1 00:00:03,120 --> 00:00:18,520 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Welcome to our twenty 2 00:00:18,560 --> 00:00:22,320 Speaker 1: twenty four US election edition of voter Nomics, the Bloomberg 3 00:00:22,360 --> 00:00:26,560 Speaker 1: podcast where politics and economics collide. All year, we've been 4 00:00:26,600 --> 00:00:29,080 Speaker 1: talking about how voters around the world have the ability 5 00:00:29,120 --> 00:00:33,440 Speaker 1: to affect markets, countries, and economies like never before. We're 6 00:00:33,440 --> 00:00:36,800 Speaker 1: going to focus on arguably the biggest of them all, 7 00:00:37,040 --> 00:00:41,239 Speaker 1: the American election. As we speak, victory has just been 8 00:00:41,280 --> 00:00:44,920 Speaker 1: called for Donald Trump. It came as he won Wisconsin. 9 00:00:45,360 --> 00:00:49,160 Speaker 1: The SMP five hundred reacted positively, did the News, as 10 00:00:49,200 --> 00:00:53,599 Speaker 1: did companies like Tesla. Donald Trump's fellow Republicans won control 11 00:00:53,720 --> 00:00:56,240 Speaker 1: of the Senate, and in every state where most votes 12 00:00:56,280 --> 00:01:00,000 Speaker 1: had been counted, Trump's performance was stronger than in twenty twenty. 13 00:01:00,520 --> 00:01:03,440 Speaker 1: So on today's Votomics, we're sharing an episode from The 14 00:01:03,440 --> 00:01:07,479 Speaker 1: Big Take podcast, Bloomberg's daily podcast, which features in depth 15 00:01:07,600 --> 00:01:11,319 Speaker 1: original reporting from around the globe. In their quick reaction 16 00:01:11,600 --> 00:01:15,640 Speaker 1: US election special, Big Take hosts Sarah Holder and Bloomberg's 17 00:01:15,640 --> 00:01:20,120 Speaker 1: Wendy Benjaminson break down how election Day played out and 18 00:01:20,160 --> 00:01:23,440 Speaker 1: get reactions from around the world, plus what we can 19 00:01:23,520 --> 00:01:27,560 Speaker 1: expect from a second Trump administration. But before all of that, 20 00:01:27,920 --> 00:01:29,720 Speaker 1: I'm a Lego Stratton and I made. 21 00:01:29,600 --> 00:01:31,199 Speaker 2: Room waldron Oge. 22 00:01:31,400 --> 00:01:32,360 Speaker 1: Did you get any sleep? 23 00:01:32,640 --> 00:01:36,120 Speaker 2: I didn't. Actually, I was very foolish because I started 24 00:01:36,200 --> 00:01:40,080 Speaker 2: just looking at my twitter feed, x feed, whatever you 25 00:01:40,160 --> 00:01:43,120 Speaker 2: want to call it, at about midnight, and that I 26 00:01:43,120 --> 00:01:47,319 Speaker 2: did a musk feed and I didn't stop, unfortunately, until 27 00:01:47,440 --> 00:01:49,720 Speaker 2: until about four point thirty five in the morning. I 28 00:01:49,800 --> 00:01:52,480 Speaker 2: just I just I just kept going because what we 29 00:01:52,480 --> 00:01:55,600 Speaker 2: were seeing in real time was a very surprising story. 30 00:01:56,480 --> 00:01:58,800 Speaker 1: Because it wasn't night Federal Quintine exactly. 31 00:01:58,840 --> 00:02:02,800 Speaker 2: I mean, we people had expect did either Harris victory 32 00:02:03,200 --> 00:02:05,840 Speaker 2: or a very very close election, which we'd still be 33 00:02:05,920 --> 00:02:08,720 Speaker 2: litigating at the moment, And what we saw was clear, 34 00:02:09,120 --> 00:02:11,360 Speaker 2: was very clear, and it was a clear Trump victory. 35 00:02:11,480 --> 00:02:14,760 Speaker 2: I don't think many pundits were expecting that at all. 36 00:02:14,960 --> 00:02:18,440 Speaker 1: And the inquest started very quickly as well, certainly in 37 00:02:18,480 --> 00:02:23,640 Speaker 1: the corresponds, I was getting around how did the left 38 00:02:23,760 --> 00:02:27,720 Speaker 1: or Democrats misjudge this, and whether or not it's worse 39 00:02:27,760 --> 00:02:30,680 Speaker 1: for them than the Hillary Clinton defeat. I mean, certainly 40 00:02:30,720 --> 00:02:34,320 Speaker 1: that sense that America wasn't yet ready for a female president, 41 00:02:34,520 --> 00:02:36,400 Speaker 1: whether or not that is the take home point in 42 00:02:36,440 --> 00:02:40,960 Speaker 1: the days ahead, but it feels that there's questions around 43 00:02:40,960 --> 00:02:43,440 Speaker 1: gender as well as questions around whether she was the 44 00:02:43,520 --> 00:02:44,160 Speaker 1: right candidate. 45 00:02:44,440 --> 00:02:46,240 Speaker 2: Yeah, we had a very peculiar sort of set of 46 00:02:46,280 --> 00:02:50,320 Speaker 2: expectations because Kamala Harris did very well in the debate 47 00:02:50,480 --> 00:02:53,840 Speaker 2: with Trump and her stocks rose, and in the last 48 00:02:53,960 --> 00:02:56,480 Speaker 2: few days before the vote, it looked as though she 49 00:02:56,560 --> 00:03:00,000 Speaker 2: was really regaining momentum, partly because of the Madison Square 50 00:03:00,200 --> 00:03:04,280 Speaker 2: Gardens absurdities, and probably because Trump seemed to be losing 51 00:03:04,360 --> 00:03:07,520 Speaker 2: a bit of his focus and flair. But clearly that 52 00:03:07,639 --> 00:03:11,119 Speaker 2: was absolutely wrong. One of the big stories of this 53 00:03:11,400 --> 00:03:16,840 Speaker 2: election is that the democratic notion of what democratic politics 54 00:03:16,880 --> 00:03:20,680 Speaker 2: is about has been exploded. They have basically been an 55 00:03:20,720 --> 00:03:26,160 Speaker 2: alliance between the educated, upper middle class elite and various 56 00:03:26,160 --> 00:03:28,760 Speaker 2: ethnic minorities. And their assumption was that they could just 57 00:03:28,880 --> 00:03:32,240 Speaker 2: keep adding ethnic minorities. They've got a big advantage with 58 00:03:32,400 --> 00:03:34,639 Speaker 2: black voters, and they could just add more and more 59 00:03:34,639 --> 00:03:37,800 Speaker 2: and more Latinos or whoever was coming in, and that's 60 00:03:37,840 --> 00:03:43,000 Speaker 2: clearly not the case. You saw Black voters voting in 61 00:03:43,640 --> 00:03:46,880 Speaker 2: surprising numbers for Trump, you saw Latino voters voting in 62 00:03:47,080 --> 00:03:52,120 Speaker 2: very surprising numbers for Trump, and Asian voters also shifting 63 00:03:52,200 --> 00:03:55,560 Speaker 2: in some significant ways. We haven't seen numbers like this since, 64 00:03:55,720 --> 00:03:58,760 Speaker 2: you know, for the Latino since since George W. Bush. 65 00:03:58,960 --> 00:04:02,960 Speaker 2: And that's as really skewered the whole way of thinking 66 00:04:03,160 --> 00:04:05,680 Speaker 2: of Democrats, because Democrats tend to think of these people 67 00:04:05,720 --> 00:04:08,800 Speaker 2: as being exploited, as being victims, as in some way 68 00:04:08,840 --> 00:04:12,920 Speaker 2: being marginal. They certainly think of the immigration issue cutting 69 00:04:13,440 --> 00:04:16,080 Speaker 2: in favor of the Democrats, and this hasn't happened. I 70 00:04:16,120 --> 00:04:20,240 Speaker 2: think it's partly because class is the overriding thing. And 71 00:04:20,640 --> 00:04:24,960 Speaker 2: I think that what the liberal elite, hyper educated, hyperwoke, 72 00:04:25,839 --> 00:04:29,120 Speaker 2: very status conscious liberal elite has done is it's basically 73 00:04:29,200 --> 00:04:32,839 Speaker 2: driven the white working class out of the Democratic coalition. 74 00:04:32,839 --> 00:04:35,560 Speaker 2: They've shifted to the Republicans. And now it's doing exactly 75 00:04:35,560 --> 00:04:39,600 Speaker 2: the same thing for ethnic minorities, slowly but very significantly. 76 00:04:39,839 --> 00:04:41,839 Speaker 1: So if we just take the helicopter view of what 77 00:04:41,920 --> 00:04:44,280 Speaker 1: this podcast why You and I and Stephanie when she's 78 00:04:44,279 --> 00:04:46,520 Speaker 1: with us, have been discussing over the last year, through 79 00:04:46,640 --> 00:04:49,160 Speaker 1: lots of ballots, lots of different elections, is this or 80 00:04:49,200 --> 00:04:52,200 Speaker 1: not since this fact that incumbents have struggled, is this 81 00:04:52,320 --> 00:04:55,440 Speaker 1: that trend playing out? Kamala Harris came in, took over 82 00:04:55,480 --> 00:04:59,040 Speaker 1: from Biden, ran very, very tight and well executed hundred 83 00:04:59,080 --> 00:05:02,360 Speaker 1: days the less probably realized too late she had to 84 00:05:02,440 --> 00:05:05,440 Speaker 1: convey that she was changed. She didn't manage to do that. 85 00:05:05,600 --> 00:05:08,719 Speaker 1: So my question is was it just she felt foul 86 00:05:08,800 --> 00:05:11,920 Speaker 1: of that tide that is beating up on the incumbent, 87 00:05:11,920 --> 00:05:14,279 Speaker 1: by which we mean the people in power they just 88 00:05:14,680 --> 00:05:17,680 Speaker 1: the electra and not feeling they're benefiting doing well enough 89 00:05:17,760 --> 00:05:20,400 Speaker 1: out of it. Or was it actually she wasn't good 90 00:05:20,480 --> 00:05:21,599 Speaker 1: enough or was it both? 91 00:05:21,760 --> 00:05:26,560 Speaker 2: I think economic discontent and inflation underlay this. People just 92 00:05:26,880 --> 00:05:30,280 Speaker 2: felt poorer and they felt angry because they felt poorer. 93 00:05:30,440 --> 00:05:32,640 Speaker 2: But there are a lot of important cultural issues as well. 94 00:05:32,680 --> 00:05:35,960 Speaker 2: There was the immigration issue that people felt that Biden 95 00:05:36,120 --> 00:05:39,800 Speaker 2: and Harris, by implication, had not taken that seriously enough. 96 00:05:40,000 --> 00:05:42,400 Speaker 2: And there's a sort of set of cultural issues that 97 00:05:42,640 --> 00:05:45,960 Speaker 2: also motivated people to sern that you might feel grumpy 98 00:05:46,000 --> 00:05:48,560 Speaker 2: and angry about inflation, but do you go to rallies 99 00:05:48,600 --> 00:05:51,880 Speaker 2: and cheer. Do you really turn out and wave banners 100 00:05:52,000 --> 00:05:55,160 Speaker 2: just because you're angry about the economy. I think Trump 101 00:05:55,279 --> 00:05:59,240 Speaker 2: was motivating a lot of resentment about the way a 102 00:05:59,360 --> 00:06:01,839 Speaker 2: very insula to the elite has been running the country 103 00:06:01,839 --> 00:06:05,440 Speaker 2: in ways that go against the opinions of large numbers 104 00:06:05,440 --> 00:06:08,560 Speaker 2: of people. So yes, underlying it all inflation and the 105 00:06:08,600 --> 00:06:12,839 Speaker 2: economy driving all of this, but we're a very rich man. 106 00:06:12,920 --> 00:06:17,520 Speaker 1: He's incredibly successful at conveying the the underdog, and it's 107 00:06:17,800 --> 00:06:20,760 Speaker 1: it's both economic, but it's also a vibe he has 108 00:06:20,960 --> 00:06:25,480 Speaker 1: that he just cuts through the blandness of the political establishment. 109 00:06:25,480 --> 00:06:30,880 Speaker 2: So you have a very sort of twee cultivated, cerebral, 110 00:06:31,240 --> 00:06:34,440 Speaker 2: rather bossy political elite out there, and you have this 111 00:06:34,720 --> 00:06:38,360 Speaker 2: vulgan we do, we do, but you have this vulgar, 112 00:06:38,640 --> 00:06:43,400 Speaker 2: boisterous man and people identify with him. They more identified 113 00:06:43,680 --> 00:06:45,359 Speaker 2: with him rather than with the Harvard yachts than in 114 00:06:45,400 --> 00:06:49,520 Speaker 2: the nineteenth century. And he's brilliant at summing up big 115 00:06:49,560 --> 00:06:52,680 Speaker 2: things in small phrases. I mean, make America great again. 116 00:06:52,720 --> 00:06:55,040 Speaker 2: It's just such a powerful thing. He's a demagogue. 117 00:06:55,200 --> 00:06:58,640 Speaker 1: Just on this question about Kamala Harris and the kind 118 00:06:58,680 --> 00:07:02,400 Speaker 1: of aloofness, did she do everything she possibly could? 119 00:07:02,600 --> 00:07:05,120 Speaker 2: I thought she was a terribly weak candidate in the 120 00:07:05,200 --> 00:07:08,520 Speaker 2: sense that she didn't really have a set of policies 121 00:07:08,560 --> 00:07:11,040 Speaker 2: and a gender. She did very well in the debate, 122 00:07:11,360 --> 00:07:13,800 Speaker 2: and then she sort of fizzled out. If you don't 123 00:07:13,880 --> 00:07:17,320 Speaker 2: present a compelling message as to why you should be 124 00:07:17,400 --> 00:07:19,880 Speaker 2: voted for, and if you don't present a set of 125 00:07:19,920 --> 00:07:23,120 Speaker 2: policies to solve people's problems, particularly the problem of the border, 126 00:07:23,360 --> 00:07:26,080 Speaker 2: then it looks as though you assume that you should 127 00:07:26,080 --> 00:07:28,320 Speaker 2: be voted for just because of the person that you are. 128 00:07:28,600 --> 00:07:32,120 Speaker 2: Now we go back to Biden. Had Biden stepped down 129 00:07:32,320 --> 00:07:35,840 Speaker 2: when he should have done, had he created an open 130 00:07:35,880 --> 00:07:40,360 Speaker 2: primary system, had the strongest democrat one, then that would 131 00:07:40,400 --> 00:07:45,360 Speaker 2: have been possible, even in difficult circumstances, for a democratic victory. 132 00:07:45,680 --> 00:07:47,559 Speaker 1: One of the things we will see in the coming 133 00:07:47,640 --> 00:07:50,480 Speaker 1: days when we do the kind of analysis of the 134 00:07:50,520 --> 00:07:56,320 Speaker 1: demographics is I think we thought and expected that women 135 00:07:56,520 --> 00:08:00,200 Speaker 1: on mass would come out for Kamala Harris across the 136 00:08:00,240 --> 00:08:06,240 Speaker 1: divide concerned about abortion rights being restricted. I wonder in 137 00:08:06,280 --> 00:08:08,480 Speaker 1: the end whether that wasn't strong enough either. You certainly 138 00:08:08,520 --> 00:08:11,400 Speaker 1: saw Kamala Harris make it front and center of many 139 00:08:11,400 --> 00:08:11,960 Speaker 1: things she did. 140 00:08:12,120 --> 00:08:15,760 Speaker 2: Absolutely. I think we will know more over the next 141 00:08:15,760 --> 00:08:19,080 Speaker 2: few days about the precise demographic makeup, but I think 142 00:08:19,120 --> 00:08:23,680 Speaker 2: Soccer Mum's women did not turn out for Harris in 143 00:08:23,760 --> 00:08:27,040 Speaker 2: the sort of numbers that we expected. Also, underneath it all. 144 00:08:27,080 --> 00:08:30,600 Speaker 2: Do people care more about that issue or do they 145 00:08:30,600 --> 00:08:32,920 Speaker 2: care more about immigration? And I think it's immigration. 146 00:08:33,160 --> 00:08:36,520 Speaker 1: When you glance at the polls and the returns on 147 00:08:36,559 --> 00:08:39,400 Speaker 1: why the things that motivated people to vote, democracy comes up, 148 00:08:39,520 --> 00:08:43,080 Speaker 1: and at first glance, the kind of complacent view is 149 00:08:43,080 --> 00:08:46,400 Speaker 1: that that favored Kamala Harris. But actually you dig deeper, 150 00:08:46,400 --> 00:08:48,760 Speaker 1: and if you've done any reporting around either America or 151 00:08:48,800 --> 00:08:52,320 Speaker 1: the UK or lots of countries, actually it does us 152 00:08:52,320 --> 00:08:54,760 Speaker 1: stand to reason that that might be something that motivated 153 00:08:54,760 --> 00:08:56,920 Speaker 1: people to vote for Trump. This sense, as you've been 154 00:08:56,960 --> 00:08:59,920 Speaker 1: talking eloquently throughout the podcast about this sense that it 155 00:09:00,160 --> 00:09:02,640 Speaker 1: was sort of, you know, the establishment was a done deal, 156 00:09:02,720 --> 00:09:05,199 Speaker 1: sewn up and an impenetrable fortress that you couldn't get 157 00:09:05,200 --> 00:09:08,400 Speaker 1: into if you were normal working pass Absolutely no, there's 158 00:09:08,400 --> 00:09:11,800 Speaker 1: this extraordinary result, which was I think the number. 159 00:09:11,520 --> 00:09:15,560 Speaker 2: Two issue that people were worried about after the economy 160 00:09:15,640 --> 00:09:17,600 Speaker 2: was the state of democracy. And you think, well, that's 161 00:09:17,600 --> 00:09:21,040 Speaker 2: a very very good indicator for Harris, and then in 162 00:09:21,080 --> 00:09:25,200 Speaker 2: fact those people broke towards Trump. So you know, we 163 00:09:25,320 --> 00:09:27,680 Speaker 2: in the media tend to think about January the sixth 164 00:09:27,679 --> 00:09:30,560 Speaker 2: and Trump's sort of contempt for due process. But in fact, 165 00:09:30,559 --> 00:09:33,520 Speaker 2: what a lot of people believe is that the media 166 00:09:33,920 --> 00:09:37,160 Speaker 2: is part of a cartel which tells a story to 167 00:09:37,240 --> 00:09:39,680 Speaker 2: other members of the media and doesn't really relate to 168 00:09:39,760 --> 00:09:41,600 Speaker 2: ordinary people. And I think this is a huge problem 169 00:09:41,640 --> 00:09:45,960 Speaker 2: for our profession that I think thirteen percent of Republicans 170 00:09:46,280 --> 00:09:50,240 Speaker 2: now believe the mainstream media, and the mainstream media quite 171 00:09:50,240 --> 00:09:53,760 Speaker 2: Franklin was in the tank for Kamala all the way 172 00:09:53,800 --> 00:09:56,520 Speaker 2: through this election. I think there's a crisis of confidence 173 00:09:56,640 --> 00:10:00,480 Speaker 2: that we have to as a profession, get out of bubble, 174 00:10:00,920 --> 00:10:05,080 Speaker 2: report on the country, on America, report on the actual 175 00:10:05,200 --> 00:10:09,040 Speaker 2: angs and Anxietism, worries about regular people, and do a 176 00:10:09,080 --> 00:10:12,040 Speaker 2: better job of reflecting what's going on out there rather 177 00:10:12,040 --> 00:10:13,040 Speaker 2: than talking to each other. 178 00:10:13,120 --> 00:10:15,880 Speaker 1: But Adrian, I mean everything you've just said, you could 179 00:10:15,880 --> 00:10:18,360 Speaker 1: have said after the Brexit vote. You could have said 180 00:10:18,400 --> 00:10:20,439 Speaker 1: after the first Trump victory. When do we learn? 181 00:10:20,960 --> 00:10:25,240 Speaker 2: And it's the corporations, the universities, the professional elite, and 182 00:10:25,240 --> 00:10:27,160 Speaker 2: they've got to reconnect with their country or we'll keep 183 00:10:27,160 --> 00:10:29,839 Speaker 2: getting these sort of surprises, not only in the United States, 184 00:10:29,880 --> 00:10:30,720 Speaker 2: but also in Europe. 185 00:10:31,080 --> 00:10:33,520 Speaker 1: Taking a step across the pond, back across the pond, 186 00:10:33,600 --> 00:10:36,160 Speaker 1: we're in London. We're in the UK reflecting on all 187 00:10:36,200 --> 00:10:39,480 Speaker 1: of this and what about the impact it has on 188 00:10:39,800 --> 00:10:43,880 Speaker 1: UK politics? Not UK politics, Actually, I think more interesting 189 00:10:44,040 --> 00:10:46,560 Speaker 1: is the economic impact. I think this morning has been 190 00:10:46,640 --> 00:10:48,320 Speaker 1: quite expensive for the government. 191 00:10:48,440 --> 00:10:51,199 Speaker 2: Absolutely. I mean I think it's all in the short term, 192 00:10:51,280 --> 00:10:53,240 Speaker 2: or in the simplest sense, it's a disaster for the 193 00:10:53,320 --> 00:10:56,640 Speaker 2: Labor Party. Because the Labor Party is interlinked with the 194 00:10:56,679 --> 00:10:59,880 Speaker 2: Democratic Party but also very hostile to Trump. 195 00:11:00,000 --> 00:11:02,439 Speaker 1: People have been speculating there might be a star a reshuffler. 196 00:11:02,480 --> 00:11:04,400 Speaker 2: Yeah, I would have thought so. I think it's very 197 00:11:04,400 --> 00:11:07,640 Speaker 2: difficult to keep this current position in place. But also 198 00:11:07,679 --> 00:11:10,600 Speaker 2: we're interlinked economies. We're going to get a big economic 199 00:11:10,600 --> 00:11:13,959 Speaker 2: boom in the United States, lower corporation tax, lower personal tax. 200 00:11:14,200 --> 00:11:18,000 Speaker 2: I think a lot of talent will shift from this country, 201 00:11:18,040 --> 00:11:20,880 Speaker 2: which is being more and more heavily taxed, to the 202 00:11:21,040 --> 00:11:22,800 Speaker 2: United States. So that to Trump world. 203 00:11:22,920 --> 00:11:24,839 Speaker 1: It is the case that Labor has pledged to spend 204 00:11:24,840 --> 00:11:28,000 Speaker 1: more on defense, but that number wasn't actually in last 205 00:11:28,040 --> 00:11:30,600 Speaker 1: week's budget, And when you look at last week's budget 206 00:11:30,679 --> 00:11:34,080 Speaker 1: and how her head room was reduced in it, it's 207 00:11:34,120 --> 00:11:36,680 Speaker 1: hard to see that she has much room for maneuver well. 208 00:11:36,679 --> 00:11:38,960 Speaker 2: I think there's a bigger European problem over the defense 209 00:11:39,000 --> 00:11:41,640 Speaker 2: because Europe as a whole has to face the fact 210 00:11:41,720 --> 00:11:45,640 Speaker 2: that it is in hawk to Trump to defend it. 211 00:11:45,679 --> 00:11:51,760 Speaker 2: That Trump is not a stable or predictable or reliable ally, 212 00:11:52,120 --> 00:11:54,960 Speaker 2: And I think that Europe and Britain will have to 213 00:11:54,960 --> 00:11:57,200 Speaker 2: get closer and closer together. They'll have to put aside 214 00:11:57,200 --> 00:12:00,440 Speaker 2: their quarrels and really deal with this defense isship. Whatever 215 00:12:00,480 --> 00:12:02,840 Speaker 2: Trump does, and I think there is a big set 216 00:12:02,880 --> 00:12:06,600 Speaker 2: of variables in what Trump does, we can't presume that 217 00:12:06,640 --> 00:12:07,120 Speaker 2: you'll do so. 218 00:12:07,240 --> 00:12:10,440 Speaker 1: At the last time round, internationally, there was some softening 219 00:12:10,480 --> 00:12:13,120 Speaker 1: of his joy. They say things to get into power. 220 00:12:13,280 --> 00:12:16,720 Speaker 2: And he likes to say very extravagant and provocative things. 221 00:12:16,760 --> 00:12:19,640 Speaker 2: But nevertheless, even if he's not as radical as he 222 00:12:19,679 --> 00:12:22,880 Speaker 2: claims he is, can we continue to be in hock 223 00:12:23,040 --> 00:12:24,640 Speaker 2: to a country that's so unpredictable. 224 00:12:24,760 --> 00:12:25,960 Speaker 1: Well, we're going to pick up on a lot of 225 00:12:26,000 --> 00:12:28,240 Speaker 1: these themes in a special edition we're going to do 226 00:12:28,600 --> 00:12:32,600 Speaker 1: next week to close the year of these elections that 227 00:12:32,640 --> 00:12:35,920 Speaker 1: we have been covering in depth, and we look forward 228 00:12:35,920 --> 00:12:38,280 Speaker 1: to hearing from Steph again. Steph right now is I 229 00:12:38,320 --> 00:12:42,199 Speaker 1: don't know, recovering retreating from a spin room somewhere anyway, 230 00:12:42,760 --> 00:12:44,920 Speaker 1: Now on to the rest of the show. This is 231 00:12:44,960 --> 00:12:48,440 Speaker 1: our Big Take special podcast on the American election. 232 00:12:57,000 --> 00:13:00,000 Speaker 3: At around two thirty on Wednesday morning, Donald Trump took 233 00:13:00,080 --> 00:13:02,720 Speaker 3: the stage at his campaign headquarters in mar A Lago 234 00:13:03,120 --> 00:13:05,680 Speaker 3: to claim victory in the US presidential election. 235 00:13:06,280 --> 00:13:07,360 Speaker 4: Look what happened? 236 00:13:07,440 --> 00:13:08,199 Speaker 5: Is this crazy? 237 00:13:14,640 --> 00:13:19,160 Speaker 4: But it's a political victory that our country has never 238 00:13:19,200 --> 00:13:21,800 Speaker 4: seen before, nothing like this. I want to thank the 239 00:13:21,840 --> 00:13:26,520 Speaker 4: American people for the extraordinary honor of being elected your 240 00:13:27,400 --> 00:13:30,679 Speaker 4: forty seventh president, and you're forty fifth president. 241 00:13:31,040 --> 00:13:34,360 Speaker 3: Earlier, as the campaign watch party for Vice President Kamala 242 00:13:34,360 --> 00:13:38,280 Speaker 3: Harris wound down at her alma mater, Howard University, her 243 00:13:38,320 --> 00:13:42,280 Speaker 3: campaign co chair Cedric Richmond, briefly addressed the crowd. 244 00:13:42,120 --> 00:13:47,520 Speaker 4: So you won't hear from the Vice president tonight, but 245 00:13:47,679 --> 00:13:50,720 Speaker 4: you will hear from her tomorrow. 246 00:13:51,960 --> 00:13:55,200 Speaker 3: When Trump spoke alongside his family, in her circle and 247 00:13:55,280 --> 00:13:58,960 Speaker 3: running mate JD. Vance, he'd already secured two hundred and 248 00:13:59,000 --> 00:14:02,320 Speaker 3: sixty seven of the two hundred and seventy Electoral College 249 00:14:02,400 --> 00:14:06,120 Speaker 3: votes he needed, clinching wins in the key battleground states 250 00:14:06,160 --> 00:14:11,559 Speaker 3: of Georgia, North Carolina, and Pennsylvania. And at five thirty am, 251 00:14:11,679 --> 00:14:15,800 Speaker 3: Trump was declared the projected winner of Wisconsin's ten electoral 252 00:14:15,840 --> 00:14:19,920 Speaker 3: College votes, bringing his total to two hundred and seventy seven. 253 00:14:20,400 --> 00:14:23,680 Speaker 3: As the results came into focus, markets reacted and the 254 00:14:23,720 --> 00:14:29,120 Speaker 3: so called Trump trade searched. Bitcoin spiked, the dollar posted 255 00:14:29,160 --> 00:14:33,400 Speaker 3: its biggest gain against major currencies since twenty twenty, clean 256 00:14:33,560 --> 00:14:40,800 Speaker 3: energy took a hit, and Treasury bonds humbled. Today on 257 00:14:40,840 --> 00:14:45,080 Speaker 3: the show how Election Day played out, reactions from around 258 00:14:45,120 --> 00:14:48,320 Speaker 3: the world, and what we can expect from a second 259 00:14:48,440 --> 00:14:51,640 Speaker 3: Trump term, I'm Sarah Holder, and this is the big 260 00:14:51,680 --> 00:15:00,360 Speaker 3: take from Bloomberg News. It's four am in walk Washington, 261 00:15:00,400 --> 00:15:05,640 Speaker 3: d C. I'm joined by Bloomberg Senior Washington editor Wendy Benjaminson. So, Wendy, 262 00:15:05,800 --> 00:15:10,680 Speaker 3: for people waking up today and catching up what happened overnight. 263 00:15:11,200 --> 00:15:14,280 Speaker 5: Donald Trump has won the presidency. It was not as 264 00:15:14,320 --> 00:15:16,520 Speaker 5: close as we expected it to be. 265 00:15:16,880 --> 00:15:19,520 Speaker 3: Well, Wendy, how does this year's Trump win compared to 266 00:15:19,560 --> 00:15:21,720 Speaker 3: his path to victory in twenty sixteen. 267 00:15:22,400 --> 00:15:27,720 Speaker 5: Well, it's not that dissimilar. He took all of the South, 268 00:15:28,480 --> 00:15:33,480 Speaker 5: he took a large swath of the Midwest, the Plain States, 269 00:15:34,080 --> 00:15:38,880 Speaker 5: and this time again he managed to break through that 270 00:15:39,160 --> 00:15:41,400 Speaker 5: so called blue wall. I think we're going to have 271 00:15:41,400 --> 00:15:45,880 Speaker 5: to rename that now because in twenty sixteen, Hillary Clinton 272 00:15:46,000 --> 00:15:50,680 Speaker 5: failed to get all of the Pennsylvania, Michigan, Wisconsin, that 273 00:15:50,800 --> 00:15:54,640 Speaker 5: industrial blue wall the Democrats have to win, and it 274 00:15:54,720 --> 00:15:58,880 Speaker 5: appears that Donald Trump succeeded in that blue wall. 275 00:15:59,200 --> 00:16:02,120 Speaker 3: What was Trump to do this campaign cycle that he 276 00:16:02,200 --> 00:16:03,880 Speaker 3: failed to do in twenty twenty. 277 00:16:04,200 --> 00:16:06,960 Speaker 5: Well, this is one of those weird Donald Trump can 278 00:16:07,040 --> 00:16:11,120 Speaker 5: get away with stuff sort of elections. He fared far 279 00:16:11,200 --> 00:16:14,920 Speaker 5: better with Hispanic voters than he did in twenty sixteen 280 00:16:15,000 --> 00:16:18,280 Speaker 5: or twenty twenty. And remember, in twenty sixteen, one of 281 00:16:18,320 --> 00:16:21,640 Speaker 5: his famous lines was Mexico is sending us their criminals 282 00:16:21,640 --> 00:16:24,840 Speaker 5: and rapists, and a lot of Hispanic voters took events 283 00:16:24,880 --> 00:16:29,960 Speaker 5: to that. The Sunday before October twenty seventh, he held 284 00:16:30,000 --> 00:16:32,640 Speaker 5: a rally of Madison Square Garden where a comedian called 285 00:16:32,640 --> 00:16:36,560 Speaker 5: Puerto Rico a floating island of garbage. And yet he 286 00:16:36,640 --> 00:16:40,120 Speaker 5: fared far better, according to exit polls with Latino voters 287 00:16:40,360 --> 00:16:41,360 Speaker 5: than he ever has. 288 00:16:41,720 --> 00:16:43,840 Speaker 3: That didn't seem to matter in the way that people 289 00:16:43,840 --> 00:16:44,560 Speaker 3: thought it might. 290 00:16:44,920 --> 00:16:50,480 Speaker 5: Right, And remember Donald Trump also won this time against 291 00:16:50,520 --> 00:16:56,360 Speaker 5: twenty sixteen with thirty four felony convictions, a civil claim 292 00:16:56,520 --> 00:17:00,920 Speaker 5: holding him responsible for rape, appointing Supreme or justices who 293 00:17:00,960 --> 00:17:05,359 Speaker 5: overturned Roe versus Wade, and a number of other comments 294 00:17:05,400 --> 00:17:08,440 Speaker 5: that he's made or proposals that he has put forward 295 00:17:08,880 --> 00:17:13,200 Speaker 5: that seem anathema to most Americans. And yet here we are, 296 00:17:13,640 --> 00:17:17,840 Speaker 5: and while the gender gap and reproductive rights were the 297 00:17:17,920 --> 00:17:20,399 Speaker 5: issues that were going to push her over the top, 298 00:17:21,080 --> 00:17:25,639 Speaker 5: it failed to materialize against the popular support that Donald 299 00:17:25,680 --> 00:17:26,720 Speaker 5: Trump seems to have had. 300 00:17:26,960 --> 00:17:29,240 Speaker 3: You mentioned some of these issues that didn't seem to 301 00:17:29,240 --> 00:17:31,280 Speaker 3: face voters when it came to Donald Trump. But let's 302 00:17:31,280 --> 00:17:33,919 Speaker 3: talk about some of the issues that did decide this election. 303 00:17:34,480 --> 00:17:37,240 Speaker 3: We've been talking all election season about the polls, including 304 00:17:37,240 --> 00:17:40,280 Speaker 3: the Bloomberg News Morning Consult polls that showed that voters 305 00:17:40,359 --> 00:17:44,840 Speaker 3: considered the economy their number one issue. Abortion also ranked 306 00:17:44,880 --> 00:17:48,159 Speaker 3: highly immigration. What do we know at this point about 307 00:17:48,280 --> 00:17:51,760 Speaker 3: how those issues specifically impacted the results we saw tonight? 308 00:17:52,040 --> 00:17:57,680 Speaker 5: Donald Trump he pinned the economy, the post COVID economy, 309 00:17:57,720 --> 00:18:02,960 Speaker 5: even though it has recovered by all all measures. He 310 00:18:03,080 --> 00:18:06,200 Speaker 5: pinned that on Joe Biden and by extension, Kamala Harris. 311 00:18:06,440 --> 00:18:10,160 Speaker 5: He kept doing that over and over again, even though 312 00:18:10,200 --> 00:18:15,280 Speaker 5: his rhetoric on immigration was authoritarian, talking about deporting millions 313 00:18:15,320 --> 00:18:18,600 Speaker 5: of people, closing the border, building the wall, all those 314 00:18:18,600 --> 00:18:23,119 Speaker 5: sort of things. Voters want a secure border, and he 315 00:18:23,280 --> 00:18:28,679 Speaker 5: talked about it constantly, even down to the falsehoods about 316 00:18:29,160 --> 00:18:33,040 Speaker 5: Haitian immigrants eating cats in Springfield, Ohio. It all spoke 317 00:18:33,119 --> 00:18:37,840 Speaker 5: to voters deep fears about the other. In quotes coming in, 318 00:18:38,280 --> 00:18:43,679 Speaker 5: Kamala Harris talked a little about immigration, saying that she 319 00:18:43,760 --> 00:18:47,359 Speaker 5: would sign the bill that Donald Trump killed last year 320 00:18:47,480 --> 00:18:52,159 Speaker 5: in Congress. She talked about a caring economy and opportunity economy. 321 00:18:52,760 --> 00:18:55,959 Speaker 5: But a lot of the time the Democrats focused on 322 00:18:56,160 --> 00:18:59,920 Speaker 5: just how awful Donald Trump is, and people who think 323 00:19:00,080 --> 00:19:03,560 Speaker 5: he's awful already think he's awful the people. Then there 324 00:19:03,560 --> 00:19:06,200 Speaker 5: are people who think he's an awful person, but they 325 00:19:06,320 --> 00:19:09,159 Speaker 5: like his policies. And then there's the people who actually 326 00:19:09,200 --> 00:19:13,800 Speaker 5: don't think he's awful. Donald Trump is awful is now 327 00:19:13,840 --> 00:19:18,800 Speaker 5: a proven two time losing strategy, And yet the Democrats 328 00:19:18,880 --> 00:19:21,119 Speaker 5: kept doing that over and over again. 329 00:19:21,359 --> 00:19:24,720 Speaker 3: And here we are, well, what about Trump's economic policies 330 00:19:24,920 --> 00:19:27,200 Speaker 3: attracted voters and how much are we going to see 331 00:19:27,240 --> 00:19:28,040 Speaker 3: the results. 332 00:19:28,720 --> 00:19:31,480 Speaker 5: Well, that's going to be the big question, Sarah, because 333 00:19:31,720 --> 00:19:36,480 Speaker 5: his economic policies he promised to offer. He offered so 334 00:19:36,600 --> 00:19:39,520 Speaker 5: many tax cuts that if every single one of them 335 00:19:39,520 --> 00:19:42,720 Speaker 5: were enacted, I'm not even sure the US government could 336 00:19:42,760 --> 00:19:46,080 Speaker 5: function because there just wouldn't be enough money coming in. 337 00:19:46,720 --> 00:19:49,879 Speaker 5: So some of those will be enacted, but it couldn't 338 00:19:49,920 --> 00:19:53,560 Speaker 5: be all of them. The tariffs he is proposing, placing 339 00:19:53,640 --> 00:19:57,560 Speaker 5: sixty percent tariffs or more on imports from China that 340 00:19:58,280 --> 00:20:01,800 Speaker 5: many economists say is going to raise prices for consumers. 341 00:20:02,680 --> 00:20:07,320 Speaker 5: And his immigration policy if he carries out the deportation 342 00:20:07,480 --> 00:20:12,960 Speaker 5: of twelve million undocumented workers in this country, an undertaking 343 00:20:13,480 --> 00:20:16,400 Speaker 5: that I don't even know how something like that works 344 00:20:16,480 --> 00:20:19,680 Speaker 5: or how long it would take. Nevertheless, that is going 345 00:20:19,760 --> 00:20:23,920 Speaker 5: to put a huge hole in the construction industry, in 346 00:20:24,119 --> 00:20:28,520 Speaker 5: the agricultural industry, and could possibly hurt the American economy. 347 00:20:28,880 --> 00:20:33,080 Speaker 5: So we'll see how popular these ideas are after he 348 00:20:33,160 --> 00:20:34,200 Speaker 5: begins to enact them. 349 00:20:34,480 --> 00:20:38,080 Speaker 3: Well, despite these long term concerns, and even before some 350 00:20:38,160 --> 00:20:41,119 Speaker 3: of these key states we're talking about were called, we 351 00:20:41,200 --> 00:20:46,800 Speaker 3: saw markets responding to Trump's lead. How did they respond well? 352 00:20:46,920 --> 00:20:51,200 Speaker 5: The dollar got stronger overnight in preparation for these tariffs 353 00:20:51,400 --> 00:20:55,640 Speaker 5: to be enacted. It's very good news for bitcoin. He's 354 00:20:55,680 --> 00:20:59,160 Speaker 5: a huge supporter of crypto, and a number of markets 355 00:20:59,400 --> 00:21:03,240 Speaker 5: rose and anticipation of certainty. I think it is not 356 00:21:03,320 --> 00:21:06,480 Speaker 5: necessarily that they are happy Donald Trump won. It's they 357 00:21:06,520 --> 00:21:09,959 Speaker 5: know who the president is and they are reacting to them. 358 00:21:11,560 --> 00:21:14,520 Speaker 3: After the break will dig deeper into the Trump campaign 359 00:21:14,640 --> 00:21:19,199 Speaker 3: promises that could become the administration's policies and what it 360 00:21:19,240 --> 00:21:30,240 Speaker 3: all means for the global economy. Wendy What if Donald 361 00:21:30,320 --> 00:21:34,199 Speaker 3: Trump's promises on the campaign trail told us about what 362 00:21:34,359 --> 00:21:38,919 Speaker 3: his next administration is likely to prioritize in office. 363 00:21:39,000 --> 00:21:42,840 Speaker 5: His priorities will certainly be the economy and immigration first 364 00:21:42,880 --> 00:21:47,080 Speaker 5: and foremost. The difference this time is that in twenty sixteen, 365 00:21:47,240 --> 00:21:50,040 Speaker 5: a lot of traditional Republicans, because that was the only 366 00:21:50,160 --> 00:21:53,879 Speaker 5: kind there was in twenty sixteen, joined his cabinet, joined 367 00:21:53,880 --> 00:21:58,880 Speaker 5: his administration because they wanted to show this newcomer how 368 00:21:59,080 --> 00:22:02,800 Speaker 5: government works and set up some guard rails for some 369 00:22:02,840 --> 00:22:06,639 Speaker 5: of his more outlandish ideas. That's not happening this time. 370 00:22:07,080 --> 00:22:09,600 Speaker 5: This time, he is going to be surrounded by people 371 00:22:09,600 --> 00:22:13,200 Speaker 5: who are loyal to him. Loyal to him is the keyword, 372 00:22:13,280 --> 00:22:16,560 Speaker 5: not the Constitution, the rule of law, things like that. 373 00:22:17,040 --> 00:22:19,399 Speaker 5: So I think there is some fear out there about 374 00:22:19,440 --> 00:22:22,600 Speaker 5: the disappearing of the guard rails that were there in 375 00:22:22,640 --> 00:22:23,400 Speaker 5: his first term. 376 00:22:23,720 --> 00:22:27,240 Speaker 3: What do tonight's results say about the future of abortion 377 00:22:27,400 --> 00:22:28,760 Speaker 3: access in this country? 378 00:22:29,480 --> 00:22:32,240 Speaker 5: Well, it is certainly now a state's issue. There is 379 00:22:32,400 --> 00:22:36,560 Speaker 5: not enough Democrats or pro reproductive rights members of Congress 380 00:22:36,800 --> 00:22:40,440 Speaker 5: to codify Roe Versus Way to put abortion rights back 381 00:22:40,520 --> 00:22:44,400 Speaker 5: into law, and so the Supreme Court decision to send 382 00:22:44,480 --> 00:22:46,800 Speaker 5: it to the states and have a patchwork of laws 383 00:22:46,800 --> 00:22:50,520 Speaker 5: all over the country seems to be now the way 384 00:22:50,560 --> 00:22:54,400 Speaker 5: it is. Remember also that there are still two Supreme 385 00:22:54,400 --> 00:22:58,800 Speaker 5: Court justices who are nearing the age at which they 386 00:22:58,920 --> 00:23:04,679 Speaker 5: might retire or pass on, and Donald Trump will have 387 00:23:04,760 --> 00:23:08,679 Speaker 5: an opportunity with a Republican Senate, at least for the 388 00:23:08,680 --> 00:23:14,840 Speaker 5: first two years, to appoint two more conservative justices on 389 00:23:14,880 --> 00:23:18,880 Speaker 5: the Supreme Court, which would of course make the Supreme 390 00:23:18,880 --> 00:23:21,320 Speaker 5: Court one of the most conservative in US history. 391 00:23:21,600 --> 00:23:24,960 Speaker 3: So if Republicans do maintain control of both chambers of 392 00:23:25,000 --> 00:23:28,320 Speaker 3: Congress and the Presidency, what will it mean for US 393 00:23:28,359 --> 00:23:32,280 Speaker 3: spending on geopolitical conflicts like the war in Ukraine or 394 00:23:32,400 --> 00:23:33,200 Speaker 3: in the Middle East. 395 00:23:33,760 --> 00:23:37,160 Speaker 5: Well, the Ukrainian President Vladimir Lensky put out a statement 396 00:23:37,200 --> 00:23:42,160 Speaker 5: this morning congratulating Trump and looking forward to his decisive leadership, 397 00:23:42,200 --> 00:23:45,639 Speaker 5: and that was the right thing to say. Diplomatically, Donald 398 00:23:45,680 --> 00:23:49,679 Speaker 5: Trump is very much into making deals. He wants to 399 00:23:49,680 --> 00:23:52,200 Speaker 5: make a deal with Putin. He wants Putin and Zelenski 400 00:23:52,280 --> 00:23:54,960 Speaker 5: to come to a table and come to terms. Those 401 00:23:55,080 --> 00:23:59,680 Speaker 5: terms would end up probably being more favorable to Russia 402 00:23:59,720 --> 00:24:03,080 Speaker 5: than to Ukraine, and the US would no longer support 403 00:24:03,160 --> 00:24:06,320 Speaker 5: Ukraine and its fight against the invasion. It is also 404 00:24:06,359 --> 00:24:09,439 Speaker 5: extremely good news for Israeli Prime Minister Benjamin net Niyaho. 405 00:24:10,000 --> 00:24:15,080 Speaker 5: Kamala Harris had at least suggested some interest in the 406 00:24:15,160 --> 00:24:19,840 Speaker 5: humanitarian crisis going on in Gaza, and what former President 407 00:24:19,840 --> 00:24:25,080 Speaker 5: Trump has said is that bb Netanyaho's nickname Bib, needs 408 00:24:25,119 --> 00:24:29,000 Speaker 5: to finish the job in Gaza. And so despite the 409 00:24:29,040 --> 00:24:31,359 Speaker 5: fact that I think he got more Arab American support 410 00:24:31,400 --> 00:24:34,359 Speaker 5: than one would have suspected, I think this is a 411 00:24:34,440 --> 00:24:36,840 Speaker 5: very good day for Putin and Netanyahu. 412 00:24:40,520 --> 00:24:43,800 Speaker 3: This is the big take from Bloomberg News. I'm Sarah Holder. 413 00:24:44,359 --> 00:24:47,399 Speaker 3: This episode was produced by David Fox, Thomas lou and 414 00:24:47,520 --> 00:24:51,640 Speaker 3: Julia Press. It was edited by Aaron Edwards and Wendy Benjaminson. 415 00:24:52,200 --> 00:24:55,200 Speaker 3: This episode was mixed by Alex Zuguia. It was fact 416 00:24:55,280 --> 00:24:59,000 Speaker 3: checked by Thomas Lou, Julia Press, and Jessica Beck. Our 417 00:24:59,040 --> 00:25:02,920 Speaker 3: senior producer is Taomi Shavin. Our senior editor is Elizabeth Ponso. 418 00:25:03,280 --> 00:25:07,159 Speaker 3: Our executive producer is Nicole beemster Boor. Sage Bauman is 419 00:25:07,160 --> 00:25:10,720 Speaker 3: Bloomberg's head of podcasts. If you liked this episode, make 420 00:25:10,760 --> 00:25:13,439 Speaker 3: sure to subscribe and review The Big Take wherever you 421 00:25:13,480 --> 00:25:16,840 Speaker 3: listen to podcasts. It helps people find the show. Thanks 422 00:25:16,880 --> 00:25:19,359 Speaker 3: for listening. We'll be back tomorrow.