1 00:00:02,520 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,840 --> 00:00:17,920 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:22,000 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business app. 4 00:00:22,360 --> 00:00:25,680 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:26,960 Speaker 1: us live on YouTube. 6 00:00:27,120 --> 00:00:29,159 Speaker 2: For Lizzie Ane sound as a Charles Schwab. I'm not 7 00:00:29,200 --> 00:00:31,320 Speaker 2: going to bury er with derivative questions. 8 00:00:31,360 --> 00:00:35,720 Speaker 3: Thank you, and stop getting people on saying it's idiosyncratic 9 00:00:36,200 --> 00:00:40,519 Speaker 3: when we know the opacity to markets in are you 10 00:00:40,520 --> 00:00:43,519 Speaker 3: you were too young to remember this, Lizana, Nobody used. 11 00:00:43,320 --> 00:00:46,080 Speaker 2: The word idiosyncratic. Now what does that word. 12 00:00:45,920 --> 00:00:49,360 Speaker 4: Mean to you? Nothing to see here, I think in 13 00:00:49,440 --> 00:00:54,880 Speaker 4: today's language, you know one off, but uh, you know, 14 00:00:55,240 --> 00:00:59,120 Speaker 4: to continue to use idiosyncratic in the in the face 15 00:00:59,200 --> 00:01:04,360 Speaker 4: of Donman's comment about cockroaches, you know, the short answer 16 00:01:04,400 --> 00:01:05,600 Speaker 4: is we don't know yet. 17 00:01:06,160 --> 00:01:08,760 Speaker 2: Two thousand and six, we just head on. Great guests 18 00:01:08,800 --> 00:01:12,920 Speaker 2: Chris Whale and Ben Laidler. I'm sorry, It's like it's 19 00:01:13,040 --> 00:01:16,360 Speaker 2: Jeremy Irons in margin call. We got to get out. 20 00:01:16,640 --> 00:01:18,680 Speaker 2: We got to sell stuff that's one hundred and fifty 21 00:01:18,720 --> 00:01:22,920 Speaker 2: to two hundred beeps higher yield than everything else behavior 22 00:01:23,040 --> 00:01:25,240 Speaker 2: hasn't changed Lazana has it. 23 00:01:25,240 --> 00:01:25,720 Speaker 5: It hasn't. 24 00:01:25,720 --> 00:01:29,400 Speaker 4: But I think we're seeing yet another bifurcation, this time 25 00:01:29,560 --> 00:01:33,560 Speaker 4: within the financials, and really it's been underway since the 26 00:01:33,640 --> 00:01:37,560 Speaker 4: twenty twenty three mini banking crisis, where you've kind of 27 00:01:37,640 --> 00:01:42,280 Speaker 4: separated out the regional banks from the large banks. I 28 00:01:42,280 --> 00:01:46,680 Speaker 4: think if there's any benefit to when this unfolded Zions 29 00:01:46,680 --> 00:01:49,520 Speaker 4: and Western Alliance is that it happened in the midst 30 00:01:49,640 --> 00:01:54,080 Speaker 4: of the larger bank earnings, and it wouldn't surprise me 31 00:01:54,480 --> 00:01:59,440 Speaker 4: to see some consolidation, which certainly happened in the aftermath 32 00:01:59,480 --> 00:02:01,680 Speaker 4: of the twenty twenty three crisis. 33 00:02:02,120 --> 00:02:04,040 Speaker 5: We're just kind of getting into the teeth of the 34 00:02:04,080 --> 00:02:07,000 Speaker 5: earnings here today. The big banks seem to be really 35 00:02:07,040 --> 00:02:09,520 Speaker 5: solid and even what their their rhetoric about their business 36 00:02:09,520 --> 00:02:11,760 Speaker 5: and what they're seeing from their customer base. What did 37 00:02:11,800 --> 00:02:13,000 Speaker 5: you take away from the big banks? 38 00:02:13,080 --> 00:02:16,400 Speaker 4: Well, I think the earning season is important broadly, but 39 00:02:16,880 --> 00:02:19,440 Speaker 4: particularly with the big banks and the absence of government 40 00:02:19,480 --> 00:02:23,120 Speaker 4: issued data, it provides a bit of a macro look 41 00:02:23,160 --> 00:02:25,280 Speaker 4: that we can't get without getting a lot of that 42 00:02:25,680 --> 00:02:29,760 Speaker 4: traditional government issued data. So not only were the big 43 00:02:29,800 --> 00:02:33,840 Speaker 4: bank earnings generally strong, but what they say about the 44 00:02:33,840 --> 00:02:37,320 Speaker 4: health of the economy, the relative health of the consumer, 45 00:02:38,520 --> 00:02:41,720 Speaker 4: I think gives a decent read into the broader macro outlook. 46 00:02:42,440 --> 00:02:45,160 Speaker 5: Since that April low Lezana, I mean, we've had the 47 00:02:45,200 --> 00:02:47,359 Speaker 5: S and P up thirty thirty five percent, but the 48 00:02:47,440 --> 00:02:50,640 Speaker 5: Russell two thousands up about forty percent. What do you 49 00:02:50,639 --> 00:02:51,040 Speaker 5: make of that? 50 00:02:51,240 --> 00:02:53,440 Speaker 4: Well, within the russele, though, you have to look at 51 00:02:53,440 --> 00:02:56,480 Speaker 4: the difference between the profitable companies and the non profitable companies. 52 00:02:56,520 --> 00:02:59,359 Speaker 4: So you got fifty seven percent of the Russell is profitable, 53 00:02:59,400 --> 00:03:03,760 Speaker 4: forty percent is not profitable. Now I know that doesn't 54 00:03:03,800 --> 00:03:06,400 Speaker 4: add up to one hundred. There's two percent of the 55 00:03:06,480 --> 00:03:09,360 Speaker 4: Rustle that you you don't you don't have earnings data 56 00:03:09,400 --> 00:03:14,120 Speaker 4: for for whatever reason. And the non profitable segment of 57 00:03:14,160 --> 00:03:17,600 Speaker 4: the Russell's performance here to date is double what it 58 00:03:17,680 --> 00:03:20,000 Speaker 4: is for the profitable. So there has been this down 59 00:03:20,120 --> 00:03:22,560 Speaker 4: quality bias to what's been working. You see it at 60 00:03:22,560 --> 00:03:25,560 Speaker 4: the basket level. You see it in terms of microcaps 61 00:03:25,600 --> 00:03:29,200 Speaker 4: out performing. That's where some of the speculative fervor has 62 00:03:29,240 --> 00:03:33,080 Speaker 4: been most dominant. I think you want to fade the 63 00:03:33,160 --> 00:03:37,440 Speaker 4: really low quality move within small caps and lean into 64 00:03:37,480 --> 00:03:38,520 Speaker 4: higher quality. 65 00:03:38,320 --> 00:03:41,400 Speaker 2: Lozanne Saunders with Charles Schwabs. She's working on this Friday. 66 00:03:41,560 --> 00:03:44,560 Speaker 2: I assume Kathy Jones took the day off. I got 67 00:03:44,600 --> 00:03:48,240 Speaker 2: price up, yield down three point nine eight percent. She 68 00:03:48,320 --> 00:03:51,560 Speaker 2: did share the ten year yield. I want you to 69 00:03:51,640 --> 00:03:56,600 Speaker 2: explain to our viewers and our listeners removed from this 70 00:03:56,840 --> 00:03:59,360 Speaker 2: they have a four toh one k either they miss 71 00:03:59,440 --> 00:04:02,800 Speaker 2: the market, they're in the market. How do they protect 72 00:04:02,840 --> 00:04:09,080 Speaker 2: themselves from the complexities of fancy Wall Street talk, credit, 73 00:04:09,280 --> 00:04:14,600 Speaker 2: loan obligations, this trench, that trench. The New York Rangers 74 00:04:14,600 --> 00:04:17,800 Speaker 2: of their own trench. Okay, how do you protect yourselves 75 00:04:18,160 --> 00:04:19,960 Speaker 2: from Wall Street complexity? 76 00:04:20,960 --> 00:04:24,560 Speaker 4: So obviously you could take a passive approach, and then 77 00:04:24,600 --> 00:04:27,360 Speaker 4: you're locking yourself into the indexes. The problem there is 78 00:04:27,400 --> 00:04:30,080 Speaker 4: that you've got such a concentration problem within the cap 79 00:04:30,160 --> 00:04:35,839 Speaker 4: weighted indexes that I think adds some risk from an 80 00:04:36,080 --> 00:04:43,200 Speaker 4: individual stocks perspective. Continue to emphasize factor based investing in screening, 81 00:04:43,640 --> 00:04:46,520 Speaker 4: and I think in this kind of environment, staying up 82 00:04:46,560 --> 00:04:49,680 Speaker 4: in quality, focusing on in an environment where there's some 83 00:04:49,720 --> 00:04:55,159 Speaker 4: concern about valuation, focus on companies that have positive earnings trends, 84 00:04:55,279 --> 00:04:59,120 Speaker 4: forward earnings revisions. In this environment, of worry, worrying about 85 00:04:59,520 --> 00:05:02,039 Speaker 4: whether there's more of these sort of debt blow ups. 86 00:05:02,320 --> 00:05:07,440 Speaker 4: Focus on lower leverage companies, so better balance sheets, lower 87 00:05:07,480 --> 00:05:12,719 Speaker 4: debt to equity, more reasonable valuations. It's it's almost like 88 00:05:12,839 --> 00:05:16,000 Speaker 4: taking a to use an old school acronym, a Garp approach. 89 00:05:16,200 --> 00:05:18,920 Speaker 5: Yeah, growth at a reasonable price, kid nail for that. 90 00:05:19,040 --> 00:05:21,280 Speaker 2: Yep, I thought it was the world according to Gart 91 00:05:21,360 --> 00:05:22,200 Speaker 2: for like twenty years. 92 00:05:22,279 --> 00:05:25,599 Speaker 5: The entire bunk debt question, the entire city of Denver 93 00:05:25,680 --> 00:05:29,560 Speaker 5: money management was based upon Garth's genius. It wasn't yet totally. 94 00:05:30,040 --> 00:05:30,839 Speaker 5: All the money moved. 95 00:05:30,640 --> 00:05:32,720 Speaker 2: Swab never bought, they never drank the kool aid. 96 00:05:32,760 --> 00:05:35,240 Speaker 5: All the money moved from Chicago to Denver back in 97 00:05:35,279 --> 00:05:39,880 Speaker 5: the day. So, lizen are there? What's the concern here? 98 00:05:39,920 --> 00:05:42,640 Speaker 5: When you go talk to your schwave clients, what's their 99 00:05:42,680 --> 00:05:46,000 Speaker 5: concern is evaluation? Is it that we bounce back so much? 100 00:05:46,400 --> 00:05:47,520 Speaker 5: Or are they just riding the wave? 101 00:05:48,000 --> 00:05:52,800 Speaker 4: The number one question I've been getting a client events. 102 00:05:51,240 --> 00:05:55,840 Speaker 5: Is AI a bubble ah good one? And even boy, 103 00:05:55,880 --> 00:05:58,679 Speaker 5: we got to seven thirty two Tom without mentioning AI today. 104 00:05:58,760 --> 00:06:01,240 Speaker 5: That's got to be a record over the last topic players. 105 00:06:01,400 --> 00:06:07,200 Speaker 4: Yeah, yeah, that is the number one topic, and there 106 00:06:07,279 --> 00:06:10,520 Speaker 4: may I find at times there's a bubble. In the 107 00:06:10,600 --> 00:06:15,400 Speaker 4: use of the word bubble, it's you are starting to 108 00:06:15,480 --> 00:06:20,320 Speaker 4: see this speculation go outside cohorts like the Magnificent Seven, 109 00:06:20,360 --> 00:06:23,159 Speaker 4: which may be a good thing in terms of sort 110 00:06:23,160 --> 00:06:25,640 Speaker 4: of the hype cycle is now in these sort of 111 00:06:25,720 --> 00:06:30,040 Speaker 4: micro segments of the market like quantum and drones, and 112 00:06:30,440 --> 00:06:35,680 Speaker 4: still in the meme stocks and nonprofitable tech. But there's 113 00:06:36,080 --> 00:06:39,919 Speaker 4: there's a lot of churn happening under the surface. We 114 00:06:39,960 --> 00:06:43,000 Speaker 4: talk about the resilience of these indexes, but when you 115 00:06:43,040 --> 00:06:45,640 Speaker 4: look at the Magnificent seven, and I think it's reflective 116 00:06:45,680 --> 00:06:50,039 Speaker 4: of some valuation concerns. You know, the best performer among 117 00:06:50,080 --> 00:06:53,760 Speaker 4: the Magnificent seven, which no surprise, is Nvidia, but it's 118 00:06:53,760 --> 00:06:57,000 Speaker 4: not even in the top sixty best performers in the 119 00:06:57,080 --> 00:07:00,120 Speaker 4: S and P five hundred. It's the number one contributor 120 00:07:00,440 --> 00:07:02,719 Speaker 4: to S and P gains, but that's by virtue of 121 00:07:02,760 --> 00:07:03,720 Speaker 4: its capsize. 122 00:07:04,320 --> 00:07:06,120 Speaker 2: I got to get this soon in one minute, left 123 00:07:06,240 --> 00:07:10,240 Speaker 2: your factor based which factor now should our listeners and 124 00:07:10,320 --> 00:07:11,680 Speaker 2: viewers focus. 125 00:07:11,320 --> 00:07:16,280 Speaker 4: On right now in this unique environment? Right now? Lower 126 00:07:16,440 --> 00:07:18,680 Speaker 4: lower to launch, lower leverage. 127 00:07:18,640 --> 00:07:22,920 Speaker 2: Lower leverage. Interesting, you're going that way? Interesting? How many 128 00:07:22,920 --> 00:07:27,000 Speaker 2: stocks out of five hundred categorizes Lizzione Saunders. 129 00:07:27,120 --> 00:07:29,440 Speaker 4: You got a stumper of a question. I don't know 130 00:07:31,360 --> 00:07:34,320 Speaker 4: he would Yeah, yeah, he might know the answer. I'm 131 00:07:34,360 --> 00:07:36,960 Speaker 4: not even sure he knows the exact number of sm 132 00:07:37,000 --> 00:07:38,280 Speaker 4: P companies. 133 00:07:37,800 --> 00:07:40,600 Speaker 2: That screams well has never seen a. 134 00:07:40,640 --> 00:07:44,360 Speaker 4: Market, has taken the day off today. 135 00:07:44,760 --> 00:07:46,160 Speaker 2: So how are you going to do? Twitter? 136 00:07:47,440 --> 00:07:48,440 Speaker 5: Notice how. 137 00:07:49,880 --> 00:07:55,920 Speaker 4: Lower my chart output is this morning. Nobody wants to 138 00:07:55,960 --> 00:07:59,160 Speaker 4: see stick figures, which is how charts would be if 139 00:07:59,200 --> 00:08:01,080 Speaker 4: I had to create the twenty seconds? 140 00:08:01,120 --> 00:08:04,040 Speaker 2: Is cash an asset for some of us? 141 00:08:04,120 --> 00:08:05,360 Speaker 4: Or John, you're seeing the flight. 142 00:08:05,600 --> 00:08:10,480 Speaker 2: That's co council game, then answer, I'm in the market 143 00:08:10,520 --> 00:08:15,520 Speaker 2: twenty four? Is a VIX at twenty four an opportunity? 144 00:08:16,480 --> 00:08:19,800 Speaker 4: You tend to do better waiting for the major spike 145 00:08:20,120 --> 00:08:22,760 Speaker 4: in VIX and then if you want to trade it, 146 00:08:22,760 --> 00:08:26,200 Speaker 4: which we wouldn't recommend, then trying to sort of catch 147 00:08:26,240 --> 00:08:28,240 Speaker 4: it in the midst of a move higher or in 148 00:08:28,240 --> 00:08:29,160 Speaker 4: the midst of them. 149 00:08:29,280 --> 00:08:31,560 Speaker 2: Flower, she's got to get back to the office. Kevin's 150 00:08:31,600 --> 00:08:36,040 Speaker 2: not there, Kathy Jones, you know, I mean, Lizzie and 151 00:08:36,080 --> 00:08:40,840 Speaker 2: Saunders on this important day with Charles Schwab with wonderful perspective. 152 00:08:41,000 --> 00:08:45,160 Speaker 2: Stay with us. More from Bloomberg Surveillance coming up after this. 153 00:08:52,400 --> 00:08:56,000 Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us Live 154 00:08:56,040 --> 00:08:59,080 Speaker 1: weekday afternoons from seven to ten am. E's durn Listen 155 00:08:59,120 --> 00:09:02,720 Speaker 1: on Apple, Karpe and Android Auto with the Bloomberg Business Up, 156 00:09:02,880 --> 00:09:04,600 Speaker 1: or watch us live on YouTube. 157 00:09:04,800 --> 00:09:06,920 Speaker 2: We're gonna calm down right now. We've been in a 158 00:09:07,000 --> 00:09:11,400 Speaker 2: colo trunched frenzy all morning, and right now we're going 159 00:09:11,480 --> 00:09:15,480 Speaker 2: to still the Christopher Waller interview yesterday, one of the 160 00:09:15,559 --> 00:09:18,440 Speaker 2: five or six candidates to be the next chairman of 161 00:09:18,440 --> 00:09:21,920 Speaker 2: the Fed, and we're honored in studio. I wish you'd 162 00:09:21,960 --> 00:09:26,520 Speaker 2: been there yesterday, annalong chief US economist at Bloomberg Economics. 163 00:09:26,559 --> 00:09:29,400 Speaker 2: And we're just going to slow down now, folks and 164 00:09:29,520 --> 00:09:34,160 Speaker 2: talk about your future, your prosperity in our central bank. 165 00:09:34,200 --> 00:09:38,800 Speaker 2: Analog more than qualified with her leadership in market economics 166 00:09:38,840 --> 00:09:42,320 Speaker 2: over the last two years. So he dodged every question. 167 00:09:42,400 --> 00:09:45,760 Speaker 2: He was a sport. Actually about it. A four point 168 00:09:45,920 --> 00:09:48,800 Speaker 2: x unemployment rate right now? That's not the same as 169 00:09:48,800 --> 00:09:52,199 Speaker 2: a four point x unemployment rate thirty forty years ago? 170 00:09:52,400 --> 00:09:55,840 Speaker 6: Is it thirty four years ago? So that was about 171 00:09:55,880 --> 00:09:59,760 Speaker 6: in the nineteen nineties right, and that time there was 172 00:09:59,800 --> 00:10:05,240 Speaker 6: a productivity boom. And also the natural rate of unemployment 173 00:10:05,280 --> 00:10:09,640 Speaker 6: at that time, if I recall, is around five percent 174 00:10:09,800 --> 00:10:12,720 Speaker 6: or something like that. And whereas the natural rate of 175 00:10:12,880 --> 00:10:15,400 Speaker 6: unemployment according to the Fed right now is more like 176 00:10:15,520 --> 00:10:16,600 Speaker 6: four point two percent. 177 00:10:16,840 --> 00:10:20,280 Speaker 2: So the unemployment rate we have now feels five ish. 178 00:10:20,440 --> 00:10:23,439 Speaker 7: That's what the governor said, yes exactly. 179 00:10:23,679 --> 00:10:27,000 Speaker 6: So I think the history of last year is you 180 00:10:27,040 --> 00:10:30,520 Speaker 6: look at non farm payils adjusted for the overstatement, which 181 00:10:30,520 --> 00:10:35,600 Speaker 6: we said would mean that payrolls is actually contracting negative 182 00:10:36,000 --> 00:10:38,559 Speaker 6: in a couple of months last year when the break 183 00:10:38,640 --> 00:10:42,120 Speaker 6: even is over two hundred, so the unemployment rate should 184 00:10:42,120 --> 00:10:44,920 Speaker 6: be rising to five percent according to all sorts of model. 185 00:10:45,280 --> 00:10:47,439 Speaker 6: I think what it is is that the unemployment rate 186 00:10:47,520 --> 00:10:51,200 Speaker 6: also have some measurement problem last year, because we do 187 00:10:51,360 --> 00:10:55,400 Speaker 6: know that the new arrivals, new immigrants, their unemployment rate 188 00:10:55,440 --> 00:10:58,600 Speaker 6: is over twelve percent. So if they are the over 189 00:10:58,880 --> 00:11:02,760 Speaker 6: fourteen millions of the immigrants that arrived in the last 190 00:11:02,760 --> 00:11:07,760 Speaker 6: four years are all counted in the household survey, I 191 00:11:07,800 --> 00:11:12,520 Speaker 6: do think that the unemployment rate was actually trending toward 192 00:11:12,920 --> 00:11:16,160 Speaker 6: there was an inersia to trend toward five percent. Last year, 193 00:11:16,200 --> 00:11:18,240 Speaker 6: if accurately measured, But. 194 00:11:18,160 --> 00:11:20,960 Speaker 5: That's not what any of us see, and that's what 195 00:11:21,559 --> 00:11:23,319 Speaker 5: does the FED see that? Did they feel that that 196 00:11:23,400 --> 00:11:26,000 Speaker 5: they understand that? And if so, that means they got 197 00:11:26,040 --> 00:11:26,600 Speaker 5: to cut right. 198 00:11:26,920 --> 00:11:31,319 Speaker 6: I think Chris Waller he is a great economist because 199 00:11:31,360 --> 00:11:35,079 Speaker 6: he doesn't take data dependency that you know, Powell has 200 00:11:35,679 --> 00:11:38,400 Speaker 6: data talk about data depends, he didn't. It doesn't take 201 00:11:38,720 --> 00:11:42,040 Speaker 6: data as gospel because when you look at data. 202 00:11:41,520 --> 00:11:44,720 Speaker 2: Do we do here? Bloomberg? Well, do you think he's 203 00:11:44,800 --> 00:11:49,800 Speaker 2: favored by Trump? If he's different than the others? Is 204 00:11:49,960 --> 00:11:53,280 Speaker 2: Waller the one that Trump can be the President could 205 00:11:53,280 --> 00:11:54,040 Speaker 2: be happy with? 206 00:11:54,600 --> 00:11:57,360 Speaker 6: I think Waller is a dark horse. And I think 207 00:11:57,480 --> 00:12:01,120 Speaker 6: that if Trump gets to know Waller better and this 208 00:12:01,200 --> 00:12:04,640 Speaker 6: prolonged process is helping that, and they get to talk 209 00:12:04,679 --> 00:12:08,640 Speaker 6: about wrestling. Waller likes this fighter. 210 00:12:09,600 --> 00:12:10,920 Speaker 5: What is extreme fighting? 211 00:12:11,080 --> 00:12:13,040 Speaker 7: Exactly? Exactly? 212 00:12:14,160 --> 00:12:14,360 Speaker 2: Yeah? 213 00:12:15,200 --> 00:12:19,840 Speaker 6: And Trump is going to host a spider ring on 214 00:12:20,000 --> 00:12:20,839 Speaker 6: Independence Day? 215 00:12:20,960 --> 00:12:22,960 Speaker 7: Yes, yeah, So I think. 216 00:12:23,280 --> 00:12:26,360 Speaker 6: If they get to bond on those things, they will 217 00:12:26,400 --> 00:12:29,320 Speaker 6: find that. In fact, Waller is a blue collar governor 218 00:12:29,400 --> 00:12:30,920 Speaker 6: who has a lot of common ground. 219 00:12:31,240 --> 00:12:34,640 Speaker 2: I think definitely. You know that's where it was yesterday, 220 00:12:34,840 --> 00:12:37,160 Speaker 2: Paul Can I ask one more nerd question. I'm going 221 00:12:37,200 --> 00:12:38,839 Speaker 2: to get this out of the way with doctor Wong 222 00:12:39,000 --> 00:12:42,840 Speaker 2: because Paul's got more intelligent questions. I asked him yesterday 223 00:12:42,840 --> 00:12:44,800 Speaker 2: and he's sort of kind of like answered it. Given 224 00:12:44,840 --> 00:12:48,680 Speaker 2: his public responsibilities, he wrote a paper in ninety one 225 00:12:48,840 --> 00:12:53,240 Speaker 2: off James Baker and bashing where the administration bash is 226 00:12:53,600 --> 00:12:56,640 Speaker 2: the Central Bank. He divides it into the nineteen ninety 227 00:12:56,679 --> 00:13:01,079 Speaker 2: one paper between a strong administration in a weak administration, 228 00:13:01,559 --> 00:13:04,920 Speaker 2: and it has classic game theory in it of Robert 229 00:13:04,960 --> 00:13:08,520 Speaker 2: Gordon and Barrow and the rest Ana Wong bring it 230 00:13:08,600 --> 00:13:11,880 Speaker 2: over to two thousand and six, and if we have 231 00:13:12,200 --> 00:13:16,920 Speaker 2: bashing and coercion from any given administration, is the FED 232 00:13:17,080 --> 00:13:20,800 Speaker 2: constrained and their ability to go from data dependent x 233 00:13:20,920 --> 00:13:25,560 Speaker 2: post out to being a little bit out ahead of 234 00:13:25,600 --> 00:13:29,400 Speaker 2: the data? Are they constrained by bashing where they are 235 00:13:29,600 --> 00:13:31,720 Speaker 2: solidly expost. 236 00:13:32,040 --> 00:13:34,800 Speaker 6: That's a great question. I think that's I think right 237 00:13:34,840 --> 00:13:39,440 Speaker 6: now Wall Street is already starting to suspect that the 238 00:13:39,480 --> 00:13:44,920 Speaker 6: FED is switching toward They have to be constrained from 239 00:13:44,920 --> 00:13:50,199 Speaker 6: being forelooking because they're afraid of being wrong. Enhanced the 240 00:13:50,920 --> 00:13:53,440 Speaker 6: institution would be for the coming out on the fire. 241 00:13:53,520 --> 00:13:56,920 Speaker 2: Paul, this is a loaded question. We hope analog in 242 00:13:56,960 --> 00:14:01,280 Speaker 2: our team shorts in town right from Barcelona. Yes, okay, 243 00:14:01,320 --> 00:14:05,480 Speaker 2: have you guys been partying for three days? Yes? But 244 00:14:05,960 --> 00:14:08,479 Speaker 2: pick it up here she is with a guy from Barcelona. 245 00:14:09,000 --> 00:14:11,520 Speaker 5: Struggle or two am. Yeah, they don't go to dinner 246 00:14:11,559 --> 00:14:16,760 Speaker 5: till ten oclock. Yes, And so the government shutdown, you 247 00:14:16,880 --> 00:14:19,680 Speaker 5: economists are not getting the data that you typically need 248 00:14:19,880 --> 00:14:23,200 Speaker 5: and use. When the government does open and we start 249 00:14:23,200 --> 00:14:25,360 Speaker 5: getting some of this data, how good is it going 250 00:14:25,400 --> 00:14:27,280 Speaker 5: to be? Should we be concerned about the quality of. 251 00:14:27,280 --> 00:14:30,640 Speaker 6: The data, Yes, very much so, so the October the 252 00:14:30,680 --> 00:14:34,240 Speaker 6: problem with CPI. So September CBI is coming out next Friday, 253 00:14:34,280 --> 00:14:38,840 Speaker 6: no problem. But the October CPI, well, we're halfway through October. 254 00:14:39,200 --> 00:14:42,280 Speaker 6: Not a single price quote has been collected, and so 255 00:14:42,640 --> 00:14:46,880 Speaker 6: this shutdown persists through the end of October. The entire 256 00:14:47,040 --> 00:14:51,360 Speaker 6: month of October housing survey will have zero price quotes. 257 00:14:51,720 --> 00:14:55,280 Speaker 6: And because of the quirks of the methodology and the 258 00:14:55,360 --> 00:14:58,800 Speaker 6: housing survey, this means that the sampling error will persist 259 00:14:59,040 --> 00:15:03,520 Speaker 6: until next May. So all throughout this period, the shelter 260 00:15:03,800 --> 00:15:07,400 Speaker 6: inflation it will be a total What you've just. 261 00:15:07,400 --> 00:15:11,800 Speaker 2: Heard there, folks Coast to coast and frankly worldwide is 262 00:15:11,960 --> 00:15:15,360 Speaker 2: analong absolutely definitive. Can I ask the elephant in the 263 00:15:15,440 --> 00:15:19,080 Speaker 2: room question, have you been contacted by the administration to 264 00:15:19,160 --> 00:15:21,160 Speaker 2: run BLS? I? 265 00:15:22,920 --> 00:15:23,680 Speaker 5: No, I have not. 266 00:15:24,600 --> 00:15:29,320 Speaker 2: I asked Lisa Mateo this morning contacted. No, you've been not. Yes, 267 00:15:29,640 --> 00:15:30,200 Speaker 2: we hope. 268 00:15:30,320 --> 00:15:33,880 Speaker 5: Yeah, she's that good at it exactly. So what's the 269 00:15:33,920 --> 00:15:36,480 Speaker 5: next thing that we need to focus on from an 270 00:15:36,480 --> 00:15:39,200 Speaker 5: economic perspective to get a handle on kind of where 271 00:15:39,200 --> 00:15:40,120 Speaker 5: this economy is going? 272 00:15:40,280 --> 00:15:44,280 Speaker 6: Okay, So, because of the shutdown and also persisting problems 273 00:15:44,360 --> 00:15:47,280 Speaker 6: in BLS, the whole Wall Street is coming up with 274 00:15:47,640 --> 00:15:50,720 Speaker 6: alternative data, right, so we also have an answer. So 275 00:15:50,760 --> 00:15:55,160 Speaker 6: in Bloomberg Economics, we have now collected online thirty eight 276 00:15:55,240 --> 00:16:00,560 Speaker 6: million online prices our little million price project, and yes, 277 00:16:00,720 --> 00:16:04,640 Speaker 6: and we are trying to mimic the BLS methodology in 278 00:16:04,720 --> 00:16:08,160 Speaker 6: processing these price quotes as possible, and so we have 279 00:16:08,240 --> 00:16:11,200 Speaker 6: a pretty uh. I think we have a pretty decent 280 00:16:11,400 --> 00:16:14,560 Speaker 6: picture of the inflation. And I think the key thing 281 00:16:14,840 --> 00:16:18,400 Speaker 6: is doing exercises like this because if you just process 282 00:16:18,400 --> 00:16:21,840 Speaker 6: alternative data at face value, they are so noisy and 283 00:16:21,880 --> 00:16:25,960 Speaker 6: this you know, noises everywhere and signal is very few 284 00:16:26,080 --> 00:16:27,360 Speaker 6: to be found. 285 00:16:27,280 --> 00:16:29,400 Speaker 5: Well, get one morn Where do I find this stuff? 286 00:16:29,760 --> 00:16:30,560 Speaker 5: Have you published it? 287 00:16:31,000 --> 00:16:33,280 Speaker 6: We have been talking about it last three days, all right, 288 00:16:34,000 --> 00:16:35,720 Speaker 6: so we're going to we'll be writing about. 289 00:16:35,560 --> 00:16:38,720 Speaker 5: It'll be on the terminal soon here. How do you 290 00:16:38,720 --> 00:16:41,880 Speaker 5: think this FED is the cadence of FED rate cuts 291 00:16:41,960 --> 00:16:43,520 Speaker 5: will go here? All I think about it? 292 00:16:43,520 --> 00:16:47,160 Speaker 2: Thank you, Paul, perfect question Waller one single sentence, one 293 00:16:47,240 --> 00:16:49,120 Speaker 2: hundred to one hundred and twenty five beeps. 294 00:16:49,200 --> 00:16:52,640 Speaker 6: Nice Yes, fifty BIPs this year and seventy five BIPs 295 00:16:52,640 --> 00:16:55,080 Speaker 6: next year, which means one hundred and twenty five bps. 296 00:16:55,120 --> 00:16:58,160 Speaker 2: Within the NERD conversation, right having What does it mean 297 00:16:58,280 --> 00:17:01,720 Speaker 2: for our listeners and viewers don't care about expost x 298 00:17:01,840 --> 00:17:06,480 Speaker 2: ante If Chairman Waller delivers one hundred and twenty five 299 00:17:06,520 --> 00:17:08,880 Speaker 2: beaps of cuts, how does our life change? 300 00:17:09,480 --> 00:17:14,400 Speaker 6: Bullish twenty twenty six inflation going above three percent in twenty. 301 00:17:14,119 --> 00:17:16,440 Speaker 5: Twenty six, President's not going to like that. 302 00:17:17,200 --> 00:17:20,040 Speaker 6: Well, the President will may decide that they need the 303 00:17:20,040 --> 00:17:21,880 Speaker 6: FED to hike in twenty twenty seven. 304 00:17:22,440 --> 00:17:27,639 Speaker 2: WHOA, what's I get? Thirty seconds? What's the key distinction 305 00:17:28,119 --> 00:17:32,440 Speaker 2: between the PhD from Pennsylvania Hassett and the PhD from 306 00:17:32,560 --> 00:17:38,360 Speaker 2: Washington State Waller. What's the distinction between Hassett and Waller economics. 307 00:17:39,040 --> 00:17:43,280 Speaker 6: Hassett economics is very more econometrics. But Hassett is a 308 00:17:43,320 --> 00:17:46,480 Speaker 6: very original thinker. Waller is also a pretty or a 309 00:17:46,600 --> 00:17:49,800 Speaker 6: grounded thinker. Actually, they have more in common than you think. 310 00:17:49,800 --> 00:17:52,240 Speaker 6: They are both blue collar that you government. 311 00:17:52,320 --> 00:17:55,840 Speaker 2: This has been brilliant. You should party more. Join from Barcelona, 312 00:17:55,880 --> 00:17:58,720 Speaker 2: Anna Walk, Thank you so much driving all of our 313 00:17:59,440 --> 00:18:02,720 Speaker 2: economic and she has just been across the nation a 314 00:18:02,880 --> 00:18:08,159 Speaker 2: world leader on a calculation of the American labor economy. 315 00:18:08,520 --> 00:18:19,760 Speaker 2: Stay with us. More from Bloomberg Surveillance coming up after this. 316 00:18:19,760 --> 00:18:23,680 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 317 00:18:23,720 --> 00:18:27,119 Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto 318 00:18:27,160 --> 00:18:30,120 Speaker 1: with the Bloomberg Business app. You can also listen live 319 00:18:30,200 --> 00:18:33,760 Speaker 1: on Amazon Alexa from our flagship New York station, Just 320 00:18:33,800 --> 00:18:36,359 Speaker 1: say Alexa Play Bloomberg eleven thirty. 321 00:18:36,720 --> 00:18:39,880 Speaker 2: Dan Eyes of web Bush is on the Pacific rim. 322 00:18:39,920 --> 00:18:42,320 Speaker 2: He'll be you know, dialing in. It's like a VPN 323 00:18:42,520 --> 00:18:45,600 Speaker 2: dial in. Okay, he's in Bangkok and he's going to 324 00:18:45,640 --> 00:18:49,080 Speaker 2: be watching it to Iowa City. Yeah, the University of 325 00:18:49,160 --> 00:18:52,360 Speaker 2: Iowa Place of beleaguered Penn State. Should we get this 326 00:18:52,400 --> 00:18:55,399 Speaker 2: out of the way, let's do before tech talk, Dan Eyes, 327 00:18:55,440 --> 00:18:57,640 Speaker 2: are you on the short list to be the new 328 00:18:57,680 --> 00:18:59,119 Speaker 2: head coach of Penn State? 329 00:19:00,800 --> 00:19:03,879 Speaker 8: I am not. I mean, look, there's been talk Sweeney 330 00:19:03,920 --> 00:19:06,880 Speaker 8: could be up there, but I think it's I think 331 00:19:06,880 --> 00:19:10,320 Speaker 8: it's Sweeney, Urban Meyer, Joe Brady. I mean, that's a 332 00:19:10,400 --> 00:19:11,400 Speaker 8: top three. 333 00:19:11,800 --> 00:19:15,200 Speaker 2: What does a school's reaction to all the money that's involved. 334 00:19:15,200 --> 00:19:17,119 Speaker 2: I got to move on to tech, Dan, I as 335 00:19:17,160 --> 00:19:20,520 Speaker 2: we really appreciate making the effort from Hong Kong, but 336 00:19:20,760 --> 00:19:22,840 Speaker 2: one more pen stake. Well, I'm going to do one. 337 00:19:22,840 --> 00:19:26,119 Speaker 2: Then Paul's got as smarter what than me? What's the 338 00:19:26,160 --> 00:19:30,919 Speaker 2: reaction of State College Pennsylvania to the professionalism of the 339 00:19:31,080 --> 00:19:32,640 Speaker 2: millions of dollars involved? 340 00:19:33,800 --> 00:19:37,600 Speaker 8: Look, it's been obviously massively disappointed, right in terms of 341 00:19:37,640 --> 00:19:40,399 Speaker 8: this season, and you know that's why they had to 342 00:19:40,400 --> 00:19:43,000 Speaker 8: make a move, you know, in terms of Franklin. But look, 343 00:19:43,000 --> 00:19:45,359 Speaker 8: I think it just comes down to, you know, for 344 00:19:45,680 --> 00:19:49,160 Speaker 8: a program like ours, we had to sort of rip 345 00:19:49,200 --> 00:19:51,560 Speaker 8: the band aid off and now find our next leader. 346 00:19:51,760 --> 00:19:55,719 Speaker 8: And it's just just the reality of college sports today. 347 00:19:56,640 --> 00:19:58,360 Speaker 5: Who would you like, Dan, I mean, there's a lot 348 00:19:58,400 --> 00:20:01,600 Speaker 5: of Presumably, if I candidates out there, who would you 349 00:20:01,680 --> 00:20:02,159 Speaker 5: like to see? 350 00:20:03,200 --> 00:20:05,560 Speaker 8: I mean, for me the top two it would be 351 00:20:05,840 --> 00:20:08,960 Speaker 8: Urban Meyer because I think from a recruiter in terms 352 00:20:09,000 --> 00:20:11,440 Speaker 8: of big games and get him back in right, Yeah, 353 00:20:11,480 --> 00:20:13,080 Speaker 8: I think he'd be a great fit. And then I 354 00:20:13,080 --> 00:20:16,399 Speaker 8: think Joe Brady of coordinator for the Bills. 355 00:20:17,080 --> 00:20:19,440 Speaker 2: Mike from Long Island just emails this is get back 356 00:20:19,480 --> 00:20:22,840 Speaker 2: on topic, Tom, Thank you Mike for that. He is 357 00:20:22,840 --> 00:20:24,800 Speaker 2: in Hong Kong. Dan ives with us here on the 358 00:20:24,840 --> 00:20:28,520 Speaker 2: moment of technology. Dan Eyes, Lizzie and Saunders mentioned it 359 00:20:28,600 --> 00:20:33,560 Speaker 2: in every meeting. It's AI. How does Dan Ives synthesize 360 00:20:33,640 --> 00:20:38,280 Speaker 2: the AI frenzy, the plus and the minus right now? 361 00:20:39,600 --> 00:20:42,040 Speaker 8: I mean, look, I'm an easier form next like two 362 00:20:42,080 --> 00:20:44,720 Speaker 8: and a half weeks. And to us it's really it's 363 00:20:44,760 --> 00:20:46,760 Speaker 8: going around the region trying to understand what the demand 364 00:20:46,800 --> 00:20:51,760 Speaker 8: looks like. Look, demands accelerated twenty thirty percent. You know 365 00:20:51,840 --> 00:20:53,720 Speaker 8: if I go back to three four months ago, I 366 00:20:53,760 --> 00:20:56,280 Speaker 8: mean demand that SUPY for M video chips is ten 367 00:20:56,320 --> 00:20:58,720 Speaker 8: to one. So to me, Tom is like, I just 368 00:20:58,760 --> 00:21:01,399 Speaker 8: focus on what is the man look like on the 369 00:21:01,520 --> 00:21:05,280 Speaker 8: chip side when it comes to the use cases. Yeah, 370 00:21:05,440 --> 00:21:08,760 Speaker 8: I think three Q earnings are going to probably exceed 371 00:21:08,840 --> 00:21:10,080 Speaker 8: even the hype for AI. 372 00:21:10,240 --> 00:21:14,439 Speaker 2: And Noah Smith Paul Sweeney out yesterday, he's saying, forget 373 00:21:14,520 --> 00:21:18,119 Speaker 2: about all the panic. The usage of AI right now 374 00:21:18,480 --> 00:21:21,280 Speaker 2: is incalculable. How it's increasing, Yeah, we'll see. 375 00:21:21,280 --> 00:21:24,399 Speaker 5: And Dan, I think what's maybe gotten some people's attention 376 00:21:24,520 --> 00:21:27,640 Speaker 5: a little bit on concerned in the last three four 377 00:21:27,640 --> 00:21:30,080 Speaker 5: weeks has been some of these what I think some 378 00:21:30,119 --> 00:21:33,159 Speaker 5: people refer to as circular deals in Vidia investing in 379 00:21:33,200 --> 00:21:35,600 Speaker 5: open Ai and then you're going to be buying some 380 00:21:35,640 --> 00:21:38,360 Speaker 5: in Nvidia chips. And we've seen a number of these 381 00:21:38,400 --> 00:21:41,400 Speaker 5: deals number one, number two. They're huge dollar amounts here. 382 00:21:41,800 --> 00:21:44,520 Speaker 5: What do you make of those types of transactions. 383 00:21:45,200 --> 00:21:47,880 Speaker 8: Look, I get some of the concerns, and people will 384 00:21:47,920 --> 00:21:50,240 Speaker 8: say powers the late nineties, I mean I disagree with 385 00:21:50,240 --> 00:21:54,840 Speaker 8: in terms of vendor finance saying the reality is, I 386 00:21:54,840 --> 00:21:58,440 Speaker 8: mean open AI if you think about it like they'll 387 00:21:58,640 --> 00:22:01,480 Speaker 8: they'll put a dollar in, and very dow are they 388 00:22:01,480 --> 00:22:03,720 Speaker 8: put in, They're gonna get fifteen twenty hours back, whether 389 00:22:03,720 --> 00:22:06,800 Speaker 8: it's A and deer n video. So I view it 390 00:22:06,880 --> 00:22:12,000 Speaker 8: much more as collaboratively building the next economy rather than 391 00:22:12,040 --> 00:22:15,800 Speaker 8: some the short er circuar of finance things, sinister. I 392 00:22:15,840 --> 00:22:18,080 Speaker 8: mean that that that's sort of my view as it 393 00:22:18,080 --> 00:22:18,640 Speaker 8: plays out. 394 00:22:19,440 --> 00:22:21,960 Speaker 2: Dan eyes with us and we continue on technology, and 395 00:22:22,119 --> 00:22:24,600 Speaker 2: of course we're discussing Penn State. There he is in 396 00:22:24,640 --> 00:22:28,760 Speaker 2: Hong Kong. He'll listen to Penn State IOWA from Bangkok 397 00:22:28,840 --> 00:22:31,680 Speaker 2: here tomorrow. It's an evening game. He'll be in the morning. 398 00:22:31,680 --> 00:22:33,399 Speaker 2: It's like three, it's like F one. You're up at 399 00:22:33,480 --> 00:22:39,480 Speaker 2: ridiculous hours. Okay, Apple web Bush ives three ten is 400 00:22:39,520 --> 00:22:42,399 Speaker 2: a target. Here's the last targets on the A n 401 00:22:42,560 --> 00:22:46,520 Speaker 2: R screen two O five, two twenty Morgan Stanley's sod 402 00:22:46,560 --> 00:22:49,640 Speaker 2: of near web Bush evercore isi sort of near web 403 00:22:49,720 --> 00:22:55,320 Speaker 2: Bush two seventy seven, two eighteen and at two oh three, 404 00:22:55,720 --> 00:22:59,600 Speaker 2: Dan i'ves discussed the gloom around Apple. 405 00:23:00,720 --> 00:23:04,439 Speaker 8: I mean the cab driver in Hong Kong's barrens and Apple, 406 00:23:05,359 --> 00:23:08,320 Speaker 8: and I think that's both because my view is like, 407 00:23:08,440 --> 00:23:11,000 Speaker 8: it's not just about units moving up in terms of 408 00:23:11,000 --> 00:23:13,920 Speaker 8: iPhone seventeen. You saw it wrapp when the air went 409 00:23:13,960 --> 00:23:17,159 Speaker 8: on sale in China, but this is really over the 410 00:23:17,160 --> 00:23:19,520 Speaker 8: next six to nine months. I think as a large 411 00:23:19,600 --> 00:23:22,320 Speaker 8: cap this could be the biggest opp performer you know, 412 00:23:22,440 --> 00:23:27,040 Speaker 8: relative the opportunity ones. I think they ultimately google Gemini, 413 00:23:27,119 --> 00:23:30,160 Speaker 8: that will probably be the AI partnership, and I think 414 00:23:30,280 --> 00:23:32,840 Speaker 8: that is going to be the sort of aha moment 415 00:23:33,440 --> 00:23:34,199 Speaker 8: for this story. 416 00:23:35,240 --> 00:23:37,359 Speaker 5: Hey Dan, you know, as a good tech analyst, you 417 00:23:37,440 --> 00:23:39,440 Speaker 5: spend a lot of time in Asia as you're doing 418 00:23:39,520 --> 00:23:43,200 Speaker 5: right now, and I tell you the China US trade 419 00:23:44,000 --> 00:23:47,880 Speaker 5: discussions are really front and center for US equity investors here. 420 00:23:47,880 --> 00:23:50,760 Speaker 5: What are you hearing over there as it relates to 421 00:23:51,240 --> 00:23:55,679 Speaker 5: just kind of trade tensions tech in particular going forward. 422 00:23:56,880 --> 00:24:00,000 Speaker 8: Look, I mean there's pensions, but I do think investors 423 00:24:00,160 --> 00:24:03,080 Speaker 8: are starting to maybe feel like there's going to be 424 00:24:03,160 --> 00:24:06,879 Speaker 8: some sort of easing. I think that's reality. I think 425 00:24:07,240 --> 00:24:09,280 Speaker 8: when you look at the rare Earth and some of 426 00:24:09,280 --> 00:24:11,840 Speaker 8: the other sort of threats, I mean our view and 427 00:24:11,960 --> 00:24:15,040 Speaker 8: the most investadors are like, look, you buy the tech 428 00:24:15,080 --> 00:24:19,960 Speaker 8: winners as it ultimately plays out, and I think the 429 00:24:20,000 --> 00:24:22,280 Speaker 8: bar's gonna be worse than bite. I mean that continues 430 00:24:22,320 --> 00:24:24,680 Speaker 8: to sort of be our view as this plays out. 431 00:24:25,280 --> 00:24:28,119 Speaker 8: You don't get scared. This is not going to dent 432 00:24:28,240 --> 00:24:31,560 Speaker 8: the AI revolution. I think cool as rebellan. It starts 433 00:24:31,600 --> 00:24:35,760 Speaker 8: obviously with the summit between President and Trump a few weeks. 434 00:24:37,240 --> 00:24:40,160 Speaker 5: So Dan just real quickly following up on Apple here, 435 00:24:40,240 --> 00:24:44,080 Speaker 5: is there a sense that Apple can in fact get 436 00:24:44,160 --> 00:24:47,240 Speaker 5: some AI wind in its sale at some point? Or 437 00:24:47,320 --> 00:24:50,240 Speaker 5: is this a ship that maybe has sailed for Apple. 438 00:24:51,359 --> 00:24:53,560 Speaker 8: Look, I mean we've talked about, you know, on the 439 00:24:53,600 --> 00:24:56,600 Speaker 8: program so much. I don't think the ship's out. I 440 00:24:56,640 --> 00:24:59,200 Speaker 8: think the best that ever happened was the Google win 441 00:24:59,280 --> 00:25:01,879 Speaker 8: the view of Jason you because that's going to now 442 00:25:02,040 --> 00:25:05,440 Speaker 8: queer the way for Apple and Google. It's ultimately head 443 00:25:05,520 --> 00:25:08,600 Speaker 8: down the path from an AI partnership with Gemini, and 444 00:25:08,640 --> 00:25:11,200 Speaker 8: that's going to be a game changer for Apple. It's 445 00:25:11,240 --> 00:25:13,120 Speaker 8: not going to come and turn on Dan. 446 00:25:12,960 --> 00:25:14,560 Speaker 2: I have too short a visit. Love to get you 447 00:25:14,600 --> 00:25:16,760 Speaker 2: back into the studio. Try to fly safe and get 448 00:25:16,760 --> 00:25:20,560 Speaker 2: some sleep on the Gulf Stream Dana's web Bush Stay 449 00:25:20,600 --> 00:25:24,480 Speaker 2: with us. More from Bloomberg Surveillance coming up after this. 450 00:25:31,720 --> 00:25:35,280 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 451 00:25:35,359 --> 00:25:38,520 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 452 00:25:38,600 --> 00:25:42,280 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 453 00:25:42,440 --> 00:25:43,920 Speaker 1: watch us live on YouTube. 454 00:25:44,119 --> 00:25:46,679 Speaker 2: Which security to Brown University. Wendy Schiller with us for 455 00:25:46,720 --> 00:25:49,199 Speaker 2: too short a visit, Wendy, what's it like when a 456 00:25:49,359 --> 00:25:53,360 Speaker 2: university when a faculty wins a Nobel Prize in economics? 457 00:25:53,400 --> 00:25:55,679 Speaker 2: What was it like when you heard the professor how 458 00:25:55,760 --> 00:25:59,359 Speaker 2: it had taken part of the Nobel Prize? 459 00:25:59,560 --> 00:26:02,399 Speaker 7: Well, it was great for Brown University. We are not 460 00:26:02,640 --> 00:26:05,960 Speaker 7: accustomed to having a lot of our faculty be contenders 461 00:26:06,040 --> 00:26:09,320 Speaker 7: or win Nobel prizes. So it's a marker. And we 462 00:26:09,359 --> 00:26:12,399 Speaker 7: have a strong economics department. Our president is an economist, 463 00:26:13,400 --> 00:26:17,200 Speaker 7: and so we were thrilled and really thrilled about that. 464 00:26:17,359 --> 00:26:22,280 Speaker 2: Your turn is next year, Wendy. What does the Congress do? 465 00:26:22,720 --> 00:26:29,000 Speaker 2: Whatever our listeners and viewers politics, there's a primal scream legislature, 466 00:26:29,119 --> 00:26:31,840 Speaker 2: get your act together. How do they do that? In 467 00:26:31,880 --> 00:26:34,080 Speaker 2: a Wendy Schiller textbook. 468 00:26:34,960 --> 00:26:37,760 Speaker 7: Well, you know, Congress in the last ten fifteen years 469 00:26:37,880 --> 00:26:40,680 Speaker 7: has figured out when they really have to get it done, 470 00:26:40,880 --> 00:26:43,880 Speaker 7: they get it done. Nobody's feeling the pressure to get 471 00:26:43,880 --> 00:26:47,960 Speaker 7: it done because they keep carving out major expenses like 472 00:26:48,000 --> 00:26:51,119 Speaker 7: the military. Now Trump says, oh, well we found some money. 473 00:26:51,280 --> 00:26:54,200 Speaker 7: They're going to get paid this week. Now they're talking 474 00:26:54,560 --> 00:27:00,280 Speaker 7: apparently about carving out essential federal employees and finding money 475 00:27:00,320 --> 00:27:02,160 Speaker 7: to pay them. What most people don't know is that 476 00:27:02,160 --> 00:27:04,760 Speaker 7: the president of the United States does have flexibility to 477 00:27:04,840 --> 00:27:07,760 Speaker 7: move money around in the federal government an executive branch, 478 00:27:08,040 --> 00:27:11,119 Speaker 7: and even though Congress is appropriates the money, if you 479 00:27:11,200 --> 00:27:13,760 Speaker 7: can prove that it's for the general welfare, that's the 480 00:27:13,840 --> 00:27:17,439 Speaker 7: clause and the Constitution, then you can move money around. 481 00:27:17,840 --> 00:27:20,760 Speaker 7: And so they're starting at the executive level, at least 482 00:27:20,920 --> 00:27:24,320 Speaker 7: under Trump, to say, well, who can recover that is 483 00:27:24,359 --> 00:27:26,560 Speaker 7: otherwise going to generate a lot of backlash. And they 484 00:27:26,600 --> 00:27:30,240 Speaker 7: started with the military. Now they're thinking about essential workers, TSA, 485 00:27:30,320 --> 00:27:34,640 Speaker 7: air traffic controllers. So if you're carving out so many 486 00:27:34,640 --> 00:27:37,000 Speaker 7: sectors of the government that will not be affected by 487 00:27:37,040 --> 00:27:39,520 Speaker 7: the shutdown, the pressure on Congress to come to the 488 00:27:39,520 --> 00:27:41,040 Speaker 7: table just gets less and less. 489 00:27:41,400 --> 00:27:45,480 Speaker 5: So is there any value in people like me sitting 490 00:27:45,520 --> 00:27:48,720 Speaker 5: back and saying, who's paying the price here, who's the 491 00:27:48,800 --> 00:27:52,120 Speaker 5: blame here, who should really be the adult in the room, 492 00:27:52,560 --> 00:27:54,919 Speaker 5: and get stuff back to the table, because it doesn't 493 00:27:55,080 --> 00:27:57,680 Speaker 5: feel like there's that much pressure this time around. 494 00:27:58,280 --> 00:28:01,400 Speaker 7: Well, the Democrats are walking a fine line. They succeeded 495 00:28:01,480 --> 00:28:04,840 Speaker 7: in holding their ranks to make sure that everybody in 496 00:28:04,880 --> 00:28:07,840 Speaker 7: America got news that they are in health insurance premiums 497 00:28:07,840 --> 00:28:09,679 Speaker 7: are going to go up, and the people who are 498 00:28:09,680 --> 00:28:13,560 Speaker 7: eligible for Obamacare tax subsidies to help with those premiums 499 00:28:14,119 --> 00:28:16,000 Speaker 7: they just learned that they're going to get. It's much 500 00:28:16,000 --> 00:28:18,879 Speaker 7: more expensive, but they've been modifying that with tax breaks, 501 00:28:19,119 --> 00:28:21,840 Speaker 7: so they managed to hold. So that's a winning point 502 00:28:21,840 --> 00:28:24,280 Speaker 7: for them, which means Republicans going be under pressure to 503 00:28:24,320 --> 00:28:27,720 Speaker 7: extend those tax breaks. However, the things that really get 504 00:28:27,720 --> 00:28:30,840 Speaker 7: affected by a shutdown are discretionary spending, and those programs 505 00:28:30,880 --> 00:28:35,200 Speaker 7: are typically designed and promoted by Democrats. There are things 506 00:28:35,200 --> 00:28:38,120 Speaker 7: the government does for people that the Republicans may not 507 00:28:38,160 --> 00:28:40,920 Speaker 7: be interested in. So the longer shutdown goes, and the 508 00:28:40,960 --> 00:28:44,280 Speaker 7: more of those employees who are furloughed and that money 509 00:28:44,320 --> 00:28:47,120 Speaker 7: doesn't go out the door, that hurts some of the Democrats' 510 00:28:47,120 --> 00:28:47,920 Speaker 7: policy priorities. 511 00:28:47,960 --> 00:28:51,520 Speaker 2: Okay, you Henry Olson's right in the Washington Post about 512 00:28:51,560 --> 00:28:56,240 Speaker 2: the Democrat Marjorie Taylor Green all fired up about the shutdown. 513 00:28:56,360 --> 00:29:02,080 Speaker 2: I'm kidding, folks, are Southern Republican Professor Schiller, is Marjorie 514 00:29:02,120 --> 00:29:03,760 Speaker 2: Green on the President's side. 515 00:29:05,320 --> 00:29:08,080 Speaker 7: No, Margie Taylor Green's on Marjorie Taylor Green's side. And 516 00:29:08,120 --> 00:29:12,040 Speaker 7: she's proven over and over again to be pretty savvy 517 00:29:12,360 --> 00:29:14,320 Speaker 7: when it comes to these things. We've also seen people 518 00:29:14,320 --> 00:29:17,360 Speaker 7: who are not typically in the news, Republicans who come 519 00:29:17,360 --> 00:29:20,760 Speaker 7: from districts that are read, states that are read. Lots 520 00:29:20,760 --> 00:29:24,440 Speaker 7: of federal employees in those districts. Think of national parks, 521 00:29:24,600 --> 00:29:26,760 Speaker 7: think of the western part of this country. There are 522 00:29:26,800 --> 00:29:29,040 Speaker 7: a lot of people who are in those red Republican 523 00:29:29,080 --> 00:29:31,760 Speaker 7: states that work for the government that are furloughed now, 524 00:29:31,920 --> 00:29:34,080 Speaker 7: and that's going to come back to really start to 525 00:29:34,120 --> 00:29:37,360 Speaker 7: haunt Republicans. So this is the thing that the Trump mistress. 526 00:29:37,480 --> 00:29:40,040 Speaker 7: You have John Thune, the majority leader of United States Senate, 527 00:29:40,320 --> 00:29:44,760 Speaker 7: begging the President for farm subsidies, for loans for payment 528 00:29:45,000 --> 00:29:48,800 Speaker 7: because China's not buying soybeans, writing seas from South Dakota. 529 00:29:48,880 --> 00:29:51,120 Speaker 7: So when you think about that, there are lots of 530 00:29:51,120 --> 00:29:53,880 Speaker 7: ways now that the Republicans are starting to feel more heat, 531 00:29:54,120 --> 00:29:57,320 Speaker 7: not necessarily from a shutdown, but from Trump policies, and 532 00:29:57,360 --> 00:29:59,640 Speaker 7: they don't seem to have a lot of leverage with 533 00:29:59,800 --> 00:30:00,560 Speaker 7: this administration. 534 00:30:00,640 --> 00:30:02,840 Speaker 2: Professor to short a visit, We'd love to speak to 535 00:30:02,880 --> 00:30:05,600 Speaker 2: you every time. Next week, Let's do it again. From 536 00:30:05,600 --> 00:30:09,920 Speaker 2: the Nobel Prize Running Brown University. It is Wendy at Schiller. 537 00:30:09,960 --> 00:30:14,760 Speaker 1: This is the Bloomberg Surveillance Podcast, available on Apple, Spotify, 538 00:30:14,880 --> 00:30:19,160 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 539 00:30:19,280 --> 00:30:22,760 Speaker 1: seven to ten am Eastern on Bloomberg dot Com, the 540 00:30:22,840 --> 00:30:26,880 Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You 541 00:30:26,920 --> 00:30:30,280 Speaker 1: can also watch us live every weekday on YouTube and 542 00:30:30,480 --> 00:30:32,200 Speaker 1: always on the Bloomberg terminal