1 00:00:01,800 --> 00:00:04,920 Speaker 1: Welcome to the Tutor Dixon Podcast. I have Larry Kudlow 2 00:00:05,000 --> 00:00:08,200 Speaker 1: with me. He is the former economic policy advisor to 3 00:00:08,240 --> 00:00:11,040 Speaker 1: President Trump and you can catch him every weekday at 4 00:00:11,080 --> 00:00:14,720 Speaker 1: four pm Eastern on his Fox Business show. Larry, thank 5 00:00:14,720 --> 00:00:16,840 Speaker 1: you so much for joining me today. Obviously, this is 6 00:00:16,840 --> 00:00:20,200 Speaker 1: a big deal. We have seen a landslide win for 7 00:00:20,280 --> 00:00:22,840 Speaker 1: Donald Trump. And I was just before we got on, 8 00:00:22,920 --> 00:00:24,560 Speaker 1: I was just saying, I wanted to go over what 9 00:00:24,640 --> 00:00:28,480 Speaker 1: you think that meant for people, what people were feeling 10 00:00:28,480 --> 00:00:30,720 Speaker 1: in the economy, what they will feel going forward. 11 00:00:32,000 --> 00:00:40,640 Speaker 2: Well, you know, I think the Democrats, kamalaw Democrats completely 12 00:00:40,760 --> 00:00:48,839 Speaker 2: miss understood the electorate. So they thought attacking Trump and 13 00:00:48,920 --> 00:00:55,560 Speaker 2: calling him names, you know, fascist and Hitler and garbage 14 00:00:55,640 --> 00:00:56,360 Speaker 2: and all that. 15 00:00:56,360 --> 00:00:58,760 Speaker 3: They thought that was going to be a great idea. 16 00:00:58,960 --> 00:01:03,000 Speaker 2: Meanwhile, the rest of the country was worried about open 17 00:01:03,040 --> 00:01:08,880 Speaker 2: border illegal immigration and crime and the economy and the 18 00:01:08,920 --> 00:01:15,080 Speaker 2: affordability crisis. So Trump stayed on message. You know, he's 19 00:01:15,160 --> 00:01:18,360 Speaker 2: become a real policy wonk. I talked to him all 20 00:01:18,440 --> 00:01:21,839 Speaker 2: the time. He's a real policy guy. You know, tax 21 00:01:21,880 --> 00:01:26,560 Speaker 2: cuts and deregulation and drill baby drill, liquid gold and 22 00:01:28,840 --> 00:01:33,039 Speaker 2: pro growth policies, and she's out there calling him names 23 00:01:33,959 --> 00:01:37,840 Speaker 2: and it just utterly failed. And so you know, it's 24 00:01:37,959 --> 00:01:41,680 Speaker 2: a tremendous victory. He picked up his coalition. I mean, 25 00:01:41,720 --> 00:01:46,920 Speaker 2: you know, the strategy from day one was a working 26 00:01:47,080 --> 00:01:58,560 Speaker 2: class Middle America populist coalition, and he scored so heavily Blacks, Hispanics, 27 00:01:59,440 --> 00:02:04,040 Speaker 2: young people particularly. He also closed the gender gap quite 28 00:02:04,040 --> 00:02:06,880 Speaker 2: a bit. And that you know, the issues were the 29 00:02:06,920 --> 00:02:12,080 Speaker 2: economy and the border. So he had a fabulous landslide. 30 00:02:13,080 --> 00:02:16,919 Speaker 2: He ended the so called blue wall in the Midwest. 31 00:02:18,000 --> 00:02:20,280 Speaker 2: He did very well, by the way, in blue states 32 00:02:20,360 --> 00:02:23,160 Speaker 2: like New York and New Jersey very well. I'm proudly 33 00:02:23,360 --> 00:02:25,560 Speaker 2: you only lost Jersey by four points. 34 00:02:25,960 --> 00:02:28,400 Speaker 3: That's crazy, which is very cool. 35 00:02:29,760 --> 00:02:33,360 Speaker 2: You know, in New York, I spend my time in 36 00:02:33,400 --> 00:02:36,400 Speaker 2: the city during the week because obviously I work at Fox. 37 00:02:36,880 --> 00:02:39,119 Speaker 2: He cut the margins in New York quite a bit. 38 00:02:39,919 --> 00:02:41,960 Speaker 1: Do you think this can happen again? Do you think 39 00:02:42,000 --> 00:02:43,839 Speaker 1: this is only a Trump thing? Or do you think 40 00:02:43,840 --> 00:02:46,640 Speaker 1: that this can carry on? Are Republicans in a position 41 00:02:46,680 --> 00:02:50,440 Speaker 1: where they understand it and they will continue it, well. 42 00:02:50,560 --> 00:02:51,600 Speaker 3: I would guess so. 43 00:02:51,720 --> 00:02:58,360 Speaker 2: I mean, he has created a realignment in politics. And 44 00:02:58,400 --> 00:03:05,440 Speaker 2: as I say that the coalition he put together working folks, 45 00:03:07,639 --> 00:03:12,440 Speaker 2: not you know, it's multi racial. That coalition I think 46 00:03:12,800 --> 00:03:15,760 Speaker 2: represents realignment and. 47 00:03:15,720 --> 00:03:16,959 Speaker 3: I think it's here to stay. 48 00:03:17,919 --> 00:03:23,720 Speaker 2: Whoever would succeed him, well certainly will certainly use that 49 00:03:23,960 --> 00:03:25,560 Speaker 2: word that expand that. 50 00:03:25,639 --> 00:03:28,480 Speaker 3: You know. That's another point I want to make is that. 51 00:03:29,800 --> 00:03:32,760 Speaker 2: A lot of the immediate types and you know liberal 52 00:03:32,800 --> 00:03:37,040 Speaker 2: pundits would say, well, he's just appealing to the base, 53 00:03:38,040 --> 00:03:43,800 Speaker 2: but that's not what happened. He expanded the base enormously 54 00:03:44,360 --> 00:03:46,480 Speaker 2: when you go through all the numbers. I was just 55 00:03:46,520 --> 00:03:51,440 Speaker 2: looking at some more numbers. You know, in some cases 56 00:03:51,920 --> 00:03:56,120 Speaker 2: he would increase his vote from you know, say black 57 00:03:56,160 --> 00:04:04,880 Speaker 2: men by fifty percent, or Hispanics total, Hispanics and Latino men. 58 00:04:05,440 --> 00:04:09,440 Speaker 2: I mean, he increased his base enormously young people. So 59 00:04:09,680 --> 00:04:13,560 Speaker 2: my point is sure, I mean, what the goop should 60 00:04:13,560 --> 00:04:19,159 Speaker 2: do is copycat what mister Trump did and. 61 00:04:19,080 --> 00:04:19,640 Speaker 3: Stay with that. 62 00:04:20,360 --> 00:04:22,520 Speaker 1: I think what you're saying is so key because we're 63 00:04:22,560 --> 00:04:25,560 Speaker 1: hearing now all of the leftist pundits come out, but 64 00:04:25,600 --> 00:04:28,080 Speaker 1: even on social media, I see the regular people coming out. 65 00:04:28,120 --> 00:04:31,200 Speaker 1: They're like, this is a racist, misogynistic country. How could 66 00:04:31,200 --> 00:04:34,080 Speaker 1: people do this? And it blows my mind because of 67 00:04:34,160 --> 00:04:36,760 Speaker 1: those numbers. So you're telling me that black men voted 68 00:04:36,800 --> 00:04:40,159 Speaker 1: against themselves. This is the These are record numbers of 69 00:04:40,240 --> 00:04:43,520 Speaker 1: black men coming out for a Republican But look at 70 00:04:43,560 --> 00:04:46,000 Speaker 1: the state of Michigan. Look at my state. He comes 71 00:04:46,040 --> 00:04:48,400 Speaker 1: out and he says, we don't want people to have 72 00:04:48,480 --> 00:04:51,520 Speaker 1: to live like they're living in Detroit. The elitists who 73 00:04:51,600 --> 00:04:53,839 Speaker 1: live in a very small portion of Detroit, they're like, 74 00:04:53,920 --> 00:04:57,240 Speaker 1: oh my gosh, how could you say this. The middle class, 75 00:04:57,480 --> 00:05:01,080 Speaker 1: they're getting their factory shut down. They have record crime. 76 00:05:01,200 --> 00:05:03,800 Speaker 1: We had a mass shooting in Detroit that was the 77 00:05:03,800 --> 00:05:06,680 Speaker 1: biggest mass shooting in history in July. No one said 78 00:05:06,680 --> 00:05:09,000 Speaker 1: a peep about it. When it comes to higher level 79 00:05:09,040 --> 00:05:12,719 Speaker 1: Democrats and Donald Trump's like, listen, it's an uncomfortable truth, 80 00:05:12,880 --> 00:05:16,159 Speaker 1: but we want to help you. Is that what resonates. 81 00:05:17,080 --> 00:05:19,240 Speaker 3: You know? The answer is yes, of course. 82 00:05:19,680 --> 00:05:25,960 Speaker 2: But when you look at this thing nationwide, well, hold on, 83 00:05:26,160 --> 00:05:30,120 Speaker 2: I want to just mention with respect to Michigan. Uh. 84 00:05:30,640 --> 00:05:34,000 Speaker 2: You know, a huge issue, as I'm sure you know, 85 00:05:35,160 --> 00:05:40,279 Speaker 2: was the sort of far left climate change. 86 00:05:41,320 --> 00:05:42,720 Speaker 3: Uh you know, it's like. 87 00:05:44,800 --> 00:05:53,320 Speaker 2: Terrorists climate change and ending gasoline powered cars and all 88 00:05:53,400 --> 00:05:58,320 Speaker 2: the EV's electric vehicles. Subject I mean, I'm not against evs, 89 00:05:58,400 --> 00:06:02,400 Speaker 2: mind you, but I don't at the government giving subsidies 90 00:06:02,440 --> 00:06:06,360 Speaker 2: and grants and free loans that they will forgive so 91 00:06:06,680 --> 00:06:10,359 Speaker 2: people should have choice. Trump said this many times. People 92 00:06:10,400 --> 00:06:14,440 Speaker 2: should have a choice. Don't stop them from driving diesel 93 00:06:14,520 --> 00:06:21,599 Speaker 2: trucks or gas powered cars, and don't force them to 94 00:06:21,920 --> 00:06:24,960 Speaker 2: buy electric vehicles where the battery is. 95 00:06:24,880 --> 00:06:25,560 Speaker 3: Made in China. 96 00:06:26,320 --> 00:06:29,920 Speaker 2: That was a big issue and the UAW rank and file. 97 00:06:30,279 --> 00:06:33,320 Speaker 2: I mean, I haven't seen numbers exactly on this, but 98 00:06:33,400 --> 00:06:37,159 Speaker 2: I think Trump probably upped his margins a lot with 99 00:06:37,360 --> 00:06:40,560 Speaker 2: auto workers. I know he did with teamsters, no question 100 00:06:40,640 --> 00:06:46,680 Speaker 2: about that, because they didn't want this kind of climate 101 00:06:47,400 --> 00:06:50,360 Speaker 2: extremism and that would cost the jobs. 102 00:06:50,480 --> 00:06:53,200 Speaker 1: Let's take a quick commercial break. We'll continue next on 103 00:06:53,240 --> 00:06:59,440 Speaker 1: the Tutor Dixon podcast. I think you also bring up 104 00:06:59,480 --> 00:07:01,600 Speaker 1: a good point because it wasn't just that they didn't 105 00:07:01,600 --> 00:07:04,320 Speaker 1: want the climate extremism. I think there was a concern, 106 00:07:04,560 --> 00:07:06,960 Speaker 1: especially in our state, in other states. You saw this 107 00:07:07,120 --> 00:07:09,159 Speaker 1: in Texas, you saw us in a couple other places 108 00:07:09,160 --> 00:07:11,480 Speaker 1: where China has come in and bought up land. It 109 00:07:11,600 --> 00:07:14,280 Speaker 1: was also a concern of Okay, even if we build 110 00:07:14,320 --> 00:07:17,440 Speaker 1: the batteries here, can we have it American manufacturing. Can 111 00:07:17,440 --> 00:07:19,360 Speaker 1: we have it American owned that we know that they're 112 00:07:19,400 --> 00:07:23,840 Speaker 1: adhering to our environmental standards because climate and environment to me, 113 00:07:23,880 --> 00:07:26,520 Speaker 1: should not be separate. It's funny to me that they 114 00:07:26,640 --> 00:07:30,800 Speaker 1: are climate crazy, but environment can go by the wayside. 115 00:07:30,800 --> 00:07:34,120 Speaker 1: So when Goshen, the Chinese battery factory, came to Michigan, 116 00:07:34,240 --> 00:07:37,120 Speaker 1: they waived the environmental review of it. How can you 117 00:07:37,200 --> 00:07:40,440 Speaker 1: do that. They're taking seven hundred thousand gallons of water 118 00:07:40,480 --> 00:07:44,600 Speaker 1: a day, they're running it through these highly toxic chemicals, 119 00:07:44,880 --> 00:07:47,520 Speaker 1: forever chemicals that we've been so careful to get out 120 00:07:47,520 --> 00:07:51,440 Speaker 1: of the state of Michigan, and there's no review of that. 121 00:07:51,680 --> 00:07:53,720 Speaker 1: There was a fear that China would come in and 122 00:07:53,760 --> 00:07:59,200 Speaker 1: destroy the environment in a way in an attempt to 123 00:07:59,240 --> 00:08:01,640 Speaker 1: protect the climate. But how can those two things be 124 00:08:01,720 --> 00:08:02,720 Speaker 1: mutually exclusive? 125 00:08:03,920 --> 00:08:08,280 Speaker 2: Well, okay, I'm not familiar with that specific issue. I 126 00:08:08,400 --> 00:08:12,880 Speaker 2: just think the general point is that the climate extremism 127 00:08:14,040 --> 00:08:20,680 Speaker 2: ending gas powered cars would cost jobs, factories would close, 128 00:08:21,480 --> 00:08:25,840 Speaker 2: And on top of that, the misnamed Inflation Reduction Act, 129 00:08:25,880 --> 00:08:32,480 Speaker 2: which was the Big Greeny Act, would basically provide massive 130 00:08:32,520 --> 00:08:38,560 Speaker 2: assistance to electric vehicles, and you could end gas powered 131 00:08:38,600 --> 00:08:42,319 Speaker 2: cars inside of ten years, and that's going to cost jobs. 132 00:08:42,640 --> 00:08:46,560 Speaker 2: So I think that I think that that played a 133 00:08:46,720 --> 00:08:50,199 Speaker 2: very important role in Michigan. However, I was going to 134 00:08:50,240 --> 00:08:54,240 Speaker 2: say earlier. When you look at these groups, whether the 135 00:08:54,520 --> 00:09:01,920 Speaker 2: unions or Blacks or Latinos, there a comb pay fell 136 00:09:02,679 --> 00:09:07,760 Speaker 2: during the Biden years. Felt real wages no matter how 137 00:09:07,800 --> 00:09:14,199 Speaker 2: you measure them, meeting income adjusted for inflation, weekly wages 138 00:09:14,280 --> 00:09:22,000 Speaker 2: adjusted for inflation, every single one declined significantly over the 139 00:09:22,040 --> 00:09:28,000 Speaker 2: past four years during the Biden Harris administration, whereas during 140 00:09:28,040 --> 00:09:32,120 Speaker 2: the Trump years those same measurements went up, you know, 141 00:09:32,240 --> 00:09:36,720 Speaker 2: between five and eight percent. So you have big take 142 00:09:36,720 --> 00:09:40,840 Speaker 2: home pay gains under Trump and take home pay losses 143 00:09:41,840 --> 00:09:42,920 Speaker 2: under Biden Harris. 144 00:09:43,040 --> 00:09:46,000 Speaker 3: That was an enormous issue. 145 00:09:46,240 --> 00:09:49,800 Speaker 2: And then you add on to that the problem with 146 00:09:49,880 --> 00:09:53,880 Speaker 2: the cost of living inflation. Over the space of nearly 147 00:09:53,960 --> 00:09:57,880 Speaker 2: four years. 148 00:09:56,120 --> 00:09:57,760 Speaker 3: In urban areas and cities. 149 00:09:57,800 --> 00:10:00,920 Speaker 2: By the way, the CPI went up about twenty six percent, 150 00:10:01,840 --> 00:10:07,800 Speaker 2: so that kills household groceries, electricity, you name it. Everything 151 00:10:07,840 --> 00:10:13,000 Speaker 2: went up, gasoline, everything went up. That was never solved 152 00:10:13,760 --> 00:10:16,920 Speaker 2: by Biden Harris. In fact, she never talked about barely. 153 00:10:17,200 --> 00:10:19,720 Speaker 2: I mean, when she did talk about it, she would 154 00:10:19,720 --> 00:10:23,240 Speaker 2: talk about I'm going to have price controls, and I'm 155 00:10:23,240 --> 00:10:26,800 Speaker 2: gonna have rent controls, and then I'm going to increase 156 00:10:26,840 --> 00:10:30,720 Speaker 2: your entitlements for childcare and all these things. 157 00:10:31,160 --> 00:10:32,440 Speaker 3: As now what people want. 158 00:10:33,240 --> 00:10:38,920 Speaker 2: They wanted a plan to give them positive gains and 159 00:10:39,000 --> 00:10:43,280 Speaker 2: take home pay and to reduce inflation so that. 160 00:10:43,240 --> 00:10:45,760 Speaker 3: Their borrowing costs would come down. 161 00:10:46,200 --> 00:10:53,520 Speaker 2: Branded cards, car loans, mortgages, that's what. So she's sitting 162 00:10:53,559 --> 00:10:57,640 Speaker 2: there and going to rallies with happy talk and word salads, 163 00:10:57,720 --> 00:11:00,679 Speaker 2: and she's attacking Trump as a fascist, and people will 164 00:11:00,720 --> 00:11:04,800 Speaker 2: even scratching their heads. What I can't spend fascism. I 165 00:11:04,840 --> 00:11:07,320 Speaker 2: can't buy a house with fascism. I don't think they 166 00:11:07,320 --> 00:11:08,640 Speaker 2: even know what fascism is. 167 00:11:08,679 --> 00:11:11,360 Speaker 1: For having's sake, Well, that's a great point. I think 168 00:11:11,400 --> 00:11:13,880 Speaker 1: that there's so middle education of. 169 00:11:13,800 --> 00:11:16,640 Speaker 3: What that fascism. I mean, I don't know. 170 00:11:17,480 --> 00:11:21,160 Speaker 2: You think people at kitchen tables were sitting around talking 171 00:11:21,160 --> 00:11:24,560 Speaker 2: about the latest biography of Benito Mussolini. 172 00:11:26,760 --> 00:11:29,079 Speaker 3: Something tells me that's not what they were doing. 173 00:11:30,000 --> 00:11:32,319 Speaker 1: So I think there are a few things that happened, 174 00:11:32,360 --> 00:11:35,320 Speaker 1: and I wonder how the Democrat Party is looking at this. 175 00:11:35,400 --> 00:11:37,360 Speaker 1: We obviously saw Bernie Sanders come out and say you 176 00:11:37,440 --> 00:11:39,920 Speaker 1: left the working person. How could you do this? But 177 00:11:40,000 --> 00:11:43,400 Speaker 1: I think it's beyond that. They kind of created. Obviously, 178 00:11:43,400 --> 00:11:46,880 Speaker 1: they installed a Kamala Harris. She wasn't ready. They didn't better, 179 00:11:46,920 --> 00:11:49,520 Speaker 1: they didn't know she wasn't ready. But they also brought 180 00:11:49,520 --> 00:11:54,000 Speaker 1: Hollywood in. Hollywood is great at creating something imaginary, and 181 00:11:54,040 --> 00:11:56,280 Speaker 1: I think that's what they did with this campaign. They 182 00:11:56,280 --> 00:11:59,320 Speaker 1: had these rallies that had Lady Gaga, and people came 183 00:11:59,360 --> 00:12:02,120 Speaker 1: for celebrity. They didn't come for Harris. So I think 184 00:12:02,200 --> 00:12:06,280 Speaker 1: Harris was shocked because she didn't realize how unpopular she was. 185 00:12:06,320 --> 00:12:09,200 Speaker 1: But the numbers all said she was unpopular. So when 186 00:12:09,200 --> 00:12:12,040 Speaker 1: they look at this, are they going to say did 187 00:12:12,080 --> 00:12:14,040 Speaker 1: they First of all, did they get kind of under 188 00:12:14,040 --> 00:12:16,640 Speaker 1: the impression that during the pandemic having Joe Biden not 189 00:12:16,760 --> 00:12:19,920 Speaker 1: come out was an effective way to campaign by saying nothing? 190 00:12:20,120 --> 00:12:22,880 Speaker 1: Were they misled by that? And will they change what 191 00:12:22,920 --> 00:12:24,959 Speaker 1: they do in the future. I mean, they obviously are 192 00:12:25,040 --> 00:12:28,720 Speaker 1: talking about how they'll change, but do they understand the 193 00:12:28,760 --> 00:12:30,360 Speaker 1: significance of what happened to them? 194 00:12:31,320 --> 00:12:37,559 Speaker 2: Listen, Tutor, I loved Lady Gaga. She's a great singer, 195 00:12:38,240 --> 00:12:42,400 Speaker 2: really super singer. I hope the Democrats continue. 196 00:12:41,960 --> 00:12:46,040 Speaker 3: To use it. I'm written for Lady Gaga. 197 00:12:47,280 --> 00:12:50,880 Speaker 2: I only want to Oprah Winfrey getting off at the end 198 00:12:50,920 --> 00:12:53,720 Speaker 2: and saying, if we lose, it'll be the last time 199 00:12:53,760 --> 00:12:58,360 Speaker 2: we vote in America. That was really stupid. But I 200 00:12:58,400 --> 00:13:01,720 Speaker 2: think George Clooney is a horrific actor, all right. I 201 00:13:01,760 --> 00:13:04,280 Speaker 2: know he's a left winger. I hope they continue to 202 00:13:04,360 --> 00:13:07,400 Speaker 2: use all those people. I'm rooting for him. I mean, 203 00:13:07,440 --> 00:13:10,160 Speaker 2: I hope they sit down and they say, the real 204 00:13:10,240 --> 00:13:13,120 Speaker 2: reason we lost is we didn't have the right Hollywood 205 00:13:13,160 --> 00:13:19,000 Speaker 2: singers on stage. That's because they are missing the point. 206 00:13:19,200 --> 00:13:24,640 Speaker 2: The issues were taking them down. Three quarters, I mean, 207 00:13:24,720 --> 00:13:30,800 Speaker 2: Paul's three quarters of the electorate said Biden Harris was 208 00:13:30,880 --> 00:13:32,600 Speaker 2: going in the wrong direction. 209 00:13:34,000 --> 00:13:36,960 Speaker 3: Okay, you know, you knew you couldn't win that way. 210 00:13:37,600 --> 00:13:43,480 Speaker 2: And Kamala did nothing to show them a different direction, 211 00:13:43,760 --> 00:13:47,280 Speaker 2: you know. I mean she was asked on the view, 212 00:13:47,920 --> 00:13:51,120 Speaker 2: what would you do different differently? And she says, I 213 00:13:51,160 --> 00:13:55,480 Speaker 2: can't think of anything. Really, she flunk the view. That's 214 00:13:55,600 --> 00:13:58,239 Speaker 2: that's impossible, beyond my comprehend. 215 00:13:58,960 --> 00:14:01,520 Speaker 1: I think she genuinely didn't have any depth. I think 216 00:14:01,559 --> 00:14:04,040 Speaker 1: she was serious when she said I can't think of 217 00:14:04,080 --> 00:14:06,760 Speaker 1: anything because I don't think she lives it. When I 218 00:14:06,800 --> 00:14:09,440 Speaker 1: would watch these interviews with Donald Trump, I'm like, he 219 00:14:09,559 --> 00:14:12,360 Speaker 1: can't be stumped because it's inside of him. He lives 220 00:14:12,400 --> 00:14:13,080 Speaker 1: it every day. 221 00:14:13,240 --> 00:14:13,640 Speaker 2: It is. 222 00:14:14,160 --> 00:14:17,160 Speaker 1: It's just part of who he is, is figuring out 223 00:14:17,200 --> 00:14:19,680 Speaker 1: all these issues. It was never part of who she was. 224 00:14:20,000 --> 00:14:20,440 Speaker 2: She was. 225 00:14:21,040 --> 00:14:21,880 Speaker 3: Trump is smart. 226 00:14:22,120 --> 00:14:25,120 Speaker 2: Trump listened as I said earlier. I mean, you know, 227 00:14:25,200 --> 00:14:28,520 Speaker 2: I'm very close to him. I worked for him for 228 00:14:28,560 --> 00:14:31,960 Speaker 2: three years. We're very close personal friends. I'll talk to 229 00:14:32,040 --> 00:14:36,160 Speaker 2: him constantly. Donald Trump has become a policy WoT. I'm 230 00:14:36,160 --> 00:14:37,480 Speaker 2: telling you that. 231 00:14:37,400 --> 00:14:39,600 Speaker 1: Would shock people. I think people want to think he's not. 232 00:14:40,120 --> 00:14:42,320 Speaker 2: I just say, yeah, I didn't let him think that. 233 00:14:43,280 --> 00:14:46,160 Speaker 2: He knows. I mean, listen, I live with it. It's 234 00:14:46,200 --> 00:14:50,480 Speaker 2: now been let's see twenty sixteen in the campaign. So 235 00:14:50,520 --> 00:14:55,600 Speaker 2: it's been eight years, almost nine years. His grasp of policy, 236 00:14:56,360 --> 00:15:03,440 Speaker 2: whether it's economy, foreign policy, immigration, tariffs, you name it is, 237 00:15:03,680 --> 00:15:07,560 Speaker 2: his grasp of policy has gotten greater and greater. This 238 00:15:07,720 --> 00:15:12,240 Speaker 2: is it's sort of a little interesting sub story, is 239 00:15:12,640 --> 00:15:14,640 Speaker 2: how good he has become. 240 00:15:14,840 --> 00:15:18,040 Speaker 3: He knows these issues, and he talks to all of us. 241 00:15:18,080 --> 00:15:21,360 Speaker 2: He talks to me, he talks to Lightheiser, he talks 242 00:15:21,400 --> 00:15:24,080 Speaker 2: to Scott Besson Minusian. 243 00:15:25,000 --> 00:15:27,960 Speaker 3: He's terrific. So you can see it, like he goes 244 00:15:28,040 --> 00:15:31,680 Speaker 3: on these radio she liked Rogan. 245 00:15:31,800 --> 00:15:35,560 Speaker 2: He goes on that show and he's completely fearless. He's 246 00:15:35,640 --> 00:15:40,200 Speaker 2: completely no notes, there's no teleprompter. He's completely fearless when 247 00:15:40,240 --> 00:15:44,320 Speaker 2: he does that. And all his rallies. Now I know, 248 00:15:44,440 --> 00:15:47,320 Speaker 2: he rips and he weaves in and out. I know 249 00:15:47,480 --> 00:15:50,440 Speaker 2: that's part of his charm, you know, Queen's New York charm. 250 00:15:51,600 --> 00:15:54,560 Speaker 2: He gets in the garbage truck, he goes to McDonald's. 251 00:15:54,560 --> 00:15:57,960 Speaker 2: That's part of his fabulous charm. But he knows this stuff. 252 00:15:58,400 --> 00:16:03,480 Speaker 3: See, he's not afraid to be interviewed by anybody. And 253 00:16:03,680 --> 00:16:07,360 Speaker 3: I think, you know this was a I forget. 254 00:16:07,560 --> 00:16:07,960 Speaker 1: Oh. I know. 255 00:16:08,720 --> 00:16:09,840 Speaker 3: A couple of weeks. 256 00:16:09,600 --> 00:16:12,960 Speaker 2: Ago, I was on the morning show on Fox News, 257 00:16:13,200 --> 00:16:16,920 Speaker 2: you know, Bill Hemmer and Dana Prier, and Bill asked 258 00:16:16,960 --> 00:16:23,200 Speaker 2: me about why does why does Biden Harris? Why do 259 00:16:23,320 --> 00:16:27,040 Speaker 2: they lie about numbers? They lie about jobs numbers for example. 260 00:16:27,120 --> 00:16:29,600 Speaker 2: I think that was the key one. The completelyne we 261 00:16:29,800 --> 00:16:32,440 Speaker 2: created all these jobs, Well that's not true. They were 262 00:16:32,520 --> 00:16:35,640 Speaker 2: bounced back jobs in the pandem And I just said, 263 00:16:35,720 --> 00:16:39,400 Speaker 2: you know the problem is from the day one, whether 264 00:16:39,440 --> 00:16:42,920 Speaker 2: it was they blamed inflation on Trump, they said they 265 00:16:43,000 --> 00:16:46,640 Speaker 2: inherited a depression from Trump. You know, they say Trump 266 00:16:46,840 --> 00:16:53,520 Speaker 2: Trump won to end abortions, ban abortions, just flat out lies, 267 00:16:54,400 --> 00:17:01,000 Speaker 2: And I think I think the public saw that and 268 00:17:01,520 --> 00:17:07,320 Speaker 2: saw it as a character flaw, and that diminished diminished 269 00:17:07,359 --> 00:17:10,680 Speaker 2: Comma it always and would have diminished Joe Biden. Also, 270 00:17:11,520 --> 00:17:14,720 Speaker 2: Trump may exaggerate, Okay, I get that, but on the 271 00:17:14,840 --> 00:17:18,960 Speaker 2: fundamental things, he can knock off all kinds of data 272 00:17:19,040 --> 00:17:22,000 Speaker 2: points and you know he will talk about take home 273 00:17:22,080 --> 00:17:23,200 Speaker 2: pay just as. 274 00:17:23,160 --> 00:17:24,800 Speaker 3: Well as I just did with you. 275 00:17:25,080 --> 00:17:29,840 Speaker 2: He knows that stuff, Paul, and that gives him tremendous advantage, 276 00:17:30,280 --> 00:17:32,080 Speaker 2: and it paid off. 277 00:17:32,160 --> 00:17:32,480 Speaker 3: I mean that. 278 00:17:33,320 --> 00:17:34,880 Speaker 2: I know there are a lot of big issues out 279 00:17:34,920 --> 00:17:37,760 Speaker 2: there and so forth, but I think people started looking 280 00:17:37,840 --> 00:17:41,480 Speaker 2: at Trump as a guy who was learned a lot 281 00:17:42,520 --> 00:17:45,800 Speaker 2: and would be an even better president in a second term. 282 00:17:46,760 --> 00:17:49,440 Speaker 2: And that is their hope and their dream, and that's 283 00:17:49,480 --> 00:17:53,160 Speaker 2: why they voted for him. He was the qualified candidate. 284 00:17:53,800 --> 00:17:57,200 Speaker 2: She flunked the qualified candidate. 285 00:17:56,920 --> 00:17:59,800 Speaker 1: Test, and it seems like he's learned even more having 286 00:18:00,119 --> 00:18:03,240 Speaker 1: a term off. And I think that people were saying, 287 00:18:03,280 --> 00:18:05,439 Speaker 1: how could this happen. It's like, well, God has an 288 00:18:05,480 --> 00:18:07,680 Speaker 1: interesting way of planning things out, because it seems like 289 00:18:07,760 --> 00:18:10,560 Speaker 1: he's going in there even stronger than he would have 290 00:18:10,720 --> 00:18:13,639 Speaker 1: had he gone right into his second term. I think 291 00:18:13,800 --> 00:18:16,400 Speaker 1: was something you're saying to me is just so valuable 292 00:18:16,480 --> 00:18:18,720 Speaker 1: right now because I saw so many candidates who didn't 293 00:18:18,760 --> 00:18:20,800 Speaker 1: do exactly what you just said, who didn't go out 294 00:18:20,840 --> 00:18:23,040 Speaker 1: and talk to everybody they could about all of the 295 00:18:23,080 --> 00:18:26,119 Speaker 1: different subjects. Nobody is a genius. Nobody just knows this 296 00:18:26,200 --> 00:18:28,520 Speaker 1: stuff off the top of their head. That's why you 297 00:18:28,680 --> 00:18:31,600 Speaker 1: have advisors, that's why you put smart people around you. 298 00:18:31,920 --> 00:18:34,200 Speaker 1: And that is so different about Donald Trump. He has 299 00:18:34,520 --> 00:18:36,880 Speaker 1: and that's what we heard from the Arab American community 300 00:18:36,920 --> 00:18:39,240 Speaker 1: here in Michigan. People go, how did he win the 301 00:18:39,320 --> 00:18:42,440 Speaker 1: Jewish community and the Arab community? While he went there 302 00:18:42,520 --> 00:18:44,280 Speaker 1: and he sat down with them and he said, tell 303 00:18:44,359 --> 00:18:47,160 Speaker 1: me about it. And then when he said, you make 304 00:18:47,200 --> 00:18:50,040 Speaker 1: the point of sometimes he's exaggerated. Sometimes he says something else. 305 00:18:50,280 --> 00:18:53,240 Speaker 1: He said something that they didn't like. They called him 306 00:18:53,400 --> 00:18:55,440 Speaker 1: and he came right back and he said, Okay, talk 307 00:18:55,480 --> 00:18:58,440 Speaker 1: to me about it. That's the difference between him and 308 00:18:58,600 --> 00:19:02,159 Speaker 1: other politicians. If he makes a mistake. He listens and 309 00:19:02,280 --> 00:19:05,879 Speaker 1: he adjusts, and he changes things for the people, not 310 00:19:06,040 --> 00:19:07,920 Speaker 1: for himself. He's a man of the people. 311 00:19:09,359 --> 00:19:12,560 Speaker 3: Yeah, I tell you, it's all very interesting. 312 00:19:13,840 --> 00:19:16,840 Speaker 2: You know. Like as I said, I've been with him 313 00:19:16,880 --> 00:19:22,040 Speaker 2: a long time and others friends of mine. It's just 314 00:19:22,240 --> 00:19:28,800 Speaker 2: all very interesting. And he has he has a tremendous 315 00:19:30,880 --> 00:19:31,920 Speaker 2: opportunity here. 316 00:19:32,400 --> 00:19:33,400 Speaker 3: This election. 317 00:19:35,080 --> 00:19:42,720 Speaker 2: Was tremendous mandate for change. I mean, the country does 318 00:19:42,880 --> 00:19:49,560 Speaker 2: not want this woke stuff, transgenderism with DEI, you know, 319 00:19:50,000 --> 00:19:54,320 Speaker 2: radical affirmative action. They don't want it. The country wants 320 00:19:54,359 --> 00:19:59,520 Speaker 2: a better economy. The country wants you know, safe borders 321 00:19:59,600 --> 00:20:03,320 Speaker 2: and say cities and so forth. The country wants to 322 00:20:03,480 --> 00:20:07,560 Speaker 2: end these wars, and the country wants to make sure 323 00:20:07,640 --> 00:20:11,399 Speaker 2: inflation stays down, cut the federal budget. You know, the 324 00:20:11,440 --> 00:20:15,400 Speaker 2: Elon Musk factor was very, very important in this race. 325 00:20:16,600 --> 00:20:22,280 Speaker 2: It's a mandate for change. They're saying to him, go ahead, 326 00:20:23,240 --> 00:20:28,240 Speaker 2: implement your promises. You know. In his speech Tuesday night, 327 00:20:28,320 --> 00:20:31,440 Speaker 2: which I thought was one of his better speeches, he said, 328 00:20:32,359 --> 00:20:37,920 Speaker 2: promise has made, promises kept. That's a big line. The 329 00:20:38,240 --> 00:20:43,600 Speaker 2: implications of that tutor are really really important, and he 330 00:20:43,840 --> 00:20:47,600 Speaker 2: is determined. I think he's really determined to make good 331 00:20:47,800 --> 00:20:52,040 Speaker 2: on the agenda that he proposed during the campaign. It's 332 00:20:52,040 --> 00:20:58,119 Speaker 2: a tremendous historical opportunity. And of course, let's look, his 333 00:20:58,640 --> 00:21:05,639 Speaker 2: victory Tuesday night marked the greatest political comeback in American history. 334 00:21:06,280 --> 00:21:08,200 Speaker 3: That is, in American history. 335 00:21:08,480 --> 00:21:11,800 Speaker 2: I know Grover Cleveland had two split terms, but those 336 00:21:11,840 --> 00:21:15,520 Speaker 2: were different times and completely different. What they did to 337 00:21:15,680 --> 00:21:18,399 Speaker 2: him while he was out of office, you know, with 338 00:21:18,520 --> 00:21:22,000 Speaker 2: the weaponization and the law fair throwing him in jail, 339 00:21:22,600 --> 00:21:27,720 Speaker 2: calling the names, etc. He just shrugged it off and 340 00:21:28,000 --> 00:21:31,240 Speaker 2: took a bullet at one point. So the greatest comeback 341 00:21:31,280 --> 00:21:35,200 Speaker 2: in history, the greatest comeback in history. But he's there now, 342 00:21:36,000 --> 00:21:39,800 Speaker 2: and he has this mandate for change, and I sincerely 343 00:21:40,000 --> 00:21:43,959 Speaker 2: believe he's going to make good on that mandate. Very 344 00:21:44,040 --> 00:21:47,160 Speaker 2: much like my other former boss, Ronald Reagan years ago. 345 00:21:48,080 --> 00:21:51,640 Speaker 2: You take three or four or five points, tutor, that's 346 00:21:51,680 --> 00:21:56,440 Speaker 2: all you need, and you implement and they have enormous 347 00:21:57,000 --> 00:22:00,359 Speaker 2: impact to change the direction of the country, you know, 348 00:22:00,560 --> 00:22:02,639 Speaker 2: get us on the right track. He talks about a 349 00:22:02,800 --> 00:22:06,240 Speaker 2: bolded age. He believes that stuff. He wont He is 350 00:22:06,840 --> 00:22:11,399 Speaker 2: the candidate of normalcy. They may yell at him and 351 00:22:11,800 --> 00:22:15,120 Speaker 2: accuse him of this. He didn't start that stuff they did. 352 00:22:15,440 --> 00:22:18,640 Speaker 2: He didn't start the Russian hopes they did. But I'm 353 00:22:18,720 --> 00:22:23,600 Speaker 2: just saying he's the candidate of normalcy and he's the guy. 354 00:22:23,840 --> 00:22:30,080 Speaker 2: As he said Tuesday night again, success will bring us together, 355 00:22:30,320 --> 00:22:34,520 Speaker 2: success will unite us. He believes that stuff, Trust me, 356 00:22:34,720 --> 00:22:37,240 Speaker 2: He believes that stuff from his heart and soul. 357 00:22:37,600 --> 00:22:40,000 Speaker 1: More with Larry Kudlow coming up, But first let me 358 00:22:40,119 --> 00:22:43,360 Speaker 1: tell you about my partners at Saber. Protecting our families 359 00:22:43,400 --> 00:22:47,000 Speaker 1: and homes is essential, but are we truly prepared. Breakin's 360 00:22:47,040 --> 00:22:50,639 Speaker 1: happen every twenty five seconds. Even with a security system, 361 00:22:51,000 --> 00:22:54,000 Speaker 1: can it really keep intruders out. 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With Larry Cudlow coming up here, 380 00:23:59,200 --> 00:24:02,080 Speaker 1: we see a kind of with him. We see Tausea Gabbard, 381 00:24:02,119 --> 00:24:05,399 Speaker 1: we see Elon Musk. This is the Unity Party right now, 382 00:24:05,560 --> 00:24:08,120 Speaker 1: regardless of what someone says. But what you just said 383 00:24:08,160 --> 00:24:11,879 Speaker 1: to me, I think that we really saw the United 384 00:24:11,920 --> 00:24:15,600 Speaker 1: States of America, the overwhelming population of the country say 385 00:24:16,040 --> 00:24:20,840 Speaker 1: we will not allow this ruthless weaponization of government to 386 00:24:20,960 --> 00:24:23,840 Speaker 1: go after a political opponent and have a dictatorship in 387 00:24:23,920 --> 00:24:26,680 Speaker 1: one party rule. And I think too many people think 388 00:24:26,720 --> 00:24:29,359 Speaker 1: they overplayed their hand. They thought we'll get him, we'll 389 00:24:29,400 --> 00:24:32,720 Speaker 1: get him, we'll get him, and the American public said, 390 00:24:32,760 --> 00:24:35,040 Speaker 1: we've never seen this before. We will not let it stand. 391 00:24:35,400 --> 00:24:37,719 Speaker 1: I really think that people will go, well, how did 392 00:24:37,760 --> 00:24:41,520 Speaker 1: he withstand all of this? It's not us, it's not America. 393 00:24:42,600 --> 00:24:48,840 Speaker 2: I worry about you know, this special counsel Jack Smith, 394 00:24:49,600 --> 00:24:52,679 Speaker 2: who was trying to bust Trump. I worry about him 395 00:24:52,680 --> 00:24:56,080 Speaker 2: because he's as of this week, he's going to be unemployed. 396 00:24:56,359 --> 00:24:58,920 Speaker 2: It's going to need a job tutor. If you have 397 00:24:59,119 --> 00:25:03,800 Speaker 2: something for him, Detroit or Michigan. I need some help us. 398 00:25:03,920 --> 00:25:07,080 Speaker 1: Don't send him to Detroit. We've got enough corruption in Michigan. 399 00:25:07,160 --> 00:25:07,480 Speaker 1: We're good. 400 00:25:07,800 --> 00:25:10,639 Speaker 2: He's gonna be out there on the employment lines and 401 00:25:10,840 --> 00:25:17,960 Speaker 2: I hate to see that personally, Twitter, I got it, jump, 402 00:25:18,240 --> 00:25:19,320 Speaker 2: You're wonderful. 403 00:25:19,520 --> 00:25:24,480 Speaker 3: You will, Hey, well, come on the show, come on set. 404 00:25:24,359 --> 00:25:27,119 Speaker 1: With me, Hunter, I absolutely I will. I'm hoping that 405 00:25:27,400 --> 00:25:30,240 Speaker 1: I'll have a chance before you go in to Washington 406 00:25:30,320 --> 00:25:31,719 Speaker 1: and change everything up. 407 00:25:32,080 --> 00:25:35,320 Speaker 3: Oh oh, can't talk about any of that stuff. 408 00:25:36,040 --> 00:25:38,480 Speaker 1: Well, we're looking forward to seeing what you do. I 409 00:25:38,600 --> 00:25:40,920 Speaker 1: know you, I know he takes your advice. So whatever 410 00:25:41,000 --> 00:25:43,359 Speaker 1: you do, we're looking forward to watching you do it. 411 00:25:43,400 --> 00:25:44,879 Speaker 1: And thank you so much for coming on today. 412 00:25:45,160 --> 00:25:47,560 Speaker 3: Yeah, thank you. You're a great lady. I appreciate it 413 00:25:47,720 --> 00:25:48,320 Speaker 3: very very much. 414 00:25:48,760 --> 00:25:49,760 Speaker 1: Thank you, have a good day.