1 00:00:00,680 --> 00:00:04,200 Speaker 1: Hi, I'm Molly John Fast and this is Fast Politics, 2 00:00:04,440 --> 00:00:07,200 Speaker 1: where we discussed the top political headlines with some of 3 00:00:07,200 --> 00:00:11,720 Speaker 1: today's best minds. And Susan Rice says Trump's calls to 4 00:00:11,800 --> 00:00:15,440 Speaker 1: putin a peer illegal. We have such a great show 5 00:00:15,560 --> 00:00:19,919 Speaker 1: for you today. Justin Wolfers, the host of the Think 6 00:00:20,120 --> 00:00:24,639 Speaker 1: Like an Economist podcast and a professor of economics and 7 00:00:24,720 --> 00:00:28,320 Speaker 1: public policy at the Gerald R. Ford School of Public 8 00:00:28,360 --> 00:00:34,360 Speaker 1: Policy at the University of Michigan, talks us through Biden's economy. 9 00:00:34,760 --> 00:00:42,360 Speaker 1: Then we'll talk to Michigan Senator and DSCC chairperson Gary Peters, 10 00:00:42,720 --> 00:00:45,240 Speaker 1: and he's going to talk us through the Senate map 11 00:00:45,320 --> 00:00:46,240 Speaker 1: for Democrats. 12 00:00:46,600 --> 00:00:51,120 Speaker 2: But first the news Somali, I am going to shock 13 00:00:51,200 --> 00:00:54,960 Speaker 2: you here that the Trump family has some eyes on 14 00:00:55,320 --> 00:00:58,000 Speaker 2: business in Israel. Who would have ever thought of them 15 00:00:58,040 --> 00:00:59,960 Speaker 2: including over in that region. 16 00:01:00,480 --> 00:01:04,720 Speaker 1: Yeah, of course it is. Any time that Trump World 17 00:01:04,880 --> 00:01:11,679 Speaker 1: is interested in a particular country, there's always always a reason, 18 00:01:11,720 --> 00:01:15,280 Speaker 1: and often it's real estate. Trump organization it was in 19 00:01:15,400 --> 00:01:20,520 Speaker 1: talks about Israeli hotels before the Hamas attack of October seventh, 20 00:01:20,800 --> 00:01:23,840 Speaker 1: and says that they want to resume them in the future. 21 00:01:24,400 --> 00:01:28,520 Speaker 1: This will be if Donald Trump wins the presidency. An enormous, 22 00:01:29,600 --> 00:01:34,840 Speaker 1: enormous conflict of interest, which is why we know that 23 00:01:34,920 --> 00:01:39,199 Speaker 1: Donald Trump will try it if he is elected. Yet again, 24 00:01:40,000 --> 00:01:44,560 Speaker 1: just such a dishonest and bad way to run a government. 25 00:01:44,720 --> 00:01:49,200 Speaker 1: Jesse Cannon. President Biden had to give a long, long 26 00:01:49,520 --> 00:01:50,440 Speaker 1: briefing today. 27 00:01:50,880 --> 00:01:53,080 Speaker 2: Well, I feel like there was a while where we 28 00:01:53,080 --> 00:01:56,760 Speaker 2: weren't hearing as much looney stuff from Marjorie Taylor Green, 29 00:01:56,840 --> 00:01:59,360 Speaker 2: but she is back on her bullshit like no one 30 00:01:59,400 --> 00:02:00,200 Speaker 2: has been lee. 31 00:02:00,440 --> 00:02:04,440 Speaker 1: President Biden gave an hour plus briefing about the previous 32 00:02:04,520 --> 00:02:08,120 Speaker 1: hurricane and Hurricane Milton, which will by the time this 33 00:02:08,320 --> 00:02:13,200 Speaker 1: podcast drops have hit Florida. This is really unusual for 34 00:02:13,680 --> 00:02:16,560 Speaker 1: Biden to do, or even for any sitting president to do, 35 00:02:16,680 --> 00:02:21,560 Speaker 1: but because of the flood of misinformation and disinformation coming 36 00:02:21,720 --> 00:02:25,440 Speaker 1: largely from Republicans, Biden had to do this. He also 37 00:02:25,600 --> 00:02:27,040 Speaker 1: had to say. 38 00:02:27,360 --> 00:02:30,119 Speaker 3: Now the claims are getting even more bizarre. Congress from 39 00:02:30,160 --> 00:02:33,000 Speaker 3: Marjorie Taylor Green and Congress from Georgia is now saying 40 00:02:33,040 --> 00:02:36,240 Speaker 3: the federal government is literally controlling the weather. We're controlling 41 00:02:36,240 --> 00:02:40,320 Speaker 3: the weather. It's found ridiculous. It's got to stop. Almost 42 00:02:40,360 --> 00:02:42,800 Speaker 3: like this. There are no red or blue states. There's 43 00:02:42,880 --> 00:02:46,280 Speaker 3: one United States. Of America where neighbors are helping neighbors. 44 00:02:46,520 --> 00:02:50,000 Speaker 3: Volunteers and first responders are risking everything, including their own lives, 45 00:02:50,480 --> 00:02:54,440 Speaker 3: to help their fellow Americans. State, local and officials are 46 00:02:54,480 --> 00:02:57,720 Speaker 3: standing side by side of a repeat. No one should 47 00:02:57,880 --> 00:03:01,280 Speaker 3: make the American people question whether our governments will make 48 00:03:01,560 --> 00:03:04,160 Speaker 3: sure that this is acting round of strikes. They'll be there. 49 00:03:04,480 --> 00:03:07,359 Speaker 1: That's a sense of what President Biden had to do 50 00:03:07,960 --> 00:03:14,800 Speaker 1: today in the hopes of debunking some of this Republican misinformation. Disinformation, 51 00:03:15,320 --> 00:03:17,840 Speaker 1: pretty bleak moment in American life. 52 00:03:18,080 --> 00:03:21,679 Speaker 2: So my Trump went on some one of these podcasts 53 00:03:21,680 --> 00:03:23,840 Speaker 2: that Baron's been telling them to go on with. I 54 00:03:23,880 --> 00:03:26,200 Speaker 2: can't even tell who it is, and I usually know these, 55 00:03:26,480 --> 00:03:28,720 Speaker 2: but there's a pretty funny moment we're going to listen to. Now. 56 00:03:31,320 --> 00:03:34,200 Speaker 4: I have a hard time doing it to them, because 57 00:03:34,840 --> 00:03:37,320 Speaker 4: you know, I'm basically a truthful person. 58 00:03:37,880 --> 00:03:46,920 Speaker 1: But here's a great sign that you're not a truthful 59 00:03:47,000 --> 00:03:51,040 Speaker 1: person when you say to the podcast that you're on, 60 00:03:51,320 --> 00:03:55,520 Speaker 1: which is a podcast of your supporters, I am basically 61 00:03:55,560 --> 00:03:59,880 Speaker 1: a truthful person, and the host cannot stop laughing. That's 62 00:04:00,000 --> 00:04:03,040 Speaker 1: what a Litnus test. If you're wondering when you say 63 00:04:03,080 --> 00:04:06,160 Speaker 1: a statement like I'm basically a truthful person and the 64 00:04:06,200 --> 00:04:08,560 Speaker 1: other person finds that hilarious. 65 00:04:08,880 --> 00:04:10,800 Speaker 2: Funny enough, somebody pointed out that when he was on 66 00:04:10,920 --> 00:04:13,880 Speaker 2: lex Fridman, he also said something like this, and Lex 67 00:04:13,880 --> 00:04:17,159 Speaker 2: Fredman couldn't even keep a straight face through a similar 68 00:04:17,200 --> 00:04:17,880 Speaker 2: statement of. 69 00:04:17,839 --> 00:04:20,040 Speaker 1: His Yeah, amazing stuff. 70 00:04:20,320 --> 00:04:22,320 Speaker 2: I feel like this is one of those things that 71 00:04:22,360 --> 00:04:25,320 Speaker 2: we see with Trump all the time, that the same 72 00:04:25,400 --> 00:04:29,560 Speaker 2: story resurfaces with that's the same theme, but just a 73 00:04:29,640 --> 00:04:32,920 Speaker 2: different detail, And this time it's about Trumo's Trump God 74 00:04:32,960 --> 00:04:35,960 Speaker 2: Bless the USA Bibles? Where do you see, dearby so these. 75 00:04:35,760 --> 00:04:39,040 Speaker 1: God Bless the USA Bibles. You'll remember last week we 76 00:04:39,160 --> 00:04:43,400 Speaker 1: learned that the only Bible that can meet the specs 77 00:04:44,000 --> 00:04:49,960 Speaker 1: for Oklahoma's Bible mandate for the schools was the Donald 78 00:04:50,000 --> 00:04:53,400 Speaker 1: Trump God Bless the USA Bible. Remember that, Well, you're 79 00:04:53,440 --> 00:04:57,320 Speaker 1: going to be shocked to find out where the Donald 80 00:04:57,320 --> 00:05:02,680 Speaker 1: Trump God Bless the USA vibe are printed. Yes, you 81 00:05:03,240 --> 00:05:07,760 Speaker 1: got it. A country that Donald Trump regularly accuses of 82 00:05:07,839 --> 00:05:12,240 Speaker 1: stealing American jobs and engaging in unfair trade practices, A 83 00:05:12,279 --> 00:05:17,000 Speaker 1: country that Donald Trump wants to enact high tariffs on 84 00:05:17,839 --> 00:05:22,200 Speaker 1: the country of China. Global trade records reviewed by the 85 00:05:22,240 --> 00:05:27,600 Speaker 1: Associated Press showed a printing company in China's Eastern city 86 00:05:27,960 --> 00:05:31,119 Speaker 1: shipped close to one hundred and twenty thousand of these 87 00:05:31,160 --> 00:05:35,159 Speaker 1: bibles to the United States between early February and late March. 88 00:05:35,200 --> 00:05:39,640 Speaker 1: Who could have seen it coming, certainly not everyone in 89 00:05:39,680 --> 00:05:40,160 Speaker 1: the world. 90 00:05:40,440 --> 00:05:43,360 Speaker 2: Yeah, I never ever would have seen him skim and 91 00:05:43,440 --> 00:05:46,839 Speaker 2: coming to light, So this is pretty interesting. The GOP 92 00:05:47,640 --> 00:05:50,600 Speaker 2: was really hoping that Vance could help them win some 93 00:05:50,640 --> 00:05:53,200 Speaker 2: more races in Ohio of the few districts left that 94 00:05:53,240 --> 00:05:56,400 Speaker 2: are Dems. But that looks like it's not quite happening. 95 00:05:56,440 --> 00:05:58,480 Speaker 2: After he made up a bunch of lives about Ohio, 96 00:05:58,480 --> 00:05:59,200 Speaker 2: what are you seeing here? 97 00:05:59,400 --> 00:06:02,400 Speaker 1: Yeah, I'm not even sure that that was what it was. Remember, 98 00:06:02,640 --> 00:06:06,719 Speaker 1: jad Evans has historically run about twenty points behind the 99 00:06:06,920 --> 00:06:11,719 Speaker 1: governor of Ohio, Mike DeWine in twenty twenty two. It's 100 00:06:11,760 --> 00:06:16,080 Speaker 1: not a total shock to see that he is not 101 00:06:16,360 --> 00:06:21,320 Speaker 1: helping any of the down valid candidates in Ohio. Marcy 102 00:06:21,480 --> 00:06:25,680 Speaker 1: Captor has a ten point lead in Ohio, and the 103 00:06:26,279 --> 00:06:32,080 Speaker 1: Republicans in Ohio are not using vans on billboards or 104 00:06:32,279 --> 00:06:37,160 Speaker 1: in any way advertising him. Politico reviewed the ad impact 105 00:06:37,279 --> 00:06:41,799 Speaker 1: data and found that despite a lot of outside spending. 106 00:06:42,480 --> 00:06:47,479 Speaker 1: They are not using images of every man jad Evans 107 00:06:47,640 --> 00:06:58,720 Speaker 1: can't imagine why. 108 00:06:53,800 --> 00:06:56,520 Speaker 2: We have even more towar dates for you. Did you 109 00:06:56,560 --> 00:06:58,880 Speaker 2: know the lincked projects? Rick wils that a past politics 110 00:06:58,920 --> 00:07:01,320 Speaker 2: bolli jug Fast or out on tour to bring you 111 00:07:01,640 --> 00:07:04,680 Speaker 2: a night of laughs for our dark political landscape. Join 112 00:07:04,760 --> 00:07:06,800 Speaker 2: us on August twenty sixth at San Francisco at the 113 00:07:06,839 --> 00:07:10,080 Speaker 2: Swedish American Hall, or in la on August twenty seventh 114 00:07:10,160 --> 00:07:12,760 Speaker 2: at the Regent Theater. Then we're headed to the Midwest 115 00:07:12,880 --> 00:07:15,080 Speaker 2: and we'll be at the Vivarium in Milwaukee on the 116 00:07:15,120 --> 00:07:17,920 Speaker 2: twenty first of September, and on the twenty second we'll 117 00:07:17,920 --> 00:07:20,040 Speaker 2: be in Chicago at City Winery. Then we're going to 118 00:07:20,120 --> 00:07:22,480 Speaker 2: hit the East coast. On September thirtieth, we'll be in 119 00:07:22,560 --> 00:07:25,240 Speaker 2: Boston at Arts at the Armory. On the first of October, 120 00:07:25,360 --> 00:07:28,160 Speaker 2: we'll be Infilliate City Winery, and then DC on the 121 00:07:28,200 --> 00:07:30,800 Speaker 2: second at the Miracle Theater. And today we just announced 122 00:07:30,840 --> 00:07:32,480 Speaker 2: that we'll be in New York on the fourteenth of 123 00:07:32,520 --> 00:07:35,320 Speaker 2: October at City Winery. If you need to laugh as 124 00:07:35,360 --> 00:07:37,920 Speaker 2: we get through this election, and hopefully never hear from 125 00:07:37,960 --> 00:07:40,000 Speaker 2: a guy who lives in a golf club again. We 126 00:07:40,080 --> 00:07:42,600 Speaker 2: got you covered. Join us in our surprise guests that 127 00:07:42,680 --> 00:07:44,480 Speaker 2: help you laugh instead of cry your way through this 128 00:07:44,520 --> 00:07:47,400 Speaker 2: election season and give you the inside analysis of what's 129 00:07:47,440 --> 00:07:50,000 Speaker 2: really going on right now. Buy your tickets now by 130 00:07:50,040 --> 00:07:54,240 Speaker 2: heading to Politics as Unusual dot bio. That's Politics as 131 00:07:54,480 --> 00:07:56,080 Speaker 2: Unusual dot bio. 132 00:07:57,840 --> 00:08:01,000 Speaker 1: Justin Wolfers is the host of the Think Like an 133 00:08:01,040 --> 00:08:04,600 Speaker 1: Economist podcast and a professor at the University of Michigan. 134 00:08:05,000 --> 00:08:10,600 Speaker 1: Welcome back, Too Fast Politics, my friend Justin Wolfers. 135 00:08:10,920 --> 00:08:12,240 Speaker 4: Hey, Molly, I was. 136 00:08:12,200 --> 00:08:18,520 Speaker 1: So excited to have you because oivey, Hey, hey, explain 137 00:08:18,600 --> 00:08:23,080 Speaker 1: to us where we are right now with the United 138 00:08:23,080 --> 00:08:25,120 Speaker 1: States economy go pretty. 139 00:08:24,880 --> 00:08:27,160 Speaker 4: Good, you might even say really good. I did a 140 00:08:27,160 --> 00:08:29,960 Speaker 4: funny thing the other day, Molly. There's an old index 141 00:08:30,120 --> 00:08:33,040 Speaker 4: people used to put together. They called it the misery index. 142 00:08:33,440 --> 00:08:35,640 Speaker 4: It adds up the bad things. It's the sum of 143 00:08:35,640 --> 00:08:39,199 Speaker 4: the unemployment rate and the inflation rate, so two bad 144 00:08:39,200 --> 00:08:42,160 Speaker 4: things they taste even worse together. And I looked at 145 00:08:42,200 --> 00:08:46,160 Speaker 4: that misery index in November of every election year for 146 00:08:46,160 --> 00:08:49,800 Speaker 4: the last fifty years. That misery index right now is 147 00:08:49,840 --> 00:08:52,040 Speaker 4: at the second lowest level that it's been over the 148 00:08:52,080 --> 00:08:54,439 Speaker 4: past fifty years. I'm not saying the economy is perfect, 149 00:08:54,440 --> 00:08:57,600 Speaker 4: But what I'm saying is that we normally approach election 150 00:08:57,800 --> 00:09:01,400 Speaker 4: day with things looking a whole lot worse than this. 151 00:09:02,200 --> 00:09:05,720 Speaker 1: So that's a really good place to start. So let's 152 00:09:05,760 --> 00:09:09,840 Speaker 1: start there. I want you to explain to us where 153 00:09:09,880 --> 00:09:13,719 Speaker 1: we are. This is the soft landing. You have been 154 00:09:13,720 --> 00:09:17,600 Speaker 1: talking about how we were going to have this soft landing. 155 00:09:17,679 --> 00:09:20,679 Speaker 1: You were cautiously optimistic, and then you were optimistic, and 156 00:09:20,720 --> 00:09:23,240 Speaker 1: now you are correct. So discuss. 157 00:09:23,440 --> 00:09:26,440 Speaker 4: Yeah. Look, great deal of credit to the administration, a 158 00:09:26,480 --> 00:09:29,679 Speaker 4: great deal of credit to J. Powell, and a little 159 00:09:29,720 --> 00:09:31,880 Speaker 4: moment for those of us who are true believers that 160 00:09:31,960 --> 00:09:35,720 Speaker 4: sometimes good things happen. Look, there's been really two major 161 00:09:35,800 --> 00:09:39,040 Speaker 4: challenges during the Biden administration. The first was he took 162 00:09:39,240 --> 00:09:44,280 Speaker 4: office during the pandemic and the deepest recession in a century. 163 00:09:44,559 --> 00:09:46,680 Speaker 4: In fact, at its deepest point, perhaps deeper than the 164 00:09:46,679 --> 00:09:50,439 Speaker 4: Great Depression. The economy is bounced back. And not only 165 00:09:50,559 --> 00:09:53,400 Speaker 4: is it bounced back, it has kept moving and in fact, 166 00:09:53,440 --> 00:09:55,600 Speaker 4: the economy today is in a better place than people 167 00:09:55,679 --> 00:09:58,320 Speaker 4: thought it was going to be in twenty nineteen, back 168 00:09:58,400 --> 00:10:01,000 Speaker 4: before they thought they'd be a pen So that was 169 00:10:01,040 --> 00:10:04,480 Speaker 4: the first challenge. We've got unemployment right now at four 170 00:10:04,520 --> 00:10:06,959 Speaker 4: point one percent, that's just a hair above a fifty 171 00:10:07,040 --> 00:10:11,359 Speaker 4: year low. The other great challenge was inflation. Supply change 172 00:10:11,600 --> 00:10:15,079 Speaker 4: became totally messed up. At the price of oil rows 173 00:10:15,080 --> 00:10:18,079 Speaker 4: at different points, all sorts of shocks were hitting the economy. 174 00:10:18,200 --> 00:10:20,480 Speaker 4: COVID was a tough time. It led to a very 175 00:10:20,520 --> 00:10:23,160 Speaker 4: sharp spike in inflation in the United States and every 176 00:10:23,160 --> 00:10:26,800 Speaker 4: other major industrialists country. And it's come down further and 177 00:10:26,840 --> 00:10:29,600 Speaker 4: faster in the United States than any other country. And 178 00:10:29,640 --> 00:10:33,240 Speaker 4: then the real victory lap here is the usual logic 179 00:10:33,640 --> 00:10:36,920 Speaker 4: says the only way to get inflation out of the 180 00:10:37,000 --> 00:10:39,439 Speaker 4: system is to create a recession, and in fact, a 181 00:10:39,440 --> 00:10:42,240 Speaker 4: lot of people were calling for that or predicting it. 182 00:10:42,320 --> 00:10:45,000 Speaker 4: But if you get it just right, you can tap 183 00:10:45,040 --> 00:10:48,800 Speaker 4: on the brakes without an abrupt stop, bring the economy 184 00:10:48,880 --> 00:10:53,200 Speaker 4: back to a sustainable pace, and possibly bring down inflation 185 00:10:53,360 --> 00:10:57,559 Speaker 4: without causing a recession. Very very hard needled a thread. 186 00:10:57,720 --> 00:10:59,440 Speaker 4: But it looks like we've done it. So we're at 187 00:10:59,440 --> 00:11:01,800 Speaker 4: a point now where inflation is back to where it 188 00:11:02,080 --> 00:11:04,559 Speaker 4: was at the start of the Biden administration. At the 189 00:11:04,640 --> 00:11:06,520 Speaker 4: end of the Trump administration two and a half percent 190 00:11:06,840 --> 00:11:09,640 Speaker 4: and unemployments back to where it was, and output has 191 00:11:09,640 --> 00:11:12,400 Speaker 4: continued to grow, and incomes have continued to grow, and 192 00:11:12,480 --> 00:11:15,800 Speaker 4: wages are growing faster than inflation, and inequality has fallen. 193 00:11:16,040 --> 00:11:17,720 Speaker 4: Sometimes good things do happen. 194 00:11:18,040 --> 00:11:21,400 Speaker 1: Yes, sometimes good things do happen. But this was also 195 00:11:21,960 --> 00:11:25,080 Speaker 1: the Inflation Reduction Act reduced inflation. 196 00:11:25,679 --> 00:11:28,360 Speaker 4: Oh my god, you are the greatest troll in human history. 197 00:11:28,400 --> 00:11:29,760 Speaker 4: And I love that about you, Molley. 198 00:11:30,000 --> 00:11:31,120 Speaker 1: So that's all I have. 199 00:11:31,480 --> 00:11:34,920 Speaker 4: Here's my favorite Thanksgiving trick. When you're at Thanksgiving in 200 00:11:34,960 --> 00:11:37,760 Speaker 4: a month's time with that trolley uncle or aunt of 201 00:11:37,840 --> 00:11:41,960 Speaker 4: yours who says Biden caused inflation and it's been a 202 00:11:42,040 --> 00:11:44,520 Speaker 4: terrible problem. You show them a graph of inflation and 203 00:11:44,559 --> 00:11:47,360 Speaker 4: then you say, look, this is where the Inflation Reduction 204 00:11:47,480 --> 00:11:52,280 Speaker 4: Act passed. And basically, as inflation peaked, the Inflation Reduction 205 00:11:52,360 --> 00:11:55,400 Speaker 4: Act passed, and then inflation fell. So if that's all 206 00:11:55,440 --> 00:11:57,800 Speaker 4: you knew about the world, you would say, oh, my goodness, 207 00:11:57,800 --> 00:12:01,760 Speaker 4: we absolutely definitely needed the Inflation Reduction Act to reduce inflation. 208 00:12:02,000 --> 00:12:06,200 Speaker 4: The reality is the Inflation Reduction Act was mostly an 209 00:12:06,280 --> 00:12:10,840 Speaker 4: environmental bill that was rebadged to get Senator Joe Manson 210 00:12:10,960 --> 00:12:13,000 Speaker 4: to vote for it. So if you take the same 211 00:12:13,040 --> 00:12:15,560 Speaker 4: piece of legislation. But you tell Mansion it doesn't save 212 00:12:15,600 --> 00:12:18,880 Speaker 4: the environment, but in fact reduces inflation. Mansion thinks it's 213 00:12:18,880 --> 00:12:21,480 Speaker 4: a terrific idea. So I think the Inflation Reduction Act 214 00:12:21,520 --> 00:12:24,360 Speaker 4: was a wonderful, wonderful piece of legislation. It may have 215 00:12:24,400 --> 00:12:28,920 Speaker 4: had a very very slight effect reducing inflation, but that's 216 00:12:29,160 --> 00:12:31,600 Speaker 4: probably not where most of the effect came from. 217 00:12:31,679 --> 00:12:33,960 Speaker 1: So where did most of the effect come from. 218 00:12:34,040 --> 00:12:37,800 Speaker 4: The seeds of this disinflation were actually right there in 219 00:12:37,840 --> 00:12:40,640 Speaker 4: the causes of inflation. So what happened was during the 220 00:12:40,679 --> 00:12:43,559 Speaker 4: pandemic or the post pandemic period, prices started rising. I 221 00:12:43,600 --> 00:12:46,480 Speaker 4: remember life was chaotic, things were hard to get, shipping 222 00:12:46,559 --> 00:12:49,360 Speaker 4: routes were all massed up. This is what economists call 223 00:12:49,400 --> 00:12:52,240 Speaker 4: a supply shark. And what happened is there's one class 224 00:12:52,240 --> 00:12:54,000 Speaker 4: of economists who were used to the idea that if 225 00:12:54,040 --> 00:12:55,839 Speaker 4: inflation goes up, it must keep going up, or it 226 00:12:55,920 --> 00:12:58,480 Speaker 4: must stay high, and everything's ruined and everything's going to 227 00:12:58,480 --> 00:13:02,520 Speaker 4: be terrible. Another possibility is that a post pandemic readjustment 228 00:13:02,960 --> 00:13:06,079 Speaker 4: is a temporary thing, and if there are some things 229 00:13:06,120 --> 00:13:08,800 Speaker 4: that are a bit messed up, give it time and 230 00:13:09,120 --> 00:13:12,199 Speaker 4: things will get back to normal. And that's essentially what happened, 231 00:13:12,200 --> 00:13:15,480 Speaker 4: which was twenty nineteen was really normal, and twenty twenty 232 00:13:15,480 --> 00:13:17,760 Speaker 4: four the economy is really normal. And what happened in 233 00:13:17,800 --> 00:13:20,160 Speaker 4: between was things got messed up and then they got unmissed. 234 00:13:20,360 --> 00:13:23,280 Speaker 4: When things got missed up, that created inflation. And when 235 00:13:23,320 --> 00:13:25,840 Speaker 4: things were turned back to normal, we got normal rates 236 00:13:25,840 --> 00:13:26,640 Speaker 4: of inflation again. 237 00:13:26,920 --> 00:13:31,120 Speaker 1: So it was really ultimately translatory inflation because of the 238 00:13:31,160 --> 00:13:31,840 Speaker 1: supply chain. 239 00:13:32,280 --> 00:13:36,280 Speaker 4: It was transitory inflation, but the word transitory turned out 240 00:13:36,320 --> 00:13:40,560 Speaker 4: to mean three years rather than three months. And then Moly, 241 00:13:40,800 --> 00:13:43,520 Speaker 4: I hear you looking for a hero in this story, 242 00:13:43,920 --> 00:13:46,480 Speaker 4: and we find this narrative of a little unsatisfying with 243 00:13:46,760 --> 00:13:48,960 Speaker 4: Inflation went up and then it went down. Y' on, 244 00:13:49,800 --> 00:13:54,000 Speaker 4: so let's go looking for a hero. Inflation went up, 245 00:13:54,520 --> 00:13:57,800 Speaker 4: and every right wing economist around the world said the 246 00:13:57,880 --> 00:14:00,720 Speaker 4: Fed needs to create a recession get rid of this. 247 00:14:01,240 --> 00:14:02,920 Speaker 1: Right, But if you. 248 00:14:03,120 --> 00:14:08,120 Speaker 4: Believed that it was really important to emphasize not just 249 00:14:08,200 --> 00:14:12,280 Speaker 4: inflation but keeping people in work, then following the prescription 250 00:14:12,440 --> 00:14:14,560 Speaker 4: of the right wing economists came with a risk you 251 00:14:14,640 --> 00:14:17,520 Speaker 4: might create a recession that you don't really need. And 252 00:14:17,640 --> 00:14:20,760 Speaker 4: so you have to if you really believe in full employment, 253 00:14:21,240 --> 00:14:23,640 Speaker 4: as I do, be willing to take a little bit 254 00:14:23,640 --> 00:14:26,520 Speaker 4: of a risk and say, hey, let's just see how 255 00:14:26,560 --> 00:14:29,320 Speaker 4: this goes for a little while. Inflationhoud might get worse, 256 00:14:29,360 --> 00:14:31,160 Speaker 4: but gee, I want to give this economy a chance 257 00:14:31,200 --> 00:14:35,120 Speaker 4: to heal without me inflicting pain on other people. And 258 00:14:35,560 --> 00:14:40,160 Speaker 4: that is the narrative that yields a hero in this story. 259 00:14:40,160 --> 00:14:43,400 Speaker 4: This says the administration's economic policy was one that was 260 00:14:43,480 --> 00:14:47,080 Speaker 4: fundamentally tied to keeping people in work and respecting the 261 00:14:47,160 --> 00:14:49,680 Speaker 4: dignity of work and the importance of work to their lives. 262 00:14:50,040 --> 00:14:52,760 Speaker 4: And they weren't willing to sacrifice that in order to 263 00:14:52,840 --> 00:14:57,120 Speaker 4: please a right wing economist's talking point. And that took courage, 264 00:14:57,480 --> 00:14:59,200 Speaker 4: and it was a bet. But it's a bet that's 265 00:14:59,240 --> 00:15:01,160 Speaker 4: paying off in million into people's lives today. 266 00:15:01,360 --> 00:15:06,400 Speaker 1: Yeah, recession has so many victims, right, it would be 267 00:15:06,560 --> 00:15:08,320 Speaker 1: terrible for many many Americans. 268 00:15:08,720 --> 00:15:10,720 Speaker 4: Well, you seem to be struggling with the idea that 269 00:15:10,760 --> 00:15:12,640 Speaker 4: recessions are bad. They're awful. 270 00:15:12,920 --> 00:15:16,240 Speaker 1: No, I'm not, but I'm trying to quantify. It's bad 271 00:15:16,360 --> 00:15:20,240 Speaker 1: for workers, but it's also it has downstream effects being 272 00:15:20,320 --> 00:15:23,440 Speaker 1: like bad for people, being miserable, and. 273 00:15:23,600 --> 00:15:27,480 Speaker 4: It's a real kitchen table problem. Right, you can't find work, 274 00:15:27,560 --> 00:15:29,880 Speaker 4: you lose your sense of self. Ours as a society, 275 00:15:29,880 --> 00:15:33,000 Speaker 4: for better or worse, to organize such that we get 276 00:15:33,040 --> 00:15:35,560 Speaker 4: our sense of worth from work. You wake up in 277 00:15:35,600 --> 00:15:37,360 Speaker 4: the morning, you light to your wife and you tell 278 00:15:37,360 --> 00:15:39,400 Speaker 4: her that you're going to go to work because you're 279 00:15:39,400 --> 00:15:41,440 Speaker 4: afraid to tell her that you don't have a job. 280 00:15:41,920 --> 00:15:43,680 Speaker 4: You tell the kids they can't go on the school 281 00:15:43,680 --> 00:15:46,960 Speaker 4: excursion because you don't have cash. There's that awful feeling 282 00:15:46,960 --> 00:15:48,480 Speaker 4: in the pit of your stomach, even if you do 283 00:15:48,600 --> 00:15:51,880 Speaker 4: have work. Layouts are coming next week. Your listeners have 284 00:15:51,960 --> 00:15:55,080 Speaker 4: lived through recessions, and they've lived through those moments, and 285 00:15:55,120 --> 00:15:57,920 Speaker 4: they know how freaking awful they are. And what I 286 00:15:58,040 --> 00:16:00,800 Speaker 4: want is to do right now is for every one 287 00:16:00,840 --> 00:16:03,240 Speaker 4: of your listeners who's not feeling that in the pit 288 00:16:03,280 --> 00:16:06,680 Speaker 4: of the stomach to recognize the absence of that fear 289 00:16:06,800 --> 00:16:10,000 Speaker 4: right now. And that's the payoff of good economics. 290 00:16:10,320 --> 00:16:12,360 Speaker 1: That was the answer I was looking for. Thank you. 291 00:16:12,600 --> 00:16:15,840 Speaker 1: I always believe that it's really important to look at 292 00:16:15,840 --> 00:16:18,360 Speaker 1: the economy in a holistic way. Right, it's not the 293 00:16:18,440 --> 00:16:22,560 Speaker 1: stock market, it's many aspects of our lives that need 294 00:16:22,640 --> 00:16:25,320 Speaker 1: to be sort of looked at as a pesties. I'm 295 00:16:25,360 --> 00:16:29,640 Speaker 1: hoping you could talk to us about right now, at 296 00:16:29,680 --> 00:16:34,960 Speaker 1: this moment, there is Republicans, and again, I think this 297 00:16:35,280 --> 00:16:39,560 Speaker 1: is sort of to be expected with the Republican war 298 00:16:39,640 --> 00:16:42,960 Speaker 1: on the federal government. When you read Project twenty twenty five, 299 00:16:43,040 --> 00:16:47,400 Speaker 1: what you see is that the Republicans are literally at 300 00:16:47,560 --> 00:16:50,600 Speaker 1: war with the federal government. They want it gone, they 301 00:16:50,680 --> 00:16:53,320 Speaker 1: want it not to exist, they want it to be 302 00:16:53,480 --> 00:16:58,320 Speaker 1: an arm of Republican presidencies. You know, they really want 303 00:16:58,320 --> 00:16:59,920 Speaker 1: to shrink it and drown in about them. 304 00:17:00,040 --> 00:17:02,000 Speaker 4: Are you still trying to decide which side to vote for? 305 00:17:02,280 --> 00:17:06,639 Speaker 1: Yes, I'm on the fence. I don't know her emails. 306 00:17:06,880 --> 00:17:09,080 Speaker 1: Just kidding, not in a funny way at all. But 307 00:17:09,200 --> 00:17:13,800 Speaker 1: I'm wondering if you could talk about Marco Rubio. Had 308 00:17:14,000 --> 00:17:16,120 Speaker 1: you know where I'm going here, because the last time 309 00:17:16,160 --> 00:17:19,919 Speaker 1: you were on this podcast, we talked about the non 310 00:17:20,320 --> 00:17:23,600 Speaker 1: partisan Bureau of Farm and Labor Statistics. 311 00:17:24,160 --> 00:17:29,199 Speaker 4: Go, I'm going to lead with fuck Marco Rubios. So 312 00:17:29,320 --> 00:17:31,520 Speaker 4: I'm a nerd, I'm a wonk. I spent my hours 313 00:17:31,560 --> 00:17:34,560 Speaker 4: my life staring at numbers and economic models and trying 314 00:17:34,560 --> 00:17:36,120 Speaker 4: to make sense of it all in the days, I'm 315 00:17:36,119 --> 00:17:38,800 Speaker 4: not doing that. I talked to room fulls of bright 316 00:17:38,840 --> 00:17:41,960 Speaker 4: young undergraduates, helping them understand the world, because I fundamentally 317 00:17:42,000 --> 00:17:45,160 Speaker 4: believe that what we need to do is look at facts, 318 00:17:45,600 --> 00:17:48,080 Speaker 4: design better policies. And I don't care if you're from 319 00:17:48,119 --> 00:17:50,199 Speaker 4: the left of the right. There's always a form of 320 00:17:50,280 --> 00:17:54,720 Speaker 4: better and there's a thing called truth. And for twenty years, 321 00:17:54,760 --> 00:17:59,440 Speaker 4: Marco Rubio marketed himself as being a bright, young wonk. 322 00:17:59,520 --> 00:18:01,560 Speaker 4: He was going to to be the ideas man of 323 00:18:01,680 --> 00:18:05,720 Speaker 4: the Republican Party. He had ideas. They weren't mine, they 324 00:18:05,720 --> 00:18:08,800 Speaker 4: were his. They needed some work. But if you wanted 325 00:18:08,840 --> 00:18:11,439 Speaker 4: to sort of be a center right politician, he was 326 00:18:11,560 --> 00:18:14,040 Speaker 4: kind of trying to do that. Last week, the employment 327 00:18:14,119 --> 00:18:17,960 Speaker 4: numbers came out and Marco Rubio gave up his last 328 00:18:18,119 --> 00:18:21,160 Speaker 4: shred of dignity, just threw it away. He said, these 329 00:18:21,280 --> 00:18:26,000 Speaker 4: numbers are fake. Yeah, everyone who knows anything about economics 330 00:18:26,040 --> 00:18:28,760 Speaker 4: knows the numbers are not fake. I have dozens of 331 00:18:28,800 --> 00:18:32,160 Speaker 4: friends inside the Bureau of Labor Statistics Molly. The day 332 00:18:32,200 --> 00:18:34,760 Speaker 4: they fake it, every one of those friends will resign. 333 00:18:35,280 --> 00:18:37,359 Speaker 4: And the day before they fake it, they'll call me 334 00:18:37,480 --> 00:18:39,800 Speaker 4: to tell me they're thinking about resigning, and I will 335 00:18:39,840 --> 00:18:42,040 Speaker 4: call you, and I will call your listeners and I 336 00:18:42,080 --> 00:18:45,359 Speaker 4: will tell them that the numbers are fake. But what 337 00:18:45,400 --> 00:18:50,000 Speaker 4: they have is very very high quality processes involving literally 338 00:18:50,080 --> 00:18:53,119 Speaker 4: hundreds of people in order to compile these numbers, the 339 00:18:53,200 --> 00:18:56,399 Speaker 4: numbers that come from multiple surveys, and you can cross 340 00:18:56,480 --> 00:18:59,560 Speaker 4: check them against private sector organizations that are doing similar 341 00:18:59,600 --> 00:19:02,560 Speaker 4: things as well. During the Trump administration. The numbers were 342 00:19:02,600 --> 00:19:05,280 Speaker 4: never fake. They were simply good. They were magnificent, they 343 00:19:05,280 --> 00:19:08,040 Speaker 4: were great, they were lovely signs of the best economy ever. 344 00:19:08,080 --> 00:19:09,560 Speaker 4: That's what he kept saying. And then all of a 345 00:19:09,600 --> 00:19:11,760 Speaker 4: sudden in October of twenty twenty four, for the first 346 00:19:11,760 --> 00:19:15,040 Speaker 4: time in his career, Marco Rubio has concerns and he 347 00:19:15,080 --> 00:19:17,840 Speaker 4: doesn't have concerns about the bier Is. You can raise concerns, 348 00:19:17,880 --> 00:19:19,800 Speaker 4: you can describe them, you can say ways in which 349 00:19:19,840 --> 00:19:22,280 Speaker 4: they're fake, how they're fake, what they're not capturing. He 350 00:19:22,440 --> 00:19:25,680 Speaker 4: just says they're fake. And from that day onward, Marco 351 00:19:25,760 --> 00:19:28,760 Speaker 4: Rubio is dead to me as any kind of policy 352 00:19:28,840 --> 00:19:32,399 Speaker 4: wont He's thrown his hat in with the bullshitters and 353 00:19:32,440 --> 00:19:34,920 Speaker 4: the deniers, and there's no coming back from that. 354 00:19:35,160 --> 00:19:37,560 Speaker 1: I just want to go one step further. The reason 355 00:19:37,600 --> 00:19:40,639 Speaker 1: why he says they're fake is not is based on 356 00:19:40,720 --> 00:19:45,359 Speaker 1: the idea that sometimes the Bureau has to revise numbers. 357 00:19:45,760 --> 00:19:48,800 Speaker 1: Explain to us just for a second, what the numbers 358 00:19:48,880 --> 00:19:50,399 Speaker 1: revision process looks like. 359 00:19:50,840 --> 00:19:53,240 Speaker 4: Yeah, so now I'm going to boil your listeners to tears. 360 00:19:53,280 --> 00:19:55,160 Speaker 4: But it's fantastic that we can do that like that. 361 00:19:55,520 --> 00:19:57,159 Speaker 4: The first thing I want your listeners to know is 362 00:19:57,320 --> 00:20:00,960 Speaker 4: the process by which official economics to tear are revised. 363 00:20:01,040 --> 00:20:04,040 Speaker 4: It follows the same calendar, the same process, the same 364 00:20:04,119 --> 00:20:07,080 Speaker 4: everything every year. We've seen this movie before. I've seen 365 00:20:07,119 --> 00:20:09,960 Speaker 4: it fifty one times during my fifty one year life. 366 00:20:10,080 --> 00:20:12,240 Speaker 4: So what happens. First of all, when we want to 367 00:20:12,359 --> 00:20:15,560 Speaker 4: know how many people firms employ, we ask firms how 368 00:20:15,600 --> 00:20:17,960 Speaker 4: many they employ. Some firms don't send their forms in 369 00:20:18,000 --> 00:20:19,560 Speaker 4: on time, and so what we have to do is 370 00:20:19,600 --> 00:20:22,280 Speaker 4: we wait those folks who eventually send their forms, and 371 00:20:22,280 --> 00:20:25,639 Speaker 4: we revise the numbers to include their numbers, to include 372 00:20:25,680 --> 00:20:28,400 Speaker 4: their forms telling us how many people were employed. That's 373 00:20:28,440 --> 00:20:30,880 Speaker 4: the first thing. The second thing is we always adjust 374 00:20:31,040 --> 00:20:34,880 Speaker 4: our numbers for what are called seasonal effects. For instance, 375 00:20:34,920 --> 00:20:37,120 Speaker 4: a lot of people go shopping in December. Now those 376 00:20:37,160 --> 00:20:41,000 Speaker 4: seasonal effects actually change through time. To give you an example, 377 00:20:41,320 --> 00:20:45,000 Speaker 4: we just had my family's favorite holiday, Prime Day, and 378 00:20:45,119 --> 00:20:47,119 Speaker 4: Prime Day didn't used to be a thing, and so 379 00:20:47,160 --> 00:20:50,000 Speaker 4: that means retail sales in October are now stronger than 380 00:20:50,040 --> 00:20:53,040 Speaker 4: they used to be in say, the year two thousand 381 00:20:53,359 --> 00:20:56,280 Speaker 4: and so we have to adjust the seasonal factors to 382 00:20:56,320 --> 00:20:59,680 Speaker 4: take account of changing seasonal patterns. That also causes revisions. 383 00:20:59,720 --> 00:21:00,920 Speaker 4: And the other thing is, if you want to know 384 00:21:00,920 --> 00:21:02,960 Speaker 4: how many people employed, we have to know how many 385 00:21:03,000 --> 00:21:05,399 Speaker 4: people are there in the United States, and we only 386 00:21:05,440 --> 00:21:08,280 Speaker 4: do that well every ten years, and then we updated 387 00:21:08,359 --> 00:21:12,200 Speaker 4: every year, and that sometimes causes what are called benchmark 388 00:21:12,200 --> 00:21:14,600 Speaker 4: revisions how many people are there or how many firms 389 00:21:14,600 --> 00:21:17,200 Speaker 4: are there. None of the revisions over the past few 390 00:21:17,359 --> 00:21:21,280 Speaker 4: weeks and months have been unusual in any historical sense whatsoever. 391 00:21:21,560 --> 00:21:23,280 Speaker 4: Half of them go one way, half of them go 392 00:21:23,359 --> 00:21:26,840 Speaker 4: the other way. There's really just absolutely nothing there. Hey, Molly, 393 00:21:26,880 --> 00:21:28,160 Speaker 4: what do I want you to do is now ask 394 00:21:28,280 --> 00:21:32,720 Speaker 4: me why is it dangerous to start calling government statistics fake? 395 00:21:33,240 --> 00:21:39,359 Speaker 1: Yes, what a good question, interviewe. Why is it dangerous? 396 00:21:39,760 --> 00:21:44,080 Speaker 4: Okay, let's say you're a senator or governor in Florida. 397 00:21:44,119 --> 00:21:46,800 Speaker 4: One day you want to say, the government just published 398 00:21:46,840 --> 00:21:49,439 Speaker 4: the unemployment rate, but it's fake. You should ignore it. 399 00:21:49,640 --> 00:21:51,920 Speaker 4: And the very next day you want to say that 400 00:21:51,960 --> 00:21:56,000 Speaker 4: the government weather bureau believes there's a hurricane coming straight 401 00:21:56,040 --> 00:21:59,040 Speaker 4: for you, and holy shit, you better run. Once you 402 00:21:59,240 --> 00:22:02,600 Speaker 4: cast down on the serious nerds who are giving us 403 00:22:02,640 --> 00:22:05,600 Speaker 4: information so we can live bigger and better lives, it 404 00:22:05,680 --> 00:22:08,160 Speaker 4: just doesn't stop. And so I don't know if you've 405 00:22:08,200 --> 00:22:10,600 Speaker 4: got a grandmother or a friend or a neighbor who's 406 00:22:10,640 --> 00:22:13,520 Speaker 4: telling you that you know, these hurricanes aren't really happening, 407 00:22:13,600 --> 00:22:16,959 Speaker 4: or democrats control the weather, but it's all the same disease, 408 00:22:17,000 --> 00:22:19,640 Speaker 4: and it's a disease that Marco Rubio is feeding, which 409 00:22:19,720 --> 00:22:22,480 Speaker 4: is when you call some stuff fake, you raise suspicion 410 00:22:22,480 --> 00:22:26,160 Speaker 4: about everything, and that means that people can't take information 411 00:22:26,320 --> 00:22:28,840 Speaker 4: seriously and it leads real people to make bad decisions 412 00:22:28,880 --> 00:22:29,680 Speaker 4: in their lives. 413 00:22:30,080 --> 00:22:33,000 Speaker 1: Yeah, and I have an aunt who's in the path 414 00:22:33,160 --> 00:22:35,960 Speaker 1: of the hurricane right now, and I pray that she's okay. 415 00:22:36,040 --> 00:22:38,040 Speaker 1: But I think that's a really good point. You can't 416 00:22:38,320 --> 00:22:40,960 Speaker 1: trust the federal government for some things and not for 417 00:22:41,040 --> 00:22:43,960 Speaker 1: other things. That is not a good message, and that's 418 00:22:43,960 --> 00:22:45,720 Speaker 1: what Republicans are doing right now. 419 00:22:46,000 --> 00:22:49,080 Speaker 4: It's a very very dangerous thing. And there are people, 420 00:22:49,119 --> 00:22:51,080 Speaker 4: and I hope it's not your aunt, who are leaving 421 00:22:51,080 --> 00:22:54,359 Speaker 4: themselves in harm's way right now because they believe that 422 00:22:54,480 --> 00:22:56,360 Speaker 4: you can't trust what the government's telling you. 423 00:22:56,520 --> 00:22:59,960 Speaker 1: Yeah, and I think that's really scary. So you can't 424 00:23:00,080 --> 00:23:02,520 Speaker 1: to me. I'll probably have you back before the election, 425 00:23:03,040 --> 00:23:06,960 Speaker 1: but it is in twenty seven days. So if Vice 426 00:23:07,000 --> 00:23:09,679 Speaker 1: President Harris, who has in some ways the benefit of 427 00:23:09,720 --> 00:23:12,639 Speaker 1: incumbency and in some ways not, is this a good 428 00:23:12,800 --> 00:23:14,720 Speaker 1: economy to be an incumbinant. 429 00:23:15,160 --> 00:23:19,120 Speaker 4: I believe it is. What's less clear is how much 430 00:23:19,200 --> 00:23:21,960 Speaker 4: that message is breaking through. And so for your listeners, 431 00:23:21,960 --> 00:23:25,000 Speaker 4: who I have a guess lean liberal, you probably want 432 00:23:25,040 --> 00:23:27,480 Speaker 4: to make sure you have some good talking points to 433 00:23:27,520 --> 00:23:33,960 Speaker 4: take to Thanksgiving because nerds like me and charismatic podcast 434 00:23:34,040 --> 00:23:38,200 Speaker 4: hosts like you, Molly only get so far. The folks 435 00:23:38,320 --> 00:23:41,600 Speaker 4: who voters are going to believe their nephews and nieces, 436 00:23:41,680 --> 00:23:44,200 Speaker 4: brothers and sisters and the folks around the Thanksgivting table. 437 00:23:44,480 --> 00:23:48,000 Speaker 4: And so my plea to your listeners is learn the 438 00:23:48,080 --> 00:23:51,920 Speaker 4: facts that unemployment's near a fifty year low, that inflation 439 00:23:52,000 --> 00:23:55,600 Speaker 4: has happened, and is behind us. That inflation happened to 440 00:23:55,720 --> 00:23:58,200 Speaker 4: at least as large as a degree in every other 441 00:23:58,320 --> 00:24:01,800 Speaker 4: industrialized country, but the US has recovered even faster, that 442 00:24:01,880 --> 00:24:05,520 Speaker 4: inequality has fallen, that as much as inflation was painful, 443 00:24:05,560 --> 00:24:08,280 Speaker 4: wages have risen ahead of inflation. So the reality is 444 00:24:08,280 --> 00:24:10,760 Speaker 4: for most American workers, you can in fact afford more 445 00:24:10,800 --> 00:24:14,760 Speaker 4: today than you could in twenty nineteen. And also that 446 00:24:14,880 --> 00:24:19,840 Speaker 4: the cavalcade of lies coming from Trump's so called policy 447 00:24:19,920 --> 00:24:23,479 Speaker 4: process is just whatever he happens to think about at 448 00:24:23,520 --> 00:24:26,720 Speaker 4: any given moment. And if you add it all up, 449 00:24:26,880 --> 00:24:29,280 Speaker 4: it's clear that he doesn't actually mean any of it 450 00:24:29,359 --> 00:24:31,439 Speaker 4: because it would bankrupt the federal government. 451 00:24:31,640 --> 00:24:34,760 Speaker 1: Yes it does, Thank you, thank you, thank you. 452 00:24:35,000 --> 00:24:37,960 Speaker 4: Justin and a great pleasure, and let's enjoy the next 453 00:24:38,000 --> 00:24:39,399 Speaker 4: few weeks. And let me say to all of us, 454 00:24:39,480 --> 00:24:41,240 Speaker 4: let's look after ourselves out there. Okay. 455 00:24:42,119 --> 00:24:44,920 Speaker 1: Are you concerned about Project twenty twenty five and how 456 00:24:44,960 --> 00:24:48,639 Speaker 1: awful Trump's second term could be? Well, so are we, 457 00:24:48,920 --> 00:24:51,159 Speaker 1: which is why we teamed up with iHeart to make 458 00:24:51,200 --> 00:24:54,840 Speaker 1: a limited series with the experts on what a disaster 459 00:24:55,320 --> 00:24:59,000 Speaker 1: Project twenty twenty five would be for America's future. Right now, 460 00:24:59,040 --> 00:25:01,879 Speaker 1: we have just really at least the final episode of 461 00:25:01,880 --> 00:25:05,639 Speaker 1: this five episode series. They're all available by looking up 462 00:25:05,760 --> 00:25:09,679 Speaker 1: Molly Jong Fast Project twenty twenty five on YouTube. And 463 00:25:09,800 --> 00:25:12,359 Speaker 1: if you are more of a podcast person and not 464 00:25:12,600 --> 00:25:15,840 Speaker 1: say a YouTuber, you can hit play and put your 465 00:25:15,880 --> 00:25:18,359 Speaker 1: phone in the lock screen and it will play back 466 00:25:18,600 --> 00:25:22,320 Speaker 1: just like a podcast. All five episodes are online now. 467 00:25:22,520 --> 00:25:25,359 Speaker 1: We need to educate Americans on what Trump's second term 468 00:25:25,600 --> 00:25:28,920 Speaker 1: would or could do to this country, So please watch 469 00:25:28,960 --> 00:25:34,520 Speaker 1: it and spread the word. Gary Peters is the junior 470 00:25:34,680 --> 00:25:42,520 Speaker 1: Senator from Michigan and the chairperson for the DSCC. Welcome 471 00:25:43,000 --> 00:25:46,520 Speaker 1: back to Fast Politics, Senator Gary Peters. 472 00:25:46,680 --> 00:25:47,960 Speaker 5: Well, it's great to be with you. 473 00:25:48,359 --> 00:25:52,240 Speaker 1: Let's dive in to the Senate map because you are 474 00:25:52,440 --> 00:25:55,119 Speaker 1: both the senator from the great state of Michigan, so 475 00:25:55,160 --> 00:25:57,960 Speaker 1: we can talk about Michigan. But also you are the 476 00:25:58,000 --> 00:26:02,119 Speaker 1: head honcho when it comes to the incredibly tight and 477 00:26:02,280 --> 00:26:04,280 Speaker 1: tough Senate map for Democrats. 478 00:26:04,520 --> 00:26:07,400 Speaker 5: Yeah, that's right. It's a tough map, but I think 479 00:26:07,680 --> 00:26:10,639 Speaker 5: where we thought we would be right now, and basically 480 00:26:10,680 --> 00:26:13,239 Speaker 5: we're kind of following the same strategy that we use 481 00:26:13,320 --> 00:26:15,520 Speaker 5: last cycle. As you recall, I ran the d SEC 482 00:26:15,640 --> 00:26:17,679 Speaker 5: last cycle and we had a tough map, and we 483 00:26:17,760 --> 00:26:19,960 Speaker 5: had a history against us, but we were able to 484 00:26:19,960 --> 00:26:22,159 Speaker 5: hold the majority and expand it and I'm expecting to 485 00:26:22,200 --> 00:26:22,720 Speaker 5: do that again. 486 00:26:22,840 --> 00:26:26,800 Speaker 1: Democrats had a tough map, but it actually did really well. 487 00:26:27,080 --> 00:26:31,760 Speaker 1: This map is tough, it's complicated. Let's start with Senator 488 00:26:31,800 --> 00:26:33,040 Speaker 1: Tester seat in Montana. 489 00:26:33,280 --> 00:26:34,639 Speaker 5: Yeah, Montana is a tough place. 490 00:26:34,680 --> 00:26:34,840 Speaker 4: You know. 491 00:26:35,040 --> 00:26:38,440 Speaker 5: Montana is a state that will likely vote for Donald 492 00:26:38,480 --> 00:26:41,479 Speaker 5: Trump by roughly twenty points or more. That's not an 493 00:26:41,480 --> 00:26:43,680 Speaker 5: easy place for a Democrat. The good news is that 494 00:26:43,800 --> 00:26:46,320 Speaker 5: John Tester knows how to win in Montana. He's had 495 00:26:46,359 --> 00:26:50,200 Speaker 5: tough races before, he has it again. He knows how 496 00:26:50,240 --> 00:26:52,680 Speaker 5: to win, and over the years he's been able to 497 00:26:52,880 --> 00:26:57,000 Speaker 5: build relationships with people in Montana. Although Montana is a 498 00:26:57,119 --> 00:27:01,520 Speaker 5: huge state geographically, it's actually fairly small population wise. It's 499 00:27:01,800 --> 00:27:05,159 Speaker 5: a little more than a congressional district, so basically you 500 00:27:05,200 --> 00:27:06,960 Speaker 5: get to know a lot of folks and not a 501 00:27:07,000 --> 00:27:08,920 Speaker 5: whole lot of votes makes the difference there. 502 00:27:09,080 --> 00:27:11,879 Speaker 1: I think the thing that makes this Senate map and 503 00:27:11,920 --> 00:27:15,960 Speaker 1: this election cycle so crazy making is that the polls 504 00:27:16,000 --> 00:27:20,480 Speaker 1: are not necessarily consistent. So right now we're seeing Harrison 505 00:27:20,560 --> 00:27:24,280 Speaker 1: a pretty good trajectory of pulling better and better. I 506 00:27:24,480 --> 00:27:28,399 Speaker 1: have seen not so many poles out of Montana, but 507 00:27:28,560 --> 00:27:32,000 Speaker 1: I have also seen polls that have she up. But 508 00:27:32,080 --> 00:27:35,080 Speaker 1: then I've seen polls that have tests her up in fact. 509 00:27:35,119 --> 00:27:37,000 Speaker 1: And I mean, is this a state where there's just 510 00:27:37,040 --> 00:27:38,040 Speaker 1: not a ton of polling? 511 00:27:38,160 --> 00:27:40,199 Speaker 5: Well, there's actually there's been a lot of polling, but 512 00:27:40,240 --> 00:27:42,400 Speaker 5: it is inconsistent to your point. You know, that bounces 513 00:27:42,440 --> 00:27:45,920 Speaker 5: around a lot, and it's not unexpected because it's just 514 00:27:45,960 --> 00:27:48,679 Speaker 5: a really difficult place to poll. It's a rural area 515 00:27:48,920 --> 00:27:50,919 Speaker 5: and right now, actually there's a lot of folks that 516 00:27:50,960 --> 00:27:53,720 Speaker 5: are that are pulling there. At least they're calling folks 517 00:27:53,760 --> 00:27:57,040 Speaker 5: because it is such a hotly contested place and because 518 00:27:57,040 --> 00:27:58,480 Speaker 5: there isn't a lot of people that they're getting a 519 00:27:58,520 --> 00:28:00,360 Speaker 5: lot of calls back to you. You know, addecdonally, you talk 520 00:28:00,400 --> 00:28:02,760 Speaker 5: to people in Montana, they're saying, like a poster's calling 521 00:28:02,800 --> 00:28:06,120 Speaker 5: me all the time, and they're saying, please don't call 522 00:28:06,160 --> 00:28:08,320 Speaker 5: me anymore, and they're using more colorful language than I 523 00:28:08,400 --> 00:28:08,760 Speaker 5: just did. 524 00:28:10,960 --> 00:28:14,160 Speaker 1: You had a sort of similar situation with your race, 525 00:28:14,280 --> 00:28:17,120 Speaker 1: I mean, maybe not quite the same, but you had 526 00:28:17,320 --> 00:28:20,399 Speaker 1: a lot of polling stuff like that. Do you think 527 00:28:20,480 --> 00:28:24,920 Speaker 1: that this is just the state of polling, and also 528 00:28:25,080 --> 00:28:27,920 Speaker 1: were there things that you think helped you towards the end? 529 00:28:28,320 --> 00:28:30,320 Speaker 5: Yeah, I mean pulling it's a science, but there's also 530 00:28:30,359 --> 00:28:32,680 Speaker 5: a lot of art involved in it. And the thing 531 00:28:32,680 --> 00:28:35,600 Speaker 5: about polling is that you have to try to figure 532 00:28:35,600 --> 00:28:37,639 Speaker 5: out exactly who's going to come out to vote, and 533 00:28:37,680 --> 00:28:39,760 Speaker 5: so you have to have the right kind of sampling 534 00:28:39,960 --> 00:28:42,800 Speaker 5: of demographics and gender, you know, all those kinds of 535 00:28:42,840 --> 00:28:47,120 Speaker 5: issues and people who lean Republican or Democrat. So there's 536 00:28:47,160 --> 00:28:49,400 Speaker 5: a lot of art and if the poster gets that wrong, 537 00:28:49,720 --> 00:28:52,480 Speaker 5: their numbers are going to be off. And so you 538 00:28:52,520 --> 00:28:55,080 Speaker 5: do see a lot of polls that have different numbers, 539 00:28:55,320 --> 00:28:57,640 Speaker 5: and part of it's probably because their model is a 540 00:28:57,680 --> 00:29:00,360 Speaker 5: little different to when they're doing that. So the question 541 00:29:00,520 --> 00:29:03,800 Speaker 5: is is it systematic error? And you try to minimize that, 542 00:29:03,920 --> 00:29:06,320 Speaker 5: and why you see these polling aggregators, you know, these 543 00:29:06,320 --> 00:29:08,440 Speaker 5: services that will take a look at ten polls and 544 00:29:08,480 --> 00:29:10,640 Speaker 5: then they average the numbers and they think, well, maybe 545 00:29:10,680 --> 00:29:12,600 Speaker 5: then we're you know, we're smoothing out some of the 546 00:29:12,720 --> 00:29:16,040 Speaker 5: errors there. But even that is not always accurate. The 547 00:29:16,040 --> 00:29:18,440 Speaker 5: only poll that's going to matter is on election day, 548 00:29:18,520 --> 00:29:21,120 Speaker 5: and other than that, everything else you get it. I 549 00:29:21,160 --> 00:29:23,440 Speaker 5: always take it with a grain of salt, especially in 550 00:29:23,480 --> 00:29:26,240 Speaker 5: a small state like Montana, where a lot of people 551 00:29:26,400 --> 00:29:28,880 Speaker 5: don't want to answer poles for a variety of reasons, 552 00:29:28,920 --> 00:29:31,280 Speaker 5: and so you often have to ask your question, who 553 00:29:31,320 --> 00:29:33,480 Speaker 5: is actually spending time with a polster telling them what 554 00:29:33,520 --> 00:29:36,560 Speaker 5: they think? And who is not? And who are you 555 00:29:36,600 --> 00:29:38,600 Speaker 5: missing because of a group of people who do not 556 00:29:38,680 --> 00:29:39,680 Speaker 5: want to talk to a bolster. 557 00:29:40,000 --> 00:29:45,280 Speaker 1: So certain races have been like boons for Democrats and 558 00:29:45,360 --> 00:29:48,280 Speaker 1: could not have worked out better. I'm thinking of Kirsten's 559 00:29:48,320 --> 00:29:52,160 Speaker 1: Cinema not running for re election, Ruben Diego getting in 560 00:29:52,200 --> 00:29:56,200 Speaker 1: there early, raising a boatload of money, continues to pull 561 00:29:56,240 --> 00:30:00,920 Speaker 1: about ten points ahead of the woman who considers herself 562 00:30:01,000 --> 00:30:04,360 Speaker 1: to be the rightful governor of the state. Carrie, Like 563 00:30:04,480 --> 00:30:07,640 Speaker 1: that turned out trump Ism doesn't scale there. But like, 564 00:30:07,800 --> 00:30:10,960 Speaker 1: talk to me about your own state of Michigan. Because 565 00:30:11,000 --> 00:30:15,560 Speaker 1: you have the Debby's Dabina has retired, is not running 566 00:30:15,560 --> 00:30:18,400 Speaker 1: for reelection, You've got a lease lock in there. The 567 00:30:18,440 --> 00:30:21,200 Speaker 1: polling seems to be good, but again, Michigan has a 568 00:30:21,320 --> 00:30:22,480 Speaker 1: number of factors apply. 569 00:30:23,000 --> 00:30:26,520 Speaker 5: Yeah, in Michigan is a tough state. We are a 570 00:30:26,560 --> 00:30:30,120 Speaker 5: battleground state. So by definition. We're a really close state, 571 00:30:30,200 --> 00:30:31,920 Speaker 5: so the numbers are going to be close as which 572 00:30:31,960 --> 00:30:34,600 Speaker 5: way we would have expected. You know, folks looked at 573 00:30:34,600 --> 00:30:37,320 Speaker 5: the election last cycle. We didn't have a Senate race, 574 00:30:37,360 --> 00:30:39,880 Speaker 5: but all of our Democrats did well. But I remind 575 00:30:39,920 --> 00:30:43,920 Speaker 5: folks we had Proposition three, which enshrined abortion rights into 576 00:30:43,960 --> 00:30:47,800 Speaker 5: the state constitution. It was by far the top vote getter. 577 00:30:47,920 --> 00:30:50,280 Speaker 5: It got more votes than anybody on the ballot, and 578 00:30:50,320 --> 00:30:53,240 Speaker 5: people who showed up tended to be folks who lean Democratic, 579 00:30:53,280 --> 00:30:55,840 Speaker 5: and we're voting for Democratic candidates. But this year we 580 00:30:55,880 --> 00:30:58,040 Speaker 5: don't have that. We don't have a referendum like that, 581 00:30:58,200 --> 00:31:00,840 Speaker 5: and so we now revert to the me which means 582 00:31:00,840 --> 00:31:03,840 Speaker 5: Michigan is a close state. When I ran in twenty 583 00:31:04,200 --> 00:31:06,720 Speaker 5: with Joe Biden on the ticket, I won by roughly 584 00:31:06,760 --> 00:31:08,880 Speaker 5: two points and he run one by roughly two and 585 00:31:08,920 --> 00:31:10,840 Speaker 5: a half points, So you know, it's a close race. 586 00:31:11,120 --> 00:31:14,000 Speaker 1: Yeah, what do you think Democrats should be doing to 587 00:31:14,080 --> 00:31:14,840 Speaker 1: win Michigan. 588 00:31:15,200 --> 00:31:17,160 Speaker 5: We have to make sure that we are running really 589 00:31:17,240 --> 00:31:20,200 Speaker 5: strong ground campaign and that's what we're doing. It's about 590 00:31:20,200 --> 00:31:23,120 Speaker 5: getting out talking to voters and then identifying those voters 591 00:31:23,200 --> 00:31:25,160 Speaker 5: who are with us, and then we have to make 592 00:31:25,200 --> 00:31:27,840 Speaker 5: sure that they actually vote. It's not enough just to 593 00:31:27,880 --> 00:31:29,840 Speaker 5: stay on a poll. I'm going to support so and so. 594 00:31:30,040 --> 00:31:32,760 Speaker 5: Are they actually getting a ballot and voting. Right now, 595 00:31:32,880 --> 00:31:36,080 Speaker 5: it's election day in Michigan, and it has been for 596 00:31:36,120 --> 00:31:38,680 Speaker 5: a few days because we have no reason absentee and 597 00:31:38,720 --> 00:31:41,640 Speaker 5: so people can request an absentee ballot or go to 598 00:31:41,680 --> 00:31:43,680 Speaker 5: the clerk and get an absentee ballot and they can 599 00:31:43,760 --> 00:31:46,280 Speaker 5: vote today if they'd like. And so we treat every 600 00:31:46,400 --> 00:31:51,120 Speaker 5: day now until November as election day and identifying our 601 00:31:51,240 --> 00:31:53,840 Speaker 5: voters and then keeping track of them to see when 602 00:31:53,880 --> 00:31:56,120 Speaker 5: they actually turn in their ballot, and if they haven't, 603 00:31:56,440 --> 00:31:59,840 Speaker 5: remind them gently at first, and then sometimes keep calling 604 00:31:59,840 --> 00:32:01,760 Speaker 5: them if you need to. And that make sure that 605 00:32:01,840 --> 00:32:05,440 Speaker 5: you can get the votes in because in a closer election, 606 00:32:05,680 --> 00:32:09,360 Speaker 5: the better ground operation can truly be a decisive factor. 607 00:32:09,560 --> 00:32:13,600 Speaker 1: And Harris has a bunch of offices in Michigan, right, 608 00:32:13,680 --> 00:32:16,120 Speaker 1: doesn't she have tons and tons of field offices. 609 00:32:16,320 --> 00:32:19,000 Speaker 5: Yeah, we do. We have a very robust field operation 610 00:32:19,320 --> 00:32:21,360 Speaker 5: here in Michigan. People are door knocking and I'll tell 611 00:32:21,400 --> 00:32:23,560 Speaker 5: you the thing that is very exciting, and it's not 612 00:32:23,640 --> 00:32:26,479 Speaker 5: just in Michigan. I can say this confidently from all 613 00:32:26,560 --> 00:32:29,400 Speaker 5: the states that I'm working on across the country that 614 00:32:29,440 --> 00:32:33,480 Speaker 5: have Senate races, is that voter enthusiasm for Kamala Harris 615 00:32:33,600 --> 00:32:36,440 Speaker 5: is very high. People are very excited about her campaign. 616 00:32:36,560 --> 00:32:40,160 Speaker 5: So the number of volunteers that we're getting is very large, 617 00:32:40,200 --> 00:32:43,640 Speaker 5: and it's spiked. It's interesting after Joe Biden decided that 618 00:32:43,720 --> 00:32:45,760 Speaker 5: he did not want to run and pass the torch 619 00:32:46,000 --> 00:32:48,960 Speaker 5: to Kamala Harris within a week as an example, the 620 00:32:49,040 --> 00:32:51,719 Speaker 5: number of volunteers, and these are volunteers we've been We 621 00:32:51,720 --> 00:32:54,000 Speaker 5: were recruiting for roughly a year and a half up 622 00:32:54,040 --> 00:32:56,520 Speaker 5: to the time that Joe Biden dropped out, but in 623 00:32:56,520 --> 00:32:59,680 Speaker 5: that next week the number doubled statewide. I mean, it 624 00:32:59,720 --> 00:33:02,720 Speaker 5: was just a huge rush of people and that has continued. 625 00:33:02,760 --> 00:33:06,400 Speaker 5: So we have very robust canvassing. People are excited and 626 00:33:06,440 --> 00:33:07,960 Speaker 5: what's most exciting to me, there are a lot of 627 00:33:07,960 --> 00:33:10,880 Speaker 5: young people. And when I've done canvas kickoffs and I 628 00:33:10,880 --> 00:33:13,560 Speaker 5: talked to young folks, probably over half of them say 629 00:33:13,600 --> 00:33:15,440 Speaker 5: this is the first campaign they've ever worked on, which 630 00:33:15,480 --> 00:33:16,160 Speaker 5: is really exciting. 631 00:33:16,440 --> 00:33:19,400 Speaker 1: Following up with that, what are the voter registration numbers? 632 00:33:19,840 --> 00:33:22,200 Speaker 5: The total registration. I don't have the percentage right, we 633 00:33:22,200 --> 00:33:24,480 Speaker 5: have a pretty high number we have. I think already 634 00:33:24,640 --> 00:33:27,120 Speaker 5: the last number I saw is over two million absentee 635 00:33:27,160 --> 00:33:31,480 Speaker 5: ballots have been requested. We'll probably have five and a 636 00:33:31,480 --> 00:33:34,080 Speaker 5: half million folks vote here in Michigan, somewhere in that range, 637 00:33:34,080 --> 00:33:36,560 Speaker 5: and so already a pretty big number of people have 638 00:33:36,640 --> 00:33:37,960 Speaker 5: requested absentee ballots. 639 00:33:38,200 --> 00:33:41,600 Speaker 1: In my mind, it strikes me that the metrics you know, 640 00:33:42,320 --> 00:33:46,640 Speaker 1: are positive for her, that are in some ways they 641 00:33:46,640 --> 00:33:49,720 Speaker 1: don't necessarily mean you win an election, but they certainly 642 00:33:49,800 --> 00:33:54,880 Speaker 1: are important. Data points are first time volunteers, first time donors, 643 00:33:55,400 --> 00:33:59,800 Speaker 1: voter registration. Right, Aren't those all numbers that are important? 644 00:34:00,120 --> 00:34:02,320 Speaker 5: Yeah, there's no question. Yeah, all of that are our 645 00:34:02,360 --> 00:34:06,360 Speaker 5: indicators for you, and those are good. But I'll say 646 00:34:06,360 --> 00:34:10,200 Speaker 5: there's enthusiasm on the Republican side too, So we definitely 647 00:34:10,640 --> 00:34:12,719 Speaker 5: know that we have to work right to the end. 648 00:34:12,719 --> 00:34:14,840 Speaker 5: We got to keep raising money. I mean, we're seeing 649 00:34:15,080 --> 00:34:18,600 Speaker 5: massive amount of money coming in into the from Republicans 650 00:34:18,640 --> 00:34:21,640 Speaker 5: into their candidates right now. You know, Tammy Balden had 651 00:34:21,640 --> 00:34:24,640 Speaker 5: this big influx. Bob Casey has a billionaire that put 652 00:34:24,760 --> 00:34:29,120 Speaker 5: thirty million against him. Crypto folks put forty million against 653 00:34:29,120 --> 00:34:32,640 Speaker 5: Sharon Brown in Ohio. So as this money is coming in, 654 00:34:33,280 --> 00:34:35,759 Speaker 5: that is a challenge and we're working to try to 655 00:34:35,800 --> 00:34:37,000 Speaker 5: match it as much as we can. 656 00:34:37,280 --> 00:34:42,480 Speaker 1: Let's talk about Dan Osborne. Not a Democrat, he's an independent. 657 00:34:42,880 --> 00:34:49,120 Speaker 1: There's some pretty incredible polland coming out of Nebraska for 658 00:34:49,200 --> 00:34:53,360 Speaker 1: any number of reasons, perhaps also because Republicans tried to 659 00:34:53,400 --> 00:34:57,360 Speaker 1: take away that electoral vote from Omaha. Talk to me 660 00:34:57,560 --> 00:35:00,440 Speaker 1: about are you helping him out? What is that like? 661 00:35:00,760 --> 00:35:03,560 Speaker 5: Yeah, no, you know, I'm the chair of the Democratic 662 00:35:03,640 --> 00:35:06,279 Speaker 5: Campaign Committee and so we support democrats. He is not 663 00:35:06,360 --> 00:35:09,799 Speaker 5: a Democrat, so I'm not engaged in that race in 664 00:35:09,840 --> 00:35:10,680 Speaker 5: any way. Oh. 665 00:35:10,960 --> 00:35:15,480 Speaker 1: Interesting, So talk to me about the other races that 666 00:35:15,760 --> 00:35:18,839 Speaker 1: are right now sort of what you're focused on. 667 00:35:19,160 --> 00:35:22,000 Speaker 5: Yeah, we talked about Montana, which is without question the 668 00:35:22,600 --> 00:35:26,160 Speaker 5: toughest race for us, But then right behind that is Ohio. 669 00:35:26,480 --> 00:35:30,040 Speaker 5: That's Shared Brown, who is the only statewide Democrat in Ohio, 670 00:35:30,080 --> 00:35:32,399 Speaker 5: and Ohio used to be a battleground state has now 671 00:35:32,440 --> 00:35:36,200 Speaker 5: really drifted more to a Republican state. And Trump won 672 00:35:36,239 --> 00:35:38,880 Speaker 5: there by eight or nine points and will likely do 673 00:35:39,160 --> 00:35:42,200 Speaker 5: the same there. But Sharon Brown knows how to win. 674 00:35:42,480 --> 00:35:47,160 Speaker 5: He's consistently one because he's a very authentic individual who 675 00:35:47,239 --> 00:35:50,920 Speaker 5: cares deeply about working people and unions in his state, 676 00:35:51,040 --> 00:35:53,840 Speaker 5: and people have been supportive of them over many years, 677 00:35:53,880 --> 00:35:57,200 Speaker 5: and I'm confident he can win. But that's another state 678 00:35:57,280 --> 00:35:59,800 Speaker 5: that is really tight. When you have the top of 679 00:35:59,840 --> 00:36:02,040 Speaker 5: the ticket winning by eight or nine points, that's a 680 00:36:02,040 --> 00:36:05,479 Speaker 5: lot of gravity for a Senate candidate. But Sharon Brown 681 00:36:05,480 --> 00:36:07,839 Speaker 5: has done it in the past, and currently right now 682 00:36:07,840 --> 00:36:10,439 Speaker 5: in Napolling, he's up not a lot. It's a tight race, 683 00:36:10,480 --> 00:36:12,239 Speaker 5: and so we know we're going to have to run hard. 684 00:36:12,640 --> 00:36:15,719 Speaker 5: He's running against a flawed candidate. And if you probably 685 00:36:15,760 --> 00:36:18,720 Speaker 5: asked me if there's one theme that we can say, 686 00:36:19,200 --> 00:36:22,200 Speaker 5: all of our Republican opponents are kind of a If 687 00:36:22,239 --> 00:36:24,080 Speaker 5: you're going to put him on a spectrum, it would 688 00:36:24,120 --> 00:36:27,880 Speaker 5: start at flawed candidate and then move to very flawed candidate. 689 00:36:28,840 --> 00:36:31,920 Speaker 5: And you mentioned one in Arizona. Carry Lake pushes the 690 00:36:32,040 --> 00:36:35,000 Speaker 5: envelope on the very flawed category as we move on 691 00:36:35,080 --> 00:36:39,359 Speaker 5: that continuum. But certainly the Republican in Ohio the same thing. 692 00:36:40,120 --> 00:36:44,200 Speaker 5: Very flawed. He's really inflated his biography, but he's also 693 00:36:44,560 --> 00:36:47,680 Speaker 5: was a car dealer and refused to pay overtime to 694 00:36:47,760 --> 00:36:51,279 Speaker 5: his employees. They had to sue him to try to 695 00:36:51,280 --> 00:36:54,440 Speaker 5: get the pay that they were deserved and earned. He 696 00:36:54,520 --> 00:36:57,640 Speaker 5: then destroyed documents. He had a fine from the court. 697 00:36:57,920 --> 00:36:59,759 Speaker 5: Not a guy that you'd want in the Senate, someone 698 00:36:59,800 --> 00:37:02,279 Speaker 5: who you think would be fighting for everyday people when 699 00:37:02,320 --> 00:37:04,240 Speaker 5: he tried to cheat amount of money that they earned 700 00:37:04,440 --> 00:37:07,400 Speaker 5: working in his place. And that's just one negative. We 701 00:37:07,440 --> 00:37:10,560 Speaker 5: could go on about negatives versus Shared Brown, who is 702 00:37:10,719 --> 00:37:13,759 Speaker 5: just a man of incredible integrity and character and has 703 00:37:13,760 --> 00:37:15,840 Speaker 5: a truck record of fighting for the people of Ohio. 704 00:37:16,080 --> 00:37:20,399 Speaker 1: So let's talk about Wisconsin Senate race. Tammy Baldwin has 705 00:37:20,480 --> 00:37:25,840 Speaker 1: been up pretty much continuously. Cook political has moved it 706 00:37:26,000 --> 00:37:28,960 Speaker 1: from a lean down to a toss up. What do 707 00:37:29,000 --> 00:37:30,319 Speaker 1: you think the thinking there is. 708 00:37:30,800 --> 00:37:34,319 Speaker 5: Wisconsin is also a tough place. It is also a 709 00:37:34,400 --> 00:37:37,680 Speaker 5: battleground state like Michigan, so we always know that it's 710 00:37:37,719 --> 00:37:41,040 Speaker 5: going to be a close race. And she's running against 711 00:37:41,040 --> 00:37:43,400 Speaker 5: a guy who's got a lot of money. He's basically 712 00:37:43,440 --> 00:37:48,399 Speaker 5: a southern California banker running now in Wisconsin, and he's 713 00:37:48,440 --> 00:37:50,800 Speaker 5: putting a lot of his own money into the race. 714 00:37:51,080 --> 00:37:54,080 Speaker 5: The Republican Committee is putting a lot of money in there. 715 00:37:54,360 --> 00:37:57,000 Speaker 5: But Tammy, similar to the other candidates I've talked about. 716 00:37:57,040 --> 00:38:00,680 Speaker 5: She is a true, authentic person who cares deeply about 717 00:38:00,680 --> 00:38:03,840 Speaker 5: the people of Wisconsin. But you know, she's running against 718 00:38:04,040 --> 00:38:07,200 Speaker 5: a lot of cash coming in. But her opponent is 719 00:38:07,239 --> 00:38:10,480 Speaker 5: also deeply flawed. There's going to be a air deeply flawed. 720 00:38:10,480 --> 00:38:13,080 Speaker 5: And some of the things he said are crazy. I mean, 721 00:38:13,080 --> 00:38:15,080 Speaker 5: one of them was that he didn't think people in 722 00:38:15,200 --> 00:38:18,239 Speaker 5: nursing homes should be able to vote because they're not 723 00:38:18,239 --> 00:38:20,560 Speaker 5: going to be living very long. I mean, it is 724 00:38:20,680 --> 00:38:22,880 Speaker 5: pretty outrageous. That offends so many people. 725 00:38:23,080 --> 00:38:28,000 Speaker 1: There's a Senate candidate, Larry Hogan. He's running against Angela 726 00:38:28,080 --> 00:38:32,440 Speaker 1: also Brooks. He's really, i want to say, a wolf 727 00:38:32,440 --> 00:38:35,880 Speaker 1: in sheep's clothing, right. He seems like a more moderate Republican, 728 00:38:35,920 --> 00:38:39,000 Speaker 1: but he in fact has been asked to run for 729 00:38:39,200 --> 00:38:41,839 Speaker 1: Senate by Mitch McConnell. What are you seeing in that race. 730 00:38:42,080 --> 00:38:44,800 Speaker 5: I think your characterization is accurate. And he's a Republican 731 00:38:45,040 --> 00:38:47,600 Speaker 5: and so if he were to win, he would put 732 00:38:47,640 --> 00:38:51,160 Speaker 5: the Republicans in the majority. Win Kamala Harris, who wins 733 00:38:51,200 --> 00:38:53,880 Speaker 5: as president, as you know as well as anyone, she 734 00:38:54,000 --> 00:38:56,960 Speaker 5: needs a Democratic majority in the Senate or she can't 735 00:38:57,040 --> 00:39:00,279 Speaker 5: accomplish the things that we want her to accomplish. Can't 736 00:39:00,320 --> 00:39:05,240 Speaker 5: even get members of her cabinet confirmed without Republicans consenting 737 00:39:05,239 --> 00:39:08,640 Speaker 5: to it, and they passed. The history is they make 738 00:39:08,719 --> 00:39:13,080 Speaker 5: that extremely difficult. So basically Hogan would give the majority 739 00:39:13,080 --> 00:39:15,840 Speaker 5: to the Republicans, which would make it difficult for Kamala 740 00:39:15,880 --> 00:39:17,600 Speaker 5: Harris to do the work that she needs to do 741 00:39:17,680 --> 00:39:20,080 Speaker 5: and wants to do and will do with the distinction, 742 00:39:20,880 --> 00:39:22,759 Speaker 5: and we just have to remind people of Maryland. I mean, 743 00:39:22,800 --> 00:39:25,279 Speaker 5: Kamala will win Maryland probably by twenty points or more 744 00:39:25,320 --> 00:39:29,480 Speaker 5: as well, but because people remember Hogan as a governor there, 745 00:39:29,760 --> 00:39:32,200 Speaker 5: he does have support. But once you tell people and 746 00:39:32,280 --> 00:39:34,960 Speaker 5: remind them that he is a Republican and that he 747 00:39:35,000 --> 00:39:38,000 Speaker 5: will give control to the Republicans, people and Maryland go 748 00:39:38,080 --> 00:39:40,640 Speaker 5: oh well, no, I've got to make sure Kamala has 749 00:39:40,680 --> 00:39:42,839 Speaker 5: a team member. This is a team sport, and then 750 00:39:42,880 --> 00:39:46,040 Speaker 5: we'll vote for Angela. So the challenge is that everybody 751 00:39:46,040 --> 00:39:47,840 Speaker 5: knows Hogan. He was a governor for a while, so 752 00:39:47,920 --> 00:39:51,720 Speaker 5: his name idea is very high. Angela a very gifted, 753 00:39:51,800 --> 00:39:55,160 Speaker 5: talented person, but she just not as well known. So 754 00:39:55,320 --> 00:39:57,360 Speaker 5: we have to make sure she has the resources for 755 00:39:57,400 --> 00:39:59,200 Speaker 5: people to get to know her, and when they do 756 00:39:59,239 --> 00:40:02,400 Speaker 5: get to know her, she'll win. But that does require resources. 757 00:40:02,640 --> 00:40:07,399 Speaker 1: Yeah, I'll say, Debbie Macarsle Powell in Florida, I want 758 00:40:07,480 --> 00:40:10,919 Speaker 1: you to do two seconds on both her and so 759 00:40:11,080 --> 00:40:14,000 Speaker 1: Colin Allread in Texas. These are states that were not 760 00:40:14,239 --> 00:40:16,400 Speaker 1: on the map but are now sort of being added 761 00:40:16,400 --> 00:40:18,040 Speaker 1: to the map. Just give me the lay of the 762 00:40:18,120 --> 00:40:18,600 Speaker 1: land here. 763 00:40:18,800 --> 00:40:22,319 Speaker 5: In addition to defense, and we're certainly playing defense with 764 00:40:22,360 --> 00:40:25,520 Speaker 5: a lot of our incumbents. And my number one job 765 00:40:25,640 --> 00:40:28,000 Speaker 5: is to make sure all of the incumbents come back. 766 00:40:28,160 --> 00:40:30,120 Speaker 5: I will tell you they remind me of that every week. 767 00:40:30,280 --> 00:40:33,279 Speaker 5: That's my job. But I also know we have an 768 00:40:33,280 --> 00:40:36,359 Speaker 5: opportunity to go on the offense. And both Florida and 769 00:40:36,440 --> 00:40:40,200 Speaker 5: Texas are real the d SC we are investing money 770 00:40:40,200 --> 00:40:42,279 Speaker 5: in both states and will encourage folks who might be 771 00:40:42,320 --> 00:40:45,560 Speaker 5: listening to do that. So, Debbie Mucersel Powell in Florida 772 00:40:45,920 --> 00:40:49,200 Speaker 5: is a gifted person. She's a former congresswoman from the 773 00:40:49,239 --> 00:40:52,440 Speaker 5: Miami area, and she's running against an incumbent, Rick Scott. 774 00:40:52,640 --> 00:40:56,080 Speaker 5: Rick Scott has been a governor and now senator. But 775 00:40:56,120 --> 00:40:58,719 Speaker 5: the thing to remember about him is that even when 776 00:40:58,840 --> 00:41:01,760 Speaker 5: there has been a hailwin behind him with a strong 777 00:41:01,960 --> 00:41:05,120 Speaker 5: Republican year. He's never won by more than just a 778 00:41:05,160 --> 00:41:08,440 Speaker 5: hair over one point, so just one percentage point, very close. 779 00:41:08,480 --> 00:41:11,399 Speaker 5: He's not that popular. And in Florida we have an 780 00:41:11,400 --> 00:41:15,000 Speaker 5: abortion referendum. I mentioned earlier the Michigan referendum and how 781 00:41:15,080 --> 00:41:18,080 Speaker 5: powerful that was, the same thing happening now in Florida. 782 00:41:18,080 --> 00:41:21,040 Speaker 5: And Florida has passed a draconian abortion lawed a six 783 00:41:21,120 --> 00:41:24,200 Speaker 5: week ban and no exceptions for rape and incest. And 784 00:41:24,280 --> 00:41:26,680 Speaker 5: Rick Scott has doubled down. He says he's voting against 785 00:41:26,719 --> 00:41:29,800 Speaker 5: the referendum and supports it. But you have to remember 786 00:41:29,840 --> 00:41:33,600 Speaker 5: that right now, based on public polling, sixty eight percent 787 00:41:33,640 --> 00:41:36,400 Speaker 5: of the people in Florida support the referendum. And my 788 00:41:36,520 --> 00:41:38,600 Speaker 5: experience is if you're on the wrong side of sixty 789 00:41:38,640 --> 00:41:40,320 Speaker 5: eight percent of the people, that's not great. 790 00:41:40,560 --> 00:41:43,880 Speaker 1: Yes, it's not great. Many people are saying, thank you 791 00:41:44,000 --> 00:41:46,120 Speaker 1: so much, Senator Peters. 792 00:41:45,880 --> 00:41:47,160 Speaker 5: Thank you. It's good to be with. 793 00:41:47,080 --> 00:41:50,880 Speaker 2: You a moment. 794 00:41:51,360 --> 00:41:53,840 Speaker 1: Thick Jesse Cannon. 795 00:41:53,920 --> 00:41:56,279 Speaker 2: Malei jung Fast. I'm going to rewind us back to 796 00:41:56,840 --> 00:42:00,600 Speaker 2: when Trump lost the election back in twenty two, and 797 00:42:00,880 --> 00:42:03,120 Speaker 2: there is the whole stop the steel effort, and one 798 00:42:03,160 --> 00:42:05,480 Speaker 2: of the people involved with it was Patrick Burn, who 799 00:42:05,520 --> 00:42:08,840 Speaker 2: is the former CEO of overstock dot Com. What are 800 00:42:08,840 --> 00:42:09,359 Speaker 2: you seeing here? 801 00:42:09,520 --> 00:42:12,600 Speaker 1: Yeah, this is like you had another situation where a 802 00:42:12,640 --> 00:42:15,560 Speaker 1: Trump supporter turns out to be like a low key 803 00:42:15,600 --> 00:42:19,200 Speaker 1: scammer slash total lunatic. This was a guy who was 804 00:42:19,239 --> 00:42:22,080 Speaker 1: supposed to give a deposition in a case brought against 805 00:42:22,160 --> 00:42:25,240 Speaker 1: him by Hunter Biden. He was a Stop the Steel 806 00:42:25,320 --> 00:42:31,040 Speaker 1: guy and he now lives in Dubai because he says 807 00:42:31,320 --> 00:42:34,880 Speaker 1: a Dea agent. Here's how you know that this guy's 808 00:42:34,920 --> 00:42:38,640 Speaker 1: doing great. He says a Dea agent told him that 809 00:42:38,680 --> 00:42:42,000 Speaker 1: the government of Venezuela has put a twenty five million 810 00:42:42,040 --> 00:42:45,080 Speaker 1: dollar bounty on his head. You think the government of 811 00:42:45,200 --> 00:42:48,080 Speaker 1: Venezuela has put a twenty five million dollar bounty on 812 00:42:48,120 --> 00:42:52,440 Speaker 1: his head? I think that someone is not doing great, 813 00:42:52,680 --> 00:42:56,120 Speaker 1: and that is our moment of fuckery. That's it for 814 00:42:56,200 --> 00:43:01,239 Speaker 1: this episode of Fast Politics. Tune in every Monday Day, Wednesday, 815 00:43:01,800 --> 00:43:06,680 Speaker 1: Thursday and Saturday to hear the best minds in politics 816 00:43:06,800 --> 00:43:10,960 Speaker 1: make sense of all the chaos. If you enjoyed this podcast, 817 00:43:11,000 --> 00:43:13,680 Speaker 1: please send it to a friend or an enemy and 818 00:43:13,840 --> 00:43:15,240 Speaker 1: keep the conversation going.