1 00:00:02,560 --> 00:00:07,040 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:12,800 --> 00:00:15,040 Speaker 2: Welcome to Everybody's Business from Bloomberg BusinessWeek. 3 00:00:15,040 --> 00:00:17,120 Speaker 3: I'm Max Chafkin and I'm Stacey Max Smith. 4 00:00:17,360 --> 00:00:20,120 Speaker 2: Stacy, we are a little less as you're listening to this. 5 00:00:20,200 --> 00:00:23,120 Speaker 4: A week from Thanksgiving. It is a time to shop 6 00:00:23,160 --> 00:00:26,880 Speaker 4: for groceries. We've been talking all about how inflation has 7 00:00:26,920 --> 00:00:28,560 Speaker 4: been making stuff more expensive. 8 00:00:28,560 --> 00:00:30,120 Speaker 2: A lot of complaints about food prices. 9 00:00:30,160 --> 00:00:32,280 Speaker 4: But Stacy, we're going to talk about a report that 10 00:00:32,360 --> 00:00:33,720 Speaker 4: kind of points in the other direction. 11 00:00:34,040 --> 00:00:36,440 Speaker 2: Thanksgiving food maybe is getting cheaper. 12 00:00:36,880 --> 00:00:38,840 Speaker 5: We will hash through all of it. It is actually 13 00:00:39,080 --> 00:00:41,480 Speaker 5: kind of complicated. Luckily we have some help. 14 00:00:41,560 --> 00:00:43,840 Speaker 3: We brought in Dina Shanker, food reporter for Business Weeks. 15 00:00:43,840 --> 00:00:44,600 Speaker 3: She'll talk us through that. 16 00:00:45,200 --> 00:00:45,440 Speaker 2: Yeah. 17 00:00:45,479 --> 00:00:49,199 Speaker 4: And then my doppelganger, another Max, Max Abelson is here 18 00:00:49,760 --> 00:00:53,600 Speaker 4: coming to us to talk about these documents, these many 19 00:00:53,640 --> 00:00:56,120 Speaker 4: tens of thousands of pages of documents that are coming 20 00:00:56,160 --> 00:01:00,720 Speaker 4: out around Jeffrey Epstein. Max covers Money and Power for Bloomberg. 21 00:01:00,760 --> 00:01:03,560 Speaker 4: He's really got an interesting take on this. 22 00:01:03,600 --> 00:01:04,839 Speaker 2: I'm excited for the conversation. 23 00:01:05,240 --> 00:01:06,880 Speaker 5: Yes, indeed, and then we're going to talk about our 24 00:01:06,920 --> 00:01:08,520 Speaker 5: underrated stories this week. 25 00:01:08,560 --> 00:01:11,200 Speaker 3: For me, Max, it's all about the k shaped economy. 26 00:01:11,840 --> 00:01:12,360 Speaker 2: Can't wait. 27 00:01:12,400 --> 00:01:15,880 Speaker 4: I've got another letter related underrated story. Stacy, you've heard 28 00:01:15,920 --> 00:01:18,720 Speaker 4: of the taco trade. I'm going to remind you or 29 00:01:18,800 --> 00:01:21,440 Speaker 4: introduce you to the mamout trade. 30 00:01:21,760 --> 00:01:22,520 Speaker 2: It's back. 31 00:01:25,600 --> 00:01:25,880 Speaker 6: Max. 32 00:01:25,920 --> 00:01:28,720 Speaker 5: Before we get started with our show, we do have 33 00:01:28,800 --> 00:01:30,240 Speaker 5: some kind of exciting news. 34 00:01:30,680 --> 00:01:35,039 Speaker 4: Yeah, listeners, we are having a live event. This is 35 00:01:35,240 --> 00:01:39,480 Speaker 4: a special event at the Bloomberg Mothership at Bloomberg Headquarters 36 00:01:39,680 --> 00:01:43,039 Speaker 4: in Midtown, Manhattan on December fourth. You have to be 37 00:01:43,280 --> 00:01:45,440 Speaker 4: a Bloomberg subscriber to go to this. 38 00:01:45,360 --> 00:01:47,119 Speaker 3: Thing, but it's not too late to subscribe. 39 00:01:47,319 --> 00:01:48,040 Speaker 2: Not too late. 40 00:01:48,600 --> 00:01:52,200 Speaker 4: I will be there, Stacy will be there, Bradstone, our 41 00:01:52,200 --> 00:01:53,920 Speaker 4: friend and boss, will be there, and we'll be talking 42 00:01:53,960 --> 00:01:57,560 Speaker 4: to Ellen Hewitt, who is an awesome journalist. She has 43 00:01:57,600 --> 00:01:59,880 Speaker 4: a book coming out. She also wrote a story about 44 00:02:00,120 --> 00:02:03,240 Speaker 4: chatbots and how they are driving people crazy. That's going 45 00:02:03,320 --> 00:02:06,520 Speaker 4: to be kind of the subject of the conversation. People 46 00:02:06,520 --> 00:02:08,120 Speaker 4: should check it out. I know we've got a lot 47 00:02:08,160 --> 00:02:11,400 Speaker 4: of RSVPs. I think there are still some places available now. 48 00:02:11,440 --> 00:02:14,400 Speaker 5: I will say that the event is quite early in 49 00:02:14,440 --> 00:02:16,600 Speaker 5: the morning. It is at eight am, but we were 50 00:02:16,600 --> 00:02:19,600 Speaker 5: going to have extremely strong coffee and from what I understand. 51 00:02:19,680 --> 00:02:22,120 Speaker 5: Everybody's business coasters will be. 52 00:02:22,080 --> 00:02:25,200 Speaker 4: On offer, Stacy. It's called a power breakfast. It's a 53 00:02:25,240 --> 00:02:25,920 Speaker 4: power breakfast. 54 00:02:25,919 --> 00:02:29,600 Speaker 5: We're going to be having a power breakfast with powercoasters. 55 00:02:29,639 --> 00:02:34,600 Speaker 4: So yeah, So go to Bloomberg dot com slash subscriptions subscribe. 56 00:02:34,680 --> 00:02:36,480 Speaker 4: If you are a subscriber, you can go to the 57 00:02:36,480 --> 00:02:39,840 Speaker 4: show notes and you'll see the details for the event. Come, come, 58 00:02:39,880 --> 00:02:42,639 Speaker 4: say hi to me and Stacy. Come ask us some questions. 59 00:02:42,720 --> 00:02:44,520 Speaker 4: We will be there. We are very excited to meet you. 60 00:02:44,560 --> 00:02:48,040 Speaker 4: We will try to be fully alert when this happens. 61 00:02:48,080 --> 00:02:49,520 Speaker 3: This is where the strong coffee comes in. 62 00:02:52,880 --> 00:02:53,680 Speaker 2: All right, Stacy. 63 00:02:53,760 --> 00:02:56,320 Speaker 4: I think before we get into our segments, we got 64 00:02:56,360 --> 00:02:59,080 Speaker 4: to talk about the economic news that's been coming out 65 00:02:59,200 --> 00:03:01,959 Speaker 4: this week. I think starting with these jobs numbers. We 66 00:03:02,040 --> 00:03:05,280 Speaker 4: got numbers for September better than expected. 67 00:03:05,560 --> 00:03:09,000 Speaker 5: Yeah, it is really good news, it seems, especially since 68 00:03:09,040 --> 00:03:11,160 Speaker 5: it has kind of felt like the economies maybe at 69 00:03:11,160 --> 00:03:14,799 Speaker 5: this turning point or in this strange liminal space. So 70 00:03:15,040 --> 00:03:16,480 Speaker 5: a lot of guys were on this job support. Of 71 00:03:16,480 --> 00:03:18,720 Speaker 5: course we didn't get it because of the government shutdown. 72 00:03:18,960 --> 00:03:20,799 Speaker 5: So these are jobs numbers for September. 73 00:03:20,960 --> 00:03:22,280 Speaker 2: Right, these are kind of out of date. 74 00:03:22,360 --> 00:03:25,640 Speaker 4: We're not going to have the jobs numbers for last 75 00:03:25,680 --> 00:03:28,760 Speaker 4: month because the BLS was not people. 76 00:03:28,480 --> 00:03:31,600 Speaker 5: Weren't they didn't have the manpower, the person power to 77 00:03:31,639 --> 00:03:32,359 Speaker 5: take the surveys. 78 00:03:32,800 --> 00:03:34,760 Speaker 3: Now, it was a little bit mixed, I should say so. 79 00:03:34,880 --> 00:03:37,520 Speaker 5: In the month of September, the US economy added about 80 00:03:37,600 --> 00:03:39,480 Speaker 5: one hundred and nineteen thousand jobs. 81 00:03:39,760 --> 00:03:41,160 Speaker 3: That is really good. 82 00:03:41,280 --> 00:03:45,720 Speaker 5: But also the unemployment rate ticked up to a little bit, 83 00:03:45,760 --> 00:03:49,520 Speaker 5: so four point four percent. Unemployment still quite low. Under 84 00:03:49,520 --> 00:03:52,720 Speaker 5: five percent is still considered very low, but it's not 85 00:03:52,760 --> 00:03:53,680 Speaker 5: headed into great direction. 86 00:03:53,800 --> 00:03:57,240 Speaker 4: Yeah, and more good news on Wednesday night in Nvidia 87 00:03:57,320 --> 00:03:59,840 Speaker 4: Reporter earnings. You know, we've been talking a lot about 88 00:04:00,200 --> 00:04:02,880 Speaker 4: how you know, this economy it feels good, but it's 89 00:04:03,040 --> 00:04:05,120 Speaker 4: just it's all just a bunch of AI stiff on 90 00:04:05,240 --> 00:04:08,000 Speaker 4: sugarh And like if the AI bubble burst, We have 91 00:04:08,040 --> 00:04:11,480 Speaker 4: good news. The AI bubble is going strong, and Video 92 00:04:11,960 --> 00:04:15,880 Speaker 4: totally blew the doors off its expectations. Stock has gone 93 00:04:15,920 --> 00:04:18,839 Speaker 4: up this morning as we're recording it. It feels like 94 00:04:18,880 --> 00:04:21,360 Speaker 4: there's still a lot of optimism, at least from kind 95 00:04:21,360 --> 00:04:24,600 Speaker 4: of the company that has benefited most from the AI bubble. 96 00:04:24,800 --> 00:04:26,960 Speaker 5: Yeah, and I feel like AI and jobs, those are 97 00:04:27,000 --> 00:04:29,679 Speaker 5: the two parts of our economy everybody's watching right now, 98 00:04:29,839 --> 00:04:33,280 Speaker 5: the two parts that I feel a little potentially fragile. 99 00:04:33,720 --> 00:04:35,680 Speaker 3: And so both of those came in with good news. 100 00:04:35,680 --> 00:04:37,200 Speaker 3: That is great news. 101 00:04:37,240 --> 00:04:39,800 Speaker 5: Of course, the markets are a little upset about it 102 00:04:39,960 --> 00:04:43,559 Speaker 5: for the comical reason that they're worried that now Jerome 103 00:04:43,640 --> 00:04:47,520 Speaker 5: Powell might not decide to cut interest rates right because 104 00:04:47,640 --> 00:04:51,840 Speaker 5: the job market looks pretty strong, classic class, classic powers. 105 00:04:51,920 --> 00:04:52,800 Speaker 2: Wall Street reaction. 106 00:04:53,120 --> 00:04:56,839 Speaker 4: You know, there is one other indicator that I think 107 00:04:56,920 --> 00:05:00,440 Speaker 4: is arguably more important than in Nvidia earnings, and that 108 00:05:00,640 --> 00:05:05,359 Speaker 4: is the Turkey Index. Thanksgiving Stacy, it is here, it 109 00:05:05,440 --> 00:05:09,480 Speaker 4: is coming. It's obviously a great opportunity to eat and 110 00:05:09,960 --> 00:05:12,920 Speaker 4: see your family and and and share a meal. It's 111 00:05:12,960 --> 00:05:16,919 Speaker 4: also a great opportunity to talk about affordability, right because 112 00:05:17,000 --> 00:05:20,600 Speaker 4: everybody is going out there and buying the same basic 113 00:05:21,080 --> 00:05:24,520 Speaker 4: handful of things. We sent our reporter Charlie Gorivin, who's 114 00:05:24,520 --> 00:05:25,920 Speaker 4: gonna be with us for the next few months on 115 00:05:25,960 --> 00:05:29,920 Speaker 4: the show, out there into the streets to ask people 116 00:05:30,040 --> 00:05:31,919 Speaker 4: about their Thanksgiving plans. 117 00:05:32,080 --> 00:05:33,279 Speaker 2: What are your Thanksgiving plants? 118 00:05:33,920 --> 00:05:37,880 Speaker 5: Go to relatives, I'm actually making Thanksgiving than. 119 00:05:40,040 --> 00:05:44,040 Speaker 3: Its likely if not heard in Masisterdaxity for three days 120 00:05:44,040 --> 00:05:45,080 Speaker 3: with my family. 121 00:05:45,160 --> 00:05:48,320 Speaker 7: And with how the economy is right now, are you 122 00:05:48,360 --> 00:05:50,039 Speaker 7: making a choice to cut back in any way? 123 00:05:50,480 --> 00:05:52,560 Speaker 8: Normally I would have gone down to Florida, So I'm 124 00:05:52,600 --> 00:05:56,800 Speaker 8: not because the airfare is I have gotten so out 125 00:05:56,800 --> 00:05:57,200 Speaker 8: of control. 126 00:05:57,320 --> 00:06:00,000 Speaker 5: We contribute the same every year, so we didn't see 127 00:06:00,080 --> 00:06:01,640 Speaker 5: reason to cutback because it's. 128 00:06:01,520 --> 00:06:06,240 Speaker 2: Not that much. We are a lot more coaches, so 129 00:06:06,920 --> 00:06:08,000 Speaker 2: we're going slowly. 130 00:06:08,160 --> 00:06:10,159 Speaker 5: This is a hard time where the food stamps are cut, 131 00:06:10,200 --> 00:06:11,240 Speaker 5: but it's always cool. 132 00:06:11,400 --> 00:06:13,719 Speaker 2: Are you guys using foods stamps mostly for christ for shopping? 133 00:06:14,240 --> 00:06:16,719 Speaker 4: Is there anything that you've been shopping for recently that's 134 00:06:16,760 --> 00:06:17,680 Speaker 4: really struck you, like. 135 00:06:17,680 --> 00:06:20,200 Speaker 3: Well, staple bread, Milky's a staple stuff. 136 00:06:20,400 --> 00:06:22,279 Speaker 2: Just what I bought skirt steak. It was twenty three 137 00:06:22,320 --> 00:06:23,080 Speaker 2: dollars a pound. 138 00:06:23,240 --> 00:06:25,719 Speaker 8: I never paid that. I had this funny story because 139 00:06:25,720 --> 00:06:28,320 Speaker 8: I wanted to get whipped green because as a treat 140 00:06:28,320 --> 00:06:30,800 Speaker 8: for myself, and I was with my husband and I 141 00:06:30,880 --> 00:06:33,760 Speaker 8: was like, it's eight dollars on principal alone, I will 142 00:06:33,800 --> 00:06:35,760 Speaker 8: not spend eight dollars for whipped. 143 00:06:36,200 --> 00:06:38,640 Speaker 4: Eight dollars for whipped green. That's a non negotiable in 144 00:06:38,720 --> 00:06:41,280 Speaker 4: my house, though, whipped cream. You gotta have the whipped cream. 145 00:06:41,440 --> 00:06:43,400 Speaker 5: Oh yeah, it's the best part of the pumpkin pie. 146 00:06:43,440 --> 00:06:45,760 Speaker 5: And I say this as a person who loves pumpkin pie. 147 00:06:46,320 --> 00:06:54,799 Speaker 9: I love it too, all right, Max, We just heard 148 00:06:54,960 --> 00:06:59,120 Speaker 9: a lot of New Yorkers talking about their Thanksgiving plans 149 00:06:59,440 --> 00:07:03,040 Speaker 9: and how much food costs, and certainly that is very 150 00:07:03,080 --> 00:07:05,480 Speaker 9: top of mind right now, food costs, and. 151 00:07:05,760 --> 00:07:11,360 Speaker 5: Specifically how much this pretty expensive ornate meal that many 152 00:07:11,400 --> 00:07:13,720 Speaker 5: of us make in this country is going to cost. 153 00:07:13,920 --> 00:07:16,120 Speaker 4: Such a good meal, though, I've been thinking about it Tuesdacy, 154 00:07:16,280 --> 00:07:19,320 Speaker 4: I am buying, I'm going to are you hosting, I'm hosting. 155 00:07:19,320 --> 00:07:23,000 Speaker 4: I'm going to pick up a very very very expensive turkey. 156 00:07:23,440 --> 00:07:26,240 Speaker 4: It's like one hundred and fifty dollars farm fresh turkey. 157 00:07:26,400 --> 00:07:28,400 Speaker 5: You're being one hundred and fifty dollars, Like, how many 158 00:07:28,440 --> 00:07:29,360 Speaker 5: people does it feed? 159 00:07:30,120 --> 00:07:33,720 Speaker 4: I haven't got the final weight of the turkey, all right, Well, 160 00:07:33,720 --> 00:07:36,000 Speaker 4: but I will come. 161 00:07:35,880 --> 00:07:37,840 Speaker 3: Back to fancy pants turkey. 162 00:07:37,840 --> 00:07:40,480 Speaker 5: Aside, we all will be shopping for a lot of 163 00:07:40,480 --> 00:07:45,200 Speaker 5: similar ingredients on different scales, and the cost of those 164 00:07:45,320 --> 00:07:47,360 Speaker 5: ingredients and the cost of food in general, has of 165 00:07:47,400 --> 00:07:49,760 Speaker 5: course been a huge topic all year and for the 166 00:07:49,800 --> 00:07:51,760 Speaker 5: last few years, so we wanted to bring on an 167 00:07:51,840 --> 00:07:55,320 Speaker 5: expert in the field, the great Dina Shanker, writer for BusinessWeek, 168 00:07:55,480 --> 00:07:57,240 Speaker 5: covers food in all of its glory. 169 00:07:57,320 --> 00:07:59,640 Speaker 6: Welcome Dina, thank you so much for having me. 170 00:08:00,080 --> 00:08:01,760 Speaker 2: Dean, Am I overpaying for turkey? 171 00:08:01,880 --> 00:08:02,080 Speaker 10: You know? 172 00:08:02,120 --> 00:08:04,160 Speaker 1: I actually I have a lot of questions about your turkey. 173 00:08:04,520 --> 00:08:08,640 Speaker 1: That means, yes, it is it a heritage turkey? 174 00:08:09,080 --> 00:08:10,480 Speaker 7: I don't know, like. 175 00:08:10,440 --> 00:08:10,960 Speaker 3: What is it? 176 00:08:11,240 --> 00:08:13,239 Speaker 5: I'd feel like they should give you a whole family 177 00:08:13,280 --> 00:08:15,440 Speaker 5: tree for a turkey if they charge you one hundred 178 00:08:15,440 --> 00:08:19,320 Speaker 5: fifty dollars for it, Especially since the American Farm Bureau 179 00:08:19,400 --> 00:08:21,880 Speaker 5: just released it has this Thanksgiving Dinner Index it puts 180 00:08:21,880 --> 00:08:24,560 Speaker 5: out every year where it tracks the price of. 181 00:08:24,440 --> 00:08:26,680 Speaker 3: All the fix ins for a. 182 00:08:27,920 --> 00:08:30,720 Speaker 5: Thanksgiving dinner for twelve very folksy, yeah, I try to 183 00:08:30,760 --> 00:08:34,800 Speaker 5: be folksy. The cost is down this year, apparently fifty 184 00:08:34,840 --> 00:08:37,600 Speaker 5: five dollars for a dinner for ten people. 185 00:08:38,200 --> 00:08:41,040 Speaker 3: And this is you know, using cheaper ingredients. But they 186 00:08:41,160 --> 00:08:43,240 Speaker 3: look at grocery stores. 187 00:08:42,960 --> 00:08:46,000 Speaker 5: Across the country and have looked at the same grocery 188 00:08:46,000 --> 00:08:49,120 Speaker 5: stores for years and years, and the major decrease in 189 00:08:49,160 --> 00:08:51,680 Speaker 5: the cost of this menu. It was fifty eight dollars 190 00:08:51,720 --> 00:08:54,240 Speaker 5: in twenty twenty four, sixty one in twenty twenty three. 191 00:08:54,320 --> 00:08:58,120 Speaker 5: Now it's fifty five. And the big drop in price 192 00:08:58,640 --> 00:08:59,520 Speaker 5: came from the Turkey. 193 00:09:00,240 --> 00:09:00,520 Speaker 6: Yeah. 194 00:09:00,559 --> 00:09:03,719 Speaker 1: I mean, we actually have a few different reports this 195 00:09:03,840 --> 00:09:05,920 Speaker 1: year telling us different things. 196 00:09:06,200 --> 00:09:08,000 Speaker 3: Yes, and entry, let's do it. 197 00:09:08,040 --> 00:09:12,360 Speaker 1: I think what we can really take away from this 198 00:09:12,720 --> 00:09:16,240 Speaker 1: is that it doesn't really matter what you're paying. 199 00:09:16,280 --> 00:09:18,079 Speaker 6: It matters how you're feeling about it. 200 00:09:18,480 --> 00:09:21,640 Speaker 1: Because if the Farm Bureau is saying costs are down 201 00:09:21,960 --> 00:09:25,800 Speaker 1: five percent, and Deloitte is saying the cost for a 202 00:09:25,880 --> 00:09:29,200 Speaker 1: dinner for eight people is up zero point six percent, 203 00:09:29,720 --> 00:09:34,120 Speaker 1: and we actually don't have CPI for October. 204 00:09:33,640 --> 00:09:36,800 Speaker 5: Cinflation report, Yeah, that comes out every month usually, right, 205 00:09:36,920 --> 00:09:37,959 Speaker 5: so we don't know. 206 00:09:38,480 --> 00:09:42,440 Speaker 1: And yet lending Tree says Thanksgiving hosts are expecting to 207 00:09:42,520 --> 00:09:45,880 Speaker 1: spend thirteen percent more than last year. 208 00:09:45,960 --> 00:09:48,559 Speaker 2: Can I just say I don't trust any of these numbers. 209 00:09:48,800 --> 00:09:51,959 Speaker 4: The Farm Bureau, it sounds like that sounds like a 210 00:09:52,080 --> 00:09:55,880 Speaker 4: very official like group, but it's it's a lobbying group. Yes, 211 00:09:55,920 --> 00:09:59,320 Speaker 4: it is a lobbying It is not like a government agency. 212 00:09:59,679 --> 00:10:04,120 Speaker 4: So on one hand, it does seem like the data 213 00:10:04,160 --> 00:10:06,199 Speaker 4: that they're putting out is fairly rigorous. 214 00:10:06,320 --> 00:10:09,839 Speaker 2: But also I feel like I have to say, like there's. 215 00:10:09,600 --> 00:10:14,440 Speaker 4: Probably some disincentives for farmers to say stuff costs more 216 00:10:14,640 --> 00:10:18,520 Speaker 4: because we're in an environment where the president is basically 217 00:10:18,559 --> 00:10:22,280 Speaker 4: threatening anyone who raises prices, and farmers have been kind 218 00:10:22,320 --> 00:10:26,200 Speaker 4: of beefing with Trump over various parts of agriculture policy 219 00:10:26,240 --> 00:10:26,640 Speaker 4: and so on. 220 00:10:26,800 --> 00:10:27,640 Speaker 2: So I don't know. 221 00:10:28,080 --> 00:10:30,880 Speaker 4: On the other hand, it seems like we have this 222 00:10:30,960 --> 00:10:33,320 Speaker 4: like Farm Bureau data, we have Deloitte. Those are two 223 00:10:33,440 --> 00:10:37,320 Speaker 4: different entities essentially saying it's not costing more, which definitely 224 00:10:37,520 --> 00:10:41,160 Speaker 4: that feels like in contradiction to how many people feel 225 00:10:41,320 --> 00:10:42,800 Speaker 4: about food prices. 226 00:10:43,280 --> 00:10:44,240 Speaker 2: It's hard to understand. 227 00:10:45,040 --> 00:10:48,760 Speaker 1: Yeah, So I did email both Deloitte and the Farm 228 00:10:48,800 --> 00:10:51,360 Speaker 1: Bureau about like, why did you guys come up with 229 00:10:51,440 --> 00:10:55,319 Speaker 1: different numbers? Number one is they have very different methodologies, 230 00:10:55,679 --> 00:10:58,840 Speaker 1: and the Farm Bureau emphasized, or maybe I should say 231 00:10:58,840 --> 00:11:03,479 Speaker 1: I emphasize. Their response included that there's is an informal 232 00:11:03,760 --> 00:11:05,240 Speaker 1: survey of prices. 233 00:11:05,640 --> 00:11:06,560 Speaker 2: Okay, okay. 234 00:11:07,000 --> 00:11:13,000 Speaker 1: Deloitte is much more formal, but their collection of information. 235 00:11:12,800 --> 00:11:15,480 Speaker 6: Is through September. But I think that that's exactly right, 236 00:11:15,480 --> 00:11:15,920 Speaker 6: and this is. 237 00:11:15,840 --> 00:11:18,920 Speaker 1: Why we are supposed to get government data. 238 00:11:18,960 --> 00:11:19,960 Speaker 3: Well, I should say that. 239 00:11:20,120 --> 00:11:22,440 Speaker 5: I spoke with Mike McDonough, who's an economist here at 240 00:11:22,440 --> 00:11:25,320 Speaker 5: Bloomberg who's putting together Thanksgiving Index, and he told me, 241 00:11:25,520 --> 00:11:28,400 Speaker 5: according to his numbers, the prices were also slightly down, 242 00:11:29,040 --> 00:11:32,080 Speaker 5: especially for turkey. And I asked about this because there 243 00:11:32,080 --> 00:11:34,959 Speaker 5: are reports that the wholesale price for turkey is way up, 244 00:11:35,040 --> 00:11:38,520 Speaker 5: like forty percent up. But what he said was, they 245 00:11:38,559 --> 00:11:41,320 Speaker 5: have like a lot of frozen turkeys. There's like a 246 00:11:41,360 --> 00:11:45,920 Speaker 5: strategic turkey reserve or something. And also that the retail 247 00:11:46,040 --> 00:11:48,640 Speaker 5: price could be very different from the wholesale price because 248 00:11:48,640 --> 00:11:51,760 Speaker 5: a lot of supermarkets might be marking down turkey to 249 00:11:51,880 --> 00:11:54,360 Speaker 5: get people into the store where they buy all the 250 00:11:54,440 --> 00:11:55,880 Speaker 5: other ingredients. 251 00:11:56,040 --> 00:11:58,920 Speaker 4: Right, And that's a classic move, giving away a frozen 252 00:11:58,960 --> 00:12:01,640 Speaker 4: turkey or whatever as way to get foot traffic in 253 00:12:01,640 --> 00:12:03,679 Speaker 4: the door. You spend a lot of money on like 254 00:12:03,760 --> 00:12:06,439 Speaker 4: pumpkin pies or whatever, more expensive items. 255 00:12:06,520 --> 00:12:08,440 Speaker 5: Yeah, I mean you'll go to a grocery store because 256 00:12:08,440 --> 00:12:10,000 Speaker 5: you're like, oh, they have a great turkey deal, and 257 00:12:10,000 --> 00:12:12,120 Speaker 5: then you'll just maybe get all the other ingredients for 258 00:12:12,160 --> 00:12:14,120 Speaker 5: your feast there. So that could be. It could be 259 00:12:14,200 --> 00:12:15,719 Speaker 5: like the hot dogs at Costco. 260 00:12:15,840 --> 00:12:18,960 Speaker 1: It's the Yeah, the lost leader brings people in. So 261 00:12:19,040 --> 00:12:22,480 Speaker 1: I reached out to David Ortega, professor of food economics 262 00:12:22,520 --> 00:12:26,079 Speaker 1: at Michigan State University, and he told me Number one 263 00:12:26,160 --> 00:12:28,320 Speaker 1: is the different findings have a lot to do with 264 00:12:28,320 --> 00:12:29,320 Speaker 1: different methodologies. 265 00:12:29,679 --> 00:12:31,160 Speaker 6: He says he looks to CPI. 266 00:12:31,720 --> 00:12:35,000 Speaker 1: CPI in September said two point seven percent grocery inflation. 267 00:12:35,559 --> 00:12:39,120 Speaker 6: That's up, but it's not that different crazy up. 268 00:12:39,240 --> 00:12:40,160 Speaker 2: It's not falling. 269 00:12:40,240 --> 00:12:44,679 Speaker 1: But he also noted that, you know, Thanksgiving prices are 270 00:12:44,760 --> 00:12:50,680 Speaker 1: really family specific, and also there are so many retailers 271 00:12:50,679 --> 00:12:54,520 Speaker 1: doing these big Thanksgiving sales. So Walmart has their lowest 272 00:12:54,520 --> 00:12:59,280 Speaker 1: price ever, all these doing one target. It's everyone. Every 273 00:12:59,320 --> 00:13:04,080 Speaker 1: retailer does some kind of Thanksgiving special. So my conclusion 274 00:13:04,120 --> 00:13:07,360 Speaker 1: from this is like Thanksgiving is a terrible gauge for 275 00:13:07,440 --> 00:13:10,120 Speaker 1: the food prices because they're all over the place. 276 00:13:10,520 --> 00:13:10,760 Speaker 3: Now. 277 00:13:11,440 --> 00:13:14,320 Speaker 1: In terms of the Farm Bureau being a lobbying organization, 278 00:13:14,880 --> 00:13:17,400 Speaker 1: I actually think that if we look even further into 279 00:13:17,440 --> 00:13:20,800 Speaker 1: the report, that's where the real clues are about what's 280 00:13:20,880 --> 00:13:24,720 Speaker 1: going on, which is they are making some points about 281 00:13:24,960 --> 00:13:30,640 Speaker 1: higher costs for inputs for farms like fertilizer that's from tariffs. 282 00:13:31,280 --> 00:13:35,240 Speaker 1: They're talking about weather patterns driving prices up. 283 00:13:35,520 --> 00:13:39,719 Speaker 3: We call that climate change sometimes. 284 00:13:38,400 --> 00:13:40,400 Speaker 6: And they're talking about a labor shortage. 285 00:13:40,960 --> 00:13:41,280 Speaker 7: Ice. 286 00:13:42,640 --> 00:13:45,520 Speaker 5: Yes, there were some of the big increases on the 287 00:13:45,920 --> 00:13:49,240 Speaker 5: Thanksgiving list were three pounds of the sweet potatoes were 288 00:13:49,320 --> 00:13:52,400 Speaker 5: up thirty seven percent. The veggie tray, which is like 289 00:13:52,480 --> 00:13:55,400 Speaker 5: carrots and celery, those costs are up sixty one percent. 290 00:13:55,760 --> 00:13:57,000 Speaker 2: Who buys a veggie? 291 00:13:57,440 --> 00:13:58,680 Speaker 6: Please don't invite me to that meal. 292 00:13:58,800 --> 00:14:01,040 Speaker 5: I mean I was gonna say, like, basically the theme 293 00:14:01,280 --> 00:14:04,600 Speaker 5: of Thanksgiving costs this year is don't buy vegetables. My 294 00:14:04,880 --> 00:14:08,160 Speaker 5: personal like inner eight year old's dream of Thanksgiving. 295 00:14:08,200 --> 00:14:10,679 Speaker 3: It's like, yes, you can't afford vegetables. 296 00:14:11,559 --> 00:14:14,360 Speaker 1: And I'll just now, Max, it's so nice that you 297 00:14:14,400 --> 00:14:15,480 Speaker 1: host Thanksgiving dinner. 298 00:14:15,720 --> 00:14:17,240 Speaker 6: That's a great service to your family. 299 00:14:17,760 --> 00:14:21,000 Speaker 1: Are you in the eighteen percent of potential hosts that 300 00:14:21,080 --> 00:14:22,200 Speaker 1: regret that decision? 301 00:14:22,560 --> 00:14:25,400 Speaker 6: No, that's up from fourteen percent last year. 302 00:14:25,920 --> 00:14:28,000 Speaker 3: Eighteen percent of people who host Thanksgiving. 303 00:14:29,520 --> 00:14:31,480 Speaker 6: That's according to lending Tree. 304 00:14:31,560 --> 00:14:33,440 Speaker 1: And I don't know that that's really specific to cost. 305 00:14:33,520 --> 00:14:36,360 Speaker 6: I mean I would regret hosting dishes. 306 00:14:36,600 --> 00:14:37,800 Speaker 3: It's dishes I. 307 00:14:37,840 --> 00:14:41,880 Speaker 4: Have such I have no regret yet, is what I'll say. 308 00:14:42,160 --> 00:14:44,920 Speaker 4: I but there is time. We're recording this a week 309 00:14:44,960 --> 00:14:48,640 Speaker 4: from Thanksgiving, and you know it's possible that that in 310 00:14:48,720 --> 00:14:51,360 Speaker 4: seven days I will be I will beware of the. 311 00:14:51,400 --> 00:14:53,360 Speaker 6: What percentage was it eighteen percent? 312 00:14:54,000 --> 00:14:55,280 Speaker 2: Now I'm in the majority for now. 313 00:14:55,520 --> 00:14:56,360 Speaker 3: I mean, this has. 314 00:14:56,240 --> 00:14:59,520 Speaker 5: Been a big moment in food prices for multiple reasons, 315 00:14:59,520 --> 00:15:04,320 Speaker 5: including one that President Trump just is like suspending tariffs 316 00:15:04,320 --> 00:15:06,840 Speaker 5: on some food items like bananas and coffee and things 317 00:15:06,880 --> 00:15:08,920 Speaker 5: like that, where they have seen prices spike because of 318 00:15:08,960 --> 00:15:15,440 Speaker 5: tariffs overall Thanksgiving feasts aside, what is happening with food prices? 319 00:15:15,520 --> 00:15:16,040 Speaker 2: Do we know? 320 00:15:16,360 --> 00:15:17,120 Speaker 3: Is it mixed? 321 00:15:17,800 --> 00:15:18,080 Speaker 2: Is it? 322 00:15:18,400 --> 00:15:20,800 Speaker 6: They seem to be going up. That's what the CPI 323 00:15:20,920 --> 00:15:23,360 Speaker 6: shows us is that they're going up. I mean I 324 00:15:23,440 --> 00:15:26,680 Speaker 6: think that. You know, when I go to the supermarket, 325 00:15:27,000 --> 00:15:27,960 Speaker 6: I like to ask the. 326 00:15:27,920 --> 00:15:31,280 Speaker 1: Cashier how many people complain about food prices? 327 00:15:31,640 --> 00:15:32,120 Speaker 4: You do. 328 00:15:33,480 --> 00:15:34,480 Speaker 3: Always be reported. 329 00:15:34,760 --> 00:15:35,320 Speaker 2: I love it. 330 00:15:35,800 --> 00:15:40,440 Speaker 1: And the answer at like my stop and shop is, oh, 331 00:15:40,520 --> 00:15:44,400 Speaker 1: almost everyone is complaining. The last time I asked, the 332 00:15:44,440 --> 00:15:48,000 Speaker 1: guy behind me in line was like, it's terrible, and 333 00:15:48,040 --> 00:15:50,800 Speaker 1: I started. We had a whole conversation about is chicken 334 00:15:50,800 --> 00:15:53,320 Speaker 1: wings and it's the meat driving the prices up? And 335 00:15:54,040 --> 00:15:57,360 Speaker 1: I think, really, prices are going up. I don't know 336 00:15:57,400 --> 00:16:01,960 Speaker 1: how closely people are tracking. Well, I paid X for 337 00:16:02,200 --> 00:16:05,080 Speaker 1: this package of chicken wings this week, but I remember 338 00:16:05,360 --> 00:16:07,600 Speaker 1: last week what I paid in a year ago. The 339 00:16:07,600 --> 00:16:10,560 Speaker 1: truth is that prices have gone up so much since 340 00:16:10,600 --> 00:16:11,440 Speaker 1: pre pandemic. 341 00:16:12,120 --> 00:16:13,360 Speaker 6: That's what people remember. 342 00:16:13,720 --> 00:16:17,880 Speaker 1: People remember prices that are never coming back now. Yes, 343 00:16:18,080 --> 00:16:22,080 Speaker 1: banana tariffs, if we remove them, it might bring bananas 344 00:16:22,120 --> 00:16:25,280 Speaker 1: down from thirty cents a banana to twenty seven cents 345 00:16:25,400 --> 00:16:30,680 Speaker 1: or whatever, but ultimately that's not that's not going to 346 00:16:30,800 --> 00:16:35,720 Speaker 1: change how you feel about your grocery costs, which might 347 00:16:35,800 --> 00:16:38,040 Speaker 1: just be people have to change how they think about 348 00:16:38,040 --> 00:16:40,680 Speaker 1: groceries in terms of how much of their paycheck they 349 00:16:40,760 --> 00:16:41,720 Speaker 1: divert to them. 350 00:16:41,960 --> 00:16:43,240 Speaker 3: Are you cooking a turkey this show? 351 00:16:43,240 --> 00:16:46,120 Speaker 6: Oh my god, I would never in a million years host. 352 00:16:45,920 --> 00:16:47,360 Speaker 7: Of Thanksgiving me all that. 353 00:16:47,760 --> 00:16:49,320 Speaker 3: I mean, you're a food reporter. It seems like you're 354 00:16:49,320 --> 00:16:49,960 Speaker 3: a food personal. 355 00:16:50,200 --> 00:16:52,280 Speaker 6: Number one is that's just a huge responsibility. 356 00:16:52,400 --> 00:16:54,200 Speaker 3: It's like a massive You don't want to be among 357 00:16:54,240 --> 00:16:54,960 Speaker 3: the eighteen percent? 358 00:16:55,040 --> 00:16:55,240 Speaker 7: Yeah? 359 00:16:55,280 --> 00:16:56,280 Speaker 3: No, I mean. 360 00:16:58,080 --> 00:17:00,480 Speaker 1: Also, I don't eat meat, so nobody wants to come 361 00:17:00,520 --> 00:17:03,320 Speaker 1: to my house for Thanksgiving. But I do host a 362 00:17:03,320 --> 00:17:07,879 Speaker 1: lot of like Friday night Shabbat dinners. We have fish, 363 00:17:08,280 --> 00:17:13,480 Speaker 1: which is extraordinarily expensive all the time, and I often 364 00:17:13,520 --> 00:17:17,439 Speaker 1: regret it, not because of the cost, but because but 365 00:17:17,480 --> 00:17:19,200 Speaker 1: I'm always happy once the guests arrive. 366 00:17:19,840 --> 00:17:22,439 Speaker 2: Stacy, are you are you cooking or what are your 367 00:17:22,480 --> 00:17:23,359 Speaker 2: Thanksgiving plans? 368 00:17:23,520 --> 00:17:27,520 Speaker 5: I am bringing a dish, which is my favorite thing. 369 00:17:27,840 --> 00:17:30,720 Speaker 5: I have not even selected which dish it. It just 370 00:17:30,760 --> 00:17:33,359 Speaker 5: depends on whatever people need. I will bring. Apparently I 371 00:17:33,359 --> 00:17:37,280 Speaker 5: need to avoid the vegetables, is what the farm Bureau 372 00:17:37,320 --> 00:17:37,720 Speaker 5: is selling me. 373 00:17:37,800 --> 00:17:39,320 Speaker 1: I just want to say, that's really great that you're 374 00:17:39,320 --> 00:17:43,560 Speaker 1: bringing something, because according to lending Tree, for what it's worth, 375 00:17:43,840 --> 00:17:46,719 Speaker 1: one in ten hosts say that they wouldn't invite an 376 00:17:46,720 --> 00:17:48,720 Speaker 1: empty handed guest back next year. 377 00:17:48,840 --> 00:17:51,720 Speaker 3: So I gradualll never be an empty handed guest. 378 00:17:51,880 --> 00:17:55,600 Speaker 4: I would never disinvite an empty handed guest. Dina Shanker, 379 00:17:55,680 --> 00:17:56,040 Speaker 4: Thank you. 380 00:17:56,280 --> 00:18:00,520 Speaker 5: Happy Thanksgiving Dina. 381 00:18:04,600 --> 00:18:08,320 Speaker 4: Okay, Stacy, I think we need to talk about the 382 00:18:08,320 --> 00:18:13,520 Speaker 4: Epstein stuff. And I hesitate to go there because this 383 00:18:13,600 --> 00:18:17,840 Speaker 4: is a business podcast, and in certain ways it's not 384 00:18:17,880 --> 00:18:18,560 Speaker 4: a business story. 385 00:18:18,560 --> 00:18:20,520 Speaker 2: But in other ways, of course, it is a huge 386 00:18:20,720 --> 00:18:21,480 Speaker 2: business story. 387 00:18:21,760 --> 00:18:25,560 Speaker 4: Yeah, both because the guy who's at the center of it, 388 00:18:25,640 --> 00:18:33,359 Speaker 4: Jeffrey Epstein, was operated ostensibly very successful business most measure, 389 00:18:33,560 --> 00:18:39,119 Speaker 4: and also because we're seeing a bunch of prominent people 390 00:18:39,280 --> 00:18:41,919 Speaker 4: in our world getting caught up in it, most recently 391 00:18:41,960 --> 00:18:44,520 Speaker 4: Larry Summers. I think he stepped back from his public 392 00:18:44,520 --> 00:18:48,719 Speaker 4: commitments at Harvard and open Ai, the big chatbot company, 393 00:18:49,200 --> 00:18:53,399 Speaker 4: and you know, all of a sudden, there's the prospect 394 00:18:53,640 --> 00:18:57,840 Speaker 4: of a bunch of Epstein files getting released. Congress over 395 00:18:58,200 --> 00:19:04,120 Speaker 4: President Trump's objections, pass this bill. Trump signed it, apparently enthusiastically. Anyway, 396 00:19:04,240 --> 00:19:06,440 Speaker 4: I want to unpack this, and to do that, We've 397 00:19:06,440 --> 00:19:10,760 Speaker 4: got a great guy, Max Abelson, who little known fact 398 00:19:10,760 --> 00:19:13,879 Speaker 4: he's a Bloomberg reporter, but we are often mistaken for 399 00:19:13,920 --> 00:19:15,200 Speaker 4: one another because of the name. 400 00:19:15,600 --> 00:19:17,720 Speaker 10: I get a lot of emails meant for this Max 401 00:19:18,240 --> 00:19:19,720 Speaker 10: and visa versa. 402 00:19:19,920 --> 00:19:23,399 Speaker 4: When Max launched his Max had a TV show, and 403 00:19:23,440 --> 00:19:27,800 Speaker 4: when it launched, I got all these congratulatory messages. But 404 00:19:28,080 --> 00:19:30,960 Speaker 4: Max is here. He covers money and power for Bloomberg. 405 00:19:31,240 --> 00:19:33,159 Speaker 4: What you've been doing for the past couple of months 406 00:19:33,240 --> 00:19:36,040 Speaker 4: is looking at Epstein emails, Right, I've been. 407 00:19:35,880 --> 00:19:38,320 Speaker 7: Reading a lot of jevery Epstein's emails. 408 00:19:38,840 --> 00:19:43,600 Speaker 10: Bloomberg News obtained more than eighteen thousand emails sent sent 409 00:19:43,680 --> 00:19:46,359 Speaker 10: to and from Epstein and not just any old emails, 410 00:19:46,359 --> 00:19:49,919 Speaker 10: but these are emails basically like a private Yahoo email address. 411 00:19:50,640 --> 00:19:55,119 Speaker 10: And this team we are doing our best to be 412 00:19:55,119 --> 00:19:59,000 Speaker 10: able to explain something that is enormous and complicated in 413 00:19:59,000 --> 00:20:01,119 Speaker 10: some ways and co eight and we've been trying to 414 00:20:01,200 --> 00:20:03,080 Speaker 10: lay it out for readers and to try to understand 415 00:20:03,080 --> 00:20:05,160 Speaker 10: it ourselves when people. 416 00:20:04,960 --> 00:20:07,000 Speaker 2: Say the Epstein files. 417 00:20:07,040 --> 00:20:09,280 Speaker 4: There was also people may remember at the beginning of 418 00:20:09,320 --> 00:20:12,000 Speaker 4: the Trump presidency there was this like amazing media event 419 00:20:12,000 --> 00:20:13,880 Speaker 4: where a bunch of right wing influencers got in front 420 00:20:13,880 --> 00:20:16,280 Speaker 4: of the White House, held up these awesome binders and 421 00:20:16,320 --> 00:20:19,240 Speaker 4: were like, we have the Epstein files. When people say 422 00:20:19,400 --> 00:20:21,720 Speaker 4: the Epstein files, like what does that even mean? 423 00:20:22,119 --> 00:20:22,919 Speaker 7: This is so interesting. 424 00:20:22,920 --> 00:20:24,959 Speaker 10: A phrases like that kind of entered the lexicon and 425 00:20:25,000 --> 00:20:27,280 Speaker 10: sort of amount to exactly like kind of nothing because 426 00:20:27,320 --> 00:20:30,040 Speaker 10: it's essentially like a meaningless phrase, but but but it's 427 00:20:30,040 --> 00:20:32,159 Speaker 10: also very meaningful. Let's all right, I'm going to do 428 00:20:32,160 --> 00:20:34,760 Speaker 10: my very best at trying to sort of, like bucket 429 00:20:34,760 --> 00:20:37,840 Speaker 10: by bucket, try to think think through the project that 430 00:20:38,000 --> 00:20:40,280 Speaker 10: I've worked with a bunch of our Bloomberg News colleagues on. 431 00:20:40,359 --> 00:20:44,440 Speaker 10: I'm thinking of Jason Leopold and Harry Wilson and Lauren Edter. 432 00:20:44,960 --> 00:20:48,199 Speaker 10: Those are emails from a Yahoo inbox that was like 433 00:20:48,440 --> 00:20:52,120 Speaker 10: really active around two thousand and seven, two thousand and eight. 434 00:20:52,040 --> 00:20:55,960 Speaker 4: That was before Epstein was convicted of I forget the 435 00:20:56,000 --> 00:20:59,160 Speaker 4: exact the original Florida conviction, right, maxis. 436 00:20:58,840 --> 00:21:00,000 Speaker 2: Because I was in two thousand and eight. 437 00:21:00,119 --> 00:21:01,280 Speaker 7: Yes, it's even better than that. 438 00:21:01,400 --> 00:21:06,639 Speaker 10: The emails start before he is charged, and that's the 439 00:21:06,680 --> 00:21:08,840 Speaker 10: Florida charges are in two thousand and six, and they 440 00:21:09,000 --> 00:21:12,760 Speaker 10: last up to and through him pleading guilty to two 441 00:21:12,840 --> 00:21:15,320 Speaker 10: charges in two thousand and eight, which were part of 442 00:21:15,359 --> 00:21:19,280 Speaker 10: the non prosecution agreement that really stops cold both state 443 00:21:19,320 --> 00:21:22,159 Speaker 10: and federal investigations. And then I'm happy to say the 444 00:21:22,240 --> 00:21:26,600 Speaker 10: emails do continue past that. So let's call that bucket one. 445 00:21:26,680 --> 00:21:27,600 Speaker 2: That's the Yahoo email. 446 00:21:27,680 --> 00:21:29,480 Speaker 7: That's that's the Bloomberg News. 447 00:21:29,480 --> 00:21:32,359 Speaker 3: Cash, that's like the exclusive Bloomberg. 448 00:21:33,200 --> 00:21:37,640 Speaker 10: Then over to the right, you've got the congressional committees 449 00:21:37,640 --> 00:21:42,159 Speaker 10: Republicans and Democrats released I think basically last week thousands 450 00:21:42,200 --> 00:21:47,280 Speaker 10: more and those are unfortunately a different email account, but 451 00:21:47,400 --> 00:21:51,960 Speaker 10: what they have is really rich stuff more recent, more 452 00:21:52,280 --> 00:21:55,520 Speaker 10: past past two thousand into the twenty tens. 453 00:21:55,760 --> 00:21:58,440 Speaker 4: Well all the way up at least till he died. 454 00:21:58,480 --> 00:22:00,880 Speaker 4: I think, yeah, until he was arrested. 455 00:22:01,040 --> 00:22:01,800 Speaker 7: That's exactly right. 456 00:22:01,840 --> 00:22:04,240 Speaker 10: It's called that Epstein batch too. That's got the summer's 457 00:22:04,240 --> 00:22:07,320 Speaker 10: emails and many more. But you know, when people talk 458 00:22:07,400 --> 00:22:11,080 Speaker 10: about the Epstein files, what they are consistently referring to 459 00:22:12,119 --> 00:22:14,879 Speaker 10: are what's to come, and that is I think a 460 00:22:15,080 --> 00:22:16,560 Speaker 10: very helpful way of thinking. 461 00:22:16,400 --> 00:22:17,600 Speaker 3: About that also emails. 462 00:22:18,320 --> 00:22:19,600 Speaker 7: My thinking is it's. 463 00:22:19,480 --> 00:22:22,200 Speaker 10: Going to be much more governmental when I think about 464 00:22:22,200 --> 00:22:24,680 Speaker 10: what we're supposed to expect now that Trump has signed 465 00:22:24,760 --> 00:22:28,000 Speaker 10: the law to release the let's just call these the 466 00:22:28,080 --> 00:22:30,879 Speaker 10: Epstein files. I think it's very helpful to think of 467 00:22:30,920 --> 00:22:33,960 Speaker 10: this as essentially DJ the Department of Justice, that they 468 00:22:34,000 --> 00:22:38,439 Speaker 10: will be releasing lots and lots of files that are 469 00:22:38,440 --> 00:22:41,440 Speaker 10: from the Department of Justice is investigation into Epstein, and 470 00:22:41,920 --> 00:22:44,359 Speaker 10: I'm assuming that we'll have a lot of emails. But 471 00:22:44,480 --> 00:22:46,160 Speaker 10: I think that sort of at least the way I'm 472 00:22:46,160 --> 00:22:48,680 Speaker 10: conceptualizing it right now, is it rather than a cache 473 00:22:48,760 --> 00:22:52,640 Speaker 10: of emails, it's going to be a much broader governmental collection, 474 00:22:52,840 --> 00:22:54,479 Speaker 10: collection of data and files. 475 00:22:55,200 --> 00:22:56,320 Speaker 3: So here's my question. 476 00:22:56,680 --> 00:23:00,320 Speaker 5: If Jeffrey Epstein was running a kind of business which 477 00:23:00,359 --> 00:23:03,840 Speaker 5: it feels like he was in a way, I'm wondering, like, 478 00:23:04,520 --> 00:23:06,639 Speaker 5: as the stuff starts to emerge, like what was the 479 00:23:06,720 --> 00:23:07,880 Speaker 5: nature of this business? 480 00:23:07,920 --> 00:23:10,600 Speaker 3: And like what was the currency here? What was he buying? 481 00:23:10,640 --> 00:23:11,399 Speaker 3: What was he selling? 482 00:23:11,440 --> 00:23:14,560 Speaker 5: Like are you starting to get kind of a larger 483 00:23:14,640 --> 00:23:18,520 Speaker 5: scope picture of what exactly was the nature of this 484 00:23:18,680 --> 00:23:20,080 Speaker 5: thing that he was running. 485 00:23:20,520 --> 00:23:23,280 Speaker 10: I'm going to answer that very very good question two ways. 486 00:23:23,520 --> 00:23:26,199 Speaker 10: The most honest and the simplest answer to give you 487 00:23:26,359 --> 00:23:28,359 Speaker 10: is that the more we find out about Epstein, the 488 00:23:28,359 --> 00:23:31,480 Speaker 10: more enigmatic he becomes. That it isn't like a kind 489 00:23:31,480 --> 00:23:34,119 Speaker 10: of normal Let's say, you know, if I'm reporting out 490 00:23:34,160 --> 00:23:36,720 Speaker 10: a magazine piece or I'm reporting out of finance story, 491 00:23:36,880 --> 00:23:38,520 Speaker 10: it's like, you talk to the people you need to 492 00:23:38,560 --> 00:23:40,400 Speaker 10: talk to, You find as many documents as you can, 493 00:23:40,680 --> 00:23:42,760 Speaker 10: and then you know, a picture emerges. As we say, 494 00:23:43,440 --> 00:23:47,200 Speaker 10: in Epstein's case, you know, even though we've put out 495 00:23:47,520 --> 00:23:50,760 Speaker 10: lots of stories that are extremely solid and I hope 496 00:23:50,800 --> 00:23:53,680 Speaker 10: push the ball forward in many concrete ways, I sit 497 00:23:53,800 --> 00:23:57,560 Speaker 10: back and I reflect on Epstein, you know, whose job 498 00:23:57,640 --> 00:23:59,399 Speaker 10: is pretty much in keeping with what I tend to 499 00:23:59,400 --> 00:24:01,400 Speaker 10: write about. I mean, I am essentially a Wall Street 500 00:24:01,400 --> 00:24:05,640 Speaker 10: reporter and Epstein was essentially a money manager. But what's 501 00:24:05,680 --> 00:24:08,520 Speaker 10: so interesting about Epstein and what I think is one 502 00:24:08,560 --> 00:24:11,400 Speaker 10: of the things that captures the imagination of I think 503 00:24:11,440 --> 00:24:14,320 Speaker 10: the American publican beyond, is that he seems to have 504 00:24:14,359 --> 00:24:17,920 Speaker 10: made a career out of connections with the most important 505 00:24:17,920 --> 00:24:22,640 Speaker 10: people in the world. And you know, sometimes that work 506 00:24:22,680 --> 00:24:25,960 Speaker 10: of financial connections on Wall Street is pretty simple, and 507 00:24:26,000 --> 00:24:29,119 Speaker 10: sometimes it's even kind of dull. There is a whole 508 00:24:29,200 --> 00:24:33,240 Speaker 10: industry of people who service. 509 00:24:33,040 --> 00:24:35,200 Speaker 7: The wallets and portfolios of the wealthy. 510 00:24:35,480 --> 00:24:36,800 Speaker 10: You can look it up on the Internet and you 511 00:24:36,800 --> 00:24:39,680 Speaker 10: can find lots of sort of elite, fancy people who 512 00:24:39,800 --> 00:24:42,080 Speaker 10: would love to charge you a little bit of money 513 00:24:42,240 --> 00:24:43,880 Speaker 10: and they're going to oversee your finances. 514 00:24:43,960 --> 00:24:46,920 Speaker 4: So is this like, uh, try to attempt an analogy 515 00:24:46,960 --> 00:24:49,480 Speaker 4: that maybe a person who's outside of this world would understand. 516 00:24:49,560 --> 00:24:51,840 Speaker 4: Like I think some people like have an accountant who 517 00:24:51,840 --> 00:24:54,560 Speaker 4: has like season tickets to the Jets or something. 518 00:24:54,800 --> 00:24:56,240 Speaker 2: Part of what that's about is I'm. 519 00:24:56,200 --> 00:24:57,280 Speaker 3: Nervous about where this is going. 520 00:24:57,400 --> 00:24:58,720 Speaker 2: Okay, just wait a second. 521 00:24:59,000 --> 00:25:02,600 Speaker 4: He pays for that season tickets out of his business expenses, 522 00:25:02,600 --> 00:25:05,320 Speaker 4: he writes them off, he gets to go to Jets games. 523 00:25:05,440 --> 00:25:07,680 Speaker 4: He also brings his clients to the Jets, it's like 524 00:25:07,840 --> 00:25:11,320 Speaker 4: part of why you choose this account, and like it's 525 00:25:11,359 --> 00:25:15,360 Speaker 4: like that, but like with Epstein, it's like being connected 526 00:25:15,760 --> 00:25:18,520 Speaker 4: to people like Larry Summers or whatever, and then as 527 00:25:18,560 --> 00:25:23,800 Speaker 4: you accumulate those connections, it becomes like an asset into itself. 528 00:25:23,840 --> 00:25:26,840 Speaker 4: I haven't brought up the fact that Epstein was also 529 00:25:26,920 --> 00:25:29,800 Speaker 4: engaging in illegal sex trafficking, which feels like part of 530 00:25:29,800 --> 00:25:31,919 Speaker 4: that too, but it sounds like part of it is 531 00:25:32,040 --> 00:25:36,040 Speaker 4: just this kind of collection of powerful people that you 532 00:25:36,040 --> 00:25:39,040 Speaker 4: know basically becomes more and more valuable the further along 533 00:25:39,040 --> 00:25:39,440 Speaker 4: he goes. 534 00:25:39,720 --> 00:25:41,520 Speaker 10: I think that's a very helpful way of laying out, 535 00:25:41,560 --> 00:25:43,480 Speaker 10: and it makes me imagine in my mind's eye while 536 00:25:43,520 --> 00:25:45,760 Speaker 10: you're talking, sort of three different things that he was doing. 537 00:25:46,040 --> 00:25:48,040 Speaker 7: On the one hand, he was running money. He was 538 00:25:48,040 --> 00:25:49,359 Speaker 7: managing the money of rich people. 539 00:25:49,600 --> 00:25:53,280 Speaker 10: There's a Ohio bill billionaire named Wexner who's well known 540 00:25:53,320 --> 00:25:57,000 Speaker 10: for Victoria's Secret, for example, and that is a sort 541 00:25:57,040 --> 00:25:59,000 Speaker 10: of traditional business. I believe it was actually called the 542 00:25:59,040 --> 00:26:03,119 Speaker 10: Financial Trust Company. There's a document from JP Morgan that 543 00:26:03,240 --> 00:26:06,480 Speaker 10: says that Epstein was not accepting clients with less than 544 00:26:06,560 --> 00:26:09,400 Speaker 10: a billion dollars, so let's consider that the business of 545 00:26:09,840 --> 00:26:13,960 Speaker 10: money management, managing money for really rich people. Then let's 546 00:26:13,960 --> 00:26:17,320 Speaker 10: think about his sort of like fancy globe trotter connections, 547 00:26:17,359 --> 00:26:19,919 Speaker 10: even sort of like a ted Talk portion of his business. 548 00:26:20,040 --> 00:26:22,200 Speaker 10: The ted Talk portion of his business is Larry Summers. 549 00:26:22,240 --> 00:26:24,399 Speaker 10: You know, I don't believe he was actually in business 550 00:26:24,400 --> 00:26:26,480 Speaker 10: with Larry Summers, but Larry Summers and people like that 551 00:26:26,600 --> 00:26:28,800 Speaker 10: at Harvard were very important to him. They were part 552 00:26:28,800 --> 00:26:31,399 Speaker 10: of a kind of academic network that provided kind of 553 00:26:31,440 --> 00:26:35,040 Speaker 10: bona fides and that seemed to pander to Epstein's interests. 554 00:26:35,040 --> 00:26:36,639 Speaker 10: And Epstein had a lot of money. He was a 555 00:26:36,680 --> 00:26:39,320 Speaker 10: donor to Harvard and MIT and other institutions. So let's 556 00:26:39,320 --> 00:26:42,720 Speaker 10: consider that, Yes, like intelligen the intelligency had the ted 557 00:26:42,720 --> 00:26:45,720 Speaker 10: Talk world. And then, of course, you know, even though 558 00:26:45,720 --> 00:26:48,840 Speaker 10: I'm a financial reporter, we can't ignore what is over 559 00:26:49,359 --> 00:26:50,800 Speaker 10: you know, I think on all of our minds as 560 00:26:50,840 --> 00:26:53,359 Speaker 10: we talk about Epstein, which is that, according to the 561 00:26:53,359 --> 00:26:56,760 Speaker 10: Department of Justice, he had more than a thousand victims 562 00:26:57,320 --> 00:27:01,199 Speaker 10: because he died while he was in jail. What was 563 00:27:01,240 --> 00:27:05,920 Speaker 10: happening with Epstein's sex crimes is may forever be unknown, 564 00:27:06,320 --> 00:27:09,120 Speaker 10: but it's it certainly has to be on the boards. 565 00:27:09,280 --> 00:27:13,560 Speaker 10: As we think about this, the question of why such 566 00:27:13,880 --> 00:27:18,040 Speaker 10: powerful people were willing to be either in business with 567 00:27:18,119 --> 00:27:21,520 Speaker 10: him literally or to be in his circle is I 568 00:27:21,520 --> 00:27:24,760 Speaker 10: think maybe possibly sort of the foundational question of the 569 00:27:24,840 --> 00:27:26,280 Speaker 10: Jeffrey Epstein story. 570 00:27:26,359 --> 00:27:29,680 Speaker 4: Just to pick up on that, like one thing that 571 00:27:29,720 --> 00:27:33,720 Speaker 4: I have like not fully understood, And I think this 572 00:27:33,760 --> 00:27:37,720 Speaker 4: will continue to be important assuming the Trump administration actually 573 00:27:37,760 --> 00:27:40,520 Speaker 4: releases something. I think there are questions about well, like 574 00:27:41,440 --> 00:27:43,920 Speaker 4: Pam Bondi, the Attorney General has a lot of leeway. 575 00:27:44,520 --> 00:27:47,440 Speaker 4: There are investigations going on there. There are various ways 576 00:27:47,720 --> 00:27:50,080 Speaker 4: I think the Trump administration could either drag their feet 577 00:27:50,560 --> 00:27:54,000 Speaker 4: or maybe produce a bunch of documents that are less 578 00:27:54,600 --> 00:27:57,720 Speaker 4: revealing than we might hope. But assuming a bunch of 579 00:27:57,760 --> 00:28:00,560 Speaker 4: documents do get produced, I think we're going to see 580 00:28:00,640 --> 00:28:03,320 Speaker 4: more names connected to business who are involved in this guy. 581 00:28:03,359 --> 00:28:05,239 Speaker 4: There are a lot of powerful people, as we know. 582 00:28:05,640 --> 00:28:09,280 Speaker 4: And the thing that I haven't fully understood is how 583 00:28:09,640 --> 00:28:13,679 Speaker 4: Larry Summers lost all his jobs like this week, And 584 00:28:13,760 --> 00:28:17,320 Speaker 4: I'm wondering why was it this week? Because I'm not 585 00:28:17,600 --> 00:28:21,680 Speaker 4: totally sure how much more information we got about Larry 586 00:28:21,720 --> 00:28:25,239 Speaker 4: Summers's connections with Jeffrey Epstein from these emails and by 587 00:28:25,280 --> 00:28:27,560 Speaker 4: the same question, like, how is it that Bill Gates, 588 00:28:27,600 --> 00:28:29,600 Speaker 4: Reid Hoffman, some of these other guys who also have 589 00:28:29,640 --> 00:28:31,280 Speaker 4: connections to Jeffrey Epstein. 590 00:28:31,400 --> 00:28:32,960 Speaker 2: It feels like we haven't fully reckoned with that. 591 00:28:33,160 --> 00:28:36,880 Speaker 10: You know. One of the very powerful things about reporting 592 00:28:36,960 --> 00:28:39,920 Speaker 10: on emails is you get to see how people talk. 593 00:28:39,840 --> 00:28:40,560 Speaker 7: To one another. 594 00:28:40,800 --> 00:28:43,560 Speaker 10: You know, normally, as an interviewer, if any of us 595 00:28:43,640 --> 00:28:46,480 Speaker 10: are sitting down with our subjects, we ask some questions 596 00:28:46,520 --> 00:28:49,600 Speaker 10: and if we get lucky, they answer them. But what's 597 00:28:49,600 --> 00:28:53,200 Speaker 10: interesting about this kind of journalism with Jason and Harry 598 00:28:53,240 --> 00:28:54,680 Speaker 10: and all of our colleagues is that we have the 599 00:28:54,720 --> 00:28:57,720 Speaker 10: ability and now the world does too, with these other emails, 600 00:28:57,760 --> 00:29:01,120 Speaker 10: to read the way powerful people are actually talking to 601 00:29:01,160 --> 00:29:03,719 Speaker 10: one another, and it is you know, it really is 602 00:29:03,800 --> 00:29:06,920 Speaker 10: one thing to sort of know in the abstract that 603 00:29:07,880 --> 00:29:10,760 Speaker 10: Bill Gates and Jeffrey Epstein were in the same room together, 604 00:29:10,960 --> 00:29:12,880 Speaker 10: or Woody Allen was in was in. 605 00:29:13,080 --> 00:29:14,640 Speaker 2: I guess that can mean a lot of different things. 606 00:29:14,720 --> 00:29:17,200 Speaker 4: Right, You can be in a room with somebody without 607 00:29:17,320 --> 00:29:18,960 Speaker 4: necessarily endorsing. 608 00:29:18,720 --> 00:29:20,360 Speaker 5: He was a connected guy, like you were saying, and 609 00:29:20,400 --> 00:29:21,760 Speaker 5: it's hard to know. It's like, well, how do you 610 00:29:21,800 --> 00:29:24,160 Speaker 5: deep did this connection go? Were they committing crimes with him? 611 00:29:24,200 --> 00:29:25,760 Speaker 5: Did they just show up at this cocktail party. 612 00:29:25,840 --> 00:29:26,680 Speaker 7: That's absolutely right. 613 00:29:26,760 --> 00:29:29,840 Speaker 10: Even even someone like Leon Black, who's a private equity billionaire, 614 00:29:30,000 --> 00:29:33,320 Speaker 10: has said, look, he was like saving me money on taxes. Essentially, 615 00:29:33,680 --> 00:29:36,840 Speaker 10: that's ultimately I mean, it's many things, but it's relatively 616 00:29:36,880 --> 00:29:41,440 Speaker 10: boring to be able to read Larry Summers, who's one 617 00:29:41,520 --> 00:29:44,440 Speaker 10: of the most important figures in global academia and a. 618 00:29:44,680 --> 00:29:46,080 Speaker 3: Most famous economists in the world. 619 00:29:46,080 --> 00:29:49,480 Speaker 10: It's really important economist, huge political figure, huge political figure. 620 00:29:50,240 --> 00:29:53,959 Speaker 10: To read the words of two men, you know, speaking 621 00:29:54,000 --> 00:29:57,280 Speaker 10: about women in the way that characters in movies do, 622 00:29:58,120 --> 00:30:03,000 Speaker 10: it's very it's very yess, yes, yes, Graham characters. I 623 00:30:03,000 --> 00:30:05,600 Speaker 10: think that all of us is, as journalists, go into 624 00:30:05,600 --> 00:30:07,880 Speaker 10: the work of journalism, especially when we're writing about money 625 00:30:07,880 --> 00:30:10,800 Speaker 10: and power, with a little bit of cynicism, a little 626 00:30:10,800 --> 00:30:14,200 Speaker 10: bit of a sense that people you know, behind closed 627 00:30:14,200 --> 00:30:17,600 Speaker 10: doors don't talk the way they do necessarily in public. 628 00:30:18,120 --> 00:30:21,560 Speaker 10: But I think to answer your question, the thing that 629 00:30:21,640 --> 00:30:24,520 Speaker 10: was really powerful was just hearing someone in his own 630 00:30:24,560 --> 00:30:27,560 Speaker 10: words talking with Jeffrey Epstein. My mind is going to 631 00:30:27,600 --> 00:30:31,640 Speaker 10: the writer Michael Wolfe, who is like was basically offering 632 00:30:31,680 --> 00:30:35,600 Speaker 10: public relations advice to Jeffrey Epstein, and you get to 633 00:30:35,640 --> 00:30:38,200 Speaker 10: read it as a reader or as a journalist going 634 00:30:38,440 --> 00:30:40,880 Speaker 10: through these emails, and it's powerful. I think it does 635 00:30:40,920 --> 00:30:42,080 Speaker 10: make a difference. Well. 636 00:30:42,080 --> 00:30:44,560 Speaker 5: Also with Larry Summers, I feel like part of the 637 00:30:44,600 --> 00:30:47,520 Speaker 5: issue was that he had had those comments at Harvard 638 00:30:47,960 --> 00:30:52,120 Speaker 5: about how women were sort of less equipped to study 639 00:30:52,160 --> 00:30:56,080 Speaker 5: the sciences, and he had lost his position. He wasn't 640 00:30:56,120 --> 00:30:57,800 Speaker 5: named the head of the Federal Reserve, like, he was 641 00:30:57,840 --> 00:31:00,440 Speaker 5: punished for that, and then he apologized, and so I 642 00:31:00,440 --> 00:31:02,880 Speaker 5: think there was this feeling of like, Okay, you know, 643 00:31:02,880 --> 00:31:04,600 Speaker 5: we all make mistakes, we all have views we're not 644 00:31:04,640 --> 00:31:07,400 Speaker 5: proud of in retrospect and things like that. But then 645 00:31:07,960 --> 00:31:10,800 Speaker 5: the idea that he apologized but then in like secret 646 00:31:11,360 --> 00:31:13,960 Speaker 5: so hard he was just like oh my god, yeah, 647 00:31:13,960 --> 00:31:17,320 Speaker 5: and it was like, hey, you like you were forgiven 648 00:31:17,400 --> 00:31:17,760 Speaker 5: for this. 649 00:31:18,440 --> 00:31:19,760 Speaker 3: And I think it was maybe. 650 00:31:19,480 --> 00:31:23,120 Speaker 2: Partly that, I want to say, Larry Summers. 651 00:31:23,240 --> 00:31:26,520 Speaker 4: All all the people we've mentioned have as being associated 652 00:31:26,560 --> 00:31:29,200 Speaker 4: with Jeffrey Epstein having one way or another said that 653 00:31:29,240 --> 00:31:32,760 Speaker 4: they regret their associations with Jeffrey Epstein, including Larry Summers, 654 00:31:32,920 --> 00:31:36,680 Speaker 4: who has said it again as vowing, oh, yeah, they 655 00:31:36,800 --> 00:31:37,800 Speaker 4: definitely regret it. 656 00:31:38,160 --> 00:31:40,200 Speaker 10: Hearing you talk just puts me in mind of a 657 00:31:40,320 --> 00:31:42,960 Speaker 10: kind of maybe it's like a sort of a bifurcation. 658 00:31:43,320 --> 00:31:46,200 Speaker 10: There are people who were in Epstein's orbit and have 659 00:31:46,280 --> 00:31:48,800 Speaker 10: now gotten in trouble for it, but then they're the 660 00:31:48,840 --> 00:31:53,040 Speaker 10: people who were Epstein's clients or the people for whom 661 00:31:53,080 --> 00:31:56,000 Speaker 10: Epstein himself was a client. And I'm thinking now with 662 00:31:56,160 --> 00:31:58,800 Speaker 10: JP Morgan, big banks exactly some of the biggest banks 663 00:31:58,800 --> 00:32:01,440 Speaker 10: in the world. And I I think that because I'm 664 00:32:01,480 --> 00:32:04,760 Speaker 10: a financial reporter and not necessarily a legal reporter, and 665 00:32:04,800 --> 00:32:08,000 Speaker 10: not even necessarily a political reporter, but I find myself 666 00:32:08,160 --> 00:32:12,080 Speaker 10: most interested in, and most excited by, and most keen 667 00:32:12,120 --> 00:32:14,520 Speaker 10: to see when all of the documents come out, has 668 00:32:14,560 --> 00:32:17,200 Speaker 10: to do with the mechanics of money making. I am 669 00:32:17,240 --> 00:32:20,440 Speaker 10: looking forward to seeing who was doing business with Epstein 670 00:32:20,480 --> 00:32:23,040 Speaker 10: that we don't know about, the ways they were doing 671 00:32:23,080 --> 00:32:26,240 Speaker 10: business that we don't totally understand yet, and what the 672 00:32:26,360 --> 00:32:29,360 Speaker 10: ramifications will be. There were clearly billionaires, There was clearly 673 00:32:29,440 --> 00:32:34,160 Speaker 10: money moving at the high echelons of finance. We certainly 674 00:32:34,160 --> 00:32:36,680 Speaker 10: do have an understanding of some of what that money 675 00:32:36,680 --> 00:32:38,920 Speaker 10: looked like and some of the banks that we're handling it. 676 00:32:39,240 --> 00:32:40,800 Speaker 7: But I do think there's more to come. 677 00:32:41,160 --> 00:32:43,479 Speaker 5: Can I ask you a question about kind of the 678 00:32:43,600 --> 00:32:46,240 Speaker 5: unvarnished nature of some of the communications you're talking about, 679 00:32:46,280 --> 00:32:48,920 Speaker 5: Like we've been talking a lot on the show about 680 00:32:48,960 --> 00:32:52,080 Speaker 5: like whatever the K shaped economy and the sort of 681 00:32:52,320 --> 00:32:56,800 Speaker 5: division between regular people and elites, the very wealthy, and 682 00:32:56,840 --> 00:32:59,960 Speaker 5: so you're reading kind of the unguarded communications between elite 683 00:33:00,040 --> 00:33:02,800 Speaker 5: it's a lot, and you report on finance. 684 00:33:03,320 --> 00:33:05,560 Speaker 3: Has this has these emails, reading all. 685 00:33:05,440 --> 00:33:09,760 Speaker 5: These thousands of emails, has this changed your view at 686 00:33:09,800 --> 00:33:13,520 Speaker 5: all on the upper echelons of our economy, the sort 687 00:33:13,560 --> 00:33:15,080 Speaker 5: of titans of business. 688 00:33:15,320 --> 00:33:17,520 Speaker 10: I think that it would be cool, and I think 689 00:33:17,520 --> 00:33:20,200 Speaker 10: I would sound cooler to your audience if I were 690 00:33:20,240 --> 00:33:21,800 Speaker 10: to sort of like shrug and be like, you know, 691 00:33:21,880 --> 00:33:25,120 Speaker 10: I've been I've been in Bloomberg News for fifteen years, 692 00:33:25,120 --> 00:33:26,640 Speaker 10: which I have, and I've been writing about money and 693 00:33:26,640 --> 00:33:28,520 Speaker 10: power for twenty years, which I have. You know, I 694 00:33:28,560 --> 00:33:31,040 Speaker 10: wasn't born yesterday. Like I know how powerful people work, 695 00:33:31,040 --> 00:33:32,760 Speaker 10: and I know they talk, and like, I wasn't surprised 696 00:33:32,760 --> 00:33:35,239 Speaker 10: many of this at all. But the truth is I 697 00:33:35,280 --> 00:33:40,120 Speaker 10: have been surprised. I find it very grim and very depressing. 698 00:33:40,360 --> 00:33:44,160 Speaker 10: And I why that is is that it has a 699 00:33:44,240 --> 00:33:48,160 Speaker 10: level of meanness and even cruelty that I'm just not 700 00:33:48,320 --> 00:33:48,600 Speaker 10: used to. 701 00:33:49,200 --> 00:33:53,080 Speaker 4: Max, you mentioned our colleague Jason Leopold. He has a 702 00:33:53,120 --> 00:33:57,080 Speaker 4: new podcast. It's called Disclosure, and he's an episode all 703 00:33:57,120 --> 00:34:00,680 Speaker 4: about following Epstein's money and about how he learned about 704 00:34:00,800 --> 00:34:05,440 Speaker 4: the DOJ investigation in Epstein's finances that stayed very. 705 00:34:05,360 --> 00:34:06,160 Speaker 2: For seventeen years. 706 00:34:06,240 --> 00:34:09,279 Speaker 4: It's awesome. People should check it out. Max Abelson, thanks 707 00:34:09,280 --> 00:34:09,680 Speaker 4: for being here. 708 00:34:09,880 --> 00:34:15,760 Speaker 10: Pleasures mine, So, Stacey. 709 00:34:16,120 --> 00:34:18,680 Speaker 4: We talked about the idea of the fifty year mortgage 710 00:34:18,760 --> 00:34:22,720 Speaker 4: on the last episode. We got to comment from a listener, Rudy. 711 00:34:22,880 --> 00:34:27,160 Speaker 4: He's from Omaha, Nebraska. He's actually a longtime fan of yours. 712 00:34:26,840 --> 00:34:30,280 Speaker 3: I believe clearly. Thank you, Rudy. 713 00:34:30,440 --> 00:34:33,080 Speaker 4: Rudy pointed out something that I don't think we quite 714 00:34:33,960 --> 00:34:36,560 Speaker 4: mentioned as clearly as we probably should have on the 715 00:34:36,600 --> 00:34:38,840 Speaker 4: last episode, which is that as you go from a 716 00:34:38,880 --> 00:34:41,520 Speaker 4: thirty year mortgage to a fifty year mortgage, the interest 717 00:34:41,600 --> 00:34:44,080 Speaker 4: rate is going to go up, because like that's how 718 00:34:44,120 --> 00:34:47,880 Speaker 4: it works when termlines go up. A fifteen year mortgage 719 00:34:47,960 --> 00:34:51,160 Speaker 4: has a lower interest rate than a thirty year mortgage, 720 00:34:51,200 --> 00:34:52,839 Speaker 4: which would have a lower interest rate of a fifty 721 00:34:52,920 --> 00:34:55,480 Speaker 4: year mortgage. Rudy sound a bunch of numbers, but Stacy, 722 00:34:55,760 --> 00:34:59,400 Speaker 4: as I said, he's also a long time listener of 723 00:34:59,480 --> 00:35:01,600 Speaker 4: The Indicator, which is was the show before this. 724 00:35:01,560 --> 00:35:04,719 Speaker 2: One was Indeed, and he answers. 725 00:35:04,239 --> 00:35:06,840 Speaker 4: The question that you I think it was in the 726 00:35:06,840 --> 00:35:08,400 Speaker 4: back of your mind as we talked about a penny 727 00:35:08,480 --> 00:35:12,120 Speaker 4: which was his favorite coin. For Rudy, it's the Morgan 728 00:35:12,320 --> 00:35:17,080 Speaker 4: silver dollar, originally minted from eighteen seventy eight to nineteen 729 00:35:17,080 --> 00:35:19,600 Speaker 4: oh four. Stacy, how do you feel about the Morgan 730 00:35:19,840 --> 00:35:21,440 Speaker 4: Are you familiar with this this coin? 731 00:35:21,800 --> 00:35:25,520 Speaker 5: I don't know anything about the Morgan dollar. It was 732 00:35:25,560 --> 00:35:28,040 Speaker 5: the first standard silver dollar minted since the passage of 733 00:35:28,080 --> 00:35:31,120 Speaker 5: the coin ejacked, which ended the free coining of silver 734 00:35:31,280 --> 00:35:35,120 Speaker 5: and the production of the previous design, the seated Liberty dollar. 735 00:35:35,640 --> 00:35:36,880 Speaker 5: Was this after free silver? 736 00:35:37,800 --> 00:35:41,040 Speaker 4: I don't know, but it is a really cool looking coin. 737 00:35:41,200 --> 00:35:44,160 Speaker 4: It is okay, and Rudy thank you. All right, let's 738 00:35:44,160 --> 00:35:46,320 Speaker 4: get to our underrated stories. You said it was something 739 00:35:46,360 --> 00:35:48,319 Speaker 4: about the letter K. I believe, yes. 740 00:35:48,400 --> 00:35:51,399 Speaker 5: So the key shaped economy is this idea that's been 741 00:35:51,960 --> 00:35:55,319 Speaker 5: sort of going around a lot about how part of 742 00:35:55,320 --> 00:35:58,120 Speaker 5: our economy is getting much, much, much wealthier like AI. 743 00:35:58,239 --> 00:36:00,239 Speaker 5: There's so much money in investment going on to that 744 00:36:00,280 --> 00:36:02,400 Speaker 5: part of the economy, a lot of excitement. Companies are 745 00:36:02,440 --> 00:36:06,279 Speaker 5: raking in record profits. At the same time wages are 746 00:36:06,280 --> 00:36:09,880 Speaker 5: not going up for lower earners. So one of the 747 00:36:10,040 --> 00:36:11,759 Speaker 5: kind of interesting back and forth I think of the 748 00:36:11,840 --> 00:36:14,760 Speaker 5: last couple of weeks has been President Donald Trump talking 749 00:36:14,840 --> 00:36:18,160 Speaker 5: about these possible stimulus checks he might send out. 750 00:36:18,400 --> 00:36:21,319 Speaker 3: I think he says, because of the surplus real terarifts. 751 00:36:23,200 --> 00:36:24,600 Speaker 2: He's going to send money to everybody. 752 00:36:24,760 --> 00:36:27,920 Speaker 5: So this organization called the Tax Foundation, which is generally 753 00:36:27,960 --> 00:36:30,480 Speaker 5: a pretty conservative organization, did the map, and as it 754 00:36:30,520 --> 00:36:33,880 Speaker 5: turns out, of course, the tariffs are not enough to 755 00:36:33,920 --> 00:36:37,440 Speaker 5: subsidize two thousand dollars checks for people, even if you limit, 756 00:36:37,760 --> 00:36:40,560 Speaker 5: even if there's an income cap. And then when they 757 00:36:40,560 --> 00:36:43,680 Speaker 5: interview Treasury Secretary Scott Besson about all this, he said, 758 00:36:44,000 --> 00:36:47,800 Speaker 5: you know, especially expressing inflationary concerns, because this is the 759 00:36:47,840 --> 00:36:49,600 Speaker 5: big worry. You pump a bunch of money out into 760 00:36:49,600 --> 00:36:51,920 Speaker 5: the economy if people spend it and then it pushes 761 00:36:52,000 --> 00:36:55,319 Speaker 5: prices up. He said, well, hopefully they wouldn't spend it. 762 00:36:56,800 --> 00:37:00,799 Speaker 5: He said hopefully people would save it. What I don't know, 763 00:37:01,000 --> 00:37:02,920 Speaker 5: it's I feel like that's what I tell myself when 764 00:37:02,960 --> 00:37:05,440 Speaker 5: I buy like multiple pints of ice cream. I'm like, oh, 765 00:37:05,680 --> 00:37:10,080 Speaker 5: save it, and with mixed success. But I feel like 766 00:37:10,440 --> 00:37:13,239 Speaker 5: what's interesting about this is why President Trump would send 767 00:37:13,280 --> 00:37:14,080 Speaker 5: stimulus out. 768 00:37:14,280 --> 00:37:15,799 Speaker 3: I mean stimulus by any other name. 769 00:37:15,920 --> 00:37:19,920 Speaker 5: But I feel like presidents from Biden to Trump now 770 00:37:19,960 --> 00:37:22,879 Speaker 5: are kind of trying to deal with this inequality because 771 00:37:22,920 --> 00:37:25,520 Speaker 5: on the one hand, our country is getting sort of 772 00:37:25,560 --> 00:37:29,880 Speaker 5: exponentially wealthier, part of our economy is getting left behind. 773 00:37:29,960 --> 00:37:35,239 Speaker 5: I think, partly because of technological advancements, partly because of 774 00:37:35,280 --> 00:37:38,360 Speaker 5: the markets. I think this is a way of handling 775 00:37:38,400 --> 00:37:40,640 Speaker 5: and maybe acknowledging the K shaped economy. That was what 776 00:37:40,680 --> 00:37:43,200 Speaker 5: I felt was kind of an underrated story of the 777 00:37:43,280 --> 00:37:44,040 Speaker 5: last Tacts. 778 00:37:44,160 --> 00:37:46,040 Speaker 2: I mean, I think that I like that take. 779 00:37:46,239 --> 00:37:48,640 Speaker 4: I mean, I think my reaction to hearing this and 780 00:37:48,640 --> 00:37:53,640 Speaker 4: seeing it is just like wow. Like Trump's coalition is 781 00:37:54,480 --> 00:37:57,839 Speaker 4: it's pretty tenuous, like because you have these kind of 782 00:37:57,880 --> 00:38:01,560 Speaker 4: like traditional Republicans who spent a lot of time when 783 00:38:01,560 --> 00:38:05,640 Speaker 4: Biden was sending out stimulus checks complaining about those stimulus checks, 784 00:38:05,680 --> 00:38:08,239 Speaker 4: and then you have the kind of like populist instinct. 785 00:38:08,520 --> 00:38:08,839 Speaker 2: It is. 786 00:38:09,200 --> 00:38:11,600 Speaker 4: And you know, amid the Epstein stuff, amid all this 787 00:38:11,680 --> 00:38:14,160 Speaker 4: news around the economy, the government shut down, like it 788 00:38:14,239 --> 00:38:15,120 Speaker 4: really does feel like. 789 00:38:15,080 --> 00:38:16,719 Speaker 2: He's scrambled like a little bit. 790 00:38:17,080 --> 00:38:19,840 Speaker 4: Yeah, he's you know, trying to find some some way 791 00:38:20,320 --> 00:38:21,960 Speaker 4: to sort of reclaim the narrative. 792 00:38:22,080 --> 00:38:23,160 Speaker 2: I want to bring up. 793 00:38:23,080 --> 00:38:27,080 Speaker 4: Another area where the Trump coalition is starting to feel 794 00:38:27,160 --> 00:38:29,800 Speaker 4: a lot stronger, and that is Elon Musk. 795 00:38:29,920 --> 00:38:34,439 Speaker 5: Now, Stacy, I could have predicted your underrated story would 796 00:38:34,440 --> 00:38:35,359 Speaker 5: be about Elon Musk. 797 00:38:35,400 --> 00:38:37,600 Speaker 2: Tell me what. Okay? 798 00:38:37,760 --> 00:38:40,680 Speaker 4: So you probably remember that in early June Elon Musk 799 00:38:40,680 --> 00:38:43,319 Speaker 4: and Donald Trump had an enormous blow up, a blow 800 00:38:43,400 --> 00:38:48,200 Speaker 4: up of epic proportions. I must, I guess rather prophetically 801 00:38:48,280 --> 00:38:52,719 Speaker 4: we should acknowledge brought up Jeffrey Epstein, but in a 802 00:38:52,760 --> 00:38:58,520 Speaker 4: way that was extremely incendiary. The relationship looked like it 803 00:38:58,640 --> 00:39:03,160 Speaker 4: was dead, and at the time I was arguing essentially 804 00:39:03,280 --> 00:39:05,359 Speaker 4: that this would not last, that this breakup, that they 805 00:39:05,360 --> 00:39:08,080 Speaker 4: were bound to get back together and borrowing you remember 806 00:39:08,080 --> 00:39:11,080 Speaker 4: the taco trade. Trump always chickens out, Oh yes, yeah, 807 00:39:11,200 --> 00:39:13,560 Speaker 4: this idea that like Donald Trump is gonna like. 808 00:39:13,600 --> 00:39:17,359 Speaker 3: He'll say, but then he'll dial it not. 809 00:39:17,239 --> 00:39:20,080 Speaker 4: Not necessarily chickening out, but but like finding a way 810 00:39:20,120 --> 00:39:24,000 Speaker 4: to moderate some of that rhetoric. I and David Poppadopolis, 811 00:39:24,120 --> 00:39:27,359 Speaker 4: the former host of elan Ing, we coined a new 812 00:39:27,440 --> 00:39:31,520 Speaker 4: term mamoot, which stands for Musk always makes up with Trump. 813 00:39:31,719 --> 00:39:34,000 Speaker 4: And I have to tell you, Stacy, it is happening. 814 00:39:34,120 --> 00:39:36,920 Speaker 4: Elon Musk went to the White House. He's like posting 815 00:39:36,960 --> 00:39:39,600 Speaker 4: on Twitter. He's talking about how great Trump is. It 816 00:39:39,719 --> 00:39:43,360 Speaker 4: looks like the relationship is back on New York Times 817 00:39:43,360 --> 00:39:47,600 Speaker 4: reporting that Musk is Taylor and Burton Taylor. 818 00:39:47,280 --> 00:39:48,880 Speaker 2: And I don't know what those times. 819 00:39:48,719 --> 00:39:51,680 Speaker 5: Elizabeth Taylor and Richard Burt that they were married and 820 00:39:51,719 --> 00:39:56,759 Speaker 5: divorced and they later got remarried, that very toxic relationship. 821 00:39:56,880 --> 00:39:59,680 Speaker 5: Who's Afraid of Virginia Wolf is a very painful movie 822 00:39:59,719 --> 00:40:03,080 Speaker 5: to watch, And I feel like maybe this is them. 823 00:40:03,239 --> 00:40:06,319 Speaker 4: You know, Musk is one of the rare people who 824 00:40:06,520 --> 00:40:10,279 Speaker 4: has divorced and then remarried his ex wife. And like 825 00:40:10,320 --> 00:40:13,000 Speaker 4: you said, that's exactly it. They are back together. The 826 00:40:13,080 --> 00:40:16,080 Speaker 4: election is coming, Trump is feeling, i'd say, maybe a 827 00:40:16,120 --> 00:40:20,040 Speaker 4: little more politically vulnerable. Musk has his own vulnerabilities, and 828 00:40:20,080 --> 00:40:23,000 Speaker 4: so we've got an alliance, and I think this is 829 00:40:23,080 --> 00:40:26,440 Speaker 4: going to be a big political story for the next year, 830 00:40:26,480 --> 00:40:28,799 Speaker 4: a no joke political story, even though it is kind 831 00:40:28,800 --> 00:40:32,600 Speaker 4: of funny that this on again, off again to pestuous 832 00:40:32,600 --> 00:40:33,520 Speaker 4: relationship is back on. 833 00:40:37,480 --> 00:40:39,000 Speaker 2: This show is produced by Stacey Wong. 834 00:40:39,280 --> 00:40:42,560 Speaker 4: Magnus Hendrickson is our supervising producer, and Amy Kean our 835 00:40:42,600 --> 00:40:47,000 Speaker 4: executive producer. Sam Rogich handles engineering, and Dave Percell fact checks. 836 00:40:47,400 --> 00:40:50,880 Speaker 4: Sage Bauman heads Bloomberg Podcasts Special thanks to Jeff Muscus, 837 00:40:50,960 --> 00:40:53,200 Speaker 4: Julia Rubin, Charlie Gorivin, and RIEA. 838 00:40:53,280 --> 00:40:55,680 Speaker 2: Ling. If you have a minute, please rate and review 839 00:40:55,719 --> 00:40:56,680 Speaker 2: the show. It'll mean a. 840 00:40:56,600 --> 00:40:59,040 Speaker 4: Lot to us, and more than that, if you have 841 00:40:59,080 --> 00:41:02,120 Speaker 4: a story that should be our business, email us at 842 00:41:02,160 --> 00:41:05,000 Speaker 4: Everybody's at Bloomberg dot net. That's everybody with an ass 843 00:41:05,080 --> 00:41:07,560 Speaker 4: at Bloomberg dot net. Thank you for listening and we 844 00:41:07,600 --> 00:41:08,640 Speaker 4: will see you next week.