1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penel podcast. I'm Paul swing you, 2 00:00:05,360 --> 00:00:07,680 Speaker 1: along with my co host Lisa Brahma wits. Each day 3 00:00:07,720 --> 00:00:10,240 Speaker 1: we bring you the most noteworthy and useful interviews for 4 00:00:10,280 --> 00:00:12,520 Speaker 1: you and your money. Whether at the grocery store or 5 00:00:12,560 --> 00:00:15,480 Speaker 1: the trading floor. Find a Bloomberg Penl podcast on Apple 6 00:00:15,520 --> 00:00:17,960 Speaker 1: podcast or wherever you listen to podcasts, as well as 7 00:00:17,960 --> 00:00:20,799 Speaker 1: at Bloomberg dot com. Paul, I'm trying to understand the 8 00:00:20,840 --> 00:00:24,520 Speaker 1: significance of this story that came out earlier today. The 9 00:00:24,600 --> 00:00:27,680 Speaker 1: United Nations experts now weighing in saying that Saudi Crown 10 00:00:27,720 --> 00:00:31,280 Speaker 1: Prince Mohammed bin Salman was possibly involved in hacking the 11 00:00:31,320 --> 00:00:34,760 Speaker 1: cell phone of Amazon dot Com CEO Jeff Bezos. And 12 00:00:34,800 --> 00:00:38,680 Speaker 1: this was revealed after an Amazon investigation. This has to 13 00:00:38,680 --> 00:00:42,520 Speaker 1: do with a What's App account that was infiltrated according 14 00:00:42,680 --> 00:00:46,479 Speaker 1: to investigators back in ten Greg Farrell here to give 15 00:00:46,520 --> 00:00:49,159 Speaker 1: us a little bit more clarity. He's an investigative reporter 16 00:00:49,280 --> 00:00:52,080 Speaker 1: for the Legal enforcement team here at Bloomberg News. Greg, 17 00:00:52,080 --> 00:00:54,280 Speaker 1: can you just sort of set the stage of what 18 00:00:54,640 --> 00:00:59,040 Speaker 1: actually is alleged to have happened here well from what 19 00:00:59,080 --> 00:01:04,880 Speaker 1: we know, um, after Jeff Bezos you know, photos from 20 00:01:04,920 --> 00:01:08,920 Speaker 1: his personal life that contributed to or you know allow 21 00:01:09,040 --> 00:01:15,480 Speaker 1: you know a year ago came out. Um, they his 22 00:01:15,560 --> 00:01:18,400 Speaker 1: team started going through like with a fine tooth comb, 23 00:01:18,800 --> 00:01:22,200 Speaker 1: everything is like, clearly he had been hacked. Clearly stuff 24 00:01:22,240 --> 00:01:24,800 Speaker 1: had been stolen from him, digital images, etcetera, from his 25 00:01:24,840 --> 00:01:28,360 Speaker 1: personal devices. So that started the process. In addition to that, 26 00:01:28,480 --> 00:01:30,880 Speaker 1: federal prosecutors in New York started looking to see if 27 00:01:30,880 --> 00:01:35,240 Speaker 1: there was any involvement by the National Enquirer UM with 28 00:01:35,520 --> 00:01:39,640 Speaker 1: you know, uh, basically some you know, unlawful activity regarding 29 00:01:39,680 --> 00:01:43,720 Speaker 1: this part of the investigation. UM went through you know, 30 00:01:43,840 --> 00:01:47,560 Speaker 1: chapter in verse every interaction with what Pisos had and 31 00:01:47,600 --> 00:01:50,800 Speaker 1: then um, you know, so there's there's a criminal investigation 32 00:01:50,920 --> 00:01:54,680 Speaker 1: in Manhattan. Here. Separately, at the United Nations, there are 33 00:01:54,720 --> 00:01:58,040 Speaker 1: a group of people dedicated to you know, justice for 34 00:01:58,200 --> 00:02:01,600 Speaker 1: extra judicial killings who been very focused on the murder 35 00:02:01,640 --> 00:02:06,160 Speaker 1: of Jamal Kashagi in October. They got involved with this 36 00:02:06,280 --> 00:02:08,840 Speaker 1: as well, and they're the ones who put out a 37 00:02:08,840 --> 00:02:11,280 Speaker 1: report today. And this is what the news reporting starting 38 00:02:11,320 --> 00:02:14,640 Speaker 1: late last night indicated is that their findings based on 39 00:02:14,760 --> 00:02:19,480 Speaker 1: the digital the forensic digital analysis of Bezos's phone indicated 40 00:02:19,760 --> 00:02:23,040 Speaker 1: lots of evidence that at the time in May of 41 00:02:24,520 --> 00:02:29,280 Speaker 1: after a benign what's app you know, transaction or what's 42 00:02:29,280 --> 00:02:33,640 Speaker 1: app message from the Prince to Bezos, then suddenly afterwards 43 00:02:33,680 --> 00:02:36,800 Speaker 1: there was this malignant, you know, coded file that got 44 00:02:36,800 --> 00:02:40,520 Speaker 1: in something called Pegasus, which I don't understand god was, 45 00:02:40,520 --> 00:02:44,320 Speaker 1: was placed in Bezos's phone and started exfiltrating massive amounts 46 00:02:44,320 --> 00:02:47,840 Speaker 1: of data, far far larger than the normal amounts of 47 00:02:47,919 --> 00:02:50,160 Speaker 1: data that would normally come in and out of a phone. 48 00:02:50,720 --> 00:02:53,480 Speaker 1: So Greg is there do we have any sense of 49 00:02:53,639 --> 00:02:56,400 Speaker 1: what Jeff Bezos would like to see happen. I mean, 50 00:02:56,400 --> 00:02:58,840 Speaker 1: it looks like obviously his security was breached, and it 51 00:02:58,919 --> 00:03:01,760 Speaker 1: was obviously had implication for him his personal life. But 52 00:03:02,280 --> 00:03:05,040 Speaker 1: as he stated, what he wants to happen if in 53 00:03:05,080 --> 00:03:07,960 Speaker 1: fact the Crown Prince is guilty of this or did 54 00:03:08,000 --> 00:03:11,320 Speaker 1: do this, No, I think right now he's playing this 55 00:03:11,400 --> 00:03:14,119 Speaker 1: carefully because there is a criminal investigation in New York 56 00:03:14,160 --> 00:03:17,440 Speaker 1: into some of the conducts surrounding that. It's proceeded very slowly. 57 00:03:17,720 --> 00:03:19,800 Speaker 1: But I think he's smart enough and he's getting the 58 00:03:19,840 --> 00:03:21,840 Speaker 1: right advice not to get in front of it and 59 00:03:21,880 --> 00:03:23,880 Speaker 1: decide what he wants to do, but to let the 60 00:03:24,080 --> 00:03:27,520 Speaker 1: you know, the most important thing the criminal investigation proceed 61 00:03:28,040 --> 00:03:33,200 Speaker 1: is the u N investigation somehow implying a connection between 62 00:03:33,240 --> 00:03:38,280 Speaker 1: the killing of Tamaka Shogi and the Jeff Bezos hack 63 00:03:39,000 --> 00:03:41,840 Speaker 1: or the leak of his personal information. Is that part 64 00:03:41,880 --> 00:03:43,480 Speaker 1: of it or it just was that. Yeah, they're making 65 00:03:43,480 --> 00:03:45,720 Speaker 1: their drawing that line. They're not there's no proof that 66 00:03:45,760 --> 00:03:48,320 Speaker 1: this led to that. But you know that's what these 67 00:03:48,320 --> 00:03:50,560 Speaker 1: people that the u WHEN are investigating. They're they're trying 68 00:03:50,600 --> 00:03:52,760 Speaker 1: to get to the bottom of how and why in 69 00:03:52,800 --> 00:03:55,520 Speaker 1: more details and hold those responsible for it the killing 70 00:03:55,560 --> 00:03:59,200 Speaker 1: of kog So you know, it's this is another element 71 00:03:59,520 --> 00:04:03,280 Speaker 1: to that whole storyline that the Saudi government has started 72 00:04:03,280 --> 00:04:05,680 Speaker 1: denying completely and then denied in part and then found 73 00:04:05,720 --> 00:04:08,800 Speaker 1: some people to find guilty um in a trial of 74 00:04:08,880 --> 00:04:11,760 Speaker 1: sorts a closed trial in Saudi Arabia earlier this year. 75 00:04:11,880 --> 00:04:14,040 Speaker 1: And the u N people are staying on this and 76 00:04:14,120 --> 00:04:18,160 Speaker 1: what's Jeff Bezos connection to the Tamaka Shogi case. Just 77 00:04:18,279 --> 00:04:20,840 Speaker 1: that Kau Shogi worked for the Washington Post, and so 78 00:04:21,000 --> 00:04:23,960 Speaker 1: the Washington Post, most of the major newspapers and news 79 00:04:24,000 --> 00:04:27,159 Speaker 1: media uh in this country have been very supportive of 80 00:04:27,160 --> 00:04:28,760 Speaker 1: efforts to get to the bottom of this, but no 81 00:04:28,880 --> 00:04:31,200 Speaker 1: one more than the Washington Post because he was one 82 00:04:31,200 --> 00:04:35,760 Speaker 1: of them, greg Asor do we know whether the investigators 83 00:04:35,760 --> 00:04:37,560 Speaker 1: are looking more broadly or are they just looking at 84 00:04:37,600 --> 00:04:40,560 Speaker 1: Jeff Bezos or their other prominent people that could be 85 00:04:40,640 --> 00:04:44,960 Speaker 1: the targets of mbs IS or the Saudi government's hacking 86 00:04:45,000 --> 00:04:47,880 Speaker 1: of phones. So two things they're one, we don't know 87 00:04:47,920 --> 00:04:51,160 Speaker 1: what the prosecutors in Manhattan are doing. That seems pretty 88 00:04:51,160 --> 00:04:53,640 Speaker 1: clear it's focused on the hack and the National Choir 89 00:04:53,839 --> 00:04:55,760 Speaker 1: and whether or not the inquirer was culpable at all, 90 00:04:55,920 --> 00:04:58,880 Speaker 1: and there's no evidence to suggest that there was. Separately, though, 91 00:04:58,920 --> 00:05:01,200 Speaker 1: that's a much bigger question. And you've hit a very 92 00:05:01,320 --> 00:05:04,400 Speaker 1: important point now that we know with a high degree 93 00:05:04,400 --> 00:05:08,159 Speaker 1: of confidence, but not absolute certainty, that something some part, 94 00:05:08,200 --> 00:05:10,200 Speaker 1: even if it wasn't the Crown Prince himself, but somebody 95 00:05:10,200 --> 00:05:13,440 Speaker 1: in Saudi Arabia was interested in hacking into a prominent, 96 00:05:13,680 --> 00:05:17,359 Speaker 1: wealthy Americans phone. This opens up the question, well, what 97 00:05:17,480 --> 00:05:21,919 Speaker 1: other prominent American officials or figures with close ties to 98 00:05:21,920 --> 00:05:26,480 Speaker 1: the government, um either the Trump administration or Congress, or 99 00:05:26,560 --> 00:05:29,240 Speaker 1: in the business community who did a lot of dealings 100 00:05:29,360 --> 00:05:31,600 Speaker 1: and had a you know, what they thought was a 101 00:05:31,640 --> 00:05:34,359 Speaker 1: personal relationship or what's app relationship with the Crown Prince 102 00:05:34,760 --> 00:05:39,160 Speaker 1: or other representatives of the Saudi ruler family. Has anybody 103 00:05:39,200 --> 00:05:41,120 Speaker 1: else been hacked and we just don't know yet. So 104 00:05:41,400 --> 00:05:44,800 Speaker 1: that's that's the bigger issue here, is that, uh, you know, 105 00:05:45,120 --> 00:05:47,360 Speaker 1: as the Saudi government been doing this to a wide 106 00:05:47,440 --> 00:05:50,320 Speaker 1: variety of people and if so, whom right, very interesting, 107 00:05:50,320 --> 00:05:53,240 Speaker 1: fascinating story that I think is just a development. Here Grege, 108 00:05:53,440 --> 00:05:56,560 Speaker 1: investigative reporter for the Legal enforcement team at Bloomberg News, 109 00:05:56,600 --> 00:05:58,560 Speaker 1: joining us here in our Bloomberg in active broker studio 110 00:05:58,560 --> 00:06:01,800 Speaker 1: with that fascinating story of Jeff Bezos, the Washington Post, 111 00:06:01,839 --> 00:06:05,880 Speaker 1: the Crown Prince of Saudi Arabia, what's app hacking? Uh, 112 00:06:06,040 --> 00:06:08,960 Speaker 1: so interesting story. So I think this is probably LEASA 113 00:06:09,000 --> 00:06:11,279 Speaker 1: something that's gonna be developing over time. Oh, I don't 114 00:06:11,279 --> 00:06:12,800 Speaker 1: think this is the last that were part of this. 115 00:06:12,960 --> 00:06:15,800 Speaker 1: If the UN panel is coming back with the same 116 00:06:15,800 --> 00:06:29,120 Speaker 1: conclusion as Jeff Bezos is uh. Private investigators markets are 117 00:06:29,200 --> 00:06:31,960 Speaker 1: rallying slightly today on news that China is ramping up 118 00:06:31,960 --> 00:06:35,920 Speaker 1: its efforts to contain the Corona virus that's killed at 119 00:06:36,000 --> 00:06:38,880 Speaker 1: least seventeen people and affect that hundreds. As the outbreak 120 00:06:38,920 --> 00:06:41,120 Speaker 1: has spread beyond age of the question is what does 121 00:06:41,120 --> 00:06:44,359 Speaker 1: it mean for global economics. We welcome Tom or Like 122 00:06:44,360 --> 00:06:47,200 Speaker 1: he's a chief economist for Bloomberg Economics, joining us from 123 00:06:47,200 --> 00:06:50,359 Speaker 1: the Bloomberg nine studio in Washington, d C. Tom, you 124 00:06:50,920 --> 00:06:52,760 Speaker 1: lived a long time in China. I wonder if you 125 00:06:52,800 --> 00:06:55,800 Speaker 1: could give us a sense for kind of how this 126 00:06:56,000 --> 00:07:00,880 Speaker 1: coronavirus compares to the stars UH virus from about seventeen 127 00:07:01,000 --> 00:07:04,279 Speaker 1: years ago, because that's certainly had some rippling effects before 128 00:07:04,279 --> 00:07:07,599 Speaker 1: the economy. So that's right, Paul. So if we go 129 00:07:07,680 --> 00:07:12,520 Speaker 1: back to two thousand and three, in that Stars outbreak, UM, 130 00:07:12,560 --> 00:07:16,200 Speaker 1: I think one of the critical factors was the slow 131 00:07:16,280 --> 00:07:20,160 Speaker 1: pace of the government response. UM. There was a failure 132 00:07:20,200 --> 00:07:24,160 Speaker 1: to acknowledge the extent of the outbreak. UM, there was 133 00:07:25,000 --> 00:07:30,200 Speaker 1: an inability to UM move policies quickly to contain it. 134 00:07:30,840 --> 00:07:34,400 Speaker 1: And what that meant was that actually the economic impact, 135 00:07:34,440 --> 00:07:39,000 Speaker 1: whilst brief, was pretty severe. We saw GDP growth for 136 00:07:39,240 --> 00:07:43,080 Speaker 1: two percentage points from the first quarter of two thousand 137 00:07:43,120 --> 00:07:45,640 Speaker 1: and thirty two thousand and three to the second quarter 138 00:07:46,080 --> 00:07:50,040 Speaker 1: of two thousand and three. The hope as we are here, 139 00:07:50,040 --> 00:07:52,400 Speaker 1: we are in twenty twenty is that the kind of 140 00:07:52,400 --> 00:07:56,400 Speaker 1: the bitter lesson which China learned back in two thousand 141 00:07:56,400 --> 00:07:59,400 Speaker 1: and three is going to enable them to be more 142 00:07:59,480 --> 00:08:03,640 Speaker 1: transpar aren't quicker, more effective as they respond to this 143 00:08:03,680 --> 00:08:07,760 Speaker 1: emerging threat from the coronavirus. How do you game out 144 00:08:07,520 --> 00:08:11,880 Speaker 1: of the potential economic impact of our pandemic? I mean, 145 00:08:12,360 --> 00:08:16,560 Speaker 1: it's basically not possible to do lisa UM. So here 146 00:08:16,600 --> 00:08:20,320 Speaker 1: we are in the very early stages of this disease, 147 00:08:21,280 --> 00:08:24,840 Speaker 1: and it's not clear how it's going to develop um 148 00:08:25,160 --> 00:08:27,960 Speaker 1: and so the best we can do is think about 149 00:08:28,000 --> 00:08:31,480 Speaker 1: the moving parts and try and think about some scenarios. 150 00:08:31,920 --> 00:08:35,520 Speaker 1: An important factor in our view is the way the 151 00:08:35,600 --> 00:08:39,880 Speaker 1: Chinese economy has evolved over the last sixteen seventeen years. 152 00:08:40,400 --> 00:08:43,960 Speaker 1: Back in two thousand and three, the Stars outbreak had 153 00:08:44,000 --> 00:08:48,400 Speaker 1: the biggest impact on the services sector. It hit tourism, 154 00:08:48,440 --> 00:08:51,559 Speaker 1: it hits shopping, it hit people going to the restaurant, 155 00:08:51,559 --> 00:08:54,400 Speaker 1: going to the cinema and such like. But back in 156 00:08:54,480 --> 00:08:57,960 Speaker 1: two thousand and three, the services share of China's economy 157 00:08:58,200 --> 00:09:02,439 Speaker 1: was really quite small. Here we are in and one 158 00:09:02,440 --> 00:09:05,760 Speaker 1: of the big success stories for China in the last 159 00:09:05,800 --> 00:09:09,720 Speaker 1: two decades has been this economic transition they've managed to 160 00:09:09,760 --> 00:09:13,000 Speaker 1: move away from industry. The services sector is named much 161 00:09:13,000 --> 00:09:16,360 Speaker 1: more important. More people eating at restaurants, more people going 162 00:09:16,679 --> 00:09:19,480 Speaker 1: to visit their friends and relatives, more people going to 163 00:09:19,480 --> 00:09:22,560 Speaker 1: the cinema. But guess what that means that if this 164 00:09:22,720 --> 00:09:28,080 Speaker 1: coronavirus does expand does spread um, then potentially the economic 165 00:09:28,120 --> 00:09:31,400 Speaker 1: impact is going to be significantly larger. And interestingly, who 166 00:09:31,760 --> 00:09:35,080 Speaker 1: who Dision, the editor of the Global Times, who's often 167 00:09:35,080 --> 00:09:38,560 Speaker 1: thought of as sort of a mouthpiece for the for Beijing, 168 00:09:39,160 --> 00:09:41,600 Speaker 1: came out and acknowledged that there would be an economic 169 00:09:41,679 --> 00:09:43,880 Speaker 1: hit that people would be traveling lest buying a fewer 170 00:09:43,920 --> 00:09:47,480 Speaker 1: items amid this holiday. Are you expecting perhaps a bigger 171 00:09:47,480 --> 00:09:52,120 Speaker 1: economic impact than might otherwise be seen, just because it 172 00:09:52,600 --> 00:09:55,160 Speaker 1: just is going to have that kind of dampening effect, 173 00:09:55,200 --> 00:09:58,199 Speaker 1: even though necessary it is contained. Yeah. I think you 174 00:09:58,280 --> 00:10:01,000 Speaker 1: raise an important point, Lisa, and that is that the 175 00:10:01,160 --> 00:10:06,440 Speaker 1: timing of this for China couldn't really be worse. We're 176 00:10:06,480 --> 00:10:10,640 Speaker 1: about to hit Chinese New Year, and at Chinese New Year, 177 00:10:10,679 --> 00:10:15,240 Speaker 1: what happens is literally hundreds of millions of people UM 178 00:10:16,000 --> 00:10:19,960 Speaker 1: go home. Many Chinese people are migrants. They work in 179 00:10:20,360 --> 00:10:22,400 Speaker 1: cities which are different from the cities they were born 180 00:10:22,440 --> 00:10:25,040 Speaker 1: in and Chinese New Year is the one point of 181 00:10:25,080 --> 00:10:28,720 Speaker 1: the year where everyone puts down what they're doing, leaves 182 00:10:28,720 --> 00:10:31,960 Speaker 1: the factory, leaves the office, gets on the train, gets 183 00:10:32,000 --> 00:10:34,560 Speaker 1: on a bus, gets on an airplane, and goes to 184 00:10:34,679 --> 00:10:37,680 Speaker 1: enjoy the Chinese New Year celebration with their family in 185 00:10:37,720 --> 00:10:40,200 Speaker 1: the same way that people do it Thanksgiving or Christmas 186 00:10:40,200 --> 00:10:42,280 Speaker 1: here in here, in the US and in the UK. 187 00:10:42,880 --> 00:10:46,880 Speaker 1: Um So the concern could be that even if this 188 00:10:47,080 --> 00:10:50,400 Speaker 1: virus is contained, even if it doesn't spread, just the 189 00:10:50,520 --> 00:10:53,320 Speaker 1: mere timing of it is going to have a larger 190 00:10:53,440 --> 00:10:58,560 Speaker 1: impact on economic activity because people cancel those plans. Tom 191 00:10:58,600 --> 00:11:00,280 Speaker 1: Moore like, thank you so much for being with us, 192 00:11:00,720 --> 00:11:03,240 Speaker 1: Tom More like chief economists for Bloomberg Economics, joining us 193 00:11:03,240 --> 00:11:08,440 Speaker 1: from our Washington d C studios. Really interestingly, coronavirus has 194 00:11:08,559 --> 00:11:11,720 Speaker 1: been at least it appears to be somewhat more contained. 195 00:11:11,800 --> 00:11:14,920 Speaker 1: There seems to be more confidence that it won't necessarily 196 00:11:15,400 --> 00:11:18,560 Speaker 1: spread rampantly, and that the Chinese government is being more 197 00:11:18,600 --> 00:11:21,880 Speaker 1: transparent this time around than the last time seventeen years ago, 198 00:11:21,920 --> 00:11:24,920 Speaker 1: in the stars epidemic was spreading much more than they 199 00:11:24,960 --> 00:11:27,760 Speaker 1: had previous expected. But really interesting what Tom said, which 200 00:11:27,800 --> 00:11:31,440 Speaker 1: is it hits services when there is a concern about 201 00:11:31,480 --> 00:11:35,040 Speaker 1: an illness, and services account for a much bigger proportion 202 00:11:35,120 --> 00:11:38,720 Speaker 1: of China's economy now, so it could potentially have a 203 00:11:38,760 --> 00:11:41,440 Speaker 1: significant economic hit even if it is contained. Yeah, and 204 00:11:41,440 --> 00:11:43,400 Speaker 1: in interesting Tom mentioned the timing of it coming around 205 00:11:43,440 --> 00:11:46,199 Speaker 1: the Chinese New Year, and how there's such a movement 206 00:11:46,200 --> 00:11:49,080 Speaker 1: of people within the country and how that could actually 207 00:11:49,160 --> 00:11:52,560 Speaker 1: unfortunately facilitate the spread of the disease. So that's something 208 00:11:52,600 --> 00:11:56,120 Speaker 1: I'm sure the Chinese officials are watching closely. And again, 209 00:11:56,320 --> 00:11:58,600 Speaker 1: as you mentioned, there's actually been some calls from government 210 00:11:58,679 --> 00:12:01,840 Speaker 1: by saying don't go home, don't travel, um, you know, 211 00:12:01,880 --> 00:12:04,120 Speaker 1: And I think they're all just that's all predicated upon 212 00:12:04,160 --> 00:12:20,120 Speaker 1: trying to limit the outbreak here. It's some housing data 213 00:12:20,200 --> 00:12:23,200 Speaker 1: come out today. US existing home sales rise to their 214 00:12:23,240 --> 00:12:27,880 Speaker 1: best pace since early two thousand eighteen, indicating once again 215 00:12:28,080 --> 00:12:31,280 Speaker 1: that the consumer continues to power the U s economy along. 216 00:12:31,559 --> 00:12:34,640 Speaker 1: We are very happy to have our next guest, Doug Duncan, 217 00:12:34,720 --> 00:12:37,160 Speaker 1: good friend of the show, Senior vice president chief economists 218 00:12:37,160 --> 00:12:39,719 Speaker 1: for Fannie May usually based in Washington, d C. But 219 00:12:39,760 --> 00:12:42,560 Speaker 1: we dragged him up here to New York City to 220 00:12:42,559 --> 00:12:45,600 Speaker 1: the Bloomberg Interactor Broker Studio. So, Doug, and it seems 221 00:12:45,600 --> 00:12:47,800 Speaker 1: like every time we chat with you, we have more 222 00:12:48,360 --> 00:12:52,520 Speaker 1: I'm gonna say great, but certainly solid housing data. What 223 00:12:52,559 --> 00:12:54,240 Speaker 1: do you make of the existing homesale data that came 224 00:12:54,240 --> 00:12:57,760 Speaker 1: out today that's consistent with the forecast we think is 225 00:12:57,800 --> 00:13:01,319 Speaker 1: going to be a good year. The consumers well positioned. 226 00:13:01,360 --> 00:13:07,200 Speaker 1: You've seen lower income groups see rising income growth relative 227 00:13:07,280 --> 00:13:09,240 Speaker 1: to middle and upper income groups, and that's where the 228 00:13:09,240 --> 00:13:12,480 Speaker 1: first time home buyers are in the millennial group, which 229 00:13:12,480 --> 00:13:16,200 Speaker 1: are driving the demand for homes. They won't peak in 230 00:13:16,320 --> 00:13:19,160 Speaker 1: terms of their household formation for another six years, So 231 00:13:19,280 --> 00:13:21,440 Speaker 1: depending on what the economy does under that, we still 232 00:13:21,480 --> 00:13:23,160 Speaker 1: have a good run to go in housing. And we're 233 00:13:23,160 --> 00:13:26,839 Speaker 1: still building two d and fifty thousand units less than 234 00:13:26,920 --> 00:13:30,600 Speaker 1: demographics would suggest annually. Well, there's been a tension in 235 00:13:30,640 --> 00:13:33,560 Speaker 1: the housing market that there are growing number of people 236 00:13:33,559 --> 00:13:36,720 Speaker 1: who want starter homes and those starter homes are getting 237 00:13:36,760 --> 00:13:41,760 Speaker 1: more and more expensive. How is that conundrum getting resolved 238 00:13:41,880 --> 00:13:44,640 Speaker 1: in order to keep these numbers going forward. Yeah, it's 239 00:13:44,679 --> 00:13:46,880 Speaker 1: kind of a fight between the boomers and the millennials, 240 00:13:46,920 --> 00:13:49,640 Speaker 1: if you will not that I'm trying to foment social 241 00:13:49,679 --> 00:13:53,000 Speaker 1: discards please go ahead. But the boomers are doing what 242 00:13:53,040 --> 00:13:54,800 Speaker 1: they said they're going to do. They're aging in place, 243 00:13:55,160 --> 00:13:58,360 Speaker 1: and that's usually where the turnovercomes. That makes existing homes 244 00:13:58,360 --> 00:14:00,920 Speaker 1: available to the first time buyer, and it's the move 245 00:14:01,000 --> 00:14:03,800 Speaker 1: up buyer who buys what the builders building. So this 246 00:14:03,880 --> 00:14:07,920 Speaker 1: is a challenge for builders to make money building starter homes. 247 00:14:07,960 --> 00:14:12,480 Speaker 1: That's not their traditional role. They're making progress our expectation 248 00:14:12,559 --> 00:14:15,520 Speaker 1: as you see probably about a five percent growth this 249 00:14:15,600 --> 00:14:19,360 Speaker 1: year in new home sales, which the square footage they're 250 00:14:19,400 --> 00:14:21,960 Speaker 1: building has been falling for about three years, so they're 251 00:14:22,000 --> 00:14:25,760 Speaker 1: trying to move toward that entry level buyer. But still 252 00:14:25,800 --> 00:14:29,520 Speaker 1: there's got to be turnover among the boomers in order 253 00:14:29,560 --> 00:14:33,440 Speaker 1: to really come back to normal relationships in the housing turnover? 254 00:14:33,760 --> 00:14:36,520 Speaker 1: What is that? What does that mean? I mean, really 255 00:14:36,880 --> 00:14:40,680 Speaker 1: digget there exactly. Well, it means when the kids have 256 00:14:40,720 --> 00:14:43,200 Speaker 1: moved out. While you may want to keep a bedroom 257 00:14:43,280 --> 00:14:44,920 Speaker 1: or two in case they come home and bring the 258 00:14:44,960 --> 00:14:48,160 Speaker 1: grand kids, you probably don't need five bedrooms. Interesting, so 259 00:14:48,560 --> 00:14:51,400 Speaker 1: are the regions of the country that are is it 260 00:14:52,200 --> 00:14:55,880 Speaker 1: fairly consistent across the country we're seeing decent household formation 261 00:14:55,920 --> 00:14:58,720 Speaker 1: in home sales, or the regions that are maybe worrying 262 00:14:58,760 --> 00:15:01,280 Speaker 1: you to some degree. Well, we've been studying the issue 263 00:15:01,280 --> 00:15:05,440 Speaker 1: of mobility, asking the question if housing is too expensive 264 00:15:05,640 --> 00:15:08,160 Speaker 1: for entry level workers to be able to afford a 265 00:15:08,160 --> 00:15:11,800 Speaker 1: house near where they work, will businesses start moving their 266 00:15:11,880 --> 00:15:14,880 Speaker 1: location to our housing is more affordable. And there is 267 00:15:14,920 --> 00:15:19,080 Speaker 1: significant anecdotal evidence of that, and also starting to be 268 00:15:19,320 --> 00:15:22,880 Speaker 1: some valid evidence of that in the data that businesses 269 00:15:22,920 --> 00:15:26,520 Speaker 1: are relocating. Although in fairness, I have spoken anecdotally to 270 00:15:26,600 --> 00:15:29,600 Speaker 1: some executives at companies that have tried to move away 271 00:15:29,640 --> 00:15:33,520 Speaker 1: from New York to other places, in particular some southern cities, 272 00:15:33,640 --> 00:15:36,880 Speaker 1: and have struggled to find the talent. Uh, And I'm wondering, 273 00:15:37,040 --> 00:15:41,680 Speaker 1: you know, does this sort of foretell further stability and 274 00:15:41,760 --> 00:15:45,200 Speaker 1: say a New York City market or a San Francisco market, 275 00:15:45,280 --> 00:15:47,600 Speaker 1: despite all of the threats that everyone's going to move 276 00:15:47,640 --> 00:15:50,080 Speaker 1: away because it's just too expensive. Yeah, I think there's 277 00:15:50,240 --> 00:15:55,600 Speaker 1: in some sense, instead of incremental additions to those already 278 00:15:55,640 --> 00:16:01,040 Speaker 1: expensive and heavily populated metros, it's the incremental are going elsewhere. 279 00:16:01,320 --> 00:16:03,800 Speaker 1: One story, for example, is if you look at where 280 00:16:03,800 --> 00:16:07,200 Speaker 1: Boise was ten years ago compared to where Boise is today, 281 00:16:07,360 --> 00:16:11,520 Speaker 1: that's absolutely all outflow from higher cost areas, and Boise's 282 00:16:11,600 --> 00:16:15,240 Speaker 1: hu's eight or and fifty thousand people in that metro. Now, uh, 283 00:16:15,280 --> 00:16:18,600 Speaker 1: that's a poster child for that kind of migration. It's 284 00:16:18,600 --> 00:16:22,120 Speaker 1: not gonna happen everywhere. Core businesses will still remain in 285 00:16:22,160 --> 00:16:25,200 Speaker 1: New York City, but the additional if you can open 286 00:16:25,240 --> 00:16:28,840 Speaker 1: another office somewhere else in that business, that's what you're 287 00:16:28,840 --> 00:16:31,120 Speaker 1: seeing some of the West Coast tech companies. They're moving 288 00:16:31,520 --> 00:16:34,840 Speaker 1: a part of their business to Utah, Salt Lake or Torno, 289 00:16:35,200 --> 00:16:38,600 Speaker 1: or to Phoenix or someplace where housing is more affordable. Doug, 290 00:16:38,640 --> 00:16:41,960 Speaker 1: what's your overall economic outlook for in that camp. It's 291 00:16:42,000 --> 00:16:46,040 Speaker 1: kind of kind of growth. We think the sustainable non 292 00:16:46,080 --> 00:16:48,560 Speaker 1: inflationary growth rate for the economy is between two and 293 00:16:48,560 --> 00:16:50,160 Speaker 1: two and a quarter, and we'll be in that range 294 00:16:50,200 --> 00:16:52,760 Speaker 1: this year, a little bit slowden last year. Boeing will 295 00:16:52,800 --> 00:16:56,720 Speaker 1: have something to do with that. The the uh uh 296 00:16:56,880 --> 00:16:59,320 Speaker 1: that that will be actually a number that will slow 297 00:16:59,680 --> 00:17:03,160 Speaker 1: the headline numbers a little bit. How's the housing market 298 00:17:03,200 --> 00:17:06,280 Speaker 1: in Fargomorehead, North Dakota. It's very well. It's a very 299 00:17:06,320 --> 00:17:08,480 Speaker 1: affordable place, and if you have a child sent to 300 00:17:08,480 --> 00:17:12,879 Speaker 1: a university, there's an excellent, Ya, North Dakota State University. 301 00:17:12,920 --> 00:17:16,680 Speaker 1: It's affordable and good quality and you're totally objective, right, 302 00:17:16,720 --> 00:17:23,720 Speaker 1: I am totally absolutely as um and I say this 303 00:17:23,840 --> 00:17:26,159 Speaker 1: actually I am going to be heading to North Dakota 304 00:17:26,200 --> 00:17:32,120 Speaker 1: State University in April. April, not January. Yeah, although it's 305 00:17:32,119 --> 00:17:38,240 Speaker 1: still joy pretty. Although it's still going to bed. Yeah, 306 00:17:38,280 --> 00:17:42,000 Speaker 1: they're about two weeks in between winter and uh in summer, 307 00:17:42,240 --> 00:17:45,000 Speaker 1: in which case it's nice. No, it's it's gonna be fun. 308 00:17:45,040 --> 00:17:47,679 Speaker 1: I actually started my career at Fargo Noice Dakota, so 309 00:17:47,760 --> 00:17:51,399 Speaker 1: I'm going to as a reporter anyway. Thank you so 310 00:17:51,480 --> 00:17:53,960 Speaker 1: much for being with us. Don Duncan, always wonderful having 311 00:17:53,960 --> 00:17:57,520 Speaker 1: you here. Don Duncan, chief economist at Fanny May joining 312 00:17:57,600 --> 00:18:00,399 Speaker 1: us with this better than expected data it again on 313 00:18:00,440 --> 00:18:13,960 Speaker 1: the US housing market. The impeachment trial continues in Washington, 314 00:18:14,119 --> 00:18:16,320 Speaker 1: d C. In the Senate, and there is a big 315 00:18:16,440 --> 00:18:20,560 Speaker 1: question about four U. S. Senators Republicans who hold the 316 00:18:20,640 --> 00:18:24,679 Speaker 1: key to whether or not the trial will involve witnesses 317 00:18:24,800 --> 00:18:27,280 Speaker 1: or not. Twitting us now to talk about the political 318 00:18:27,320 --> 00:18:30,120 Speaker 1: consequences of the impeachment proceedings is when do you shill 319 00:18:30,119 --> 00:18:32,560 Speaker 1: our professor of political science and public Policy at Brown 320 00:18:32,680 --> 00:18:36,760 Speaker 1: University joining us from Providence, Rhode Island. Professor Schiller, thank 321 00:18:36,800 --> 00:18:38,520 Speaker 1: you so much for being with us. I want to 322 00:18:38,560 --> 00:18:42,359 Speaker 1: start with the significance of this decision on behalf of 323 00:18:42,400 --> 00:18:45,359 Speaker 1: that handful of senators who really are the key to 324 00:18:45,440 --> 00:18:48,199 Speaker 1: whether or not there will be witnesses in this in 325 00:18:48,240 --> 00:18:51,440 Speaker 1: this trial. Yeah, I mean, I think it's really crucial 326 00:18:51,440 --> 00:18:53,920 Speaker 1: to understand the politics of it. So Miss McConnell wants 327 00:18:53,920 --> 00:18:57,000 Speaker 1: to keep control of the United States Senate after election. 328 00:18:57,280 --> 00:19:00,640 Speaker 1: He's got vulnerable senators, he's got vulnerable centers in Maine, Um, 329 00:19:01,200 --> 00:19:06,679 Speaker 1: North Carolina, Arizona, and Colorado, among others. And he's just 330 00:19:06,720 --> 00:19:09,520 Speaker 1: doing the math. And Susan Collins in particular is viewed 331 00:19:09,560 --> 00:19:12,919 Speaker 1: to be quite vulnerable on this issue. And the question 332 00:19:13,000 --> 00:19:15,080 Speaker 1: is if this is going to take it seriously? This 333 00:19:15,160 --> 00:19:18,160 Speaker 1: is impeachment. Did the president of uses power? We sort 334 00:19:18,200 --> 00:19:20,320 Speaker 1: of know they're not going to vote to convict. We've 335 00:19:20,359 --> 00:19:22,639 Speaker 1: got to get that idea. That's parts and loyalty, But 336 00:19:22,880 --> 00:19:25,080 Speaker 1: should we all have a fair trial and a fair 337 00:19:25,119 --> 00:19:27,159 Speaker 1: hearing of all the evidence. In fact, it could be 338 00:19:27,240 --> 00:19:30,159 Speaker 1: that the evidence supports the idea that he shouldn't be 339 00:19:30,160 --> 00:19:32,920 Speaker 1: convicted and Austin and removed from office, and that would 340 00:19:32,960 --> 00:19:36,000 Speaker 1: help those four vulnerable senators. It's not clear to me 341 00:19:36,359 --> 00:19:39,200 Speaker 1: that if you present the evidence or some witnesses, you're 342 00:19:39,320 --> 00:19:43,840 Speaker 1: definitely strengthening the House Democrats case on impeachment. So that's 343 00:19:43,840 --> 00:19:46,040 Speaker 1: the puzzle, and the question is are you going to 344 00:19:46,040 --> 00:19:49,040 Speaker 1: appear to be fair and open in states where you're 345 00:19:49,040 --> 00:19:51,960 Speaker 1: really gonna be vying for those independents and suburban voters 346 00:19:52,000 --> 00:19:56,400 Speaker 1: in so, Professor, assuming that I guess witnesses are not 347 00:19:56,480 --> 00:19:59,840 Speaker 1: called and there is no conviction, what would be a 348 00:20:00,040 --> 00:20:03,480 Speaker 1: win for the Democrats here. Well, I think you're already 349 00:20:03,520 --> 00:20:05,600 Speaker 1: seeing part of the win, Paul, which is that the 350 00:20:05,640 --> 00:20:07,719 Speaker 1: speech is particularly last night. If you watch some of them, 351 00:20:07,760 --> 00:20:10,400 Speaker 1: they got a little heated, they got a little fiery, uh. 352 00:20:10,440 --> 00:20:13,880 Speaker 1: And the House Democrats are trying to use this opportunity, 353 00:20:13,880 --> 00:20:17,480 Speaker 1: I think, to rile or you know, secure the Democratic 354 00:20:17,520 --> 00:20:19,880 Speaker 1: Party base. As we know, there's a lot of conflict 355 00:20:19,920 --> 00:20:23,600 Speaker 1: in the Democratic presidential nomination process. There's no clear front runner, 356 00:20:23,840 --> 00:20:26,520 Speaker 1: nobody's madly in love with any of the choices, and 357 00:20:26,560 --> 00:20:28,840 Speaker 1: that has to concern the Democrats in terms of turnout. 358 00:20:28,960 --> 00:20:31,520 Speaker 1: But if you can drive this from the House effort. 359 00:20:31,680 --> 00:20:34,359 Speaker 1: In other words, the House, as in eighteen, did very 360 00:20:34,359 --> 00:20:36,320 Speaker 1: well to take it back the Democrats. If you could 361 00:20:36,400 --> 00:20:39,680 Speaker 1: drive that and really rile up the base based on impeachment, 362 00:20:39,920 --> 00:20:44,639 Speaker 1: particularly constituencies within the base on impeachment, that becomes a 363 00:20:44,680 --> 00:20:47,600 Speaker 1: political victory down the road for the Democrats, even if 364 00:20:47,640 --> 00:20:50,240 Speaker 1: they don't get the conviction that they're seeking. Really, what 365 00:20:50,320 --> 00:20:53,440 Speaker 1: about pushback? People say, look, the economy is doing really well. 366 00:20:53,440 --> 00:20:56,640 Speaker 1: What's your plan for that at a time when President 367 00:20:56,680 --> 00:21:02,040 Speaker 1: Trump's policies have at least allowed it to keep going? Right, Lisa, 368 00:21:02,080 --> 00:21:04,680 Speaker 1: this is exactly right. So it's a different audience. Right, 369 00:21:04,680 --> 00:21:07,840 Speaker 1: You've got the independence who are probably going to vote 370 00:21:07,840 --> 00:21:10,080 Speaker 1: for Trump at the economy stays good, even though they 371 00:21:10,119 --> 00:21:12,000 Speaker 1: may not like him. The question is will to be 372 00:21:12,040 --> 00:21:14,919 Speaker 1: Trump fatigue? Will Trump do something else that looks like 373 00:21:14,960 --> 00:21:17,040 Speaker 1: this that just takes people over the edge and they 374 00:21:17,080 --> 00:21:19,520 Speaker 1: can't stand them anymore. That's a possibility, but that's a 375 00:21:19,560 --> 00:21:22,080 Speaker 1: different base. The Democrats have to worry about turnout in 376 00:21:22,119 --> 00:21:24,560 Speaker 1: their own base. What cost Hillary Clinton is a lot 377 00:21:24,560 --> 00:21:28,000 Speaker 1: of factors, but partially lower turnout among African Americans and 378 00:21:28,080 --> 00:21:31,040 Speaker 1: defections among women in particular. We saw women go back 379 00:21:31,040 --> 00:21:33,919 Speaker 1: to the Democrat Party in will they stick with the 380 00:21:33,960 --> 00:21:38,320 Speaker 1: Democrat Party in so having people out there who are showcasing, 381 00:21:38,320 --> 00:21:42,000 Speaker 1: particularly from these constituencies, that may be enough to get 382 00:21:42,040 --> 00:21:45,840 Speaker 1: that energy level back up, sustaining the gains and not 383 00:21:46,000 --> 00:21:50,000 Speaker 1: fall into the travel which was conflict and some dislike 384 00:21:50,000 --> 00:21:52,919 Speaker 1: and apathy. Professor Shuler, is there any evidence that the 385 00:21:52,960 --> 00:21:57,320 Speaker 1: impeachment proceedings have in fact been successful at energizing the 386 00:21:57,320 --> 00:22:01,480 Speaker 1: Democratic base? Not yet, But we haven't seen the turnout 387 00:22:01,480 --> 00:22:03,439 Speaker 1: in the primaries yet because we haven't gotten there right. 388 00:22:03,440 --> 00:22:05,520 Speaker 1: We've got the Iowa caucuses them, we have New Hampshire, 389 00:22:05,680 --> 00:22:07,840 Speaker 1: we have Nevada, we have South Carolina. We have to 390 00:22:07,840 --> 00:22:11,280 Speaker 1: see what that that primary turnout looks like. Yes, it's competitive, 391 00:22:11,440 --> 00:22:14,240 Speaker 1: but turnout is also an indication of interest. People are 392 00:22:14,240 --> 00:22:16,480 Speaker 1: still registering the same places and mostly voting in the 393 00:22:16,480 --> 00:22:18,960 Speaker 1: same places they vote in eighteen. That's an advantage for 394 00:22:18,960 --> 00:22:20,880 Speaker 1: the Democrats to get out the door. If we see 395 00:22:20,960 --> 00:22:25,800 Speaker 1: high primary turnout, that's gonna be evidence of engage Democratic Party. 396 00:22:26,080 --> 00:22:28,600 Speaker 1: And that means that, you know, the Democrats can try 397 00:22:28,600 --> 00:22:31,159 Speaker 1: to be hopeful about getting their base out. We know 398 00:22:31,240 --> 00:22:33,520 Speaker 1: the Trump base will get out and so the question 399 00:22:33,560 --> 00:22:35,480 Speaker 1: is do all Republicans get out the door, they tend 400 00:22:35,520 --> 00:22:37,960 Speaker 1: to be more loyal, more unified, and they vote bigger 401 00:22:38,040 --> 00:22:41,639 Speaker 1: numbers in presidential elections for their candidate that independent base. 402 00:22:41,960 --> 00:22:44,280 Speaker 1: But I think, you know, as people actually watch this, 403 00:22:44,400 --> 00:22:46,399 Speaker 1: if they watch, which they can watch, you know, tape 404 00:22:46,400 --> 00:22:48,920 Speaker 1: it or watch it live, but as they actually see 405 00:22:48,960 --> 00:22:51,679 Speaker 1: the Senate go through this and realize how historic this is. 406 00:22:52,080 --> 00:22:54,320 Speaker 1: You know, this could have reverb down the line six 407 00:22:54,400 --> 00:22:57,200 Speaker 1: eight months. It all depends on Trump's behavior. If he 408 00:22:57,240 --> 00:23:00,200 Speaker 1: triggers something else, people will say to the Republicans, why 409 00:23:00,200 --> 00:23:02,080 Speaker 1: didn't you go after him harder? Why didn't you call 410 00:23:02,080 --> 00:23:04,800 Speaker 1: it witnesses, Why didn't you dig deeper? That's a gamble 411 00:23:04,880 --> 00:23:06,879 Speaker 1: I think that McConnell and the Republican Party is taking 412 00:23:06,880 --> 00:23:09,879 Speaker 1: by not doing that. Professor, what's the role of Chief 413 00:23:10,040 --> 00:23:13,520 Speaker 1: Justice Roberts in this proceeding? Well? To keep the trains 414 00:23:13,600 --> 00:23:16,720 Speaker 1: running on time? I mean, he already admonished both sides, 415 00:23:16,800 --> 00:23:18,560 Speaker 1: you know, in a very quiet way last night, but 416 00:23:18,600 --> 00:23:21,359 Speaker 1: he he admolished them basically to say, listen, keep it civil, 417 00:23:21,600 --> 00:23:23,480 Speaker 1: you know, and he quoted something from the early part 418 00:23:23,480 --> 00:23:25,880 Speaker 1: of the twentieth century saying, look, you know, just keep 419 00:23:25,880 --> 00:23:28,240 Speaker 1: it civil, keep it to the facts, and I think 420 00:23:28,240 --> 00:23:30,520 Speaker 1: he's gonna have to make sure that rhetoric doesn't get 421 00:23:30,520 --> 00:23:33,199 Speaker 1: too heated and that things stick to the facts of 422 00:23:33,200 --> 00:23:36,280 Speaker 1: the case. How much he intervenes, we all have to see. 423 00:23:36,480 --> 00:23:38,920 Speaker 1: But that's his role. It's so interesting. The vice President 424 00:23:38,960 --> 00:23:40,840 Speaker 1: doesn't have a role. Normally, the Vice President presides of 425 00:23:40,840 --> 00:23:43,359 Speaker 1: the United States Senate, so even breaking a tie or 426 00:23:43,440 --> 00:23:46,399 Speaker 1: ruling on emotion, this is all the Chief Justice. So 427 00:23:46,440 --> 00:23:49,480 Speaker 1: it's a different Senate that we usually are typically um 428 00:23:49,600 --> 00:23:52,640 Speaker 1: habituated to seeing. And he's gonna have to really run 429 00:23:53,000 --> 00:23:55,320 Speaker 1: run the ship in a steady way. It has everything 430 00:23:55,320 --> 00:23:57,240 Speaker 1: to do with the Senate, but also for the reputation 431 00:23:57,240 --> 00:23:59,600 Speaker 1: of the Supreme Court itself. You know, I just uh 432 00:24:00,000 --> 00:24:02,760 Speaker 1: want to eliminate your background. I mean, you've been on 433 00:24:02,800 --> 00:24:06,200 Speaker 1: the staff of Senator Patrick moynihan and Governor Mario Cuomo. 434 00:24:06,560 --> 00:24:11,400 Speaker 1: You've been extensively involved in the democratic political engine um 435 00:24:11,560 --> 00:24:14,440 Speaker 1: throughout the years, and I think that it's really important 436 00:24:14,480 --> 00:24:18,399 Speaker 1: to find out what is the potential ramification for the 437 00:24:18,440 --> 00:24:23,359 Speaker 1: Democrats that the Republicans energized their base based on the 438 00:24:23,400 --> 00:24:28,040 Speaker 1: impeachment with with President Trump succeeding and convincing them that 439 00:24:28,119 --> 00:24:31,040 Speaker 1: it is a witch hunt. In his words, Yeah, I mean, 440 00:24:31,080 --> 00:24:33,120 Speaker 1: I think you're You're absolutely right, And you know it's 441 00:24:33,600 --> 00:24:36,639 Speaker 1: in my early pre academic life, I was very involved 442 00:24:36,640 --> 00:24:38,560 Speaker 1: in Democrat politics and now it's been a long time, 443 00:24:38,600 --> 00:24:41,680 Speaker 1: so I've been out of the loop, but observing from 444 00:24:41,720 --> 00:24:44,760 Speaker 1: Afar and essentially what you can look at for the 445 00:24:44,800 --> 00:24:49,399 Speaker 1: Republicans solidification of the loyalty of the Republican voter to 446 00:24:49,520 --> 00:24:52,440 Speaker 1: the Republican party across the board. That's what they're hoping 447 00:24:52,480 --> 00:24:54,320 Speaker 1: to get out of this impeachment trial process, and I 448 00:24:54,320 --> 00:24:56,640 Speaker 1: think they will get that, which is to say, don't 449 00:24:56,680 --> 00:25:00,200 Speaker 1: go anywhere. We've got this guy under control. We're watching things, 450 00:25:00,280 --> 00:25:03,280 Speaker 1: we're gonna protect him, we're gonna protect our party gains, 451 00:25:03,600 --> 00:25:05,600 Speaker 1: and we're gonna do what you want us to do. 452 00:25:05,840 --> 00:25:08,800 Speaker 1: And I think that's a clear, unified message that they 453 00:25:08,920 --> 00:25:11,880 Speaker 1: are sending now that they continue to send. The question 454 00:25:12,080 --> 00:25:15,200 Speaker 1: is what the president does after this, and that's something 455 00:25:15,280 --> 00:25:17,560 Speaker 1: they can't control, which is why I still think it's 456 00:25:17,560 --> 00:25:19,440 Speaker 1: a bit of a gamble on their part, particularly in 457 00:25:19,440 --> 00:25:21,840 Speaker 1: those vulnerable states that are going to be really contested. 458 00:25:21,880 --> 00:25:24,800 Speaker 1: In very good Wendy Chiller, thanks so much. For joining us. 459 00:25:25,040 --> 00:25:28,000 Speaker 1: Wendy is the professor of political science and public policy 460 00:25:28,040 --> 00:25:31,560 Speaker 1: at Brown University, giving us her thoughts on the impeachment process. 461 00:25:31,880 --> 00:25:34,119 Speaker 1: Thanks for listening to the Bloomberg P and L podcast. 462 00:25:34,280 --> 00:25:36,880 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts 463 00:25:36,960 --> 00:25:40,040 Speaker 1: or whatever podcast platform you prefer. Paul Sweeney, I'm on 464 00:25:40,080 --> 00:25:42,639 Speaker 1: Twitter at pt Sweeney. I'm Lisa A. Bram Woods. I'm 465 00:25:42,680 --> 00:25:45,639 Speaker 1: on Twitter at Lisa Bramwood's one before the podcast. You 466 00:25:45,640 --> 00:25:48,160 Speaker 1: can always catch us worldwide on Bloomberg Radio.