1 00:00:02,440 --> 00:00:09,119 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:09,160 --> 00:00:13,280 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:13,360 --> 00:00:16,320 Speaker 1: Eastern on Affo card playing Android otto with the Bloomberg 4 00:00:16,400 --> 00:00:19,640 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:19,960 --> 00:00:21,640 Speaker 1: or watch us live on YouTube. 6 00:00:23,000 --> 00:00:24,959 Speaker 2: Let's sit down to Washington, DC's talk a little bit 7 00:00:25,000 --> 00:00:27,280 Speaker 2: of policy here, and we could do that with Nathan Dean. 8 00:00:27,320 --> 00:00:30,720 Speaker 2: He's a Bloomberg Intelligence Senior policy analyst. Nathan, what's the 9 00:00:30,760 --> 00:00:33,480 Speaker 2: feeling in DC as the rest of the country starts 10 00:00:33,560 --> 00:00:36,880 Speaker 2: going to the polls here? Anybody any smart money leaning 11 00:00:36,920 --> 00:00:38,600 Speaker 2: one way or the other? Or is it, as most 12 00:00:38,640 --> 00:00:41,280 Speaker 2: folks suggest, really too close to call at this point. 13 00:00:41,960 --> 00:00:43,600 Speaker 3: So I think it's too close to call on the 14 00:00:43,640 --> 00:00:46,080 Speaker 3: presidential race and then the House race. I think essentially 15 00:00:46,200 --> 00:00:48,239 Speaker 3: I could think I can tell you who I think 16 00:00:48,320 --> 00:00:49,360 Speaker 3: is going to win, but then I have to give 17 00:00:49,400 --> 00:00:51,360 Speaker 3: you a five minute explanation, and if I do that, 18 00:00:51,440 --> 00:00:53,959 Speaker 3: I'm not really explaining anything. But what we can say 19 00:00:54,080 --> 00:00:55,800 Speaker 3: is is that we generally think the Republicans are going 20 00:00:55,840 --> 00:00:58,640 Speaker 3: to take the Senate. Why this is a very difficult 21 00:00:58,680 --> 00:01:01,200 Speaker 3: race for the Democrats. They're defending twenty three out of 22 00:01:01,240 --> 00:01:04,160 Speaker 3: the thirty four seats out there, Senator Joe Manchin is resigning. 23 00:01:04,280 --> 00:01:06,959 Speaker 3: The Republicans are gonna most likely take bust Virginia. They 24 00:01:07,000 --> 00:01:09,959 Speaker 3: could potentially take Montana as well. You know, Senator John 25 00:01:10,000 --> 00:01:12,360 Speaker 3: Tester is not doing so well there in the polling wise, 26 00:01:12,520 --> 00:01:14,080 Speaker 3: But why does that matter? What it means that if 27 00:01:14,080 --> 00:01:16,880 Speaker 3: President Trump wins, a deregulatory effort can happen much quicker. 28 00:01:17,160 --> 00:01:19,440 Speaker 3: And if Kamala Harris wins, it means the Republicans can 29 00:01:19,480 --> 00:01:22,600 Speaker 3: effectively block under jam up a lot of her nominees 30 00:01:22,640 --> 00:01:25,000 Speaker 3: for their own regulatory efforts. But just on the main 31 00:01:25,120 --> 00:01:27,120 Speaker 3: thing of who's gonna win the race, We're gonna have 32 00:01:27,160 --> 00:01:27,960 Speaker 3: to wait until tonight. 33 00:01:29,480 --> 00:01:33,040 Speaker 4: What are the implications for investors here and for markets? 34 00:01:33,319 --> 00:01:35,800 Speaker 4: You know, what kind of results could we be hearing 35 00:01:35,920 --> 00:01:39,360 Speaker 4: in the next few days that would move the market 36 00:01:39,440 --> 00:01:41,080 Speaker 4: that investors would need to know about. 37 00:01:41,800 --> 00:01:43,200 Speaker 3: Yeah, So we were trying to think of like the 38 00:01:43,360 --> 00:01:46,280 Speaker 3: major catalysts of what happens if you get a Harris 39 00:01:46,400 --> 00:01:48,920 Speaker 3: victory versus a Trump victory. The first one is tariff's 40 00:01:49,160 --> 00:01:50,720 Speaker 3: I mean, we think that the tariffs are going to 41 00:01:50,760 --> 00:01:52,600 Speaker 3: come no matter who wins the president next year. But 42 00:01:52,760 --> 00:01:55,360 Speaker 3: is it a broad tarot tariff sixty percent on all 43 00:01:55,400 --> 00:01:58,000 Speaker 3: goods coming from China or a very small subset. So 44 00:01:58,320 --> 00:02:00,480 Speaker 3: once you decide, once we figure out who the president is, 45 00:02:00,800 --> 00:02:03,440 Speaker 3: will know what the tariff outlook look likes for next year. 46 00:02:03,720 --> 00:02:06,240 Speaker 3: The other thing is investment banks. If Kamala Harris wins 47 00:02:06,440 --> 00:02:08,640 Speaker 3: the Buzzle three end game, a rule that increases capital 48 00:02:08,680 --> 00:02:11,239 Speaker 3: about nine percent for the banks, well must likely go forward. 49 00:02:11,280 --> 00:02:13,760 Speaker 3: If President Trump wins, that's not gonna happen. The Inflation 50 00:02:13,919 --> 00:02:17,800 Speaker 3: Reduction Act mostly cemented if Kamala Harris wins, could be tweaked. 51 00:02:17,800 --> 00:02:20,360 Speaker 3: So if you have exposure to renewables and the renewables industry, 52 00:02:20,639 --> 00:02:22,720 Speaker 3: that's something to keep in mind. And then the last 53 00:02:22,760 --> 00:02:24,600 Speaker 3: thing is is that if the Republicans have a great 54 00:02:24,680 --> 00:02:26,840 Speaker 3: night and take the House, the Senate, and the presidency, 55 00:02:27,320 --> 00:02:30,760 Speaker 3: then the opportunity for reconciliation for massive tax reform next 56 00:02:30,840 --> 00:02:33,839 Speaker 3: year think multi trillion dollar tax reform at the tail 57 00:02:33,919 --> 00:02:36,200 Speaker 3: end of twenty twenty five. That comes to play if 58 00:02:36,200 --> 00:02:37,359 Speaker 3: the Republicans have a great night. 59 00:02:38,200 --> 00:02:41,200 Speaker 2: If President former President Trump were to win, what would 60 00:02:41,240 --> 00:02:43,519 Speaker 2: he do on day one? Would he be a just 61 00:02:43,680 --> 00:02:45,560 Speaker 2: doing tariffs across the board, because that is something that 62 00:02:45,600 --> 00:02:46,400 Speaker 2: a president can do. 63 00:02:47,280 --> 00:02:49,720 Speaker 3: Yeah, so you know, President Trump, if you look at 64 00:02:49,760 --> 00:02:52,560 Speaker 3: the executive orders now, our view is is that i'd 65 00:02:52,600 --> 00:02:55,040 Speaker 3: say about eighty five percent of executive orders are symbolic 66 00:02:55,120 --> 00:02:56,840 Speaker 3: in nature. It's the fancy way of the president picking 67 00:02:56,880 --> 00:02:59,000 Speaker 3: up the phone and directing to his or her staff 68 00:02:59,040 --> 00:03:01,480 Speaker 3: do something either legit slate route or the regular toy route. 69 00:03:01,720 --> 00:03:03,519 Speaker 3: But the power of the presidency is more powerful in 70 00:03:03,600 --> 00:03:07,320 Speaker 3: that other fifteen percent, and that's national security, foreign relations, tariffs, 71 00:03:07,440 --> 00:03:11,240 Speaker 3: and trade. Now, Congress is largely delegated tariffs to the president, 72 00:03:11,600 --> 00:03:13,240 Speaker 3: and there's some thought out there that, you know, President 73 00:03:13,280 --> 00:03:15,760 Speaker 3: Trump would need congressional authorization. Our view is is that 74 00:03:15,840 --> 00:03:18,959 Speaker 3: there's a lot that he could do nilatterally, and so 75 00:03:19,040 --> 00:03:21,919 Speaker 3: if President Trump comes in day one, expect those executive 76 00:03:21,960 --> 00:03:23,760 Speaker 3: orders to come out. Now, when it comes to tariff, 77 00:03:24,080 --> 00:03:25,760 Speaker 3: I think you would see the red line come across 78 00:03:25,800 --> 00:03:28,919 Speaker 3: the Bloomberg terminal and say, you know, President Trump's signs 79 00:03:28,960 --> 00:03:31,960 Speaker 3: executive order on tariff. Within the language of that tariff 80 00:03:32,080 --> 00:03:35,040 Speaker 3: executive order, though there'd be languages essentially saying this won't 81 00:03:35,040 --> 00:03:37,200 Speaker 3: go into fruition for another two hundred seventy days or 82 00:03:37,200 --> 00:03:40,160 Speaker 3: three hundred and sixty five days. Why, it's a negotiation tool, 83 00:03:40,240 --> 00:03:42,760 Speaker 3: and presidents don't want to back themselves up into corners. 84 00:03:43,000 --> 00:03:45,680 Speaker 3: They want the flexibility to see what the reciprocal tariff 85 00:03:45,680 --> 00:03:48,160 Speaker 3: would look like before it actually goes into fruition. So 86 00:03:48,240 --> 00:03:50,000 Speaker 3: there's a little bit of headline risk there, but the 87 00:03:50,120 --> 00:03:53,280 Speaker 3: ultimate impact of a tariff, if President Trump wins, would 88 00:03:53,280 --> 00:03:55,120 Speaker 3: probably be in the second or third quarter of next year. 89 00:03:55,880 --> 00:03:57,840 Speaker 4: And Nathan, what are you going to be watching for 90 00:03:58,120 --> 00:04:02,360 Speaker 4: policy wise with the l duck president if we do 91 00:04:02,560 --> 00:04:05,160 Speaker 4: find out a winner, let's say this week or even 92 00:04:05,200 --> 00:04:05,640 Speaker 4: next week. 93 00:04:06,320 --> 00:04:08,000 Speaker 3: Yeah, you know, it's hard to believe we're talking about 94 00:04:08,040 --> 00:04:10,200 Speaker 3: lame duck, but Congress comes back next week. And so 95 00:04:10,360 --> 00:04:12,640 Speaker 3: there are a couple things that the lobbyists around town 96 00:04:13,000 --> 00:04:15,040 Speaker 3: are all love and see if they can get this attached, 97 00:04:15,040 --> 00:04:16,960 Speaker 3: because remember we have a government funding fight coming up 98 00:04:17,000 --> 00:04:19,720 Speaker 3: in December. Now, there's two things that we're really looking on. 99 00:04:19,839 --> 00:04:20,840 Speaker 5: First as stable coins. 100 00:04:20,880 --> 00:04:23,200 Speaker 3: Now, there's this idea that there's a stable coin bill 101 00:04:23,560 --> 00:04:25,280 Speaker 3: that get passed during the lame duck. I may be 102 00:04:25,360 --> 00:04:27,200 Speaker 3: a little bit out of consensus. I don't think it's 103 00:04:27,240 --> 00:04:29,480 Speaker 3: going to happen. I think it's they're going to push 104 00:04:29,520 --> 00:04:32,040 Speaker 3: the can to twenty twenty five because lame ducks are 105 00:04:32,040 --> 00:04:35,279 Speaker 3: always optimistic from the lobbyist perspective, but when the reality 106 00:04:35,360 --> 00:04:37,040 Speaker 3: hits and most people just want to go home because 107 00:04:37,040 --> 00:04:39,840 Speaker 3: the election's over, they usually don't tend to have much 108 00:04:39,920 --> 00:04:42,400 Speaker 3: outs there. The other thing I would just note is 109 00:04:42,480 --> 00:04:44,800 Speaker 3: Senator Dick Durbin of Illinois will most likely try to 110 00:04:44,839 --> 00:04:48,280 Speaker 3: reattach his bill called the Credit Card Competition Act. If 111 00:04:48,279 --> 00:04:50,279 Speaker 3: you've flown through La Guardia Newark, you may have seen 112 00:04:50,320 --> 00:04:53,080 Speaker 3: the ads about these credit card This bill taking away 113 00:04:53,160 --> 00:04:55,560 Speaker 3: credit card points associated with airlines and so for like that. 114 00:04:55,839 --> 00:04:58,400 Speaker 3: Like this this would open up competition in terms of 115 00:04:58,480 --> 00:05:01,840 Speaker 3: networks on credit cards. Again, some headline risk there. I 116 00:05:01,960 --> 00:05:03,719 Speaker 3: don't think it's going to happen though. I think again 117 00:05:03,760 --> 00:05:06,479 Speaker 3: they'll get kicked to twenty twenty five, but certainly something 118 00:05:06,520 --> 00:05:07,320 Speaker 3: we have to pay attention to. 119 00:05:07,680 --> 00:05:09,440 Speaker 2: All Right, Nathan, thank you so much. We appreciate it. 120 00:05:09,520 --> 00:05:12,520 Speaker 2: Nathan Dean, he's a senior policy analyst for Bloomberg Intelligence. 121 00:05:12,760 --> 00:05:16,080 Speaker 2: He's down there in Washington, DC. He and his Tim team, 122 00:05:16,200 --> 00:05:19,960 Speaker 2: they really focus on policies coming out of Congress and 123 00:05:20,080 --> 00:05:23,080 Speaker 2: which industries and then maybe down to the company levels 124 00:05:23,080 --> 00:05:25,040 Speaker 2: which will be impacted. And that's the research that he 125 00:05:25,120 --> 00:05:28,360 Speaker 2: and his team do, and it's widely valued by Bloomberg 126 00:05:28,400 --> 00:05:31,560 Speaker 2: customers because we know many many industries are heavily regulated 127 00:05:31,640 --> 00:05:34,920 Speaker 2: and dependent upon government policy. So it's good to have 128 00:05:35,040 --> 00:05:36,640 Speaker 2: Nathan Dean and his team down there in TC. 129 00:05:38,480 --> 00:05:42,320 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 130 00:05:42,440 --> 00:05:45,360 Speaker 1: weekdays at ten am Eastern on applecar. 131 00:05:45,000 --> 00:05:47,719 Speaker 6: Play and Android Otto with the Bloomberg Business App. 132 00:05:47,880 --> 00:05:50,680 Speaker 1: You can also listen live on Amazon Alexa from our 133 00:05:50,760 --> 00:05:55,119 Speaker 1: flagship New York station Just Say Alexa playing Bloomberg eleven thirty. 134 00:05:56,279 --> 00:05:58,960 Speaker 2: Let's get back to this election here. Henrietta Trez has 135 00:05:58,960 --> 00:06:03,160 Speaker 2: been a valued a source for us all things politics 136 00:06:03,200 --> 00:06:05,320 Speaker 2: here for a long time. We appreciate getting a few 137 00:06:05,360 --> 00:06:07,720 Speaker 2: minutes or a time. She's managing partner and director of 138 00:06:07,800 --> 00:06:12,440 Speaker 2: Economic policy at Vada Partners. Henrietta, we've got early votes. 139 00:06:13,600 --> 00:06:15,720 Speaker 2: Is there anything we can glean from early voting? And 140 00:06:15,760 --> 00:06:17,760 Speaker 2: if so, which states should we kind of look at? 141 00:06:19,080 --> 00:06:20,960 Speaker 7: Yeah, we do have early votes. 142 00:06:21,000 --> 00:06:23,200 Speaker 8: I think there's really only two states that I feel 143 00:06:23,279 --> 00:06:27,240 Speaker 8: comfortable saying or giving us strong indications right now, and 144 00:06:27,279 --> 00:06:29,680 Speaker 8: they're both very promising for Donald Trump. I think in 145 00:06:29,960 --> 00:06:34,200 Speaker 8: Nevada and in North Carolina, the early vote turnout. The 146 00:06:34,480 --> 00:06:37,359 Speaker 8: get out the vote initiative that the Trump campaign has 147 00:06:37,480 --> 00:06:40,560 Speaker 8: embraced this year, unlike the last cycle, is really for 148 00:06:40,720 --> 00:06:43,760 Speaker 8: in person early voting, and both states have done that 149 00:06:43,920 --> 00:06:46,320 Speaker 8: in droves, and we're seeing that sort of nationwide and 150 00:06:46,400 --> 00:06:49,320 Speaker 8: all the early voting, a lot of rural Republican voters 151 00:06:49,360 --> 00:06:53,040 Speaker 8: have turned out much larger numbers than we saw either 152 00:06:53,120 --> 00:06:55,720 Speaker 8: in twenty twenty two or in twenty twenty. So his 153 00:06:55,880 --> 00:06:59,080 Speaker 8: supporters are definitely getting the email and the memo about 154 00:06:59,080 --> 00:06:59,839 Speaker 8: getting out there early. 155 00:07:01,240 --> 00:07:05,240 Speaker 4: So does that change your forecast at all for who 156 00:07:05,480 --> 00:07:08,800 Speaker 4: actually is going to win the electoral college? Because if 157 00:07:08,800 --> 00:07:12,520 Speaker 4: I'm reading the notes, your most recent forecast was that 158 00:07:12,960 --> 00:07:17,080 Speaker 4: president or Vice President Harris would actually win the electoral college. 159 00:07:18,120 --> 00:07:18,520 Speaker 7: That's right. 160 00:07:18,600 --> 00:07:21,120 Speaker 8: So the early vote is telling me that the electoral 161 00:07:21,160 --> 00:07:24,120 Speaker 8: college map that I have passed out for each candidate 162 00:07:24,520 --> 00:07:27,200 Speaker 8: is still holding strong and looks correct. So I expect 163 00:07:27,320 --> 00:07:29,800 Speaker 8: Donald Trump to win Nevada. I expect Donald Trump to 164 00:07:29,840 --> 00:07:33,320 Speaker 8: win North Carolina and Georgia. The two of the last 165 00:07:33,400 --> 00:07:38,080 Speaker 8: two are pickups. Arizona, Georgia and North Nevada are all 166 00:07:38,120 --> 00:07:40,800 Speaker 8: pickups for Donald Trump this year that I'm expecting. 167 00:07:40,840 --> 00:07:43,400 Speaker 7: And that's what early voting is showing. There's a lot 168 00:07:43,440 --> 00:07:44,480 Speaker 7: of different opinion out there. 169 00:07:44,560 --> 00:07:46,920 Speaker 8: John Ralston, who is excellent in Nevada, is saying that 170 00:07:48,280 --> 00:07:50,520 Speaker 8: sorry couple areas is going to win by zero point 171 00:07:50,560 --> 00:07:54,000 Speaker 8: three percent in Nevada. And of course Democrats have eked 172 00:07:54,000 --> 00:07:56,000 Speaker 8: out wins in the state of Nevada for the last 173 00:07:56,120 --> 00:07:59,200 Speaker 8: two cycles, and that's based off of sort of the 174 00:07:59,280 --> 00:08:02,480 Speaker 8: legacy if they Harry Reid machine, and Jackie Rosen continues 175 00:08:02,560 --> 00:08:05,040 Speaker 8: to pull well ahead of her competitor in the state. 176 00:08:05,120 --> 00:08:07,680 Speaker 8: At the Senate level, what you're seeing in Nevada and 177 00:08:07,840 --> 00:08:12,240 Speaker 8: Arizona is actually that fifteen percent of the Republican constituency 178 00:08:12,360 --> 00:08:15,360 Speaker 8: in those two states are voting for the Democratic Senate candidate. 179 00:08:15,640 --> 00:08:18,320 Speaker 8: So if there's crossover that early vote can't pick up. 180 00:08:18,520 --> 00:08:20,040 Speaker 8: I don't know how you voted, I just know that 181 00:08:20,080 --> 00:08:24,160 Speaker 8: you did vote. If there's crossover amongst Republicans into the 182 00:08:24,240 --> 00:08:27,320 Speaker 8: Harris camp, that is a that's going to be a 183 00:08:27,400 --> 00:08:30,000 Speaker 8: surprise that is not registered either in the polls, which 184 00:08:30,040 --> 00:08:32,600 Speaker 8: are finding everything sort of neck and neck, and it's 185 00:08:32,640 --> 00:08:33,760 Speaker 8: not going to be something that we know from the 186 00:08:33,760 --> 00:08:35,880 Speaker 8: early vote, because we don't know how you voted, so 187 00:08:36,000 --> 00:08:39,320 Speaker 8: that could be a shift that we see on election night, 188 00:08:39,360 --> 00:08:42,600 Speaker 8: But my expectation that they both go for Trump. But overarchingly, 189 00:08:42,679 --> 00:08:45,280 Speaker 8: I still anticipate that Harris will win Michigan, Wisconsin, and 190 00:08:45,280 --> 00:08:47,640 Speaker 8: Pennsylvania and that gets her two hundred and seventy Electoral 191 00:08:47,679 --> 00:08:50,000 Speaker 8: College votes, and that's why my odds are sixty percent that. 192 00:08:50,040 --> 00:08:50,440 Speaker 7: She will win. 193 00:08:50,960 --> 00:08:52,880 Speaker 2: Interesting, Henriette, we had a poll come out in the 194 00:08:52,920 --> 00:08:55,360 Speaker 2: last couple days from the state of Iowa that was 195 00:08:55,360 --> 00:08:57,920 Speaker 2: surprising for a lot of people showing that Vice President 196 00:08:58,000 --> 00:09:00,959 Speaker 2: Harris doing a leading in next which typically is a 197 00:09:01,040 --> 00:09:04,079 Speaker 2: Republican state. What did you make of that poll in 198 00:09:04,240 --> 00:09:05,839 Speaker 2: that What does that tell you? 199 00:09:07,400 --> 00:09:11,720 Speaker 8: You know, it really reinforces the story of this election cycle. 200 00:09:11,920 --> 00:09:14,240 Speaker 8: There's been a tremendous amount of focus on the black 201 00:09:14,280 --> 00:09:17,760 Speaker 8: and Latino youth vote, and specifically the youth mail vote, 202 00:09:17,960 --> 00:09:21,160 Speaker 8: and how there's been a draw away from the Democratic 203 00:09:21,240 --> 00:09:24,079 Speaker 8: Party and towards the Republican Party. What I think that 204 00:09:24,320 --> 00:09:28,080 Speaker 8: whole conversation has missed is that the story of elections 205 00:09:28,160 --> 00:09:31,199 Speaker 8: is really the suburbs. The suburbs vote the most, They 206 00:09:31,400 --> 00:09:35,640 Speaker 8: are the arbiters of the election cycle. So in twenty sixteen, 207 00:09:35,800 --> 00:09:38,960 Speaker 8: they swung four points for Donald Trump. In twenty twenty, 208 00:09:39,040 --> 00:09:41,400 Speaker 8: they swung two points for Joe Biden, and they decided 209 00:09:41,440 --> 00:09:44,680 Speaker 8: the outcome of the election. Right now, in critical states 210 00:09:44,760 --> 00:09:48,880 Speaker 8: like Philadelphia, Pennsylvania, the Philadelphia suburbs are going strongly for 211 00:09:49,120 --> 00:09:51,720 Speaker 8: Kamala Harris. And so the story of the Seltzer poll 212 00:09:51,840 --> 00:09:54,679 Speaker 8: I thought was fascinating. The twenty three percent of the 213 00:09:55,040 --> 00:09:58,720 Speaker 8: Iowa voters in the suburbs plus twenty three for Kamala Harris. 214 00:09:59,400 --> 00:10:01,920 Speaker 8: That's an indicat that the suburb story is correct, and 215 00:10:02,120 --> 00:10:04,840 Speaker 8: I think we can translate that nationwide. I don't expect 216 00:10:04,840 --> 00:10:07,079 Speaker 8: Tamala Hiris to win Iowa, but the story of the 217 00:10:07,120 --> 00:10:09,760 Speaker 8: suburbs is what I really want to focus on when 218 00:10:09,800 --> 00:10:12,560 Speaker 8: I see that poll and then transcribe to swing states. 219 00:10:13,920 --> 00:10:16,959 Speaker 4: How of each candidates kind of catered toward towards that 220 00:10:17,400 --> 00:10:22,240 Speaker 4: suburban vote. Are there certain issues that you study that 221 00:10:22,440 --> 00:10:25,520 Speaker 4: resonate more with the suburban voters that the candidates have 222 00:10:25,600 --> 00:10:28,760 Speaker 4: been I guess trying to touch on democracy. 223 00:10:28,880 --> 00:10:31,240 Speaker 8: This concept of democracy being on the ballot is a 224 00:10:31,320 --> 00:10:34,000 Speaker 8: really big deal in the suburbs. They think that that 225 00:10:34,120 --> 00:10:37,559 Speaker 8: issue is critical and then beyond that you have abortion 226 00:10:37,840 --> 00:10:40,240 Speaker 8: that Democrats try to hammer home, and on the right 227 00:10:40,360 --> 00:10:41,120 Speaker 8: you have immigration. 228 00:10:41,320 --> 00:10:43,480 Speaker 7: It's really those top three issues. 229 00:10:43,559 --> 00:10:47,559 Speaker 8: The economy is important, but it's such a misleading or 230 00:10:47,640 --> 00:10:51,439 Speaker 8: misguiding polling question these days because your view of the 231 00:10:51,559 --> 00:10:55,560 Speaker 8: economy is mostly defined by whether you support Joe Biden 232 00:10:55,880 --> 00:10:59,880 Speaker 8: or Donald Trump Biden's administration or Trump on the camp 233 00:11:00,000 --> 00:11:02,040 Speaker 8: pay trail. So if you side with either of those 234 00:11:02,080 --> 00:11:05,400 Speaker 8: two parties, that dictates your view of how the economy 235 00:11:05,480 --> 00:11:08,120 Speaker 8: is going. I think once now that inflation has been 236 00:11:09,240 --> 00:11:12,480 Speaker 8: tamped down and gas prices are back well below their 237 00:11:12,520 --> 00:11:15,800 Speaker 8: twenty twenty two levels and are down now to three 238 00:11:16,120 --> 00:11:20,079 Speaker 8: dollars or less nationwide on average, it's an opportunity for 239 00:11:20,240 --> 00:11:23,000 Speaker 8: the two campaigns to talk about other issues besides just 240 00:11:23,120 --> 00:11:25,840 Speaker 8: the economy, and we see abortion, immigration leading. 241 00:11:25,960 --> 00:11:28,400 Speaker 7: And then democracy in these suburbs is really critical. 242 00:11:28,760 --> 00:11:30,439 Speaker 2: And we had a summer suggesting that we may not 243 00:11:30,640 --> 00:11:35,040 Speaker 2: know the winner of the presidential race for days. Isn't 244 00:11:35,080 --> 00:11:37,640 Speaker 2: that in and of itself a problem for the US 245 00:11:38,000 --> 00:11:41,679 Speaker 2: should in our country, with our technology, be able to 246 00:11:41,800 --> 00:11:44,679 Speaker 2: know almost in real time kind of how the voting's going. 247 00:11:44,720 --> 00:11:46,880 Speaker 2: I just don't understand where it feels it feels like 248 00:11:46,920 --> 00:11:48,119 Speaker 2: our system is so antiquated. 249 00:11:49,320 --> 00:11:51,400 Speaker 8: I completely agree, and I think it's a great point 250 00:11:51,480 --> 00:11:54,760 Speaker 8: to make. Right now, Why can't we start counting ballots 251 00:11:54,800 --> 00:11:56,920 Speaker 8: the second that they start coming in? You know, I 252 00:11:57,040 --> 00:11:59,280 Speaker 8: think that's a little frustrating. So you have a state 253 00:11:59,400 --> 00:12:02,240 Speaker 8: like pennsylvani where all these poll workers and they have 254 00:12:02,440 --> 00:12:05,120 Speaker 8: so many this year that are you know, really doing 255 00:12:05,280 --> 00:12:08,640 Speaker 8: the large work. They're you know, they're early, they're expanding 256 00:12:08,760 --> 00:12:13,040 Speaker 8: voting hours, and they are you ready to put those 257 00:12:13,200 --> 00:12:16,520 Speaker 8: ballots through the machine to have them read. We should 258 00:12:16,720 --> 00:12:19,120 Speaker 8: definitely be capable of starting that early. They had the 259 00:12:19,160 --> 00:12:21,200 Speaker 8: opportunity in the last couple of years with all these 260 00:12:21,280 --> 00:12:25,680 Speaker 8: different refinements in the ballot process and collecting and changing 261 00:12:25,720 --> 00:12:28,120 Speaker 8: of laws like we've seen in Georgia, for example, they're 262 00:12:28,120 --> 00:12:31,080 Speaker 8: going to start reporting out different county data at eight pm, 263 00:12:31,200 --> 00:12:33,160 Speaker 8: which is going to be one of our first arbiters 264 00:12:33,240 --> 00:12:34,280 Speaker 8: of how the night is going. 265 00:12:34,880 --> 00:12:38,040 Speaker 7: But I completely agree. I wish they could move this along. 266 00:12:38,520 --> 00:12:38,720 Speaker 5: Yeah. 267 00:12:38,840 --> 00:12:41,280 Speaker 2: Interesting, I'm sure some kid in garage that in Palalatha 268 00:12:41,320 --> 00:12:43,040 Speaker 2: could come up the napp and like, you know, a day. 269 00:12:43,800 --> 00:12:45,880 Speaker 2: Henrietta Trez, thank you so much for joining us. Henriette. 270 00:12:45,880 --> 00:12:48,080 Speaker 2: It has been so helpful to us during this whole 271 00:12:48,200 --> 00:12:51,000 Speaker 2: election process. She's a managing partner and director of Economic 272 00:12:51,080 --> 00:12:54,600 Speaker 2: Policy and VATA Partners. She is down there in New Orleans, 273 00:12:54,640 --> 00:12:56,520 Speaker 2: I believe Louisiana's where she's Basically. 274 00:12:57,440 --> 00:13:01,280 Speaker 1: You're listening to the Bloomberg Intelligence part Catch us live 275 00:13:01,400 --> 00:13:04,760 Speaker 1: weekdays at ten am Eastern on Focarplay and enroud Otto 276 00:13:04,840 --> 00:13:07,719 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 277 00:13:07,840 --> 00:13:10,800 Speaker 1: get your podcasts, or watch us live on YouTube. 278 00:13:12,679 --> 00:13:15,800 Speaker 2: Damily Graffeo sitting in for Alex Steel on Pulse when 279 00:13:15,800 --> 00:13:18,840 Speaker 2: you were live here in our Bloomberg Interactive Broker's studio. 280 00:13:18,960 --> 00:13:23,400 Speaker 2: Complete coverage of this election throughout the day, markets, trading, hires, 281 00:13:23,440 --> 00:13:25,920 Speaker 2: John is just reporting. Let's check in with Jennifer Lawless. 282 00:13:26,080 --> 00:13:30,160 Speaker 2: She's a professor at the University of Virginia. Did you 283 00:13:30,320 --> 00:13:33,080 Speaker 2: arrange this? Is this you're doing? This was a pleasant 284 00:13:33,120 --> 00:13:37,200 Speaker 2: spri very good. Emily Graffeo was also a proud graduate 285 00:13:37,280 --> 00:13:40,839 Speaker 2: of the University of Virginia down in Charlottesville. Jennifer, what 286 00:13:40,880 --> 00:13:44,080 Speaker 2: are you looking for today? What should we are our listeners, 287 00:13:44,160 --> 00:13:46,959 Speaker 2: our viewers, what should they be paying attention to today? 288 00:13:48,840 --> 00:13:51,800 Speaker 9: Well, The most important thing is that every listener who 289 00:13:51,800 --> 00:13:54,439 Speaker 9: hasn't already cast a ballot go out and vote. And 290 00:13:54,679 --> 00:13:57,000 Speaker 9: looking at the length of those lines, just getting a 291 00:13:57,080 --> 00:13:59,920 Speaker 9: sense of the enthusiasm at the polling places, I think 292 00:14:00,200 --> 00:14:02,400 Speaker 9: will at least let people know whether this is going 293 00:14:02,480 --> 00:14:03,839 Speaker 9: to be a high turnout election or not. 294 00:14:04,360 --> 00:14:05,680 Speaker 7: But we're really not going to know. 295 00:14:05,720 --> 00:14:08,360 Speaker 9: Anything until this evening, when the polls close and the 296 00:14:08,480 --> 00:14:10,760 Speaker 9: early signs will be in North Carolina and Georgia. 297 00:14:11,760 --> 00:14:14,640 Speaker 4: What are we hearing so far? I guess how are 298 00:14:14,720 --> 00:14:18,520 Speaker 4: you understanding the closing messages from both candidates? I know 299 00:14:18,640 --> 00:14:22,480 Speaker 4: that Trump is set to speak at eleven am. 300 00:14:22,840 --> 00:14:25,680 Speaker 2: Perhaps it's uncertain, so we'll see. 301 00:14:25,880 --> 00:14:28,000 Speaker 4: So but what are we understanding right now? Professor Lawllace 302 00:14:28,040 --> 00:14:30,960 Speaker 4: about the closing messages from both candidates. 303 00:14:31,520 --> 00:14:33,600 Speaker 9: Well, it seems to me that the closing messages for 304 00:14:33,840 --> 00:14:37,040 Speaker 9: the Harris campaign are the messages that she's been conveying 305 00:14:37,080 --> 00:14:39,280 Speaker 9: for the last ninety or one hundred days. She's been 306 00:14:39,400 --> 00:14:42,200 Speaker 9: very disciplined and on script, and that's basically that it's 307 00:14:42,280 --> 00:14:45,480 Speaker 9: time to turn a new page. If people want new leadership, 308 00:14:45,520 --> 00:14:48,760 Speaker 9: if they want a new generation, if they want new policies. 309 00:14:49,120 --> 00:14:51,840 Speaker 9: Kamala Harris is the way forward, and Donald Trump is 310 00:14:51,920 --> 00:14:54,640 Speaker 9: basically trying to make the case that the Biden Harris 311 00:14:54,680 --> 00:14:57,200 Speaker 9: administration broke it and he can fix it. It's a 312 00:14:57,280 --> 00:14:59,600 Speaker 9: challenge for him, obviously, both because he has a hard 313 00:14:59,640 --> 00:15:03,440 Speaker 9: time stay on message, but also because he's been president already, 314 00:15:03,560 --> 00:15:06,280 Speaker 9: so he's trying to portray himself as the change candidate 315 00:15:06,560 --> 00:15:08,640 Speaker 9: and she's trying to portray him as the incumbent. 316 00:15:09,640 --> 00:15:13,160 Speaker 2: Jennifer, how long are we gonna have to wait, you 317 00:15:13,280 --> 00:15:16,840 Speaker 2: believe for the presidential election to be called? I mean, 318 00:15:16,920 --> 00:15:18,920 Speaker 2: this is going to be a dicey situation from what 319 00:15:19,080 --> 00:15:22,080 Speaker 2: we understand because of some of the mail inboundings, and 320 00:15:22,280 --> 00:15:23,520 Speaker 2: just because it's so close. 321 00:15:24,800 --> 00:15:28,640 Speaker 9: It's difficult to know. But if Harris performs well or 322 00:15:28,840 --> 00:15:31,920 Speaker 9: wins in North Carolina or Georgia, it's hard to see 323 00:15:31,960 --> 00:15:34,480 Speaker 9: a Trump victory, and then we would likely know early. 324 00:15:34,560 --> 00:15:35,920 Speaker 7: We would probably know by tomorrow. 325 00:15:36,400 --> 00:15:39,080 Speaker 9: If Donald Trump wins in North Carolina and Georgia, both 326 00:15:39,160 --> 00:15:41,960 Speaker 9: of which are states that he's been actively campaigning in 327 00:15:42,360 --> 00:15:45,120 Speaker 9: and Republicans typically win, then it could go on for 328 00:15:45,200 --> 00:15:47,120 Speaker 9: a lot longer because we're going to have to wait 329 00:15:47,200 --> 00:15:50,240 Speaker 9: for all of the counting in Pennsylvania and perhaps Arizona, 330 00:15:50,440 --> 00:15:53,280 Speaker 9: both of which are notoriously slow and don't start counting 331 00:15:53,360 --> 00:15:53,840 Speaker 9: until late. 332 00:15:55,400 --> 00:15:58,520 Speaker 4: You have written a number of books that have to 333 00:15:58,640 --> 00:16:02,360 Speaker 4: do with gender and politics, and I'm wondering, when you 334 00:16:02,440 --> 00:16:07,880 Speaker 4: look at this presidential race, to what extent has gender 335 00:16:08,040 --> 00:16:13,680 Speaker 4: played a role? Have you been surprised? I guess maybe 336 00:16:13,760 --> 00:16:18,440 Speaker 4: about the lack of gender roles. At least it seems 337 00:16:18,520 --> 00:16:22,720 Speaker 4: like Vice President Harris has not played up as much 338 00:16:23,120 --> 00:16:25,240 Speaker 4: that she is a woman running, and she has perhaps 339 00:16:25,280 --> 00:16:27,160 Speaker 4: brought up other issues a little bit more. But I'm 340 00:16:27,200 --> 00:16:29,640 Speaker 4: wondering what you think that's right. 341 00:16:29,960 --> 00:16:33,520 Speaker 9: Kamala Harris has not played into the breaking the glass ceiling. 342 00:16:33,640 --> 00:16:35,160 Speaker 9: She would be the first woman in the White House 343 00:16:35,240 --> 00:16:37,960 Speaker 9: narrative that we saw very prominently featured in the twenty 344 00:16:38,040 --> 00:16:41,920 Speaker 9: sixteen campaign of Hillary Clinton. But gender is still very 345 00:16:42,040 --> 00:16:45,120 Speaker 9: very significant this selection cycle. Not only do we have 346 00:16:45,160 --> 00:16:47,640 Speaker 9: a substantial gender gap where women are more likely than 347 00:16:47,720 --> 00:16:50,520 Speaker 9: men to prefer Harris and men are significantly more likely 348 00:16:50,640 --> 00:16:53,080 Speaker 9: than women to prefer Trump, but the issues on the 349 00:16:53,120 --> 00:16:57,360 Speaker 9: agenda have also been speaking specifically to gendered roles in 350 00:16:57,480 --> 00:17:00,400 Speaker 9: gendered concerns, and so the Harris campaign, for a example, 351 00:17:00,480 --> 00:17:04,040 Speaker 9: has really been highlighting reproductive rights and freedom and abortion 352 00:17:04,240 --> 00:17:07,479 Speaker 9: rights and what a Trump administration would mean for women's 353 00:17:07,520 --> 00:17:10,919 Speaker 9: bodily autonomy and the Trump administer The Trump campaign has 354 00:17:11,000 --> 00:17:14,399 Speaker 9: basically seeded a lot of those female swing voters and 355 00:17:14,480 --> 00:17:18,240 Speaker 9: has tried very very hard to motivate young men, especially 356 00:17:18,320 --> 00:17:20,760 Speaker 9: those between the ages of eighteen and twenty nine, to 357 00:17:20,880 --> 00:17:23,760 Speaker 9: come out and vote under this threat of their country 358 00:17:23,800 --> 00:17:26,760 Speaker 9: being taken away from them. So, even though the sex 359 00:17:26,800 --> 00:17:29,359 Speaker 9: of the candidate hasn't been as prominently featured in the 360 00:17:29,400 --> 00:17:33,160 Speaker 9: campaign narratives, the issues and the vuying for male versus 361 00:17:33,240 --> 00:17:35,280 Speaker 9: female voters has been on high display. 362 00:17:36,480 --> 00:17:40,399 Speaker 2: Jennifer Below the presidential election down ballot, what are the 363 00:17:40,480 --> 00:17:41,119 Speaker 2: key races for you? 364 00:17:42,800 --> 00:17:46,320 Speaker 9: The key Senate races to watch are John Tester in Montana. 365 00:17:46,400 --> 00:17:48,959 Speaker 9: If he somehow manages to hold on, then it's going 366 00:17:49,040 --> 00:17:51,600 Speaker 9: to be a very good night for the Democrats and 367 00:17:51,840 --> 00:17:55,280 Speaker 9: Colin already vying against Ted Cruz in Texas. If already 368 00:17:55,320 --> 00:17:57,840 Speaker 9: manages to knock out Ted Cruz, that would be the 369 00:17:57,920 --> 00:18:00,440 Speaker 9: shocker of the night. It's likely that the it will 370 00:18:00,480 --> 00:18:03,080 Speaker 9: go Republican, but there are a couple of indicators that 371 00:18:03,200 --> 00:18:05,840 Speaker 9: could be harbingers of success for Democrats. 372 00:18:08,200 --> 00:18:11,919 Speaker 4: So what is the What does a professor of politics 373 00:18:12,680 --> 00:18:15,760 Speaker 4: at the University of Virginia do an election night? Do 374 00:18:15,840 --> 00:18:19,560 Speaker 4: you stay up all night and hope that a decision 375 00:18:19,960 --> 00:18:23,240 Speaker 4: comes in or do you just go to sleep and 376 00:18:23,359 --> 00:18:25,320 Speaker 4: know that this is going to take a while because 377 00:18:25,320 --> 00:18:27,719 Speaker 4: I'm wondering, like what we should what we should all 378 00:18:27,800 --> 00:18:28,120 Speaker 4: be doing? 379 00:18:29,600 --> 00:18:32,680 Speaker 9: Well, I committed to you guys for five ten am 380 00:18:32,720 --> 00:18:35,240 Speaker 9: tomorrow morning, so a lot of sleep will not be had. 381 00:18:36,600 --> 00:18:40,399 Speaker 9: But yeah, I mean it's basically the election day is 382 00:18:41,040 --> 00:18:42,760 Speaker 9: where it all comes to an end. There's nothing to 383 00:18:42,800 --> 00:18:45,199 Speaker 9: do anymore, there's nothing to watch, there are no events, 384 00:18:45,240 --> 00:18:48,440 Speaker 9: there are no final you know, strategies to assess. This 385 00:18:48,600 --> 00:18:51,320 Speaker 9: is it, and so once the returns start coming in, 386 00:18:51,560 --> 00:18:53,840 Speaker 9: it's just a matter of watching and trying to analyze 387 00:18:53,880 --> 00:18:56,280 Speaker 9: the results of the exit polls that are released and 388 00:18:56,440 --> 00:18:58,720 Speaker 9: getting a better sense of where the numbers are. But 389 00:18:59,160 --> 00:19:00,959 Speaker 9: if we look back to twenty twenty, I don't think 390 00:19:01,000 --> 00:19:04,280 Speaker 9: I slept for five days. The winner wasn't announced until Saturday. 391 00:19:04,359 --> 00:19:06,560 Speaker 9: So it's just a matter of watching those ticking screens 392 00:19:06,600 --> 00:19:08,960 Speaker 9: the same way that everybody else does and trying to 393 00:19:09,000 --> 00:19:11,200 Speaker 9: figure out what's going on. But I would tell people 394 00:19:11,320 --> 00:19:14,960 Speaker 9: that you know, if Harris doesn't win North Carolina or 395 00:19:15,000 --> 00:19:17,440 Speaker 9: Georgia early, they can go to sleep because we're not 396 00:19:17,520 --> 00:19:18,240 Speaker 9: going to know tonight. 397 00:19:18,520 --> 00:19:20,560 Speaker 2: All right, Jennifer, thank you so much for joining us. 398 00:19:20,800 --> 00:19:24,199 Speaker 2: Jennifer Lawless, she's a professor at the University of Virginia. 399 00:19:24,280 --> 00:19:26,200 Speaker 2: Joining us from Charlottesville via zoom. 400 00:19:27,480 --> 00:19:31,320 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 401 00:19:31,440 --> 00:19:34,359 Speaker 1: weekdays at ten am Eastern on applecar. 402 00:19:34,000 --> 00:19:36,720 Speaker 6: Play and Android Auto with the Bloomberg Business Act. 403 00:19:36,880 --> 00:19:39,679 Speaker 1: You can also listen live on Amazon Alexa from our 404 00:19:39,760 --> 00:19:44,119 Speaker 1: flagship New York station, Just say Alexa Play Bloomberg eleven thirty. 405 00:19:45,600 --> 00:19:48,000 Speaker 2: Yeah, Mylikafreo sitting in for Alex steel On Paul Sweeneyer 406 00:19:48,040 --> 00:19:50,159 Speaker 2: live here from a Bloomberg Interactive Brokers studio in New 407 00:19:50,200 --> 00:19:52,920 Speaker 2: York City to our world wide audience streaming live on 408 00:19:53,000 --> 00:19:56,840 Speaker 2: YouTube as well. All right, Swing States, Pennsylvania, Michigan, Wisconsin, 409 00:19:56,960 --> 00:19:59,600 Speaker 2: North Carolina, Arizona, Nevada. Do we just look at the 410 00:19:59,640 --> 00:20:02,400 Speaker 2: state or do you drill down even more to maybe 411 00:20:02,760 --> 00:20:04,960 Speaker 2: local towns or local counties and to see how this 412 00:20:05,000 --> 00:20:06,320 Speaker 2: thing is going to go. I have no idea what 413 00:20:06,359 --> 00:20:10,000 Speaker 2: our next guest does. David Paleologus, director of the Political 414 00:20:10,160 --> 00:20:13,880 Speaker 2: Research Center at Suffolk University, joining us from Boston, mass 415 00:20:14,040 --> 00:20:17,679 Speaker 2: via that zoom thing. David, again, we know the swing states. 416 00:20:18,119 --> 00:20:20,720 Speaker 2: Do you go even more granular to look at certain 417 00:20:20,800 --> 00:20:23,119 Speaker 2: parts of the states, certain towns? How do you do it? 418 00:20:24,040 --> 00:20:27,800 Speaker 10: Yeah, we do, and we've gone mainstream with the weather 419 00:20:28,000 --> 00:20:32,400 Speaker 10: model of the bellweathers are areas that correctly predict where 420 00:20:32,440 --> 00:20:35,120 Speaker 10: the statewide vote is going to go. I just tweeted 421 00:20:35,160 --> 00:20:37,720 Speaker 10: a list in the swing states, so what counties or 422 00:20:38,359 --> 00:20:41,360 Speaker 10: cities to take a look at. But the first three 423 00:20:41,440 --> 00:20:46,040 Speaker 10: states that you mentioned, Paul, are really the ground zero Pennsylvania, Michigan, 424 00:20:46,160 --> 00:20:49,600 Speaker 10: and Wisconsin. According to a lot of the aggregator models 425 00:20:50,359 --> 00:20:55,760 Speaker 10: they have wascon they have Georgia, Arizona, and North Carolina 426 00:20:55,800 --> 00:20:59,080 Speaker 10: attacking toward Trump. So that puts a lot more pressure 427 00:20:59,160 --> 00:21:02,600 Speaker 10: on those three Russ spelt states. And within those states, 428 00:21:02,640 --> 00:21:05,119 Speaker 10: we're looking at specific counties, as. 429 00:21:05,000 --> 00:21:10,439 Speaker 4: You say, and what makes a county worthy of an 430 00:21:10,600 --> 00:21:15,840 Speaker 4: extra eye. I know that you've written Northampton, Erie in Pennsylvania, 431 00:21:16,320 --> 00:21:21,520 Speaker 4: Kent in Michigan, What specifically about those counties makes them 432 00:21:21,680 --> 00:21:23,480 Speaker 4: worthy of watching so closely? 433 00:21:24,560 --> 00:21:28,080 Speaker 10: So it's a proprietary model, but Generally speaking, what we 434 00:21:28,200 --> 00:21:33,440 Speaker 10: look for is, does the county flip when the state 435 00:21:33,520 --> 00:21:37,560 Speaker 10: flips or vice versa from Democrat to Republican back to 436 00:21:37,680 --> 00:21:42,600 Speaker 10: Democrat A and B. When it does flip, does the 437 00:21:43,200 --> 00:21:49,680 Speaker 10: county vote close to as close to perfect accurately reflect 438 00:21:49,760 --> 00:21:53,560 Speaker 10: what the actual percentages were when the flip happened. So 439 00:21:54,000 --> 00:21:56,760 Speaker 10: it has to not only just flip. It can't flip 440 00:21:56,920 --> 00:21:59,720 Speaker 10: sixty forty and it'll be a two percent flip on 441 00:21:59,760 --> 00:22:02,560 Speaker 10: the state. It has to be if it flips and 442 00:22:02,640 --> 00:22:05,200 Speaker 10: it shows a candidate winning by three or four, the 443 00:22:05,280 --> 00:22:08,480 Speaker 10: state should show the same. So, and there are a 444 00:22:08,560 --> 00:22:11,760 Speaker 10: bunch of other indices that we use in our screening process. 445 00:22:12,680 --> 00:22:15,800 Speaker 10: But those counties, when you're watching tonight and you're hovering 446 00:22:15,840 --> 00:22:18,360 Speaker 10: your mouse over the map and you're looking at your 447 00:22:18,400 --> 00:22:21,040 Speaker 10: own sort of prediction of how the states are going 448 00:22:21,080 --> 00:22:25,680 Speaker 10: to vote, Northampton and Erie have been remarkably prescient in 449 00:22:25,800 --> 00:22:29,760 Speaker 10: terms of predicting the state wide outcomes in Pennsylvania, as 450 00:22:30,280 --> 00:22:34,520 Speaker 10: has Kent and Door County in Michigan and Wisconsin, respectively. 451 00:22:35,200 --> 00:22:39,920 Speaker 2: David our last guest, had the prediction I guess Harris 452 00:22:39,960 --> 00:22:42,880 Speaker 2: two and seventy electoral votes Trump two at sixty eight. 453 00:22:43,320 --> 00:22:46,240 Speaker 2: Do you guys Suffolk have a similar type of prediction 454 00:22:46,480 --> 00:22:47,439 Speaker 2: or you're none in that business. 455 00:22:48,119 --> 00:22:52,040 Speaker 10: So we don't model. We do poll and we give 456 00:22:52,080 --> 00:22:55,200 Speaker 10: our information out to the public and it's consumed by 457 00:22:55,800 --> 00:23:00,000 Speaker 10: aggregators like Nate Silver and five thirty eight and Tie 458 00:23:00,240 --> 00:23:03,560 Speaker 10: Cook and Larry Sabateow and they take our information with 459 00:23:03,720 --> 00:23:07,200 Speaker 10: others and they run their own models. But it's a 460 00:23:07,280 --> 00:23:09,680 Speaker 10: really close race, you know. And I can tell you 461 00:23:09,800 --> 00:23:12,520 Speaker 10: that just by virtue of polling some of these bell 462 00:23:12,560 --> 00:23:16,560 Speaker 10: weather areas. And what I'll be looking at though, is 463 00:23:16,960 --> 00:23:19,159 Speaker 10: maybe a little bit different. I'm gonna be looking at 464 00:23:19,200 --> 00:23:21,919 Speaker 10: New Hampshire first off, because we're gonna get New Hampshire 465 00:23:21,960 --> 00:23:25,960 Speaker 10: numbers fairly quickly, and it's got an evenly balanced party affiliation. 466 00:23:27,040 --> 00:23:29,800 Speaker 10: And in Biden one on New Hampshire in twenty twenty 467 00:23:29,880 --> 00:23:32,719 Speaker 10: by seven and a half points. Kamala Harris wins by 468 00:23:32,760 --> 00:23:36,960 Speaker 10: between six and nine points, no need to worry about 469 00:23:37,040 --> 00:23:40,520 Speaker 10: New Hampshire. But if she wins by twelve or ten 470 00:23:40,880 --> 00:23:44,879 Speaker 10: in New Hampshire, that signals to me that independents who 471 00:23:44,920 --> 00:23:47,760 Speaker 10: really make up the undecided, it's a swinging blue and 472 00:23:47,880 --> 00:23:52,399 Speaker 10: you could see that reverberate across the country. If Harris 473 00:23:52,520 --> 00:23:56,080 Speaker 10: only wins by one, two or three, will loses New Hampshire. 474 00:23:56,359 --> 00:23:58,160 Speaker 10: I think the opposite could be to it. You could 475 00:23:58,160 --> 00:24:01,119 Speaker 10: see Trump carrying in some of those other states. So 476 00:24:01,160 --> 00:24:02,920 Speaker 10: I'm going to keep a little bit of an eye 477 00:24:03,880 --> 00:24:06,320 Speaker 10: on New Hampshire and how those results are coming in. 478 00:24:06,440 --> 00:24:09,680 Speaker 10: And I've also listed a couple of the bellwether towns 479 00:24:10,880 --> 00:24:14,600 Speaker 10: in New Hampshire. Hampton is one of them in Jaffrey, 480 00:24:14,680 --> 00:24:15,240 Speaker 10: New Hampshire. 481 00:24:16,720 --> 00:24:19,520 Speaker 4: I know it's so hard to tell right now, but 482 00:24:19,760 --> 00:24:23,640 Speaker 4: what is your sense for just how long the counting 483 00:24:24,000 --> 00:24:26,480 Speaker 4: is going to take and how many days we'll have 484 00:24:26,640 --> 00:24:29,720 Speaker 4: to wait to see when these results come out. 485 00:24:30,600 --> 00:24:32,720 Speaker 10: Maybe I'm just an optimist, but I think we're going 486 00:24:32,760 --> 00:24:36,920 Speaker 10: to be pleasantly surprised. I think, you know, there's a 487 00:24:37,000 --> 00:24:40,760 Speaker 10: lot of trusts in our national poll of local precinct warden. 488 00:24:41,480 --> 00:24:43,879 Speaker 10: People have a lot of trust in their own local 489 00:24:44,280 --> 00:24:49,240 Speaker 10: community's ability to process and count votes, and I think 490 00:24:49,600 --> 00:24:52,560 Speaker 10: they don't want to lose that trust, and so I 491 00:24:52,640 --> 00:24:55,480 Speaker 10: think they're taking great pains to try and improve the 492 00:24:55,520 --> 00:24:59,159 Speaker 10: efficiency of their own operations. They improved a little bit 493 00:24:59,200 --> 00:25:00,920 Speaker 10: in twenty twenty two. I think they'll do a little 494 00:25:00,920 --> 00:25:05,440 Speaker 10: bit better. I hope it doesn't carry on for days 495 00:25:05,480 --> 00:25:09,640 Speaker 10: and weeks, and I think, you know, I think we're 496 00:25:09,680 --> 00:25:12,840 Speaker 10: going to have at least due diligence on the part 497 00:25:12,920 --> 00:25:16,920 Speaker 10: of the counting process as best we can. So I'm 498 00:25:16,960 --> 00:25:20,080 Speaker 10: hopeful that it will only be a day tops or two, 499 00:25:20,720 --> 00:25:21,399 Speaker 10: not weeks. 500 00:25:22,320 --> 00:25:24,359 Speaker 2: David, thank you so much for joining us. Appreciate getting 501 00:25:24,640 --> 00:25:28,560 Speaker 2: your perspective. David Palio Logos, director of the Political Research 502 00:25:28,640 --> 00:25:32,479 Speaker 2: Center at Suffolk University. Again, they're one of the sources 503 00:25:32,560 --> 00:25:34,359 Speaker 2: for a lot of this polling data for the folks 504 00:25:34,400 --> 00:25:38,680 Speaker 2: that are in the business of making predictions. So we'll 505 00:25:38,680 --> 00:25:41,040 Speaker 2: see how it goes. But again, the message has been 506 00:25:41,160 --> 00:25:44,159 Speaker 2: very clear, too close to call here, so I'll be 507 00:25:44,200 --> 00:25:46,359 Speaker 2: interested to see how the networks handle it this evening 508 00:25:46,440 --> 00:25:48,399 Speaker 2: in terms of kind of what we've been you know, 509 00:25:48,440 --> 00:25:49,800 Speaker 2: I kind of grew up with you kind of knew 510 00:25:49,800 --> 00:25:51,600 Speaker 2: this stuff by nine or ten o'clock and networks were 511 00:25:51,640 --> 00:25:53,800 Speaker 2: making the call, and I'm not sure we're in that 512 00:25:53,920 --> 00:25:54,600 Speaker 2: environment this year. 513 00:25:54,760 --> 00:25:58,960 Speaker 4: It's so interesting to see just how carefully these pollsters 514 00:25:59,400 --> 00:26:03,920 Speaker 4: and these as data scientists zoom in to counties. Yeah, 515 00:26:03,960 --> 00:26:05,040 Speaker 4: it's just really incredible, and. 516 00:26:05,080 --> 00:26:07,520 Speaker 2: It's also incredible is I don't know. I have to 517 00:26:07,560 --> 00:26:09,080 Speaker 2: see how accurate they are or not. 518 00:26:09,520 --> 00:26:14,960 Speaker 1: Coming forward, you're listening to the Bloomberg Intelligence Podcast. Catch 519 00:26:15,040 --> 00:26:18,480 Speaker 1: us live weekdays at ten am Eastern on applecar. 520 00:26:18,119 --> 00:26:20,840 Speaker 6: Play and Android Auto with the Bloomberg Business app. 521 00:26:21,000 --> 00:26:23,800 Speaker 1: You can also listen live on Amazon Alexa from our 522 00:26:23,880 --> 00:26:28,240 Speaker 1: flagship New York station Just say Alexa playing Bloomberg eleven thirty. 523 00:26:30,119 --> 00:26:32,320 Speaker 2: It is Emily Grafoe sitting in for Alex Steel. I'm 524 00:26:32,320 --> 00:26:34,320 Speaker 2: Paul Sweeney. You're live here in our Bloomberg Interactive Brooker 525 00:26:34,359 --> 00:26:36,760 Speaker 2: Studio and our streaming live on YouTube as well as 526 00:26:36,760 --> 00:26:39,360 Speaker 2: to check us out there at Bloomberg Podcast is where 527 00:26:39,359 --> 00:26:42,800 Speaker 2: you can go search for us. You know, every cycle, 528 00:26:42,880 --> 00:26:45,479 Speaker 2: every election cycle, seems to one of the key key 529 00:26:45,560 --> 00:26:48,200 Speaker 2: issues is always it's the economy. You know, focus on 530 00:26:48,600 --> 00:26:50,159 Speaker 2: the economy. Are you better off now than you were 531 00:26:50,200 --> 00:26:52,119 Speaker 2: four years ago? And so on and so forth. Our 532 00:26:52,160 --> 00:26:54,280 Speaker 2: next guest thinks about that stuff as well. Christopher Smart, 533 00:26:54,320 --> 00:26:57,680 Speaker 2: managing partner in our Growth group and former Special Assistant 534 00:26:57,720 --> 00:27:01,720 Speaker 2: to the President for International Economics, join us from Boston, Massachusetts, 535 00:27:01,800 --> 00:27:05,400 Speaker 2: via that Zoom thing. Christopher, how again too close to call? 536 00:27:05,480 --> 00:27:09,080 Speaker 2: We get all that how are you kind of framing 537 00:27:09,119 --> 00:27:11,920 Speaker 2: out this election and kind of the risk and opportunities 538 00:27:12,200 --> 00:27:13,920 Speaker 2: just from an economic policy perspective. 539 00:27:16,600 --> 00:27:19,560 Speaker 11: Well, I think, as you were mentioning earlier, the market 540 00:27:20,240 --> 00:27:23,520 Speaker 11: really does focus also, by the way, on the economics. 541 00:27:23,920 --> 00:27:27,760 Speaker 11: And weirdly, as all of our political tools to predict 542 00:27:27,760 --> 00:27:30,159 Speaker 11: the outcome of this election seem to be failing us today, 543 00:27:31,359 --> 00:27:34,639 Speaker 11: the economic data seems like it's actually painting a pretty 544 00:27:34,800 --> 00:27:35,679 Speaker 11: consistent picture. 545 00:27:36,160 --> 00:27:37,200 Speaker 5: Good growth, low. 546 00:27:37,119 --> 00:27:41,960 Speaker 11: Unemployment, inflation coming down. Rates will find out Thursday, but 547 00:27:42,640 --> 00:27:44,959 Speaker 11: money likely to become cheaper, and that I think, more 548 00:27:45,040 --> 00:27:47,000 Speaker 11: than anything, explains what's going on in. 549 00:27:47,080 --> 00:27:48,080 Speaker 5: The market overall. 550 00:27:48,600 --> 00:27:50,399 Speaker 11: I think what's also a little bit strange is that, 551 00:27:50,880 --> 00:27:53,159 Speaker 11: you know, in one way, we don't know what's going 552 00:27:53,200 --> 00:27:56,480 Speaker 11: to happen tomorrow or tonight, But in another way, neither 553 00:27:56,520 --> 00:27:58,720 Speaker 11: outcome is going to be a huge surprise for the market, 554 00:27:58,760 --> 00:28:01,119 Speaker 11: the way it was, for example, in twenty sixteen when 555 00:28:01,160 --> 00:28:03,600 Speaker 11: President Trump first won against Hillary Clinton. 556 00:28:04,000 --> 00:28:06,040 Speaker 5: And so I guess, you know, with some. 557 00:28:08,080 --> 00:28:10,040 Speaker 11: Certainty about who the next president is going to be, 558 00:28:10,160 --> 00:28:12,280 Speaker 11: we hope we find that out tonight tomorrow. 559 00:28:14,119 --> 00:28:16,600 Speaker 5: That should lead the market to rally a little bit. 560 00:28:16,680 --> 00:28:18,760 Speaker 11: But I'm not sure we could expect a big move 561 00:28:18,840 --> 00:28:21,320 Speaker 11: one way or the other, except in some of these 562 00:28:21,440 --> 00:28:25,639 Speaker 11: key so called Trump trades, either rising or falling depending 563 00:28:25,680 --> 00:28:26,199 Speaker 11: on the outcome. 564 00:28:27,119 --> 00:28:30,680 Speaker 4: Christopher, to what extent do you think prediction markets and 565 00:28:30,800 --> 00:28:35,080 Speaker 4: I guess the rise of betting on the outcome of 566 00:28:35,200 --> 00:28:40,600 Speaker 4: the election have somehow changed this election versus what we 567 00:28:40,680 --> 00:28:44,400 Speaker 4: have seen in prior races. What role have those prediction 568 00:28:44,520 --> 00:28:45,239 Speaker 4: markets played here? 569 00:28:47,840 --> 00:28:49,520 Speaker 11: I think that's a great question, and I'm not sure 570 00:28:49,520 --> 00:28:51,320 Speaker 11: I have a good answer yet. I mean, I think 571 00:28:51,400 --> 00:28:53,560 Speaker 11: we need to sort of see these markets develop over 572 00:28:54,520 --> 00:28:55,520 Speaker 11: a couple of cycles. 573 00:28:56,280 --> 00:29:00,400 Speaker 5: I'm not sure I believe you know that they are 574 00:29:00,720 --> 00:29:01,920 Speaker 5: great predictors of the outcome. 575 00:29:01,960 --> 00:29:04,120 Speaker 11: I mean, you've seen actually them moving with the polls 576 00:29:04,240 --> 00:29:07,880 Speaker 11: to some extent as President Trump's momentum seems to have 577 00:29:07,960 --> 00:29:08,680 Speaker 11: flagged of light. 578 00:29:08,840 --> 00:29:10,560 Speaker 5: You've seen some of those things tighten. 579 00:29:11,160 --> 00:29:13,960 Speaker 11: You've seen the bitcoin trade come off except for today, 580 00:29:14,520 --> 00:29:17,800 Speaker 11: you've seen the peso bounce a little bit as Vice 581 00:29:17,840 --> 00:29:21,120 Speaker 11: President Harris's odds appear to be improving in the polls. 582 00:29:21,680 --> 00:29:23,800 Speaker 11: So I think we'll be looking at those markets more 583 00:29:23,840 --> 00:29:27,000 Speaker 11: closely in terms of how deep they are, who's participating, 584 00:29:27,400 --> 00:29:29,400 Speaker 11: who's got the really big bets, on are they big 585 00:29:29,480 --> 00:29:33,360 Speaker 11: enough to actually move those numbers? But I think they're 586 00:29:33,760 --> 00:29:37,120 Speaker 11: kind of interesting, but maybe not gonna move a lot 587 00:29:37,200 --> 00:29:38,240 Speaker 11: of money one way or the other. 588 00:29:39,640 --> 00:29:42,280 Speaker 2: Chris, I hear a lot about the Trump trade. Is 589 00:29:42,320 --> 00:29:44,400 Speaker 2: that anything more than I do know? Long the dollar 590 00:29:44,520 --> 00:29:47,200 Speaker 2: short bonds? Is that a reasonable way to think about 591 00:29:47,280 --> 00:29:48,760 Speaker 2: or is a more nuanced than that? 592 00:29:49,520 --> 00:29:52,640 Speaker 5: I think that's very well, it's more nuanced. 593 00:29:52,720 --> 00:29:55,840 Speaker 11: And when you dig down into clean energy stocks versus 594 00:29:55,920 --> 00:29:59,440 Speaker 11: oil stocks, when you look at, for example, retailers that 595 00:29:59,480 --> 00:30:04,320 Speaker 11: are very sensitive to tariffs, they are they are the 596 00:30:04,360 --> 00:30:07,560 Speaker 11: anti Trump trade versus banks that are probably less sensitive 597 00:30:07,560 --> 00:30:09,360 Speaker 11: to tariffs and maybe hoping. 598 00:30:09,160 --> 00:30:10,080 Speaker 5: For some deregulation. 599 00:30:10,440 --> 00:30:13,240 Speaker 11: So within certain sectors, I think you get a differentiation, 600 00:30:13,360 --> 00:30:15,840 Speaker 11: But I think overall there is a sense that a 601 00:30:15,920 --> 00:30:20,480 Speaker 11: Trump presidency will, ironically for Republicans over the past number 602 00:30:20,480 --> 00:30:28,200 Speaker 11: of years, be the less the less fiscal hawkish administration. Uh. 603 00:30:28,440 --> 00:30:30,960 Speaker 11: And so that is a trade where you know, if 604 00:30:31,000 --> 00:30:34,680 Speaker 11: he wins, the expectation is more inflation, a bigger budget deficit, 605 00:30:35,040 --> 00:30:38,360 Speaker 11: maybe higher tariffs with I'm sure higher prices with tariffs, 606 00:30:38,800 --> 00:30:42,120 Speaker 11: and a crack down on immigration. That I think is 607 00:30:42,200 --> 00:30:45,640 Speaker 11: what what captures it all in terms of what you're 608 00:30:45,680 --> 00:30:49,560 Speaker 11: seeing in bond yields as well as maybe stock prices. 609 00:30:50,560 --> 00:30:54,120 Speaker 4: How much do you anticipate the f o MC meeting 610 00:30:54,200 --> 00:30:57,240 Speaker 4: in the in the FED decision on Thursday to drive 611 00:30:57,440 --> 00:31:01,520 Speaker 4: markets when it comes during you know, such a pivotal 612 00:31:01,600 --> 00:31:05,360 Speaker 4: week for the future of the US presidency. 613 00:31:06,680 --> 00:31:08,640 Speaker 11: Well, I think a lot of us have forgotten that 614 00:31:08,760 --> 00:31:12,840 Speaker 11: there was an f MC meeting this week. With all 615 00:31:13,040 --> 00:31:15,480 Speaker 11: apologies to Jerum Powell, he may appreciate the fact that 616 00:31:15,600 --> 00:31:16,800 Speaker 11: the spotlight. 617 00:31:16,440 --> 00:31:18,760 Speaker 5: Won't be so glaring on him on Thursday. 618 00:31:19,600 --> 00:31:21,760 Speaker 11: I think the FED has done an extraordinary job, through 619 00:31:21,840 --> 00:31:25,200 Speaker 11: an election cycle, through a very partisan period in our 620 00:31:25,400 --> 00:31:29,800 Speaker 11: in our in our history, to really focus on its 621 00:31:29,840 --> 00:31:32,800 Speaker 11: own knitting, really focus on the data, really focus on, 622 00:31:33,080 --> 00:31:35,160 Speaker 11: you know, when it feels it can. 623 00:31:35,200 --> 00:31:40,160 Speaker 5: Bring price interest rates down and. 624 00:31:40,920 --> 00:31:43,440 Speaker 11: Other than a few partisan voices on one side or 625 00:31:43,480 --> 00:31:45,800 Speaker 11: the other, I think the markets don't believe that this 626 00:31:46,040 --> 00:31:49,720 Speaker 11: is a partisan move on their part, and I think 627 00:31:49,760 --> 00:31:52,160 Speaker 11: that's why they have, you know, really tried to make 628 00:31:52,200 --> 00:31:54,520 Speaker 11: sure they are delivering that message. 629 00:31:54,520 --> 00:31:55,720 Speaker 5: And I think that's what most people believe. 630 00:31:56,720 --> 00:31:58,760 Speaker 2: All right, christerpher thank you so much. We appreciate that. 631 00:31:58,840 --> 00:32:01,360 Speaker 2: Christopher Smart, he is a managing partner at Our Growth 632 00:32:01,400 --> 00:32:04,320 Speaker 2: Group and a former Special Assistant to the President for 633 00:32:04,520 --> 00:32:06,840 Speaker 2: International economics, joining us from Boston. 634 00:32:07,280 --> 00:32:11,760 Speaker 1: This is the Bloomberg Intelligence Podcast, available on apples, Spotify, 635 00:32:12,000 --> 00:32:15,640 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 636 00:32:15,760 --> 00:32:18,720 Speaker 1: ten am to noon Eastern on Bloomberg dot com, the 637 00:32:18,840 --> 00:32:22,240 Speaker 1: iHeartRadio app tune In, and the Bloomberg Business app. You 638 00:32:22,320 --> 00:32:25,480 Speaker 1: can also watch us live every weekday on YouTube and 639 00:32:25,680 --> 00:32:27,200 Speaker 1: always on the Bloomberg terminal.