It's hy politicized more 165 00:08:50,640 --> 00:08:54,319 Speaker 1: than I think in any other country that I've I've studied. 166 00:08:55,200 --> 00:09:01,360 Speaker 1: Attitudes towards the pandemic itself varies substantially across party lines. 167 00:09:01,480 --> 00:09:04,640 Speaker 1: If you look at civics data, Democrats are still really 168 00:09:04,679 --> 00:09:09,400 Speaker 1: worried about COVID betein in their area and Republicans really aren't. 169 00:09:09,800 --> 00:09:13,880 Speaker 1: You look at the different strategies states have adopted. The 170 00:09:13,960 --> 00:09:17,960 Speaker 1: speaking Blue states slower to reopen uh US in touch 171 00:09:18,120 --> 00:09:23,240 Speaker 1: lockdowns all along and red states UH less intense locklands 172 00:09:23,440 --> 00:09:27,439 Speaker 1: ease earlier reopening. And so what that translates in a 173 00:09:27,520 --> 00:09:32,280 Speaker 1: really striking feature, really striking divergence in not only have 174 00:09:32,320 --> 00:09:35,719 Speaker 1: them on the recovery, but the second wave problem. Now, 175 00:09:35,720 --> 00:09:39,440 Speaker 1: there's a slightly confounding fact here which shares some uh, 176 00:09:39,679 --> 00:09:42,600 Speaker 1: some eidemiologists have been commenting on in the last twenty 177 00:09:42,600 --> 00:09:46,600 Speaker 1: four hours that part of what makes COVID nineteens spread 178 00:09:46,679 --> 00:09:50,360 Speaker 1: a lot is their conditioning teams, and so in states 179 00:09:50,400 --> 00:09:54,240 Speaker 1: that are hotter, like Arizona where people actually don't want 180 00:09:54,240 --> 00:09:56,440 Speaker 1: to be outside because it's so hot, in mus Try, 181 00:09:56,440 --> 00:09:59,320 Speaker 1: in parts of Texas, obviously in Florida, air con use 182 00:09:59,400 --> 00:10:01,840 Speaker 1: has gone up in the last couple of months. And 183 00:10:01,920 --> 00:10:05,080 Speaker 1: so because of the correlation between red states and hot states, 184 00:10:05,360 --> 00:10:08,880 Speaker 1: it's not just a partisan divide that's driving a second 185 00:10:08,880 --> 00:10:10,679 Speaker 1: wave in red states. It's also the fact that they're 186 00:10:10,720 --> 00:10:13,760 Speaker 1: hot states. Yeah, and I will say our books southerl 187 00:10:13,800 --> 00:10:16,400 Speaker 1: Under a great column on that. The other day, Neil 188 00:10:16,480 --> 00:10:19,199 Speaker 1: talked to us about the different approaches to reopening around 189 00:10:19,240 --> 00:10:23,320 Speaker 1: the world, because obviously, you know, countries can't stay closed forever. 190 00:10:23,480 --> 00:10:27,920 Speaker 1: And you have Italy, which was extraordinarily badly hit reopening 191 00:10:27,960 --> 00:10:30,120 Speaker 1: and I'm sure they were terrified, but they did it. 192 00:10:31,080 --> 00:10:33,800 Speaker 1: The likes of Sweden, which didn't take the same approach whatsoever, 193 00:10:33,960 --> 00:10:37,600 Speaker 1: and as having sort of different problems. Now, is there 194 00:10:37,600 --> 00:10:41,880 Speaker 1: a model that's maybe the perfect model. Well, there are 195 00:10:41,920 --> 00:10:45,840 Speaker 1: certainly better models than the one that the US is adopting, 196 00:10:45,880 --> 00:10:49,559 Speaker 1: which my colleague Hoover John Cochin called the dumb reopening, 197 00:10:49,600 --> 00:10:52,960 Speaker 1: where you just go back to normal without social distancing 198 00:10:53,000 --> 00:10:55,560 Speaker 1: really and without mask wearing. If you go all the 199 00:10:55,559 --> 00:10:59,480 Speaker 1: way to East Asia where the pandemic struck first, the 200 00:10:59,600 --> 00:11:03,240 Speaker 1: role more balls of Taiwan and South Korea, which really 201 00:11:03,280 --> 00:11:06,720 Speaker 1: pioneered early testing and contact tracing, didn't have to do 202 00:11:06,800 --> 00:11:09,400 Speaker 1: full lockdowns, and in fact, in the case of Taiwan, 203 00:11:09,440 --> 00:11:13,880 Speaker 1: have had minimal COVID nine for COVID nineteen fatalities. Europe 204 00:11:13,920 --> 00:11:16,160 Speaker 1: lies somewhere in the middle, and it is a very 205 00:11:16,320 --> 00:11:19,720 Speaker 1: picture because you've had pretty disastrous experiences in Italy and 206 00:11:19,760 --> 00:11:24,439 Speaker 1: Spain and Belgium, whereas in Germany and also interestingly in 207 00:11:24,480 --> 00:11:28,680 Speaker 1: Greece they quickly cottoned onto the need for for testing 208 00:11:28,760 --> 00:11:31,480 Speaker 1: and contact tracing. And I think if you look at 209 00:11:31,520 --> 00:11:34,880 Speaker 1: the European states that have reopened the soonest, and that 210 00:11:34,920 --> 00:11:41,520 Speaker 1: would include Germany, Austria, Denmark as well as Switzerland, there's 211 00:11:41,520 --> 00:11:44,480 Speaker 1: no sign as at this point of second waves in 212 00:11:44,520 --> 00:11:47,800 Speaker 1: those countries, not in case numbers and certainly not immortality. 213 00:11:48,240 --> 00:11:51,280 Speaker 1: It's all about jumping on these super spreader events because 214 00:11:51,280 --> 00:11:54,840 Speaker 1: COVID nineteen is is spread by a relative minority of 215 00:11:54,880 --> 00:11:57,280 Speaker 1: people who given to a lot of people, like twent 216 00:11:57,720 --> 00:12:01,200 Speaker 1: of infected people are responsible for eight a send of infections. 217 00:12:01,320 --> 00:12:04,280 Speaker 1: If you're doing testing and contact tracing, you can get 218 00:12:04,280 --> 00:12:08,360 Speaker 1: those super spreaders or stop the super spreader events from happening. 219 00:12:08,640 --> 00:12:11,920 Speaker 1: If you don't do testing and contact tracing in a 220 00:12:12,000 --> 00:12:15,600 Speaker 1: systematic way, which is the American route that we're going down, 221 00:12:15,960 --> 00:12:18,680 Speaker 1: it's basically playing lack a mole with a blindfold on, 222 00:12:18,800 --> 00:12:20,760 Speaker 1: and if you've ever tried that, you'll find that you 223 00:12:20,840 --> 00:12:23,360 Speaker 1: miss a lot of mold ken you know, at the 224 00:12:23,360 --> 00:12:25,800 Speaker 1: beginning of this whole issue, here, this whole process of 225 00:12:26,000 --> 00:12:28,800 Speaker 1: dealing with the pandemic, I was surprised there wasn't a 226 00:12:28,880 --> 00:12:31,920 Speaker 1: federal response. It was more of a state by state response, 227 00:12:32,000 --> 00:12:34,400 Speaker 1: and we became accustomed hearing Governor Cuomwell from the State 228 00:12:34,400 --> 00:12:37,400 Speaker 1: of New York giving this the daily update. Should I 229 00:12:37,400 --> 00:12:42,679 Speaker 1: have expected a federal response, well, historically, because it's a 230 00:12:42,679 --> 00:12:47,120 Speaker 1: federal system which devolves a lot of responsibility to state 231 00:12:47,280 --> 00:12:51,560 Speaker 1: and indeed municipalities. The answer that question, no, really because 232 00:12:51,600 --> 00:12:54,240 Speaker 1: in all the previous pandemics, whether you look at the 233 00:12:54,280 --> 00:12:59,240 Speaker 1: Big Influenza or there the other influenza pandemic of fifty 234 00:12:59,240 --> 00:13:04,120 Speaker 1: seven fifty, it was essentially a decentralized story where state 235 00:13:04,360 --> 00:13:08,800 Speaker 1: municipalities took their own decisions about how strictly to limit 236 00:13:08,840 --> 00:13:12,800 Speaker 1: public gatherings. So this is certainly not an unprecedented story. 237 00:13:13,160 --> 00:13:15,600 Speaker 1: I do think that the federal government has a role 238 00:13:15,640 --> 00:13:17,520 Speaker 1: to play, though, and I don't think it played that 239 00:13:17,600 --> 00:13:22,040 Speaker 1: role very brillian. This is usually blamed on President Trump, 240 00:13:22,120 --> 00:13:25,360 Speaker 1: I think to access by the media. Clearly his judgment 241 00:13:25,480 --> 00:13:30,560 Speaker 1: wasn't fantastic, and indeed on some issues it was downright crazy. 242 00:13:30,600 --> 00:13:32,640 Speaker 1: But if you look at what was going on at 243 00:13:32,679 --> 00:13:35,119 Speaker 1: the level of the Department of Health and Human Services 244 00:13:35,160 --> 00:13:38,120 Speaker 1: and look down at CDC, there was a pretty serious 245 00:13:38,160 --> 00:13:41,600 Speaker 1: public health failure at the federal level. Testing, far from 246 00:13:41,640 --> 00:13:45,680 Speaker 1: being ramped up, actually was held back by CDC. And 247 00:13:45,760 --> 00:13:47,960 Speaker 1: I do think there's a lot of questions still to 248 00:13:48,000 --> 00:13:52,840 Speaker 1: be asked about why it was that HHS generally failed 249 00:13:53,040 --> 00:13:56,800 Speaker 1: but at least communicate effectively to the states what they 250 00:13:56,800 --> 00:13:58,480 Speaker 1: needed to do. So no, I think there was a 251 00:13:58,480 --> 00:14:01,840 Speaker 1: failure at the federal level, even in this system that 252 00:14:01,960 --> 00:14:05,120 Speaker 1: is relatively de central minded. Neil, thank you so much 253 00:14:05,240 --> 00:14:08,040 Speaker 1: for joining us. We really appreciate your insight. Neil Ferguson. 254 00:14:08,280 --> 00:14:12,319 Speaker 1: He's a senior fellow at the Hoover Institution at Stanford University. 255 00:14:12,320 --> 00:14:15,680 Speaker 1: Also Bloomberg opinion columnists based at their in beautiful Palo 256 00:14:15,840 --> 00:14:19,120 Speaker 1: out There, California, one of the greatest, most beautiful places 257 00:14:19,160 --> 00:14:23,720 Speaker 1: in the US. Well, as you know, it's been quite 258 00:14:23,720 --> 00:14:27,400 Speaker 1: the volatile a few months. Markets underwritten by central banks 259 00:14:27,400 --> 00:14:31,760 Speaker 1: around the world, and plenty plenty demand four dollars. Let's 260 00:14:31,760 --> 00:14:33,320 Speaker 1: bring in somebody who knows a little bit about how 261 00:14:33,320 --> 00:14:35,720 Speaker 1: to put together a portfolio and what to do maybe 262 00:14:35,760 --> 00:14:38,480 Speaker 1: in an era of such volatility. Down scaley as head 263 00:14:38,480 --> 00:14:40,960 Speaker 1: of market research and Strategy of Wealth Management, and Morgan 264 00:14:41,040 --> 00:14:44,840 Speaker 1: Stanley Don thanks for joining. You obviously have plenty of 265 00:14:44,880 --> 00:14:47,440 Speaker 1: clients that are probably calling you and saying, what do 266 00:14:47,520 --> 00:14:50,560 Speaker 1: we do, where do we put our our our money 267 00:14:50,560 --> 00:14:53,520 Speaker 1: to work? What asset classes could benefit us here? What 268 00:14:53,560 --> 00:14:56,400 Speaker 1: do you say to them? Yeah, good morning, Bonny, and 269 00:14:56,400 --> 00:14:58,360 Speaker 1: thank you so much for having me on your your 270 00:14:58,400 --> 00:15:01,200 Speaker 1: show this morning. So a look, we're getting called and 271 00:15:01,240 --> 00:15:04,560 Speaker 1: we're getting zoomed. Of course now by time, so we're 272 00:15:04,640 --> 00:15:07,760 Speaker 1: telling them a couple of things. Number One, we're saying 273 00:15:07,800 --> 00:15:10,640 Speaker 1: that you've seen the big crash and the big euphoric 274 00:15:10,760 --> 00:15:13,440 Speaker 1: rally back and the big news. The big fireworks are 275 00:15:13,480 --> 00:15:16,000 Speaker 1: over for now. We think the market is likely to 276 00:15:16,040 --> 00:15:19,160 Speaker 1: consolidate into a arrange the next three to six months, 277 00:15:19,240 --> 00:15:23,440 Speaker 1: as the market starts to consider some other factors including 278 00:15:23,960 --> 00:15:28,000 Speaker 1: what's the rate of change on the reopening amid the reopening, 279 00:15:28,080 --> 00:15:31,640 Speaker 1: what does the virus flare ups look like? Um. At 280 00:15:31,640 --> 00:15:34,080 Speaker 1: the same time, you're gonna start to hear more positive 281 00:15:34,160 --> 00:15:39,680 Speaker 1: progress or potential headlines around vaccines, anti viral therapy. Uh. 282 00:15:39,680 --> 00:15:42,520 Speaker 1: And so the market is really juggling a lot of factors, 283 00:15:42,560 --> 00:15:45,000 Speaker 1: both to the upside and the downside, and in some 284 00:15:45,160 --> 00:15:48,320 Speaker 1: we think that keeps the market rather consolidated at least 285 00:15:48,360 --> 00:15:50,280 Speaker 1: for the next three or six months. But we do 286 00:15:50,400 --> 00:15:53,080 Speaker 1: think going into next year, and you've heard Morgan family 287 00:15:53,160 --> 00:15:56,120 Speaker 1: talk about this extensively now for three months, we do 288 00:15:56,280 --> 00:15:59,800 Speaker 1: think the overarching theme is a V shaped economic for 289 00:16:00,000 --> 00:16:03,240 Speaker 1: every going into next year. All right, Dan, So the 290 00:16:03,360 --> 00:16:06,640 Speaker 1: V shape recovery going into next year, that's you know, 291 00:16:06,640 --> 00:16:08,600 Speaker 1: at one point that was kind of I would call 292 00:16:08,640 --> 00:16:11,960 Speaker 1: it consensus initially uh, and then that seemed to fade. 293 00:16:12,040 --> 00:16:15,240 Speaker 1: Here is the the depths of the pandemic. Any economic 294 00:16:15,320 --> 00:16:17,080 Speaker 1: data started coming out and people are saying, I don't 295 00:16:17,080 --> 00:16:19,720 Speaker 1: think that V is gonna happen. Now it seems to 296 00:16:19,760 --> 00:16:22,520 Speaker 1: be coming back a little bit. What's the the kind 297 00:16:22,520 --> 00:16:24,840 Speaker 1: of the two or three drivers for you to say 298 00:16:24,920 --> 00:16:29,120 Speaker 1: a V shape recovery? Sure, it's it's an excellent question, 299 00:16:29,160 --> 00:16:32,680 Speaker 1: and one I would just highlight we we really reiterated 300 00:16:32,720 --> 00:16:37,560 Speaker 1: throughout despite potentially you know, changing sentiments among among the consensus. 301 00:16:37,600 --> 00:16:40,520 Speaker 1: So what's driving the V shape recovery. It's really the 302 00:16:40,840 --> 00:16:44,040 Speaker 1: size and the scope and the speed of policy. So 303 00:16:44,080 --> 00:16:47,760 Speaker 1: when you look at fiscal and monetary policy combined, we've 304 00:16:47,800 --> 00:16:52,440 Speaker 1: already executed around a level around fifty five oh of 305 00:16:52,600 --> 00:16:56,240 Speaker 1: U s GDP, which we all know it far exceeds 306 00:16:56,280 --> 00:17:00,240 Speaker 1: any historical stimulus measures in any cycle ever. So that's 307 00:17:00,320 --> 00:17:04,199 Speaker 1: number one. Number two, we think that the speed of 308 00:17:04,240 --> 00:17:07,880 Speaker 1: the policy response has been incredibly notable. Why because when 309 00:17:07,880 --> 00:17:10,679 Speaker 1: you look at precedents like oh A, it took the 310 00:17:10,720 --> 00:17:13,639 Speaker 1: FED and it took Congress months to put together the 311 00:17:13,640 --> 00:17:18,080 Speaker 1: emergency playbooks they executed back then, and that unfortunately allowed 312 00:17:18,080 --> 00:17:20,760 Speaker 1: the credit cycle to deepen. And so what's really different 313 00:17:20,840 --> 00:17:24,680 Speaker 1: this time is that the policymakers acted immediately. And the 314 00:17:24,760 --> 00:17:28,240 Speaker 1: fact was the episode of the crisis was health. So 315 00:17:28,280 --> 00:17:32,800 Speaker 1: it's a completely bipartisan related epicenter and and and something 316 00:17:32,840 --> 00:17:36,920 Speaker 1: everyone could band together around. And I think that's really crucial, right, 317 00:17:36,960 --> 00:17:41,200 Speaker 1: because it prevented a health slash economic crisis from morphing 318 00:17:41,240 --> 00:17:44,000 Speaker 1: into a financial crisis. So the second part of the 319 00:17:44,040 --> 00:17:49,200 Speaker 1: policy V shaped impact is truly seeing the credit markets 320 00:17:49,240 --> 00:17:52,560 Speaker 1: and some of the liquidity in the markets, functioning companies 321 00:17:52,600 --> 00:17:56,240 Speaker 1: accessing capital markets very efficiently as you've seen. And I 322 00:17:56,240 --> 00:17:58,760 Speaker 1: guess I would say the last part, right is we 323 00:17:58,880 --> 00:18:01,720 Speaker 1: all know we are a consumer lead economy, and when 324 00:18:01,760 --> 00:18:06,040 Speaker 1: you look at the initial reaction from consumers who are 325 00:18:06,080 --> 00:18:09,320 Speaker 1: just starting to reopen and resume normal activities. We saw 326 00:18:09,359 --> 00:18:13,400 Speaker 1: the retail sales upside surprise recently. We heard a very 327 00:18:13,440 --> 00:18:17,200 Speaker 1: positive housing and mortgage update at our Morgan Stanley Financials 328 00:18:17,200 --> 00:18:20,359 Speaker 1: conference recently. We think the consumer is going to come 329 00:18:20,400 --> 00:18:23,080 Speaker 1: back particularly strong given the pend up demand, and that 330 00:18:23,160 --> 00:18:26,679 Speaker 1: all informs the V shaped scenario done. What proportion of 331 00:18:26,720 --> 00:18:30,040 Speaker 1: the people you speak with, both clients and colleagues are 332 00:18:30,040 --> 00:18:36,080 Speaker 1: concerned about inflation? Very very few, So it's something we 333 00:18:36,160 --> 00:18:40,439 Speaker 1: don't hear often either from our institutional clients. Were the 334 00:18:40,480 --> 00:18:42,720 Speaker 1: largest prime broker in the world. We don't hear it 335 00:18:43,040 --> 00:18:46,959 Speaker 1: very often from our wealth management clients. Perhaps sporadically from 336 00:18:46,960 --> 00:18:50,119 Speaker 1: the wealth management clients too, are particularly um you know, 337 00:18:50,320 --> 00:18:53,960 Speaker 1: from business owning backgrounds, etcetera. Who are you know? They're 338 00:18:54,040 --> 00:18:56,560 Speaker 1: very focused on the deficit as an example, and and 339 00:18:56,640 --> 00:19:00,560 Speaker 1: that makes sense. But in terms of the overall fears 340 00:19:00,640 --> 00:19:04,360 Speaker 1: or concerns around inflation, I would say it's very limited. 341 00:19:04,520 --> 00:19:07,200 Speaker 1: And I think that's another point Morgan Stanley has made 342 00:19:07,280 --> 00:19:11,320 Speaker 1: in terms of an upside surprise having that policy response, 343 00:19:11,480 --> 00:19:15,119 Speaker 1: that continuation in policy, particularly on the fiscal side, we 344 00:19:15,200 --> 00:19:18,479 Speaker 1: do expect a re up of fiscal upwards of a 345 00:19:18,480 --> 00:19:22,680 Speaker 1: trillion when the some of the benefits expire July month 346 00:19:22,760 --> 00:19:26,080 Speaker 1: end um. We also would highlight again the consumer demand 347 00:19:26,400 --> 00:19:32,360 Speaker 1: the recovering commodity markets. We've seen tremendous capital expenditure declines 348 00:19:32,400 --> 00:19:36,040 Speaker 1: in oil given everything that's happening there now, We've obviously 349 00:19:36,040 --> 00:19:38,440 Speaker 1: seen a pickup in driving well, I'm sure we'll see 350 00:19:38,440 --> 00:19:42,760 Speaker 1: eventually a pick up in more airline related transportation fuel 351 00:19:43,080 --> 00:19:46,520 Speaker 1: demand that will take longer obviously, but it'll happen, and 352 00:19:46,560 --> 00:19:48,720 Speaker 1: thus you get to see an upward bias towards commodity 353 00:19:48,720 --> 00:19:51,480 Speaker 1: prices um and then, last but not least, what happens 354 00:19:51,480 --> 00:19:54,880 Speaker 1: with China. Right, this is really an enormous question mark 355 00:19:55,240 --> 00:19:58,600 Speaker 1: in terms of capital uh moving around the world, supply 356 00:19:58,720 --> 00:20:01,600 Speaker 1: chains and to the extent we have supply chain restoring, 357 00:20:02,040 --> 00:20:06,160 Speaker 1: that's potentially another source of inflation down the road. Hey, Dan, 358 00:20:06,200 --> 00:20:07,879 Speaker 1: thanks so much for joining us day. We really appreciate 359 00:20:07,920 --> 00:20:10,440 Speaker 1: your thoughts. We've covered a lot of ground there. Dan Skelly, 360 00:20:10,680 --> 00:20:14,360 Speaker 1: head of Equity market Model, Portfolios and market Strategy at 361 00:20:14,400 --> 00:20:16,600 Speaker 1: Morgan Stanley Wealth Manager. They have about two and a 362 00:20:16,680 --> 00:20:20,600 Speaker 1: half trillion dollars under management, so they get to see 363 00:20:20,680 --> 00:20:23,080 Speaker 1: a lot of the market. Giving us his thoughts there, 364 00:20:23,080 --> 00:20:25,399 Speaker 1: And Vonnie, I think the key thing is there Morgan 365 00:20:25,480 --> 00:20:27,960 Speaker 1: Stanley holding to that V shaped recovery. Yeah. And I'm 366 00:20:27,960 --> 00:20:31,080 Speaker 1: really fascinated that not more people are just floating the 367 00:20:31,119 --> 00:20:34,120 Speaker 1: idea of potential inflation. And perhaps it is because Bill 368 00:20:34,200 --> 00:20:38,080 Speaker 1: Dudley's op ed in Bloomberg Opinion put it in my 369 00:20:38,119 --> 00:20:40,439 Speaker 1: mind today. But there is a huge balance street out there, 370 00:20:40,480 --> 00:20:41,840 Speaker 1: and you have to wonder how long it will be 371 00:20:41,840 --> 00:20:45,400 Speaker 1: before people do start to be concerned about inflation. Yeah, 372 00:20:45,440 --> 00:20:49,080 Speaker 1: you think about a ten trillion dollar balance. She just extraordinary. 373 00:20:49,080 --> 00:20:51,760 Speaker 1: We were a below four billion dollars just several months ago. 374 00:20:54,840 --> 00:20:57,480 Speaker 1: Now we have a very interesting interview for you this 375 00:20:57,880 --> 00:21:02,119 Speaker 1: as travel begins to ramp up just ever so slowly again, Delta, 376 00:21:02,160 --> 00:21:04,160 Speaker 1: for example, saying that it was going to restart flights 377 00:21:04,240 --> 00:21:07,439 Speaker 1: to China via Soul this week. It's only going to 378 00:21:07,480 --> 00:21:09,200 Speaker 1: be once a week, and then July it will be 379 00:21:09,280 --> 00:21:12,000 Speaker 1: twice a week. But we are seeing just very small 380 00:21:12,040 --> 00:21:16,800 Speaker 1: green shoots of travel starting up. Bryantsky is Airbnbs CEO. 381 00:21:17,440 --> 00:21:20,399 Speaker 1: He is discussing with Bloomberg here now White travel as 382 00:21:20,400 --> 00:21:23,160 Speaker 1: we know it will never actually be the same. None 383 00:21:23,200 --> 00:21:26,600 Speaker 1: of us were prepared for really a once in a 384 00:21:26,680 --> 00:21:31,160 Speaker 1: century crisis. Our industry travel has described COVID as as 385 00:21:31,160 --> 00:21:33,480 Speaker 1: big as nine eleven and two thousand and eight, many 386 00:21:33,560 --> 00:21:36,439 Speaker 1: times over, something more akin to World War Two. And 387 00:21:36,480 --> 00:21:39,480 Speaker 1: when that happened, it felt like I was working on 388 00:21:39,520 --> 00:21:41,720 Speaker 1: our S one. We were going to file it March 389 00:21:41,800 --> 00:21:45,080 Speaker 1: thirty one, and it felt like twelve years of success, 390 00:21:45,119 --> 00:21:47,399 Speaker 1: and you know, had all these things, and life was 391 00:21:47,480 --> 00:21:51,760 Speaker 1: great and suddenly in you know, you build something in 392 00:21:51,800 --> 00:21:55,000 Speaker 1: twelve weeks and you lose most of it in four weeks. 393 00:21:55,320 --> 00:21:57,960 Speaker 1: I can't quite describe what that feels like. And it 394 00:21:58,040 --> 00:22:01,080 Speaker 1: just felt like everything the company oak. I felt like 395 00:22:01,119 --> 00:22:03,600 Speaker 1: a captain of a ship in our torpedo just hit 396 00:22:03,640 --> 00:22:05,840 Speaker 1: the side of the ship. Now, travel came basically to 397 00:22:06,040 --> 00:22:09,040 Speaker 1: a standstill, and in many cases people didn't want to travel, 398 00:22:09,160 --> 00:22:13,240 Speaker 1: or they couldn't travel legally. It was illegal to rent 399 00:22:13,440 --> 00:22:17,399 Speaker 1: an airbnb. What was the lowest point for you? The 400 00:22:17,520 --> 00:22:21,040 Speaker 1: darkest hour? There were so many dark hours. That's the 401 00:22:21,080 --> 00:22:23,480 Speaker 1: old like quote attribute to Winston Churchill. If you're going 402 00:22:23,520 --> 00:22:26,960 Speaker 1: through hell, just keep going and man um I will 403 00:22:27,000 --> 00:22:30,240 Speaker 1: tell you the first dark moment was when we had 404 00:22:30,280 --> 00:22:33,639 Speaker 1: about a billion dollars of cancelations from guests. You also 405 00:22:33,920 --> 00:22:37,520 Speaker 1: had to cut of the company, and you gave you know, 406 00:22:37,560 --> 00:22:41,080 Speaker 1: an incredibly generous severance package your note to the team. 407 00:22:41,119 --> 00:22:45,199 Speaker 1: I could I could feel the pain in there, you know, 408 00:22:45,400 --> 00:22:49,879 Speaker 1: talk to me about going through that process cut your staff. 409 00:22:50,359 --> 00:22:52,360 Speaker 1: It was the saddest thing I've ever done in my life, 410 00:22:52,440 --> 00:22:56,600 Speaker 1: at least professionally, and we weren't sure if we'd have 411 00:22:56,640 --> 00:22:58,879 Speaker 1: to do a layoff and we had to face the 412 00:22:58,920 --> 00:23:03,639 Speaker 1: hard truth that travel we did not know when it 413 00:23:03,720 --> 00:23:06,920 Speaker 1: was gonna return, and we knew that when travel returned, 414 00:23:06,920 --> 00:23:08,800 Speaker 1: it would be different, it would never be the same. 415 00:23:09,040 --> 00:23:15,320 Speaker 1: You don't think travel will ever be the same, Well, um, 416 00:23:15,359 --> 00:23:17,639 Speaker 1: I will. I I don't know for sure, but here's 417 00:23:17,640 --> 00:23:21,119 Speaker 1: what I'll say. Travel will be back, but we'll look different. 418 00:23:21,200 --> 00:23:24,240 Speaker 1: What trends are you seeing in Europe and Asia versus 419 00:23:24,280 --> 00:23:28,639 Speaker 1: the United States? So United States has been very, very strong. 420 00:23:28,720 --> 00:23:31,840 Speaker 1: It's again, I don't want to I want to clarify, 421 00:23:31,960 --> 00:23:35,840 Speaker 1: it's we. We we cannot declare recovery anywhere because we 422 00:23:35,920 --> 00:23:39,480 Speaker 1: don't yet know where it's pent up demand in temporary 423 00:23:39,600 --> 00:23:44,720 Speaker 1: or sustainable recovery. But we've seen a temporary recovery. United States, Europe, 424 00:23:45,240 --> 00:23:48,960 Speaker 1: most of Europe we've seen a recovery, a temporary recovery. 425 00:23:48,960 --> 00:23:51,560 Speaker 1: Other than the United Kingdom. United Kingdom I think is 426 00:23:51,560 --> 00:23:56,359 Speaker 1: still lockdown until July one, But France, Germany, Italy, Spain, 427 00:23:56,400 --> 00:23:59,719 Speaker 1: you're seeing really strong growth. Um, Latin America is not 428 00:24:00,080 --> 00:24:03,880 Speaker 1: covered in. Asia is starting to recover but not yet recovered. 429 00:24:03,880 --> 00:24:07,479 Speaker 1: So North America and Europe are extremely strong. Latin America 430 00:24:07,560 --> 00:24:10,840 Speaker 1: Asia kind of a bit behind. How much do you 431 00:24:10,840 --> 00:24:13,399 Speaker 1: think getting back to a normal defense on a vaccine 432 00:24:13,480 --> 00:24:17,639 Speaker 1: or even then, things are going to be different. Travel 433 00:24:17,720 --> 00:24:19,960 Speaker 1: as you knew it is over. You're never ever gonna 434 00:24:20,000 --> 00:24:22,440 Speaker 1: see it again. I'll just say that right there, travel 435 00:24:22,480 --> 00:24:24,800 Speaker 1: as we knew it from the Valentine's Day and before 436 00:24:25,000 --> 00:24:28,000 Speaker 1: is over. It's gone. It doesn't mean travel is gone, 437 00:24:28,119 --> 00:24:31,000 Speaker 1: but that travel is gone, and nobody knows quite what 438 00:24:31,080 --> 00:24:33,040 Speaker 1: it's going to be because it's really up to the 439 00:24:33,080 --> 00:24:36,040 Speaker 1: industry to invent the way forward. But again, I think 440 00:24:36,080 --> 00:24:38,520 Speaker 1: business travel is really really going to be hit for 441 00:24:38,560 --> 00:24:40,600 Speaker 1: a while. I think a lot of people are realizing 442 00:24:40,600 --> 00:24:43,239 Speaker 1: they can do meetings on zoom, the rethinking a lot 443 00:24:43,280 --> 00:24:46,280 Speaker 1: of the conventions and conferences. People are going to rediscover 444 00:24:46,400 --> 00:24:49,720 Speaker 1: the outdoors. For example, there's four hundred national parks in 445 00:24:49,760 --> 00:24:52,480 Speaker 1: the country. Most Americans have never been a national park. 446 00:24:52,760 --> 00:24:54,280 Speaker 1: Most Americans don't even know if they live within two 447 00:24:54,320 --> 00:24:57,480 Speaker 1: hundred miles in national park. I think one prediction national 448 00:24:57,520 --> 00:24:59,520 Speaker 1: parks gonna be in People are going to travel a 449 00:24:59,560 --> 00:25:01,639 Speaker 1: lot more out yours. These are things that are going 450 00:25:01,680 --> 00:25:03,200 Speaker 1: to happen. And the other thing that I think is 451 00:25:03,200 --> 00:25:05,920 Speaker 1: going to happen is travel in living are going to 452 00:25:06,000 --> 00:25:08,640 Speaker 1: blend together. What do I mean, Well, if you can 453 00:25:08,680 --> 00:25:11,720 Speaker 1: do your job from home, then if you can work 454 00:25:11,760 --> 00:25:14,159 Speaker 1: from home, you can fearly work from any home anywhere 455 00:25:14,160 --> 00:25:15,800 Speaker 1: in the world, as long as you're in the right 456 00:25:15,800 --> 00:25:18,000 Speaker 1: time zone. And so what you're gonna start to see 457 00:25:18,160 --> 00:25:21,800 Speaker 1: is not just travel redistribution, but you might see and 458 00:25:21,800 --> 00:25:25,560 Speaker 1: no one can say for sure, population redistribution. People may 459 00:25:25,600 --> 00:25:29,159 Speaker 1: start moving to small towns and communities. That was a 460 00:25:29,200 --> 00:25:34,400 Speaker 1: fascinating discussion Airbnb CEO Bryant Chesky speaking with Bloomer Technologies 461 00:25:34,440 --> 00:25:36,800 Speaker 1: Emily Chang on why travel as we know it will 462 00:25:36,840 --> 00:25:40,320 Speaker 1: never be the saying that's a big, big statement, Vonni. 463 00:25:40,400 --> 00:25:42,920 Speaker 1: I wonder how things will in fact play out. I mean, 464 00:25:42,960 --> 00:25:45,399 Speaker 1: it's good to actually hear the truth, right Poles. So 465 00:25:45,440 --> 00:25:48,000 Speaker 1: many people pretending that, you know, at some point we 466 00:25:48,000 --> 00:25:51,720 Speaker 1: will go back to pre pandemic times, but that's never 467 00:25:51,760 --> 00:25:54,040 Speaker 1: gonna happen. We're never going to be pre pandemic again. 468 00:25:54,119 --> 00:25:56,520 Speaker 1: And you know, as much as people say these things 469 00:25:56,600 --> 00:25:59,679 Speaker 1: emerge every twenty years or so, when it's true, this one, 470 00:25:59,760 --> 00:26:01,480 Speaker 1: for you is different in the sense that it is 471 00:26:01,520 --> 00:26:05,879 Speaker 1: just so ridiculously easy to catch, and you know, vaccines 472 00:26:06,040 --> 00:26:08,160 Speaker 1: are so far away. We don't know how long they last. 473 00:26:08,200 --> 00:26:10,320 Speaker 1: So yeah, I can completely imagine the travel as we 474 00:26:10,400 --> 00:26:12,439 Speaker 1: knew it, where you just could hop out to the 475 00:26:12,440 --> 00:26:15,240 Speaker 1: air board, jump on a you know, a shuttle plane 476 00:26:15,240 --> 00:26:16,960 Speaker 1: down to DC or wherever you wanted to go in 477 00:26:16,960 --> 00:26:19,320 Speaker 1: the world that's done. Yeah, it'll be interesting to see. 478 00:26:19,320 --> 00:26:22,600 Speaker 1: I mean, Brian Chesky, Airbnb CEO, he certainly has a 479 00:26:22,640 --> 00:26:26,679 Speaker 1: great window into global travel trends. I mean, Airbnb is 480 00:26:26,720 --> 00:26:30,800 Speaker 1: just everywhere, and he was suggesting that certain European markets 481 00:26:30,840 --> 00:26:34,320 Speaker 1: coming back a little bit sooner than some others. UK 482 00:26:34,480 --> 00:26:37,439 Speaker 1: still in lockdown, and you're seeing some pockets of strength 483 00:26:37,480 --> 00:26:39,919 Speaker 1: here in the US. Um. But again, I think the 484 00:26:40,400 --> 00:26:43,520 Speaker 1: until there is you know, arguably, I think a lot 485 00:26:43,560 --> 00:26:46,520 Speaker 1: of observers say, until there is a globally available vaccine 486 00:26:47,080 --> 00:26:49,760 Speaker 1: that you know, just consumer activity in general on a 487 00:26:49,800 --> 00:26:54,280 Speaker 1: global scale will be greatly reduced or just certainly impacted. 488 00:26:54,320 --> 00:26:55,800 Speaker 1: And I think that's kind of what we're hearing from 489 00:26:55,840 --> 00:26:58,760 Speaker 1: the Airbnb CEO. And it's interesting that he hasn't ruled 490 00:26:58,760 --> 00:27:00,600 Speaker 1: out an i P O this year, but artney, yeah, 491 00:27:00,600 --> 00:27:03,680 Speaker 1: I'm sure it's not something they're immediately thinking about. Also, 492 00:27:03,760 --> 00:27:06,640 Speaker 1: that lawsuit with New York City has now been settled 493 00:27:06,680 --> 00:27:09,639 Speaker 1: about providing host data, and in New York you you 494 00:27:09,720 --> 00:27:12,440 Speaker 1: have to stay for thirty days now, which also changes 495 00:27:12,480 --> 00:27:15,040 Speaker 1: the business model. Yeah, absolutely so off to see how 496 00:27:15,040 --> 00:27:19,000 Speaker 1: that plays out for the good folks at Airbnb. Thanks 497 00:27:19,000 --> 00:27:22,320 Speaker 1: for listening to Bloomberg Markets podcast. You can subscribe and 498 00:27:22,359 --> 00:27:25,720 Speaker 1: listen to interviews at Apple Podcasts or whatever a podcast 499 00:27:25,720 --> 00:27:28,959 Speaker 1: platform you prefer. I'm Bonnie Quinn. I'm on Twitter at 500 00:27:29,000 --> 00:27:32,200 Speaker 1: Bonnie Quinn. And Paul Sweeney I'm on Twitter at pt Sweeney. 501 00:27:32,200 --> 00:27:34,879 Speaker 1: Before the podcast, you can always catch us worldwide at 502 00:27:34,920 --> 00:27:35,680 Speaker 1: Bloomberg Radio