1 00:00:00,840 --> 00:00:04,000 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, alongside 2 00:00:04,040 --> 00:00:05,280 Speaker 1: my co host Matt Miller. 3 00:00:05,640 --> 00:00:09,600 Speaker 2: Every business day we bring you interviews from CEOs, market pros, 4 00:00:09,720 --> 00:00:13,600 Speaker 2: and Bloomberg experts, along with essential market moven news. 5 00:00:14,160 --> 00:00:17,279 Speaker 1: Find the Bloomberg Markets podcast called Apple Podcasts or wherever 6 00:00:17,400 --> 00:00:20,480 Speaker 1: you listen to podcasts, and at Bloomberg dot com slash podcast. 7 00:00:21,160 --> 00:00:23,000 Speaker 3: We've got a good block of time here and we're 8 00:00:23,000 --> 00:00:23,520 Speaker 3: gonna need it. 9 00:00:23,600 --> 00:00:24,000 Speaker 4: Daniel D. 10 00:00:24,120 --> 00:00:28,160 Speaker 1: Martino Booth joins us here on our Bloomberg Interactive Broker's studio. 11 00:00:28,360 --> 00:00:30,120 Speaker 3: You know her, you know her work. 12 00:00:30,040 --> 00:00:34,000 Speaker 1: CEO and chief strategists at QI Research. Daniel, thanks so 13 00:00:34,080 --> 00:00:36,760 Speaker 1: much for joining us here, Boyd. A lot of economic 14 00:00:36,800 --> 00:00:39,559 Speaker 1: data coming out over the last several days. I don't know, 15 00:00:39,600 --> 00:00:42,720 Speaker 1: the economy seems pretty darn strong to me. I'm not 16 00:00:42,760 --> 00:00:45,440 Speaker 1: sure if the recession talk is off the table. What 17 00:00:45,600 --> 00:00:46,960 Speaker 1: does our Federal Reserve do? 18 00:00:47,400 --> 00:00:48,960 Speaker 3: Look at some of the eco data we've seen over 19 00:00:48,960 --> 00:00:50,000 Speaker 3: the last several days. 20 00:00:50,320 --> 00:00:52,199 Speaker 5: Well, you have to bear in mind, I'm of the 21 00:00:52,240 --> 00:00:54,840 Speaker 5: mind that the Federal Reserve wants a reason to keep 22 00:00:54,920 --> 00:00:59,440 Speaker 5: raising rates. Okay, and we follow one metric at QI 23 00:00:59,520 --> 00:01:03,520 Speaker 5: Research the most closely because it's got the least noise 24 00:01:03,560 --> 00:01:09,000 Speaker 5: in it, so not statistically not seasonally adjusted continuing claims. 25 00:01:09,080 --> 00:01:11,080 Speaker 3: Okay, So I'm gonna make this really simple. 26 00:01:11,160 --> 00:01:13,679 Speaker 5: Last September, there were zero states in the United States 27 00:01:13,680 --> 00:01:17,640 Speaker 5: of America that had rising year over year continuing claimants. 28 00:01:17,760 --> 00:01:21,240 Speaker 5: So the number of individuals in zero states in terms 29 00:01:21,280 --> 00:01:26,000 Speaker 5: of rising beneficiaries. Okay, last September, forty six states as 30 00:01:26,080 --> 00:01:33,240 Speaker 5: of this morning's data have rising continuing claimants. That's ninety 31 00:01:34,080 --> 00:01:35,240 Speaker 5: ninety four percent of the population. 32 00:01:35,319 --> 00:01:38,399 Speaker 3: Wow, Okay, so what's that tell you that? 33 00:01:38,640 --> 00:01:40,240 Speaker 5: And it's been gradual, by the way, this is not 34 00:01:40,319 --> 00:01:43,000 Speaker 5: like from September and a light flipped on in July. 35 00:01:43,080 --> 00:01:46,840 Speaker 5: It's a very gradual move. And it tells me that 36 00:01:46,959 --> 00:01:50,160 Speaker 5: even though the data is not fast moving, that seasonality 37 00:01:50,240 --> 00:01:52,640 Speaker 5: is really giving a lot of trouble to a lot 38 00:01:52,680 --> 00:01:54,760 Speaker 5: of these other data sets. And it just tells you 39 00:01:54,800 --> 00:01:58,680 Speaker 5: that there's been a steady, a steady degradation in the 40 00:01:58,800 --> 00:02:03,200 Speaker 5: US economy viewed through the purest prism of people continuing 41 00:02:03,640 --> 00:02:07,200 Speaker 5: to claim jobless benefits. Not initial, they're not they're not applying, 42 00:02:07,440 --> 00:02:08,720 Speaker 5: they're they're collecting. 43 00:02:09,080 --> 00:02:10,880 Speaker 3: What is eighty I don't know what to do with 44 00:02:10,919 --> 00:02:11,680 Speaker 3: ad you. 45 00:02:11,680 --> 00:02:12,760 Speaker 6: Know, you know, what do you do with ADP? 46 00:02:12,840 --> 00:02:14,320 Speaker 3: I tell you what with ADP? 47 00:02:14,480 --> 00:02:17,200 Speaker 5: You go, Look, we've had about four hundred and we've 48 00:02:17,200 --> 00:02:19,919 Speaker 5: we've had about three hundred and forty eight thousand last 49 00:02:19,960 --> 00:02:23,720 Speaker 5: six months NFP non farm payrolls YEP ADPs three hundred 50 00:02:23,720 --> 00:02:26,680 Speaker 5: and sixty three last six months. Okay, fine, it's caught up. 51 00:02:27,120 --> 00:02:29,799 Speaker 5: Moving on some of that. Some of the aberrations in. 52 00:02:29,760 --> 00:02:30,880 Speaker 3: The data are bizarre. 53 00:02:31,760 --> 00:02:35,720 Speaker 5: Leisure in hospitality, mining. Did we discover copper in America? 54 00:02:36,200 --> 00:02:36,399 Speaker 7: Mining? 55 00:02:36,440 --> 00:02:40,040 Speaker 5: Because that was a huge pop in mining. So and 56 00:02:40,040 --> 00:02:43,880 Speaker 5: we've seen the Baylor, We've seen the Baker, Riggs, Hughes, 57 00:02:43,919 --> 00:02:46,560 Speaker 5: rigcount I can't speak this one. I've had too much coffee. 58 00:02:46,600 --> 00:02:49,720 Speaker 5: We've seen rig counts come down. Okay, So there's no 59 00:02:49,760 --> 00:02:51,680 Speaker 5: reason to think that there's a whole bunch of shale 60 00:02:51,760 --> 00:02:54,720 Speaker 5: formation that's pulling people into the energy patch. 61 00:02:55,160 --> 00:02:56,760 Speaker 1: So you think the economy is weaker than some of 62 00:02:56,760 --> 00:02:59,440 Speaker 1: the underlying some of the headline data is showing. 63 00:02:59,639 --> 00:03:01,320 Speaker 5: I think the economy is weaker if you look on 64 00:03:01,400 --> 00:03:01,800 Speaker 5: a grant. 65 00:03:02,800 --> 00:03:04,360 Speaker 3: When I give the Fed some reasons that just to 66 00:03:04,400 --> 00:03:05,320 Speaker 3: pause if not, I. 67 00:03:05,280 --> 00:03:07,520 Speaker 5: Don't think the Fed wants to pause Okay, I think 68 00:03:07,520 --> 00:03:09,919 Speaker 5: the Fed is looking for reasons to keep going. I 69 00:03:10,000 --> 00:03:13,480 Speaker 5: think if you pay attention to how they will not 70 00:03:13,560 --> 00:03:17,160 Speaker 5: discuss the balance sheet. We're not talking about quantitative tightening. 71 00:03:17,560 --> 00:03:20,240 Speaker 5: It's like Voldemort. They won't talk about it. But they 72 00:03:20,240 --> 00:03:22,840 Speaker 5: can't have quantitative tightening. They can't continue to shrink the 73 00:03:22,840 --> 00:03:26,320 Speaker 5: balance sheet. If a discussion is even entered into about 74 00:03:26,320 --> 00:03:29,240 Speaker 5: easing where rates are they have to keep rights high 75 00:03:29,280 --> 00:03:30,399 Speaker 5: to keep shrinking the balance sheet. 76 00:03:30,400 --> 00:03:32,360 Speaker 8: So we're getting all of this labor data ahead of 77 00:03:32,480 --> 00:03:35,920 Speaker 8: tomorrow's important jobs report, and it's interesting. I'm looking at 78 00:03:35,960 --> 00:03:38,320 Speaker 8: Ecogo and the terminal and it looks like the unemployment 79 00:03:38,360 --> 00:03:40,200 Speaker 8: rate it's actually going to tick down from three point 80 00:03:40,280 --> 00:03:43,680 Speaker 8: seven percent through three point six percent based on analysts 81 00:03:43,720 --> 00:03:45,840 Speaker 8: that we're pulling in the terminal. You look at the 82 00:03:46,480 --> 00:03:48,720 Speaker 8: when it comes to non farm payrolls about two hundred 83 00:03:48,720 --> 00:03:51,800 Speaker 8: and twenty five thousand. What is your take on what 84 00:03:52,000 --> 00:03:55,080 Speaker 8: we could see tomorrow and obviously how that could potentially 85 00:03:55,160 --> 00:03:57,480 Speaker 8: relate to how US stocks are moving on the back 86 00:03:57,520 --> 00:03:59,680 Speaker 8: of this type of data that clearly not even just 87 00:03:59,720 --> 00:04:01,360 Speaker 8: the stuf Bock market, but looking what's happening with a 88 00:04:01,400 --> 00:04:03,440 Speaker 8: two year and the. 89 00:04:03,360 --> 00:04:05,760 Speaker 5: Two year really is where it is all at at 90 00:04:05,760 --> 00:04:10,000 Speaker 5: this point, right, you know, I think I can't tell 91 00:04:10,000 --> 00:04:13,080 Speaker 5: you what NFP is going to do tomorrow. I had 92 00:04:13,080 --> 00:04:14,680 Speaker 5: a friend of Mit, Peter Sheher, he's a good friend 93 00:04:14,840 --> 00:04:17,680 Speaker 5: of Bloomberg's, you know, he made the comment, what are 94 00:04:17,680 --> 00:04:20,279 Speaker 5: the statistically speaking, what are the odds that fourteen months 95 00:04:20,320 --> 00:04:22,560 Speaker 5: in a row all the economists missed the estimate? 96 00:04:23,680 --> 00:04:24,520 Speaker 3: And what are the odds? 97 00:04:24,560 --> 00:04:27,680 Speaker 5: I mean, the bls will tell you that forty two 98 00:04:27,760 --> 00:04:30,240 Speaker 5: percent of the jobs created in the last forty two 99 00:04:30,320 --> 00:04:35,119 Speaker 5: months are against a backdrop of the fastest bankruptcy cycle 100 00:04:35,160 --> 00:04:37,479 Speaker 5: since two thousand and nine. So how do we have 101 00:04:37,520 --> 00:04:40,120 Speaker 5: a birth death adjustment that adds forty two percent net 102 00:04:40,160 --> 00:04:43,200 Speaker 5: net of all non farm payroll jobs. Forty two percent 103 00:04:43,240 --> 00:04:45,280 Speaker 5: is not a small number over the last twelve months 104 00:04:45,279 --> 00:04:49,640 Speaker 5: in the aggregate, assuming that this is all berths, when 105 00:04:49,839 --> 00:04:52,560 Speaker 5: you can pull up BCY, go on the terminal and 106 00:04:52,600 --> 00:04:55,200 Speaker 5: see the biggest number since two thousand and nine. 107 00:04:55,480 --> 00:04:57,880 Speaker 8: So when you see the two year at a sixteen 108 00:04:58,000 --> 00:05:00,040 Speaker 8: year high, what do you think the bond market it 109 00:05:00,160 --> 00:05:00,720 Speaker 8: is telling us. 110 00:05:00,720 --> 00:05:02,440 Speaker 5: It's telling you that Fed's going to keep raising rates 111 00:05:03,720 --> 00:05:04,600 Speaker 5: come what may. 112 00:05:05,360 --> 00:05:10,279 Speaker 1: So we've got ninety percent priced in for the next meeting, 113 00:05:10,600 --> 00:05:12,560 Speaker 1: they go again after that, you think it's September. 114 00:05:13,520 --> 00:05:16,040 Speaker 5: I think it really becomes data dependent at that point, 115 00:05:16,200 --> 00:05:18,240 Speaker 5: unless there's going to be an investigation launched to the 116 00:05:18,279 --> 00:05:21,800 Speaker 5: Bureau of Labor Statistics, because they're already questioning the inflation data. 117 00:05:22,000 --> 00:05:25,560 Speaker 5: That's a matter of public knowledge. So I mean, barring that, 118 00:05:26,279 --> 00:05:29,960 Speaker 5: you don't get to forty six states with rising continuing 119 00:05:29,960 --> 00:05:32,880 Speaker 5: claimants without somebody starting to notice that there's a problem 120 00:05:32,960 --> 00:05:33,520 Speaker 5: in the country. 121 00:05:34,480 --> 00:05:37,240 Speaker 1: So what is the I mean, what is your overall 122 00:05:37,279 --> 00:05:39,880 Speaker 1: take of this economy that there is in fact more 123 00:05:39,880 --> 00:05:42,960 Speaker 1: weakness than the I guess the headline data would show. 124 00:05:43,760 --> 00:05:46,320 Speaker 3: But yet they're still going to rate raise rates. 125 00:05:46,720 --> 00:05:50,240 Speaker 5: It's the butt Yet remember the employee Retention credit they 126 00:05:50,320 --> 00:05:53,480 Speaker 5: advertise all the time. It just pumped twenty eight point 127 00:05:53,520 --> 00:05:56,240 Speaker 5: eight billion dollars into the US economy in the month 128 00:05:56,279 --> 00:05:59,200 Speaker 5: of June alone. It's been about twenty billion dollars a 129 00:05:59,240 --> 00:06:02,480 Speaker 5: month now for about eighteen months. There's a massive form 130 00:06:02,720 --> 00:06:05,720 Speaker 5: of COVID fiscal stimulus that continues to make its way 131 00:06:05,720 --> 00:06:08,640 Speaker 5: into this economy. You see it in international travel. But 132 00:06:08,720 --> 00:06:10,839 Speaker 5: his tourist and slack came out in his morning note 133 00:06:10,839 --> 00:06:13,560 Speaker 5: this morning and said the US consumer slowing. I think 134 00:06:13,560 --> 00:06:15,680 Speaker 5: it pained him to say that, But if you look 135 00:06:15,720 --> 00:06:19,000 Speaker 5: beyond the recipients of this employee retention credit, kind of 136 00:06:19,000 --> 00:06:22,640 Speaker 5: the wealthiest, the highest income earners, you're seeing decided signs 137 00:06:22,640 --> 00:06:23,920 Speaker 5: of slowing in consumption. 138 00:06:24,360 --> 00:06:27,240 Speaker 8: So then with this jobs report tomorrow, we have CPI 139 00:06:27,400 --> 00:06:30,640 Speaker 8: on July twelfth, so next week, and then we'll have 140 00:06:30,720 --> 00:06:34,120 Speaker 8: the FED meeting on July twenty fifth and twenty six, 141 00:06:34,240 --> 00:06:37,520 Speaker 8: So those are the last major data points before that. 142 00:06:37,720 --> 00:06:41,160 Speaker 8: Is that enough for them to decide to potentially hike Oh? 143 00:06:41,320 --> 00:06:41,920 Speaker 5: I think it is. 144 00:06:42,360 --> 00:06:42,880 Speaker 9: I really do. 145 00:06:43,839 --> 00:06:44,080 Speaker 3: Again. 146 00:06:44,120 --> 00:06:47,320 Speaker 5: He's focused on an inflation metric of his own design, 147 00:06:48,160 --> 00:06:51,480 Speaker 5: the core CPI net of shelter, and it is a 148 00:06:51,560 --> 00:06:54,320 Speaker 5: slow moving animal. We've gone back and looked at it historically, 149 00:06:54,400 --> 00:06:56,839 Speaker 5: prior to the pandemic, it was usually running at about 150 00:06:56,839 --> 00:06:59,799 Speaker 5: two to three percent, but two percent was a rarity, 151 00:07:00,200 --> 00:07:04,080 Speaker 5: that isolated metric that J. Powell has conceived out of 152 00:07:04,080 --> 00:07:08,159 Speaker 5: thin air. So in that he's looking at that, I 153 00:07:08,200 --> 00:07:11,120 Speaker 5: think that it's very conceivable. We're you know, O Mayr 154 00:07:11,200 --> 00:07:14,040 Speaker 5: Sharif is saying, you know, look for used cars prices 155 00:07:14,080 --> 00:07:17,480 Speaker 5: to come down, you know, look for shelter to continue falling. 156 00:07:17,600 --> 00:07:20,800 Speaker 5: Look for that next CPI print to be very bond 157 00:07:20,840 --> 00:07:24,400 Speaker 5: market friendly unless Ja Powel's just going to look through 158 00:07:24,400 --> 00:07:27,160 Speaker 5: it as you go forty eight hours into blackout right 159 00:07:27,200 --> 00:07:27,960 Speaker 5: before the next for. 160 00:07:28,120 --> 00:07:30,360 Speaker 3: MC, what are one of the many reasons we're like 161 00:07:30,360 --> 00:07:32,520 Speaker 3: speaking to you is you rip out some data points 162 00:07:32,560 --> 00:07:34,000 Speaker 3: that quite frankly, I've never heard of. 163 00:07:34,200 --> 00:07:35,920 Speaker 1: What are some of the data points that you and 164 00:07:36,000 --> 00:07:37,640 Speaker 1: your team are kind of looking at here to get 165 00:07:38,120 --> 00:07:39,920 Speaker 1: a sense that maybe aren't on eco go. 166 00:07:40,560 --> 00:07:42,120 Speaker 3: So we actually. 167 00:07:41,800 --> 00:07:46,400 Speaker 5: Follow weekly data from light Cast. They started tracking the 168 00:07:46,480 --> 00:07:49,360 Speaker 5: data as of January twenty twenty to get a benchmark 169 00:07:49,400 --> 00:07:51,800 Speaker 5: for which types of job openings there are in the nation, 170 00:07:52,360 --> 00:07:56,360 Speaker 5: so jobs with minimal education required, I mean they needed 171 00:07:56,360 --> 00:07:58,880 Speaker 5: a new scale in order to track how many job 172 00:07:58,920 --> 00:08:01,960 Speaker 5: openings there were for lee, your hospitality, bus boys, you 173 00:08:02,040 --> 00:08:06,200 Speaker 5: name it. That's recently through the week of June twenty 174 00:08:06,240 --> 00:08:09,480 Speaker 5: fourth come down to zero, so there are effectively no 175 00:08:09,600 --> 00:08:12,760 Speaker 5: job opening Using a benchmark of January of twenty twenty, 176 00:08:12,960 --> 00:08:17,840 Speaker 5: I follow trueflation very closely truflation. We actually were able 177 00:08:17,880 --> 00:08:20,440 Speaker 5: to get their full data set back to twenty twelve. 178 00:08:20,680 --> 00:08:24,720 Speaker 5: We ran a correlation analysis with the headline CPI last Friday, 179 00:08:25,040 --> 00:08:29,000 Speaker 5: ninety seven percent since twenty twelve. The correlation where it's 180 00:08:29,040 --> 00:08:32,680 Speaker 5: trueflation today two point two percent. Okay, it's thirty million 181 00:08:32,720 --> 00:08:35,640 Speaker 5: real time prices. It's a daily inflation print, but a 182 00:08:35,720 --> 00:08:40,200 Speaker 5: ninety seven percent correlation since twenty twelve. With headline CPI 183 00:08:40,400 --> 00:08:42,280 Speaker 5: tells you exactly where inflation is headed. 184 00:08:42,480 --> 00:08:45,760 Speaker 1: So inflation's headed lower, much lower. And isn't that good 185 00:08:45,800 --> 00:08:47,839 Speaker 1: news for Jpal? And that's what he wants to see. 186 00:08:47,920 --> 00:08:50,480 Speaker 5: Ran, It's not good news for that Jpal That Japal 187 00:08:50,559 --> 00:08:53,160 Speaker 5: wants to continue shrinking that balance sheet, oh Man, and 188 00:08:53,200 --> 00:08:55,920 Speaker 5: he wants a reason to continue shrinking that balance sheet. 189 00:08:56,080 --> 00:08:58,600 Speaker 5: So he's going to focus on job openings remaining high, 190 00:08:58,840 --> 00:09:00,560 Speaker 5: even though work out of the Dallas Fed shows that 191 00:09:00,640 --> 00:09:03,520 Speaker 5: ninety percent of those job openings are written for the 192 00:09:03,920 --> 00:09:07,880 Speaker 5: specific purpose of poaching your closest competitors employees so you 193 00:09:07,880 --> 00:09:09,640 Speaker 5: don't have to spend the money training them. The other 194 00:09:09,679 --> 00:09:13,920 Speaker 5: ten percent actually reflect organic demand in the economy for 195 00:09:14,080 --> 00:09:17,520 Speaker 5: new job openings. That's being reflected in indeed dot com 196 00:09:17,559 --> 00:09:19,920 Speaker 5: as well. You're seeing in d dot com job postings 197 00:09:19,960 --> 00:09:22,920 Speaker 5: have come down tremendously over the last twelve months. That's 198 00:09:22,960 --> 00:09:25,040 Speaker 5: another big one that we follow. And again it's a 199 00:09:25,080 --> 00:09:28,000 Speaker 5: weekly data set and they're speaking to thousands and thousands 200 00:09:28,040 --> 00:09:30,160 Speaker 5: of companies across the country. That's what you want. You 201 00:09:30,200 --> 00:09:32,120 Speaker 5: want people who are speaking to people on the ground. 202 00:09:32,920 --> 00:09:35,280 Speaker 8: And so even though we see the Fed's preferred gauge 203 00:09:35,320 --> 00:09:38,160 Speaker 8: PCE moving in the right direction, to you, that's still 204 00:09:38,200 --> 00:09:40,000 Speaker 8: not enough when you're looking at what's happening with the 205 00:09:40,000 --> 00:09:41,000 Speaker 8: strength on the labor's side. 206 00:09:41,000 --> 00:09:42,920 Speaker 5: And I'm going to quote Powell here, until the job 207 00:09:43,000 --> 00:09:46,120 Speaker 5: is done, yep, until we get to two percent. 208 00:09:46,480 --> 00:09:48,480 Speaker 3: And two percent, what is the two percent number? That 209 00:09:48,600 --> 00:09:49,440 Speaker 3: is the core x. 210 00:09:50,800 --> 00:09:53,240 Speaker 5: He's looking for core PCE to be two percent. That 211 00:09:53,320 --> 00:09:55,640 Speaker 5: is typically the gauge that you're talking about internally. 212 00:09:55,800 --> 00:09:57,840 Speaker 3: Okay, all right, and we're not there yet. 213 00:09:58,280 --> 00:10:01,160 Speaker 10: No, we got no excluding food and energy. 214 00:10:01,440 --> 00:10:03,720 Speaker 5: But he's going to keep you also, like to house weeds, 215 00:10:03,760 --> 00:10:06,120 Speaker 5: we get data out today at just after four o'clock. 216 00:10:06,240 --> 00:10:08,400 Speaker 5: You're going to see a big chunk of quantitative tightening 217 00:10:08,480 --> 00:10:10,559 Speaker 5: when that data hits late after the bill today. 218 00:10:10,760 --> 00:10:12,960 Speaker 1: All right, Danielle Dee Martine Booth, thank you so much 219 00:10:13,080 --> 00:10:15,760 Speaker 1: for joining us. He know, Danielle de Martino Booth, she 220 00:10:15,960 --> 00:10:18,200 Speaker 1: is the CEO, and she is the chief. 221 00:10:18,120 --> 00:10:19,800 Speaker 3: Strategist at QI Research. 222 00:10:19,880 --> 00:10:22,480 Speaker 1: She's also did a stint at the Dallas Federal Reserve, 223 00:10:22,640 --> 00:10:24,679 Speaker 1: so you know about the Dallas Federal Reserve and how 224 00:10:24,679 --> 00:10:27,320 Speaker 1: the central bankers think across the board. So I always 225 00:10:27,320 --> 00:10:29,679 Speaker 1: appreciate getting some of Danielle's thoughts here. 226 00:10:31,120 --> 00:10:34,959 Speaker 11: You're listening to the Team Ken's live program Bloomberg Markets 227 00:10:35,000 --> 00:10:38,080 Speaker 11: weekdays at ten am Eastern on Bloomberg dot Com, the 228 00:10:38,160 --> 00:10:41,280 Speaker 11: iHeartRadio app, and the Bloomberg Business App, or listen on 229 00:10:41,360 --> 00:10:43,320 Speaker 11: demand wherever you get your podcasts. 230 00:10:45,800 --> 00:10:48,720 Speaker 8: To our next guest, Michael Green, portfolio manager in chief 231 00:10:48,720 --> 00:10:52,160 Speaker 8: Strategists at Simplify Asset Management. Michael, thank you for joining us. 232 00:10:52,200 --> 00:10:55,200 Speaker 8: Before we get more into what you're going to talk about, 233 00:10:55,240 --> 00:10:57,440 Speaker 8: as far as what you like about sectors in the 234 00:10:57,520 --> 00:10:59,080 Speaker 8: S and P five hundred, I have to get your 235 00:10:59,120 --> 00:11:01,640 Speaker 8: take as far as these massive moves in the bond market, 236 00:11:01,679 --> 00:11:04,120 Speaker 8: especially with the two year treasury trading round its highest 237 00:11:04,240 --> 00:11:07,040 Speaker 8: level in about sixteen years. 238 00:11:07,520 --> 00:11:10,040 Speaker 12: Well, I have to confess that I actually see the 239 00:11:10,200 --> 00:11:13,440 Speaker 12: current level of the two year as being remarkably attractive. 240 00:11:13,720 --> 00:11:15,760 Speaker 12: But I have been wrong in thinking that for a 241 00:11:15,840 --> 00:11:19,640 Speaker 12: while now. So you know my general belief is that 242 00:11:19,760 --> 00:11:23,240 Speaker 12: the economy is slowing. The inflation problem is for seeing 243 00:11:23,280 --> 00:11:26,920 Speaker 12: in the ism services today is largely one that's in 244 00:11:27,200 --> 00:11:29,920 Speaker 12: very mirror, and the risk that we're actually creating and 245 00:11:29,960 --> 00:11:33,839 Speaker 12: through interest rate policy is the higher level of interest 246 00:11:33,920 --> 00:11:36,440 Speaker 12: rates themselves are actually now the key risk. 247 00:11:36,520 --> 00:11:39,400 Speaker 7: This is exactly what we saw with the banking system. 248 00:11:39,120 --> 00:11:42,800 Speaker 4: Earlier in here. I think it's working its way. 249 00:11:42,600 --> 00:11:45,440 Speaker 12: Through the corporate sector where we're seeing a dramatic rise 250 00:11:45,480 --> 00:11:46,319 Speaker 12: in bankruptcies. 251 00:11:46,920 --> 00:11:48,840 Speaker 4: The odd thing for me is simply that it's not 252 00:11:48,880 --> 00:11:49,840 Speaker 4: reflected in spreads. 253 00:11:49,880 --> 00:11:51,640 Speaker 7: It doesn't seem to be reflected in. 254 00:11:51,600 --> 00:11:55,600 Speaker 4: Any way in the federal reserves calculations, and candidly, when 255 00:11:55,640 --> 00:11:56,559 Speaker 4: we look at the job. 256 00:11:56,520 --> 00:12:00,880 Speaker 12: Data today, certainly coming from the ADP, I have to 257 00:12:00,920 --> 00:12:04,120 Speaker 12: confess that I'm pot off sides in terms of that strength. 258 00:12:04,360 --> 00:12:06,120 Speaker 4: I cannot reconcile the data. 259 00:12:06,760 --> 00:12:07,600 Speaker 7: If I look. 260 00:12:07,520 --> 00:12:10,600 Speaker 12: At the numbers for twenty twenty three on a non 261 00:12:10,720 --> 00:12:13,920 Speaker 12: seasonally adjusted basis and compare them to the data from 262 00:12:14,480 --> 00:12:17,120 Speaker 12: twenty twenty two, they're lower. 263 00:12:16,880 --> 00:12:19,920 Speaker 4: In every category. So oddly we. 264 00:12:19,960 --> 00:12:23,199 Speaker 12: Have this seasonal adjustment factor that again is raising its 265 00:12:23,200 --> 00:12:25,760 Speaker 12: head and just making me really question whether the data 266 00:12:25,800 --> 00:12:27,280 Speaker 12: that we're receiving is accurate. 267 00:12:28,760 --> 00:12:32,040 Speaker 1: So I guess let's let's look at it the economy 268 00:12:32,040 --> 00:12:32,840 Speaker 1: from a different way. 269 00:12:33,360 --> 00:12:34,439 Speaker 3: Earnings, corporate earnings. 270 00:12:34,520 --> 00:12:36,400 Speaker 1: I'm looking at the you know, the earnings for the 271 00:12:36,440 --> 00:12:39,880 Speaker 1: S and P five hundred consensus of analysts about two 272 00:12:39,960 --> 00:12:42,320 Speaker 1: hundred and twenty two dollars per share for this year. 273 00:12:43,280 --> 00:12:45,360 Speaker 1: How much risk, if any, do you see in that 274 00:12:45,440 --> 00:12:47,400 Speaker 1: earnings number for corporate America. 275 00:12:48,360 --> 00:12:51,400 Speaker 12: Well, I think that there's a remarkable disconnect between the 276 00:12:51,800 --> 00:12:55,760 Speaker 12: expectations data and the actual data that we're experiencing in 277 00:12:55,800 --> 00:12:58,800 Speaker 12: the gap form, right, so they generally accepted accounting principles 278 00:12:58,840 --> 00:13:01,520 Speaker 12: earnings for the S and P or down one seventy nine. 279 00:13:01,960 --> 00:13:03,960 Speaker 12: That's off of a level of about two zho nine 280 00:13:04,000 --> 00:13:06,959 Speaker 12: from last year. It shows no dynamic that would suggests 281 00:13:06,960 --> 00:13:09,959 Speaker 12: that the rebound that analysts are forecasting is in play. 282 00:13:11,040 --> 00:13:14,040 Speaker 4: Much of what I would argue we're seeing is basically. 283 00:13:13,679 --> 00:13:19,360 Speaker 12: An attempt to ignore the one time costs associated with 284 00:13:19,559 --> 00:13:22,760 Speaker 12: either unemployment or layoffs. 285 00:13:22,960 --> 00:13:26,600 Speaker 4: And in many ways, again, it just feels like data is. 286 00:13:26,600 --> 00:13:29,319 Speaker 12: Being created to match a narrative of rising prices with 287 00:13:29,440 --> 00:13:32,800 Speaker 12: the reality of rising prices and stock markets, versus what 288 00:13:32,840 --> 00:13:34,520 Speaker 12: we're actually seeing empirically in the. 289 00:13:34,480 --> 00:13:37,560 Speaker 8: Economy, Michael, the S and P five hundreds trading around, 290 00:13:37,600 --> 00:13:39,480 Speaker 8: it's the lowest level in about a week. Something I 291 00:13:39,600 --> 00:13:41,480 Speaker 8: was curious about when we're looking at some of this 292 00:13:41,640 --> 00:13:45,840 Speaker 8: stronger than expected labor data, is this potentially a reason 293 00:13:46,040 --> 00:13:49,600 Speaker 8: for certain stock investors to sell after what was a 294 00:13:49,760 --> 00:13:51,319 Speaker 8: very strong first half. 295 00:13:53,360 --> 00:13:56,840 Speaker 12: Well, I think that there is very much a focus, 296 00:13:56,920 --> 00:13:59,480 Speaker 12: correctly on what the FED is going to do, and 297 00:13:59,520 --> 00:14:00,120 Speaker 12: so we're. 298 00:14:00,080 --> 00:14:02,040 Speaker 7: Clearly seeing, as you let into the. 299 00:14:01,920 --> 00:14:06,520 Speaker 12: Discussion here, indications that interest rates are moving higher. That 300 00:14:06,760 --> 00:14:09,520 Speaker 12: Lori Logan came out today and said she expects additional 301 00:14:09,559 --> 00:14:13,920 Speaker 12: interest rates going forward. I think, broadly speaking that that 302 00:14:14,120 --> 00:14:17,319 Speaker 12: is really what's powering the market as of this immediate 303 00:14:17,360 --> 00:14:21,120 Speaker 12: sell office, compared to kicking gains or anything else. 304 00:14:21,160 --> 00:14:24,000 Speaker 4: You've seen a fairly significant a balance of. 305 00:14:24,880 --> 00:14:27,440 Speaker 12: Disconnect between the S and P five hundred, which is 306 00:14:27,480 --> 00:14:31,160 Speaker 12: obviously market cap weighted and dominated by the large market 307 00:14:31,200 --> 00:14:34,040 Speaker 12: cap names, and what we've seen in said the Russell 308 00:14:34,080 --> 00:14:37,240 Speaker 12: two thousand, which is not up nearly as much on 309 00:14:37,280 --> 00:14:40,080 Speaker 12: a year today basis, and in fact the equal weighted 310 00:14:40,160 --> 00:14:40,920 Speaker 12: Russell two. 311 00:14:40,720 --> 00:14:42,400 Speaker 4: Thousand is barely up for the year. 312 00:14:42,920 --> 00:14:44,760 Speaker 12: So this has been an environment in which the vast 313 00:14:44,760 --> 00:14:48,080 Speaker 12: majority of stocks have been relatively weak, even as a 314 00:14:48,120 --> 00:14:51,440 Speaker 12: few MEGGA cap names, Apple, Microsoft, and Video et cetera 315 00:14:51,560 --> 00:14:53,120 Speaker 12: have been very strong. 316 00:14:54,040 --> 00:14:57,480 Speaker 4: In my view that that would represent mostly. 317 00:14:57,040 --> 00:15:02,800 Speaker 12: A you know, flow store, effectively money going into AI 318 00:15:02,920 --> 00:15:07,000 Speaker 12: and technology space driving performance as compared to any indication 319 00:15:07,160 --> 00:15:08,640 Speaker 12: of real economics display. 320 00:15:09,800 --> 00:15:14,400 Speaker 1: Mike, I'm sensing a distinct tone of cautiousness in your 321 00:15:14,480 --> 00:15:17,880 Speaker 1: view of the markets and the economy. How are you 322 00:15:17,960 --> 00:15:22,240 Speaker 1: allocating your portfolio these days? Stocks, bonds, what sectors, that 323 00:15:22,280 --> 00:15:22,760 Speaker 1: type of thing. 324 00:15:23,640 --> 00:15:26,200 Speaker 12: Yeah, I know, as I indicated, I absolutely have been 325 00:15:26,240 --> 00:15:30,440 Speaker 12: caught in the wrong positioning on this last move. I 326 00:15:30,520 --> 00:15:34,520 Speaker 12: genuinely look at the two year bond at five plus 327 00:15:34,600 --> 00:15:37,120 Speaker 12: right now and say, I can't believe that we're being 328 00:15:37,160 --> 00:15:40,360 Speaker 12: given this opportunity in an environment in which it seems 329 00:15:40,480 --> 00:15:45,320 Speaker 12: very clear that at least the economy has slowed dramatically. 330 00:15:46,520 --> 00:15:48,760 Speaker 12: Whether it continues to slow it is really the question, 331 00:15:49,320 --> 00:15:54,520 Speaker 12: and I see few opportunities for continued growth and expansion. 332 00:15:55,240 --> 00:15:58,120 Speaker 4: Today's ADP is obviously a wrinkle in that. 333 00:15:58,360 --> 00:16:00,480 Speaker 7: But you know, again, I just think. 334 00:16:00,400 --> 00:16:02,800 Speaker 12: The data that we will receive from ADP today is wrong. 335 00:16:03,320 --> 00:16:06,480 Speaker 12: Can't fully explain it, but that's what it appears to be. 336 00:16:06,560 --> 00:16:07,600 Speaker 7: Where the non. 337 00:16:07,480 --> 00:16:11,880 Speaker 12: Seasonally adjusted data is showing a significant divergence from the 338 00:16:11,960 --> 00:16:15,080 Speaker 12: seasonally adjusted data. That's true for the claims data, that's 339 00:16:15,080 --> 00:16:18,240 Speaker 12: true for the unemployment data, that's true for. 340 00:16:18,200 --> 00:16:19,720 Speaker 7: The ADP data. 341 00:16:20,440 --> 00:16:23,400 Speaker 8: Something that struck me just looking at the industries within 342 00:16:23,440 --> 00:16:25,640 Speaker 8: the S and P five hundred, more of those cyclically 343 00:16:25,680 --> 00:16:28,440 Speaker 8: related corners of the market are leading to clients when 344 00:16:28,440 --> 00:16:32,160 Speaker 8: you're looking at energy, also materials, technology down a little 345 00:16:32,200 --> 00:16:34,760 Speaker 8: bit under one percent. Also the NAZAQ one hundred down 346 00:16:34,960 --> 00:16:37,560 Speaker 8: more than one percent. But when you think about the 347 00:16:37,560 --> 00:16:41,280 Speaker 8: correlation between bonds and what's happening when it comes to 348 00:16:41,440 --> 00:16:44,720 Speaker 8: technology stocks in particular or growth shares, would you expect 349 00:16:44,720 --> 00:16:47,440 Speaker 8: them to be more pressured given what we're seeing in 350 00:16:47,440 --> 00:16:48,680 Speaker 8: the bond market. 351 00:16:49,560 --> 00:16:50,040 Speaker 13: So I'm not a. 352 00:16:50,080 --> 00:16:52,800 Speaker 12: Huge believer in this idea that growth stocks or large 353 00:16:52,800 --> 00:16:55,880 Speaker 12: cap growth stocks in particular have a quote unquote high duration, 354 00:16:55,960 --> 00:16:58,560 Speaker 12: in other words, a high degree of sensitivity and interest rates. 355 00:16:58,600 --> 00:17:01,360 Speaker 12: I think we've obviously seen that, you know, with the 356 00:17:01,360 --> 00:17:03,680 Speaker 12: strength of the Apples and the Microsoft's on a here 357 00:17:03,720 --> 00:17:05,639 Speaker 12: to day basis, where despite the fact that we have 358 00:17:05,720 --> 00:17:10,479 Speaker 12: much higher interest rates, they continue to push higher. If anything, 359 00:17:10,520 --> 00:17:13,440 Speaker 12: I think that there's an explanation that has much more 360 00:17:13,520 --> 00:17:16,800 Speaker 12: to do a kind of portfolio allocation dynamics than any 361 00:17:16,960 --> 00:17:20,040 Speaker 12: sort of fundamentals around interest rates and valuation. 362 00:17:21,680 --> 00:17:23,000 Speaker 7: Again, you know, I. 363 00:17:22,920 --> 00:17:25,960 Speaker 4: Would just lean towards the direction that what we're worried. 364 00:17:25,640 --> 00:17:28,399 Speaker 12: About at this point is the FED continuing to be 365 00:17:28,680 --> 00:17:32,080 Speaker 12: overly aggressive with the hikes that are already in the system, 366 00:17:32,359 --> 00:17:35,479 Speaker 12: not in any way reflected in the underlying data that 367 00:17:35,520 --> 00:17:39,080 Speaker 12: we're receiving. Yet, as that moves forward, if the FED 368 00:17:39,119 --> 00:17:43,840 Speaker 12: continues to hike for pauses in its response, that creates 369 00:17:43,840 --> 00:17:45,040 Speaker 12: conditions under which. 370 00:17:44,920 --> 00:17:47,320 Speaker 7: A slowdown could actually. 371 00:17:47,119 --> 00:17:49,760 Speaker 12: End up being much more severe than it's currently being 372 00:17:49,840 --> 00:17:54,040 Speaker 12: priced in or versus expectation, and that unfortunately continues to 373 00:17:54,080 --> 00:17:57,280 Speaker 12: be my rising rates case. If the FED is simply 374 00:17:57,359 --> 00:18:00,880 Speaker 12: behind the curve in the opposite direction again, ism prices 375 00:18:00,920 --> 00:18:04,280 Speaker 12: paid data would suggest that the inflation story as well 376 00:18:04,320 --> 00:18:04,800 Speaker 12: behind us. 377 00:18:04,840 --> 00:18:07,480 Speaker 4: We see this in Europe with the CPI the producer 378 00:18:07,560 --> 00:18:09,000 Speaker 4: price indexes turn negative. 379 00:18:09,600 --> 00:18:13,440 Speaker 12: We're just seeing data that they suggest that the inflation 380 00:18:13,600 --> 00:18:16,080 Speaker 12: story is no longer the operative dynamic. 381 00:18:17,680 --> 00:18:20,960 Speaker 4: Doesn't necessarily mean that that's right, though, all right, So. 382 00:18:21,240 --> 00:18:23,000 Speaker 1: Real quick there, Mike, what do you think we're going 383 00:18:23,040 --> 00:18:24,840 Speaker 1: to hear from our feder Reserve at the next meeting 384 00:18:24,840 --> 00:18:25,960 Speaker 1: and maybe even the meeting after that. 385 00:18:27,119 --> 00:18:29,879 Speaker 12: Well, I think it's hard to argue with the market, right, So, 386 00:18:29,920 --> 00:18:32,120 Speaker 12: when the market suggests that they are more than eighty 387 00:18:32,119 --> 00:18:35,040 Speaker 12: five percent probability of going, and historically it's been about 388 00:18:35,080 --> 00:18:38,520 Speaker 12: seventy percent, it's been very rare for the Fed not 389 00:18:38,640 --> 00:18:42,600 Speaker 12: to take advantage of that. I would expect that they'll 390 00:18:42,640 --> 00:18:45,920 Speaker 12: ultimately hike, and that they'll indicate, as the data suggests 391 00:18:45,920 --> 00:18:50,359 Speaker 12: certainly today, that the economy continues to represent strength. I 392 00:18:50,359 --> 00:18:53,160 Speaker 12: don't really think that they're focused on the inflation story 393 00:18:53,200 --> 00:18:55,800 Speaker 12: as much as they are focused on or the direction 394 00:18:55,880 --> 00:18:59,119 Speaker 12: of inflation story, which is clearly downwards, as much as 395 00:18:59,119 --> 00:19:02,560 Speaker 12: they are focused on the idea we've got to get right. 396 00:19:02,920 --> 00:19:05,760 Speaker 12: That is going to be the real question is, you know, 397 00:19:05,840 --> 00:19:08,639 Speaker 12: do they continue to hip until we get to two percent? 398 00:19:08,720 --> 00:19:11,440 Speaker 4: Which right, just that they're going to be way behind 399 00:19:11,480 --> 00:19:13,680 Speaker 4: the curve opposite direction. All right. 400 00:19:13,720 --> 00:19:17,960 Speaker 8: Michael Green, portfolio manager in chief strategist at Simplify Asset Management, 401 00:19:18,000 --> 00:19:20,320 Speaker 8: thank you so much for joining us and getting your 402 00:19:20,359 --> 00:19:20,960 Speaker 8: purview here. 403 00:19:21,400 --> 00:19:24,480 Speaker 11: You're listening to the tape Can's our live program Bloomberg 404 00:19:24,600 --> 00:19:28,199 Speaker 11: Markets weekdays at ten am Eastern on Bloomberg Radio, the 405 00:19:28,240 --> 00:19:30,200 Speaker 11: tune in app, Bloomberg dot Com, and. 406 00:19:30,160 --> 00:19:31,480 Speaker 13: The Bloomberg Business App. 407 00:19:31,520 --> 00:19:34,320 Speaker 11: You can also listen live on Amazon Alexa from our 408 00:19:34,359 --> 00:19:39,400 Speaker 11: flagship New York station. Just say Alexa Play Bloomberg eleven thirty. 409 00:19:40,040 --> 00:19:42,000 Speaker 1: Let's get right to our next guest at Mona Mahadgen, 410 00:19:42,200 --> 00:19:46,479 Speaker 1: senior investment strategists at Edward Jones. Mon A crazy, crazy 411 00:19:46,560 --> 00:19:48,800 Speaker 1: day in the markets here. I love to get your 412 00:19:48,800 --> 00:19:51,600 Speaker 1: sense of kind of what the economic data is telling you, 413 00:19:51,920 --> 00:19:53,439 Speaker 1: and what do you think it's telling the Federal Reserve. 414 00:19:54,640 --> 00:19:57,439 Speaker 14: Yeah, great points there, and look, I think there was 415 00:19:57,480 --> 00:20:00,280 Speaker 14: some really market moving data this morning that we think 416 00:20:00,320 --> 00:20:03,200 Speaker 14: highlighted a few trends. First of all, the services part 417 00:20:03,240 --> 00:20:07,360 Speaker 14: of the economy continues to remain remarkably resilient. We saw 418 00:20:07,359 --> 00:20:10,239 Speaker 14: that not only with the ADP jobs report, where we 419 00:20:10,240 --> 00:20:12,560 Speaker 14: were up four hundred and ninety seven thousand jobs when 420 00:20:12,600 --> 00:20:15,080 Speaker 14: we expected just two hundred and twenty five thousand, but 421 00:20:15,200 --> 00:20:19,080 Speaker 14: really what drove that was the services sectors, including areas 422 00:20:19,119 --> 00:20:22,480 Speaker 14: like leisure and hospitality. We also got the Ism services 423 00:20:22,560 --> 00:20:26,240 Speaker 14: data this morning, which continued to show an upward trend 424 00:20:26,359 --> 00:20:29,080 Speaker 14: rather than what many had expected to be a little 425 00:20:29,119 --> 00:20:33,280 Speaker 14: bit more moderation. Now. On the positive side, both the 426 00:20:33,320 --> 00:20:37,520 Speaker 14: ADP and the ISM services data did show some cooling 427 00:20:37,640 --> 00:20:40,960 Speaker 14: in inflation. ADP data wage gains came in at six 428 00:20:41,000 --> 00:20:44,680 Speaker 14: point four percent, still elevated, but following a trend lower 429 00:20:44,760 --> 00:20:48,400 Speaker 14: over the last several months, and similarly, the ISM prices 430 00:20:48,480 --> 00:20:53,879 Speaker 14: paid component came in below expectations. And so hopefully the 431 00:20:54,359 --> 00:20:57,479 Speaker 14: message is that, yes, the economy has remained resilient, but 432 00:20:57,520 --> 00:21:01,720 Speaker 14: the inflation data continues to show of moderation. Now. Of course, 433 00:21:02,000 --> 00:21:05,840 Speaker 14: from a FED perspective, I think this gives them another 434 00:21:05,920 --> 00:21:09,719 Speaker 14: green light to move forward in July at least, and 435 00:21:09,760 --> 00:21:12,879 Speaker 14: we heard a little bit of dissent and debate when 436 00:21:12,880 --> 00:21:16,160 Speaker 14: we got the minutes yesterday. I think this certainly kind 437 00:21:16,200 --> 00:21:19,080 Speaker 14: of adds to the case that they could do one, 438 00:21:19,320 --> 00:21:22,919 Speaker 14: perhaps two more rate hikes ahead, but they are closer 439 00:21:22,920 --> 00:21:26,040 Speaker 14: to a pause than they have been in recent history now. 440 00:21:26,080 --> 00:21:28,440 Speaker 14: I think the other big part of the markets today, 441 00:21:28,440 --> 00:21:30,520 Speaker 14: of course, has been what's happening with yields, and the 442 00:21:30,600 --> 00:21:33,800 Speaker 14: upward moving yields close to now highs for the year 443 00:21:34,440 --> 00:21:37,440 Speaker 14: does put some downward pressure on equity markets, particularly those 444 00:21:37,480 --> 00:21:39,400 Speaker 14: higher valuation parts of the market as well. 445 00:21:40,000 --> 00:21:42,840 Speaker 8: And we've heard from FED chair Pale as well as 446 00:21:43,000 --> 00:21:46,280 Speaker 8: other members of the Central Bank and were referring to 447 00:21:46,320 --> 00:21:48,720 Speaker 8: this as far as at least two more rate increases 448 00:21:48,760 --> 00:21:50,920 Speaker 8: this year. If we do end up seeing another one 449 00:21:50,920 --> 00:21:52,760 Speaker 8: at the end of this month, what would need to 450 00:21:52,800 --> 00:21:55,320 Speaker 8: happen with the data between now and then when we 451 00:21:55,400 --> 00:21:58,639 Speaker 8: have the Federal reserves following meeting in September, after the 452 00:21:58,720 --> 00:22:01,359 Speaker 8: July meeting for them to end up maybe potentially having 453 00:22:01,400 --> 00:22:03,639 Speaker 8: two consecutive rate increases. 454 00:22:04,680 --> 00:22:05,600 Speaker 10: Yeah, it's a good point. 455 00:22:05,640 --> 00:22:07,679 Speaker 14: And look, we do get a lot of data between 456 00:22:07,720 --> 00:22:09,840 Speaker 14: now and September, and of course this month alone, we'll 457 00:22:09,840 --> 00:22:12,760 Speaker 14: get an additional set of CPI and PPI data next week, 458 00:22:13,160 --> 00:22:15,800 Speaker 14: will of course start earning season towards the end of July, 459 00:22:15,920 --> 00:22:19,480 Speaker 14: and we'll have that July rate hike or rate decision 460 00:22:19,880 --> 00:22:23,520 Speaker 14: at the end of July, So the Fed and the 461 00:22:23,560 --> 00:22:26,719 Speaker 14: markets will have to digest quite a bit. Our view 462 00:22:26,840 --> 00:22:29,720 Speaker 14: is that over time we will continue to see inflation 463 00:22:29,840 --> 00:22:32,159 Speaker 14: moderate and so perhaps the one rate hike that the 464 00:22:32,200 --> 00:22:35,200 Speaker 14: markets are pricing in could be a final rate hike 465 00:22:35,240 --> 00:22:35,760 Speaker 14: for the Fed. 466 00:22:36,440 --> 00:22:37,160 Speaker 10: But if the. 467 00:22:37,160 --> 00:22:42,560 Speaker 14: Economy does continue at this pace, especially in the services sectors, 468 00:22:43,160 --> 00:22:46,680 Speaker 14: that could keep services inflation elevated. Keep in mind, the 469 00:22:46,720 --> 00:22:49,960 Speaker 14: FED has broken down inflation into three core buckets, which 470 00:22:50,000 --> 00:22:53,160 Speaker 14: are goods inflation, which have shown signs of rolling, over 471 00:22:53,680 --> 00:22:57,959 Speaker 14: housing shelter inflation, which we do think over time will 472 00:22:58,000 --> 00:23:01,240 Speaker 14: see cooling. That there's a lag there, and real time 473 00:23:01,320 --> 00:23:03,359 Speaker 14: data is showing some cooling and we think that shows 474 00:23:03,440 --> 00:23:05,880 Speaker 14: up over time. But it's really that third bucket, which 475 00:23:05,880 --> 00:23:10,400 Speaker 14: they categorize as non housing services inflation, that has yet 476 00:23:10,440 --> 00:23:12,959 Speaker 14: to show meaningful signs of moderation. So they'll be watching 477 00:23:13,000 --> 00:23:16,000 Speaker 14: that closely. And I think if that continues to show 478 00:23:16,040 --> 00:23:19,960 Speaker 14: signs at least of stabilizing moving lower, we'll have one 479 00:23:20,040 --> 00:23:22,080 Speaker 14: rate hike ahead of us. If not that, the second 480 00:23:22,080 --> 00:23:22,960 Speaker 14: one is on the table. 481 00:23:23,160 --> 00:23:25,840 Speaker 8: So then, as a strategist, what is your outlook for 482 00:23:25,880 --> 00:23:27,920 Speaker 8: the second half of the year after we had such 483 00:23:27,960 --> 00:23:29,639 Speaker 8: a strong first six months? 484 00:23:30,640 --> 00:23:33,240 Speaker 14: Yeah, absolutely, Look, it was a stellar first half of 485 00:23:33,280 --> 00:23:36,879 Speaker 14: the year with the SMP up over fourteen percent. You know, 486 00:23:36,920 --> 00:23:39,679 Speaker 14: keep in mind, there have been some positives and reasons 487 00:23:39,680 --> 00:23:43,200 Speaker 14: for optimism. The economic data is coming out ahead of expectations. 488 00:23:43,240 --> 00:23:46,359 Speaker 14: Inflation as we noted is showing signs of moderation and 489 00:23:46,400 --> 00:23:48,919 Speaker 14: the FED maybe towards the end of its rate hiking cycle. 490 00:23:49,359 --> 00:23:52,480 Speaker 14: But we'd be cautious to extrapolate that strong move higher 491 00:23:52,480 --> 00:23:55,000 Speaker 14: in the first half to a straight line up in 492 00:23:55,040 --> 00:23:56,960 Speaker 14: the second half of the year. Now, history does tell 493 00:23:57,040 --> 00:23:59,280 Speaker 14: us when you are up over ten percent the first half, 494 00:23:59,280 --> 00:24:02,360 Speaker 14: it bodes well for the second half. In our view, 495 00:24:02,440 --> 00:24:06,160 Speaker 14: we do think bouts of volatility maybe likely, especially if 496 00:24:06,200 --> 00:24:09,400 Speaker 14: the economy starts to show signs of cooling. But will 497 00:24:09,400 --> 00:24:13,760 Speaker 14: we get another bear market or meaningful downturn that we 498 00:24:13,960 --> 00:24:16,760 Speaker 14: see is unlikely at this point, and in fact, we 499 00:24:16,840 --> 00:24:20,680 Speaker 14: think those bouts of volatility could be used as opportunities, 500 00:24:20,800 --> 00:24:24,359 Speaker 14: especially as investors look towards twenty twenty four, where you 501 00:24:24,400 --> 00:24:29,960 Speaker 14: could get a meaningful bounce back in earnings, better inflation, 502 00:24:30,119 --> 00:24:32,120 Speaker 14: and have FED that not only is pausing, but they've 503 00:24:32,119 --> 00:24:35,040 Speaker 14: told us they might start thinking about pivoting lower as well. 504 00:24:35,640 --> 00:24:37,920 Speaker 14: So really want to start positioning for what we think 505 00:24:38,160 --> 00:24:41,960 Speaker 14: could be a broader based market rally and participation towards 506 00:24:41,960 --> 00:24:45,119 Speaker 14: the back half of the year, and both in equities 507 00:24:45,160 --> 00:24:46,520 Speaker 14: and in bond markets as well. 508 00:24:47,000 --> 00:24:49,920 Speaker 1: So do I think about small MidCap stocks Mona. They've 509 00:24:50,359 --> 00:24:53,080 Speaker 1: historically lagged some of the bigger cap names, but if 510 00:24:53,080 --> 00:24:54,720 Speaker 1: this thing's going to broaden that a little bit, maybe 511 00:24:55,040 --> 00:24:55,920 Speaker 1: small and midcaps. 512 00:24:56,920 --> 00:24:59,480 Speaker 14: Yeah, it's a good point. And look, small caps have 513 00:24:59,600 --> 00:25:01,399 Speaker 14: meaningful lagged in the first half of the year, so 514 00:25:01,440 --> 00:25:03,600 Speaker 14: we certainly think there is room for catchup now. When 515 00:25:03,640 --> 00:25:07,080 Speaker 14: we look historically, small caps tend to do well when 516 00:25:07,119 --> 00:25:10,080 Speaker 14: the economy is re emerging from any sort of softness 517 00:25:10,440 --> 00:25:12,880 Speaker 14: or downturn. They tend to lead on the way up. 518 00:25:12,960 --> 00:25:14,800 Speaker 10: And so when we think about what we. 519 00:25:14,720 --> 00:25:18,719 Speaker 14: Call a recovery basket, that could certainly include areas like 520 00:25:18,760 --> 00:25:21,680 Speaker 14: small cap stocks, like cyclicals, and we're starting to see 521 00:25:21,680 --> 00:25:26,520 Speaker 14: some strength in industrials, materials, perhaps even financials in that basket. 522 00:25:26,640 --> 00:25:29,639 Speaker 14: International equities tend to do well in that environment. Those 523 00:25:29,640 --> 00:25:33,280 Speaker 14: we think can compliment what we're seeing right now, because 524 00:25:33,280 --> 00:25:37,040 Speaker 14: we do think the story behind AI and growth sectors 525 00:25:37,280 --> 00:25:41,000 Speaker 14: does have a long term secular tailwind behind it, although 526 00:25:41,040 --> 00:25:44,200 Speaker 14: a lot of it has been priced very quickly upfront 527 00:25:44,240 --> 00:25:47,080 Speaker 14: as well, So we think a complement of both the 528 00:25:47,119 --> 00:25:49,360 Speaker 14: growth and the more cyclical parts of the market will 529 00:25:49,359 --> 00:25:51,560 Speaker 14: work better As we head towards twenty twenty four. 530 00:25:51,760 --> 00:25:53,960 Speaker 8: We only have about forty five seconds left. What's the 531 00:25:53,960 --> 00:25:55,920 Speaker 8: top question that you hear from clients? 532 00:25:57,359 --> 00:25:59,040 Speaker 10: Yeah, you know, I think it's still the big one. 533 00:25:59,080 --> 00:26:02,240 Speaker 14: Around recession, we tend to hear a lot more, especially 534 00:26:02,280 --> 00:26:05,600 Speaker 14: now that the Fed is continuing to raise rates. And 535 00:26:05,640 --> 00:26:09,040 Speaker 14: we do think that what we're seeing now is a 536 00:26:09,080 --> 00:26:12,280 Speaker 14: potential for cooling in the economy, but perhaps not your 537 00:26:12,320 --> 00:26:15,479 Speaker 14: typical two back to back quarters of negative GDP growth. 538 00:26:15,680 --> 00:26:18,920 Speaker 14: We think a softness to below trend growth is likely though, 539 00:26:19,320 --> 00:26:20,600 Speaker 14: sometime in the second half of the year. 540 00:26:21,280 --> 00:26:23,119 Speaker 1: All right, Mona, thank you so much for joining us. 541 00:26:23,119 --> 00:26:25,679 Speaker 1: We really appreciate getting some of your time. Mona ma Hodgen. 542 00:26:25,840 --> 00:26:28,920 Speaker 1: She's a senior investment strategist at Edward Jones. 543 00:26:30,320 --> 00:26:33,720 Speaker 11: You're listening to the team Ken's are Live program Bloomberg 544 00:26:33,760 --> 00:26:37,119 Speaker 11: Markets weekdays at ten am Eastern on Bloomberg dot Com, 545 00:26:37,200 --> 00:26:40,359 Speaker 11: the iHeartRadio app and the Bloomberg Business App, or listen 546 00:26:40,440 --> 00:26:42,560 Speaker 11: on demand wherever you get your podcasts. 547 00:26:44,840 --> 00:26:47,320 Speaker 1: Threads is a thing. I'm there for what it's worth starting. 548 00:26:47,560 --> 00:26:49,440 Speaker 1: Let's take a little tech round table here. Let's bring 549 00:26:49,480 --> 00:26:52,800 Speaker 1: in Deep Seing. He covers the tech for Bloomberg Intelligence 550 00:26:52,880 --> 00:26:57,240 Speaker 1: and Ed Ludlow. After a very difficult zoom situation this morning. 551 00:26:57,240 --> 00:27:00,399 Speaker 1: He is our technology guy out in San Francisco, joints 552 00:27:00,440 --> 00:27:01,679 Speaker 1: US as well, so we got it all. 553 00:27:01,560 --> 00:27:05,359 Speaker 3: Covered for you. Mandie. Let's start with you here in 554 00:27:05,400 --> 00:27:06,200 Speaker 3: our studio here. 555 00:27:07,240 --> 00:27:08,959 Speaker 1: What is Metal looking to do here? Is this going 556 00:27:09,000 --> 00:27:11,560 Speaker 1: to be a business for them? Is this a real 557 00:27:11,600 --> 00:27:13,600 Speaker 1: competitor for Twitter? To just give us the business case. 558 00:27:14,000 --> 00:27:16,919 Speaker 6: The business case is they want to add that dimension 559 00:27:16,960 --> 00:27:20,480 Speaker 6: of real time public conversations that are going on related 560 00:27:20,520 --> 00:27:24,920 Speaker 6: to politics, related to breaking news, and that weren't happening 561 00:27:24,960 --> 00:27:28,080 Speaker 6: on Instagram. Probably they were happening on Core Blue app. 562 00:27:28,080 --> 00:27:31,280 Speaker 6: But they've been losing engagement, so it's an engagement play 563 00:27:31,359 --> 00:27:34,720 Speaker 6: for them to keep users on their family of apps, 564 00:27:34,720 --> 00:27:37,320 Speaker 6: and they've done a great job of adding reels content. 565 00:27:37,920 --> 00:27:40,560 Speaker 6: This is another dimension. And look, they don't need to 566 00:27:40,600 --> 00:27:43,840 Speaker 6: focus on monetization right now. If they're able to get 567 00:27:43,840 --> 00:27:47,040 Speaker 6: that engagement in terms of getting the core creators from 568 00:27:47,119 --> 00:27:50,120 Speaker 6: Twitter to threads, that'll be a big win for them. 569 00:27:50,600 --> 00:27:53,880 Speaker 8: And is this likely to be a big player here 570 00:27:54,040 --> 00:27:55,800 Speaker 8: or what kind of hurdles are ahead for it? 571 00:27:56,200 --> 00:27:59,040 Speaker 6: Well, the hurdles is, you know, the interest graph and 572 00:27:59,160 --> 00:28:02,960 Speaker 6: the followers that Twitter has over the course of their 573 00:28:03,359 --> 00:28:07,479 Speaker 6: last fifteen twenty years. You know, people have accumulated their 574 00:28:07,880 --> 00:28:11,160 Speaker 6: followers and they like to see a certain curated feed 575 00:28:11,240 --> 00:28:14,840 Speaker 6: when it comes to the home screen. Well, right now, 576 00:28:14,840 --> 00:28:17,879 Speaker 6: when you go to Threads, they have an AI generated 577 00:28:17,920 --> 00:28:20,240 Speaker 6: feed and there are a lot of brands and I've 578 00:28:20,280 --> 00:28:22,440 Speaker 6: tried to you know, viewed a lot of them. I mean, 579 00:28:22,520 --> 00:28:24,560 Speaker 6: that's not the experience you want to have. And that's 580 00:28:24,600 --> 00:28:27,920 Speaker 6: where scale and network effects is what drives social media 581 00:28:28,000 --> 00:28:32,200 Speaker 6: engagement and early movers have always had an advantage. What 582 00:28:32,240 --> 00:28:35,480 Speaker 6: TikTok did was great in terms of leveraging AI to 583 00:28:35,680 --> 00:28:39,440 Speaker 6: come up with great recommendations. That is the playbook here 584 00:28:39,480 --> 00:28:42,760 Speaker 6: for Meta is to use their user graph as well 585 00:28:42,800 --> 00:28:45,560 Speaker 6: as AI to drive the curated content feed. 586 00:28:45,640 --> 00:28:48,160 Speaker 3: All right, Ed, When I think of cutting edge technology, 587 00:28:48,160 --> 00:28:49,120 Speaker 3: I think of Ed Ludlow. 588 00:28:49,360 --> 00:28:52,720 Speaker 1: I think Silicon Valley is Silicon Valley out there in 589 00:28:52,760 --> 00:28:56,320 Speaker 1: San Francisco. Ed, what's the buzz if anything out there 590 00:28:56,360 --> 00:28:59,120 Speaker 1: in the valley about what our good friends at Facebook 591 00:28:59,160 --> 00:28:59,880 Speaker 1: are trying to do here? 592 00:29:00,680 --> 00:29:03,200 Speaker 15: Yeah, and the adoption has been really interesting to track. 593 00:29:03,440 --> 00:29:06,920 Speaker 15: I was signed up to Threads as us the number 594 00:29:06,920 --> 00:29:10,120 Speaker 15: one hundred and thirty, two thousand and nine. Wow. So 595 00:29:10,160 --> 00:29:12,800 Speaker 15: I made it in in the initial batch. I mean 596 00:29:12,800 --> 00:29:15,920 Speaker 15: it's Bloomberg's tech editor Sarah Fryer was like number two thousand. 597 00:29:16,760 --> 00:29:19,720 Speaker 15: You know, overnight she's a player, and overnight we hit 598 00:29:19,760 --> 00:29:22,000 Speaker 15: the ten million mark. And my understanding is that we're 599 00:29:22,080 --> 00:29:25,840 Speaker 15: closer now to thirty million users on the platform. But 600 00:29:26,000 --> 00:29:29,360 Speaker 15: I find Mandya's commentary really interesting. There are clearly ux 601 00:29:29,440 --> 00:29:33,360 Speaker 15: differences right between what you get on the threads platform 602 00:29:33,360 --> 00:29:36,480 Speaker 15: what you get on Twitter. It's very simplified right now. 603 00:29:36,480 --> 00:29:38,280 Speaker 15: There are a few, you know, there's no sort of 604 00:29:38,360 --> 00:29:41,600 Speaker 15: ad stream on it. The biggest piece of use for 605 00:29:41,640 --> 00:29:43,200 Speaker 15: me in the last twenty four hours was a post 606 00:29:43,200 --> 00:29:47,280 Speaker 15: by Zuckerberg basically suggesting that a billion users is possible, 607 00:29:47,880 --> 00:29:51,120 Speaker 15: and you know, to jump from thirty million to a billion, 608 00:29:51,760 --> 00:29:54,320 Speaker 15: you know, I think a number of SALSIH analysts this 609 00:29:54,400 --> 00:29:58,680 Speaker 15: morning kind of see difficulty in getting to that scale. 610 00:29:58,720 --> 00:30:03,040 Speaker 15: But think about it this way, Facebook, WhatsApp, Instagram, if 611 00:30:03,080 --> 00:30:06,200 Speaker 15: Meta onboarded just one out of every ten users on 612 00:30:06,280 --> 00:30:10,800 Speaker 15: its existing platforms, it would already eclipse what Twitter's monthly 613 00:30:11,120 --> 00:30:14,600 Speaker 15: or installed active user bases. So you can kind of 614 00:30:14,600 --> 00:30:17,640 Speaker 15: see them eclipsing Twitter a billion hard to. 615 00:30:17,560 --> 00:30:21,560 Speaker 8: See men deep something I'm curious about is, especially when 616 00:30:21,600 --> 00:30:23,760 Speaker 8: you think of Meta and the cost cutting efforts that 617 00:30:23,800 --> 00:30:25,880 Speaker 8: it has clearly gone through, and it stocks up more 618 00:30:25,880 --> 00:30:29,320 Speaker 8: than two hundred percent since early November, how much could 619 00:30:29,320 --> 00:30:32,520 Speaker 8: this potentially either support that stock price or is it 620 00:30:32,560 --> 00:30:34,200 Speaker 8: just too early to be seen when you're looking at 621 00:30:34,240 --> 00:30:34,720 Speaker 8: cell side. 622 00:30:35,280 --> 00:30:39,360 Speaker 6: Well, so, in terms of incremental revenue, I think, look, 623 00:30:39,400 --> 00:30:41,960 Speaker 6: this is not going to move the stock a Twitter 624 00:30:42,040 --> 00:30:45,640 Speaker 6: had revenue of you know, around six billion when before 625 00:30:45,640 --> 00:30:48,920 Speaker 6: they went private, and even if they are losing revenue 626 00:30:49,200 --> 00:30:54,520 Speaker 6: and you know, Meta can lier ads over time, You're 627 00:30:54,600 --> 00:30:57,920 Speaker 6: not buying the stock here with the hope that you know, 628 00:30:58,440 --> 00:31:01,360 Speaker 6: this product is going to generate two three billion dollars 629 00:31:01,400 --> 00:31:05,040 Speaker 6: in incremental revenue. But what it can do is drive 630 00:31:05,120 --> 00:31:08,920 Speaker 6: that engagement because ultimately, if you go to Twitter right now, 631 00:31:09,120 --> 00:31:12,520 Speaker 6: their average time spent per user is around twenty seven 632 00:31:12,560 --> 00:31:15,960 Speaker 6: to thirty minutes every day for the daily active users. 633 00:31:16,240 --> 00:31:19,600 Speaker 6: If they can take a share of that, that'll be huge. Again, 634 00:31:19,720 --> 00:31:22,840 Speaker 6: the cumulative effect of social media when you think about 635 00:31:22,920 --> 00:31:26,440 Speaker 6: you know, meta is what people spend their time on 636 00:31:26,600 --> 00:31:30,280 Speaker 6: the core blue app, Instagram and WhatsApp. You add another 637 00:31:30,360 --> 00:31:33,560 Speaker 6: dimension to it. It helps with their AI it helps 638 00:31:33,600 --> 00:31:36,880 Speaker 6: with the overall advertisers, and that is what meta is 639 00:31:36,920 --> 00:31:37,480 Speaker 6: after here. 640 00:31:38,360 --> 00:31:40,840 Speaker 1: All right, So, Ed, what's the feeling in the valley 641 00:31:40,880 --> 00:31:44,400 Speaker 1: about Elon Musk. What's his response going to be? What's 642 00:31:44,400 --> 00:31:47,480 Speaker 1: the future of Twitter? How do you think this plays up? 643 00:31:48,720 --> 00:31:48,920 Speaker 5: You know? 644 00:31:49,800 --> 00:31:52,360 Speaker 1: He Oh, by the way, I just did my first 645 00:31:52,400 --> 00:31:55,600 Speaker 1: post on threads telling people to go to YouTube to 646 00:31:55,640 --> 00:31:56,800 Speaker 1: watch our streaming. 647 00:31:57,120 --> 00:31:59,640 Speaker 3: So I am multidad. I will tasking out. 648 00:31:59,640 --> 00:32:02,560 Speaker 15: I will I will repost that. Just give me a second. 649 00:32:02,720 --> 00:32:05,440 Speaker 15: I'm on air with you right now. Look, I mean 650 00:32:05,440 --> 00:32:09,120 Speaker 15: Elon's tweeted. He said it is infinitely preferable to be 651 00:32:09,160 --> 00:32:12,480 Speaker 15: attacked by strangers on Twitter then indulge in the false 652 00:32:12,520 --> 00:32:15,880 Speaker 15: happiness of hide the pain Instagram. And I think his 653 00:32:16,080 --> 00:32:20,240 Speaker 15: point is that historically Instagram is a photo based app 654 00:32:20,280 --> 00:32:22,600 Speaker 15: where you give the perception that your life is very 655 00:32:22,600 --> 00:32:27,840 Speaker 15: different to reality. I guess from a happiness perspective. Linda Yakarino, 656 00:32:27,920 --> 00:32:31,240 Speaker 15: who is the new Twitter CEO, has tweeted in the 657 00:32:31,280 --> 00:32:34,760 Speaker 15: last thirty minutes. I wouldn't call it cryptic, but I 658 00:32:34,760 --> 00:32:37,920 Speaker 15: would say that she really emphasizes what she feels is 659 00:32:37,920 --> 00:32:41,880 Speaker 15: good about Twitter. She doesn't specifically name or call out threads, 660 00:32:42,800 --> 00:32:44,680 Speaker 15: but you know, they're essentially the same thing. I'm a 661 00:32:44,680 --> 00:32:46,840 Speaker 15: big meme guy, and you guys will have seen that 662 00:32:46,960 --> 00:32:51,920 Speaker 15: Zuckerberg tweeted. He did his first tweet in since twenty twelve, 663 00:32:51,960 --> 00:32:55,239 Speaker 15: eleven years, and it's the classic Spider Man pointing at 664 00:32:55,240 --> 00:32:58,320 Speaker 15: Spider Man. The reference to episode nineteen B at the 665 00:32:58,400 --> 00:33:02,880 Speaker 15: nineteen sixty seven animated series is called double identity. They're 666 00:33:02,920 --> 00:33:05,640 Speaker 15: the same platform, and I you know, Mandy may disagree 667 00:33:05,640 --> 00:33:08,080 Speaker 15: with me, but to all intents and purposes, they're the same. 668 00:33:08,120 --> 00:33:13,400 Speaker 15: And that's probably ahead of the cage match upset, mister Musk. 669 00:33:13,840 --> 00:33:16,280 Speaker 8: So do you think that it's likely that Meadow would 670 00:33:16,280 --> 00:33:19,720 Speaker 8: be able to take a big chunk of users when 671 00:33:19,720 --> 00:33:21,800 Speaker 8: it comes to Twitter? Obviously, as you know, there's been 672 00:33:21,840 --> 00:33:24,160 Speaker 8: problems that Elon has had to go through when it 673 00:33:24,160 --> 00:33:26,080 Speaker 8: comes to the Twitter platform over the past year. 674 00:33:26,880 --> 00:33:28,520 Speaker 15: Oh thank goodness. I thought you were going to ask, 675 00:33:28,640 --> 00:33:31,400 Speaker 15: is it likely that Muskan Zuckerberg actually like each other 676 00:33:31,440 --> 00:33:36,320 Speaker 15: in a cage? You know, I think that what I 677 00:33:36,480 --> 00:33:39,400 Speaker 15: noticed anecdotally. I was on it for hours yesterday. It 678 00:33:39,440 --> 00:33:42,360 Speaker 15: was a bit cringe fair. I sent many threads. I 679 00:33:42,400 --> 00:33:44,680 Speaker 15: really engaged with people. A lot of what people were 680 00:33:44,680 --> 00:33:48,320 Speaker 15: talking about is that they wanted the tone of Threads 681 00:33:48,760 --> 00:33:51,520 Speaker 15: to be a pleasant place, a nice place, and many 682 00:33:51,560 --> 00:33:54,680 Speaker 15: of them explicitly referenced the idea that they felt that 683 00:33:54,760 --> 00:33:58,000 Speaker 15: Twitter was not that way. And so you know, this 684 00:33:58,160 --> 00:34:00,280 Speaker 15: is also playing out on Twitter in parallel, by the way, 685 00:34:00,320 --> 00:34:02,680 Speaker 15: the irony lots of people on Twitter are talking about 686 00:34:02,960 --> 00:34:05,720 Speaker 15: you're only going to threads as a vote against Musk 687 00:34:05,800 --> 00:34:09,160 Speaker 15: himself because you don't like him or his personality. I don't. 688 00:34:09,280 --> 00:34:12,520 Speaker 15: It's how can any of us quantify what kind of 689 00:34:13,080 --> 00:34:16,920 Speaker 15: driver that will be for Thread's growth. I think Mandy's 690 00:34:16,920 --> 00:34:19,759 Speaker 15: points on the future of the content on the on 691 00:34:19,800 --> 00:34:21,160 Speaker 15: the Threads platform is the key bit. 692 00:34:21,480 --> 00:34:24,440 Speaker 1: Hey, let's just quick change gears here. I know you 693 00:34:24,440 --> 00:34:26,719 Speaker 1: spoke with the CEO of Rivian yesterday, Ed, what's the 694 00:34:27,000 --> 00:34:27,799 Speaker 1: key takeaway there? 695 00:34:28,760 --> 00:34:31,439 Speaker 15: Yeah, I mean two pieces of news. One, the court 696 00:34:31,440 --> 00:34:34,120 Speaker 15: has just gone is the first time the supply chains normalized, 697 00:34:34,160 --> 00:34:37,080 Speaker 15: and that was evidence by their output. They've made some 698 00:34:37,120 --> 00:34:39,799 Speaker 15: tech fixes and they're really starting to ramp now and 699 00:34:40,200 --> 00:34:43,839 Speaker 15: they basically suggested that they will outperform their guidance, which 700 00:34:43,880 --> 00:34:46,279 Speaker 15: would be interesting. Professor's The other is there that he 701 00:34:46,320 --> 00:34:48,520 Speaker 15: told me they're trying to negotiate with Amazon to get 702 00:34:48,560 --> 00:34:51,760 Speaker 15: out of the Amazon's exclusivity to buy the commercial vans 703 00:34:51,760 --> 00:34:54,160 Speaker 15: from Ribbean. So they say that those talks are going 704 00:34:54,200 --> 00:34:57,080 Speaker 15: well and that if there's a successful Ribbean can start 705 00:34:57,080 --> 00:35:00,200 Speaker 15: selling these electric delivery bands that other players and and 706 00:35:00,239 --> 00:35:03,480 Speaker 15: as we know from this program, right, electrifying last mail 707 00:35:03,520 --> 00:35:07,200 Speaker 15: delivery in the logistics space is a big market opportunity. 708 00:35:07,280 --> 00:35:08,759 Speaker 15: So that was a really good takeaway. Check it out 709 00:35:08,760 --> 00:35:09,680 Speaker 15: on Bloomberg dot com. 710 00:35:09,719 --> 00:35:11,560 Speaker 1: All right, great stuff at Ed Ludlow doing all the 711 00:35:11,600 --> 00:35:15,759 Speaker 1: tech stuff for Bloomberg Technology and Bloomberg News out there 712 00:35:15,760 --> 00:35:18,160 Speaker 1: in San Francisco. Man, you've seen, of course senior technology 713 00:35:18,200 --> 00:35:19,920 Speaker 1: channels for Bloomberg Intelligence. 714 00:35:20,200 --> 00:35:23,320 Speaker 11: You're listening to the tape catch are live program Bloomberg 715 00:35:23,400 --> 00:35:26,960 Speaker 11: Markets weekdays at ten am Eastern on Bloomberg Radio, the 716 00:35:27,040 --> 00:35:29,000 Speaker 11: tune in app, Bloomberg dot Com, and. 717 00:35:28,960 --> 00:35:30,279 Speaker 13: The Bloomberg Business app. 718 00:35:30,320 --> 00:35:33,120 Speaker 11: You can also listen live on Amazon Alexa from our 719 00:35:33,160 --> 00:35:38,160 Speaker 11: flagship New York station. Just say Alexa, play Bloomberg eleven thirty. 720 00:35:40,120 --> 00:35:43,239 Speaker 1: This is not necessarily tech, but you think about the 721 00:35:43,280 --> 00:35:45,520 Speaker 1: tech enabled boxes that end up on your front door 722 00:35:45,600 --> 00:35:47,839 Speaker 1: every single day, and everybody knows what I'm talking about 723 00:35:48,200 --> 00:35:50,400 Speaker 1: let's get a sense of like the business of the 724 00:35:50,440 --> 00:35:53,759 Speaker 1: box business, Ryan Fox. He covers a carrogated market for 725 00:35:53,840 --> 00:35:58,080 Speaker 1: Bloomberg Intelligence. So Ryan, give us a sense of just 726 00:35:58,880 --> 00:36:00,960 Speaker 1: kind of the stuff you covered, DoD Me just give 727 00:36:01,000 --> 00:36:03,680 Speaker 1: us a sense of the industry that we all touch 728 00:36:03,719 --> 00:36:05,640 Speaker 1: every day because it lands on our doorstep every day. 729 00:36:06,520 --> 00:36:08,480 Speaker 16: Yeah, so the average American is going to call it 730 00:36:08,480 --> 00:36:10,960 Speaker 16: a cardboard box. In the industry, we call it a 731 00:36:11,000 --> 00:36:16,800 Speaker 16: corrugated box, nice anadetically, like ninety five percent of consumer 732 00:36:16,840 --> 00:36:19,759 Speaker 16: goods right in these boxes every day. So it's a 733 00:36:19,880 --> 00:36:22,200 Speaker 16: very good indicator of what's going on in the economy. 734 00:36:23,040 --> 00:36:26,360 Speaker 16: And well, for the last year, we've seen a gradual 735 00:36:26,400 --> 00:36:30,839 Speaker 16: decline in box shipments by producers of those boxes going 736 00:36:30,880 --> 00:36:32,880 Speaker 16: to brands who. 737 00:36:32,680 --> 00:36:34,280 Speaker 8: Are the main players in that space. 738 00:36:35,320 --> 00:36:38,440 Speaker 16: Yeah, many players are going to be International Paper West 739 00:36:38,520 --> 00:36:41,440 Speaker 16: Rock Packaging Corp. At least domestically here in the US. 740 00:36:41,800 --> 00:36:45,040 Speaker 8: And you mentioned a slow down. What was the catalyst 741 00:36:45,120 --> 00:36:47,960 Speaker 8: to that in what would that also mean for the 742 00:36:48,000 --> 00:36:49,239 Speaker 8: trajectory of the economy. 743 00:36:50,280 --> 00:36:55,399 Speaker 16: Yeah, So initially the slowdown, it was linked to these 744 00:36:56,040 --> 00:36:58,279 Speaker 16: the de stocking narrative that's been going on for about 745 00:36:58,280 --> 00:37:01,239 Speaker 16: the last year. Most of the producers are saying their 746 00:37:01,360 --> 00:37:06,080 Speaker 16: customers were pushing back, that they had plenty of inventory. 747 00:37:07,600 --> 00:37:10,359 Speaker 16: Things weren't moving very quickly, and some of it we 748 00:37:10,400 --> 00:37:15,239 Speaker 16: saw in our data. We saw that first quarter of 749 00:37:15,320 --> 00:37:19,560 Speaker 16: twenty twenty two, lead times to get boxes went out 750 00:37:20,000 --> 00:37:24,000 Speaker 16: on average like four and five weeks, And this was 751 00:37:24,080 --> 00:37:27,279 Speaker 16: a huge departure from the norm. The average lead time 752 00:37:27,280 --> 00:37:29,760 Speaker 16: to get boxes is like three to five business days, 753 00:37:30,040 --> 00:37:32,440 Speaker 16: so to have something about five weeks on average was 754 00:37:32,600 --> 00:37:35,719 Speaker 16: just astronomical. So when you think about a manufacturer and 755 00:37:35,760 --> 00:37:38,359 Speaker 16: how they have to place their orders, this caused them 756 00:37:38,360 --> 00:37:43,040 Speaker 16: to change their ordering. Some manufacturers during the pandemic had 757 00:37:43,040 --> 00:37:47,880 Speaker 16: even gone to AI platforms that were initiating automatic orders 758 00:37:47,920 --> 00:37:50,640 Speaker 16: even when they maybe didn't need them, and so at 759 00:37:50,680 --> 00:37:53,320 Speaker 16: some point in the second quarter they found themselves sitting 760 00:37:53,360 --> 00:37:56,160 Speaker 16: on a lot of boxes that they didn't really need. 761 00:37:56,680 --> 00:37:59,640 Speaker 16: And so producers saw that slowdown at the end of 762 00:37:59,680 --> 00:38:03,240 Speaker 16: the second quarter going into the midyear, and it really 763 00:38:03,239 --> 00:38:04,319 Speaker 16: just slowed down from there. 764 00:38:04,960 --> 00:38:08,320 Speaker 1: All right, but where are we now versus pre pandemic. 765 00:38:08,400 --> 00:38:12,239 Speaker 1: There's a lot more boxes out there, right, Uh, well, 766 00:38:13,280 --> 00:38:15,359 Speaker 1: I'm getting so many a day. 767 00:38:15,760 --> 00:38:16,040 Speaker 13: All right. 768 00:38:16,080 --> 00:38:19,799 Speaker 3: Here's my thing. I'm really good at breaking down the 769 00:38:19,840 --> 00:38:21,520 Speaker 3: box as soon as it comes in and we empty it. 770 00:38:21,640 --> 00:38:23,960 Speaker 1: I'm breaking that box down. I'm the opposite, and I'm 771 00:38:24,000 --> 00:38:26,799 Speaker 1: putting it in recycling. But really it's got to be 772 00:38:26,840 --> 00:38:28,320 Speaker 1: like way higher than pre pandemic. 773 00:38:29,280 --> 00:38:33,359 Speaker 16: No, So we're actually after the first quarter we were 774 00:38:33,400 --> 00:38:37,200 Speaker 16: tracking with twenty seventeen as far as the volume of 775 00:38:37,239 --> 00:38:41,040 Speaker 16: boxes it was going out. Our data indicates that through 776 00:38:41,080 --> 00:38:44,319 Speaker 16: the second quarter we're probably still on that pace, maybe 777 00:38:44,360 --> 00:38:47,360 Speaker 16: even a little bit behind there, and it's not looking 778 00:38:47,360 --> 00:38:48,560 Speaker 16: good going in the second half. 779 00:38:48,680 --> 00:38:51,480 Speaker 1: Really, wow, I never would have guessed that, Hey, go 780 00:38:51,680 --> 00:38:54,000 Speaker 1: following up on that, because I'm a big recycler, and 781 00:38:54,040 --> 00:38:55,800 Speaker 1: I think this is every time I break down a 782 00:38:55,840 --> 00:38:57,759 Speaker 1: box and put it into recycond I feel like I 783 00:38:57,840 --> 00:38:59,359 Speaker 1: might be part of a scam here that it doesn't 784 00:38:59,400 --> 00:39:02,560 Speaker 1: want to work. Tell us how the industry recycles boxes 785 00:39:02,560 --> 00:39:03,000 Speaker 1: and stuff. 786 00:39:03,840 --> 00:39:07,920 Speaker 16: Sure, So, first of all, about over ninety percent of 787 00:39:07,960 --> 00:39:10,600 Speaker 16: all of the recycled boxes that we get, and really 788 00:39:10,640 --> 00:39:13,040 Speaker 16: all recycled commodities are going to come from commercial and 789 00:39:13,080 --> 00:39:16,080 Speaker 16: industrial sectors. So we're going to be thinking about Walmart's 790 00:39:16,080 --> 00:39:19,520 Speaker 16: and Kroger's and Albertson's and big retailers like that. That's 791 00:39:19,640 --> 00:39:22,760 Speaker 16: where most of the old what we call old quirdated 792 00:39:22,800 --> 00:39:27,440 Speaker 16: cartons or OCC, that's where they come from. Curbside recycling 793 00:39:27,640 --> 00:39:32,440 Speaker 16: is really not great. It's about seven to eight percent 794 00:39:32,440 --> 00:39:36,000 Speaker 16: of the total, and it represents about two million tons 795 00:39:36,040 --> 00:39:39,560 Speaker 16: a year. Americans just aren't great at recycling. 796 00:39:39,840 --> 00:39:42,040 Speaker 3: I'm really good at it, but I just so does 797 00:39:42,080 --> 00:39:45,920 Speaker 3: International Paper take my box and then redo it and 798 00:39:45,920 --> 00:39:46,640 Speaker 3: send it back out to me? 799 00:39:46,719 --> 00:39:48,920 Speaker 8: That's what I was curious about, because do they do that? 800 00:39:49,160 --> 00:39:52,200 Speaker 8: Or also are there renewable basic materials that go into 801 00:39:52,239 --> 00:39:54,360 Speaker 8: tissues and other personal care products? 802 00:39:54,960 --> 00:39:59,560 Speaker 16: Yeah, so OCC is a very highly sought commodity. It's 803 00:40:00,320 --> 00:40:02,880 Speaker 16: we export about ten million tons a year of to 804 00:40:03,080 --> 00:40:07,360 Speaker 16: other countries, but internally, we consume about twenty five million 805 00:40:07,400 --> 00:40:11,200 Speaker 16: tons of old corgated boxes every single year, and we 806 00:40:11,239 --> 00:40:15,160 Speaker 16: make new boxes out of them. 807 00:40:15,320 --> 00:40:17,040 Speaker 3: Do I play these stocks? Do? I? I mean, do 808 00:40:17,120 --> 00:40:20,480 Speaker 3: I play it on? I mean, if I'm Mike, is 809 00:40:20,560 --> 00:40:23,400 Speaker 3: my call on International Paper? Just how much stuff is 810 00:40:23,440 --> 00:40:24,600 Speaker 3: getting shipped around the world. 811 00:40:27,239 --> 00:40:33,120 Speaker 16: That's a great question. I mean, I don't know, I 812 00:40:33,120 --> 00:40:36,920 Speaker 16: don't know the right answer to that. They're they're traditionally 813 00:40:37,400 --> 00:40:40,319 Speaker 16: very very stable companies. I mean, like I said, with 814 00:40:40,400 --> 00:40:43,520 Speaker 16: ninety five percent of the world's goods that consumers buy 815 00:40:43,640 --> 00:40:45,880 Speaker 16: riding in these boxes. It's it's not like they're going 816 00:40:45,960 --> 00:40:47,120 Speaker 16: to go away anytime soon. 817 00:40:47,280 --> 00:40:49,760 Speaker 3: Yeah, I mean, I don't know just about my household. 818 00:40:49,800 --> 00:40:52,160 Speaker 1: It just seems like, you know, Tom Keane's always complaining 819 00:40:52,160 --> 00:40:53,560 Speaker 1: about you know, his doormans. 820 00:40:53,600 --> 00:40:54,880 Speaker 13: What are you getting delivery? 821 00:40:55,160 --> 00:40:59,040 Speaker 3: I don't know. It's it's shampoo comes. I mean, you 822 00:40:59,160 --> 00:41:01,680 Speaker 3: don't go to the store anymore. You just click. It's crazy. 823 00:41:01,760 --> 00:41:02,680 Speaker 3: So I don't know what's. 824 00:41:02,520 --> 00:41:04,960 Speaker 16: Going on, all right, So we did some math on 825 00:41:05,000 --> 00:41:07,279 Speaker 16: it and the average America. So if we were to 826 00:41:07,280 --> 00:41:09,680 Speaker 16: take the volume of boxes that are made in average year, 827 00:41:09,760 --> 00:41:13,399 Speaker 16: divided equally across everybody in the country, it's about twelve 828 00:41:13,480 --> 00:41:15,319 Speaker 16: hundred square feet per person per year. 829 00:41:15,920 --> 00:41:18,920 Speaker 1: So there, Well, I'm telling you all right, Ryan, thanks 830 00:41:18,960 --> 00:41:21,359 Speaker 1: so much for joining us, Ryan Fox, he is thanks. 831 00:41:21,440 --> 00:41:24,480 Speaker 1: Corgated market analysts with Bloomberg Intelligence. 832 00:41:25,080 --> 00:41:26,799 Speaker 3: Learned a lot there. But I don't know. I feel 833 00:41:26,800 --> 00:41:29,439 Speaker 3: like I'm a good recycler, but you know, Ryan's telling 834 00:41:29,440 --> 00:41:30,879 Speaker 3: me that I'm just it's not that big a deal. 835 00:41:30,960 --> 00:41:32,760 Speaker 8: Think I'm ordering I'm Juney boxes. 836 00:41:33,400 --> 00:41:36,080 Speaker 3: I'm not moving the needle. But anyway, good stuff. To 837 00:41:36,120 --> 00:41:37,520 Speaker 3: catch up on that part of the business. 838 00:41:37,640 --> 00:41:40,759 Speaker 11: You're listening to the tape Cat's are Live program Bloomberg 839 00:41:40,840 --> 00:41:44,440 Speaker 11: Markets weekdays at ten am Eastern on Bloomberg Radio, the 840 00:41:44,480 --> 00:41:46,560 Speaker 11: tune in app, Bloomberg dot Com. 841 00:41:46,280 --> 00:41:47,719 Speaker 13: And the Bloomberg Business App. 842 00:41:47,760 --> 00:41:50,560 Speaker 11: You can also listen live on Amazon Alexa from our 843 00:41:50,560 --> 00:41:54,960 Speaker 11: flagship New York station Just Say Alexa, playing Bloomberg eleven thirty. 844 00:41:57,200 --> 00:41:59,040 Speaker 1: Just met and Paul sween here in a Bloomberg Interactive 845 00:41:59,080 --> 00:42:02,160 Speaker 1: Brokers studio. This week, the Supreme Court struck down the 846 00:42:02,160 --> 00:42:05,239 Speaker 1: Biden administration's student loan forgiveness plan, which would have done 847 00:42:05,239 --> 00:42:09,080 Speaker 1: away with it as much as twenty thousand dollars per borrower. 848 00:42:09,880 --> 00:42:13,040 Speaker 1: And remember, House also used the deal to raise the 849 00:42:13,120 --> 00:42:15,920 Speaker 1: nation's debt sailing to force borrowers to start paying back 850 00:42:15,960 --> 00:42:18,320 Speaker 1: their loans in October, which is sooner than planned. So 851 00:42:18,360 --> 00:42:20,960 Speaker 1: it's really tough on that student loan forgiveness front. Let's 852 00:42:20,960 --> 00:42:23,240 Speaker 1: get the latest on what that could beat economically. We 853 00:42:23,239 --> 00:42:27,320 Speaker 1: welcome Claudia Sam, founder of Some Consulting, former senior economist 854 00:42:27,400 --> 00:42:30,279 Speaker 1: at the White House Council of Economic Advisors, so she 855 00:42:30,360 --> 00:42:31,600 Speaker 1: knows about this policy stuff. 856 00:42:31,800 --> 00:42:33,359 Speaker 3: Laudia, thanks so much for joining us here. 857 00:42:33,719 --> 00:42:36,359 Speaker 1: Give us your view of what kind of we saw 858 00:42:36,400 --> 00:42:38,399 Speaker 1: from the Supreme Court and from Congress over the last 859 00:42:38,440 --> 00:42:40,960 Speaker 1: couple of weeks as it relates to student debt and 860 00:42:41,000 --> 00:42:42,359 Speaker 1: loan forgiveness and that type of thing. 861 00:42:44,520 --> 00:42:47,239 Speaker 17: Student loan forgiveness not making it through the Supreme Court. 862 00:42:47,280 --> 00:42:49,360 Speaker 17: I don't think that should be a surprise to anyone 863 00:42:49,800 --> 00:42:53,920 Speaker 17: using executive powers to do four hundred billion in spending, 864 00:42:54,440 --> 00:42:56,799 Speaker 17: and yet it came. This was the second of two 865 00:42:56,840 --> 00:43:01,520 Speaker 17: blows to student borrowers this uh that week, and you 866 00:43:01,600 --> 00:43:05,480 Speaker 17: mentioned in the repayments start sooner and for a lot 867 00:43:05,480 --> 00:43:07,680 Speaker 17: of people that is going to be a hardship, right, 868 00:43:07,760 --> 00:43:10,600 Speaker 17: like for you know, the time that they've not been paying. 869 00:43:10,680 --> 00:43:12,000 Speaker 9: That really eased up some space. 870 00:43:12,600 --> 00:43:16,319 Speaker 17: It's coming back somewhat sooner than the administration said it 871 00:43:16,360 --> 00:43:18,719 Speaker 17: was going to end too. But this is this is earlier, 872 00:43:19,800 --> 00:43:23,000 Speaker 17: so you're not getting this the forgiveness to help smooth 873 00:43:23,040 --> 00:43:25,359 Speaker 17: over the period of adjusting, and you are getting your 874 00:43:25,360 --> 00:43:28,840 Speaker 17: payments back sooner. So there's you know, it was not 875 00:43:29,040 --> 00:43:32,640 Speaker 17: a good couple of weeks for people with student loans. 876 00:43:33,600 --> 00:43:36,400 Speaker 8: So with interest beginning to accrue in August and then 877 00:43:36,440 --> 00:43:39,560 Speaker 8: those payments needing to be paid in October. How does 878 00:43:39,600 --> 00:43:44,040 Speaker 8: that affect consumer spending? And obviously the trajectory of the economy. 879 00:43:45,239 --> 00:43:49,600 Speaker 17: Right, So it's clearly not good for the for the economy. 880 00:43:49,719 --> 00:43:53,719 Speaker 17: It is the case that you know, the people themselves 881 00:43:53,719 --> 00:43:56,480 Speaker 17: who are in these situations have student loans. This deeply 882 00:43:56,520 --> 00:44:00,440 Speaker 17: affects them. And yet the amount of money we're talking about, 883 00:44:00,480 --> 00:44:03,759 Speaker 17: like the new payments, it's really not the kind of 884 00:44:03,800 --> 00:44:07,200 Speaker 17: magnitudes that really move the needle on GDP, like in 885 00:44:07,239 --> 00:44:09,120 Speaker 17: the sense that oh, this would or demand and make 886 00:44:09,160 --> 00:44:10,960 Speaker 17: it like, oh, the Fed doesn't have to do as 887 00:44:11,000 --> 00:44:15,120 Speaker 17: much because these payments are expiring. So I think with 888 00:44:15,239 --> 00:44:20,360 Speaker 17: this policy, the macro lens is less important than the 889 00:44:20,400 --> 00:44:22,839 Speaker 17: people side of it. 890 00:44:22,880 --> 00:44:25,760 Speaker 1: Isn't there already something along the lines of the Public 891 00:44:25,800 --> 00:44:28,279 Speaker 1: Service Loan Forgiveness program? Can you tell us with that 892 00:44:28,520 --> 00:44:31,400 Speaker 1: is how that works and how that might you know, 893 00:44:31,480 --> 00:44:34,000 Speaker 1: help more people kind of deal with their student debt. 894 00:44:34,440 --> 00:44:36,480 Speaker 17: You know, In my piece I made the point is like, look, 895 00:44:36,480 --> 00:44:38,719 Speaker 17: we're at a time where you've got a moment of 896 00:44:38,760 --> 00:44:41,719 Speaker 17: reflection and how you go forward. President Biden said he's 897 00:44:41,760 --> 00:44:43,640 Speaker 17: going to try and keep figuring out how to do this, 898 00:44:44,239 --> 00:44:46,239 Speaker 17: and it's also a time where they could take stock 899 00:44:46,320 --> 00:44:49,080 Speaker 17: and say, hey, let's look at some other forgiveness programs, 900 00:44:49,280 --> 00:44:51,799 Speaker 17: what didn't go well, what did go well? And the 901 00:44:51,840 --> 00:44:54,719 Speaker 17: one example that I talk about are these the debt 902 00:44:54,760 --> 00:44:58,360 Speaker 17: forgiveness to people who work in a public service of 903 00:44:58,400 --> 00:44:58,839 Speaker 17: any form. 904 00:44:58,840 --> 00:44:59,400 Speaker 9: You can think of. 905 00:44:59,440 --> 00:45:07,200 Speaker 17: As teachers, doctors, firefighters, right, any like, there's a pretty 906 00:45:07,280 --> 00:45:10,640 Speaker 17: there's a big group. And in fact, the group that 907 00:45:11,040 --> 00:45:14,480 Speaker 17: would qualify for these loans is big in terms of 908 00:45:14,560 --> 00:45:17,160 Speaker 17: jobs of the economy. It can almost be twenty five 909 00:45:17,160 --> 00:45:19,480 Speaker 17: percent of jobs. That's not to say all those people 910 00:45:19,480 --> 00:45:21,560 Speaker 17: are eligible and they have student loan debt, but this 911 00:45:21,600 --> 00:45:25,600 Speaker 17: is not a trivial subset. And one of the things 912 00:45:25,640 --> 00:45:29,719 Speaker 17: that they have really struggled with that the Biden did 913 00:45:29,719 --> 00:45:32,759 Speaker 17: not is setting up a plan where people actually get 914 00:45:32,760 --> 00:45:35,319 Speaker 17: the benefit at the end. Right, they have a low 915 00:45:35,360 --> 00:45:37,680 Speaker 17: take up rate and they have a low success rate. 916 00:45:38,160 --> 00:45:40,120 Speaker 17: But it's a complicated program. You got to pay back 917 00:45:40,160 --> 00:45:42,839 Speaker 17: ten years, you know. So there are things there that 918 00:45:43,160 --> 00:45:47,359 Speaker 17: but the Biden's forgiveness plan, sign up for it was 919 00:45:47,560 --> 00:45:51,239 Speaker 17: so fast and massive, so there's lessons to be learned there. 920 00:45:52,160 --> 00:45:54,920 Speaker 17: And I mean there are functional parts of that student 921 00:45:54,960 --> 00:45:55,600 Speaker 17: loan setup. 922 00:45:55,880 --> 00:45:57,680 Speaker 9: So that could also. I think there could be. 923 00:45:57,640 --> 00:46:00,319 Speaker 17: A real exchange of ideas that would be fruit full, 924 00:46:00,760 --> 00:46:04,239 Speaker 17: both for the forgiveness plan we actually have and the 925 00:46:04,600 --> 00:46:07,680 Speaker 17: thinking about what would be next for a student loan forgiveness. 926 00:46:08,160 --> 00:46:10,880 Speaker 8: When it comes to the inflation front, there were concerns 927 00:46:10,920 --> 00:46:16,240 Speaker 8: about macroeconomists about how the potential forgiveness could potentially spur 928 00:46:16,800 --> 00:46:19,959 Speaker 8: a spark in inflation. What do you think this means 929 00:46:20,000 --> 00:46:22,439 Speaker 8: when we're looking on the inflation front moving forward. 930 00:46:24,200 --> 00:46:27,759 Speaker 17: We're talking about basis points, right, like, you know, yes, 931 00:46:27,840 --> 00:46:30,120 Speaker 17: it will probably have an effect. Yes, it probably did 932 00:46:30,200 --> 00:46:32,560 Speaker 17: allow spending to be a little higher as the you know, 933 00:46:33,040 --> 00:46:35,359 Speaker 17: you didn't have to do the payments with. 934 00:46:35,400 --> 00:46:36,239 Speaker 9: A student loan debt. 935 00:46:36,280 --> 00:46:39,359 Speaker 17: That's forgiveness. That's even less applical because it's spread out 936 00:46:39,360 --> 00:46:43,760 Speaker 17: over ten years like the whole process. And it's yes, 937 00:46:43,880 --> 00:46:45,920 Speaker 17: it will have an effect on demand, depending if it's 938 00:46:45,920 --> 00:46:48,560 Speaker 17: there or it's taken away. And yet this is not 939 00:46:49,080 --> 00:46:51,920 Speaker 17: that's not the argument that should bring down a program 940 00:46:52,280 --> 00:46:54,640 Speaker 17: like this is the inflationary effects. 941 00:46:55,120 --> 00:46:58,759 Speaker 1: So, Claudie, we have received a lot of economic data, 942 00:46:58,880 --> 00:47:01,839 Speaker 1: including today that's just this economy perhaps is stronger than 943 00:47:01,840 --> 00:47:04,680 Speaker 1: people think that perhaps the recession is not right around 944 00:47:04,680 --> 00:47:07,600 Speaker 1: the corner. I would love to get your recession outlook, 945 00:47:07,960 --> 00:47:11,839 Speaker 1: maybe talk talk to us about something called the Psalm rule. 946 00:47:11,960 --> 00:47:14,759 Speaker 9: Yeah, what's that? Yeah. 947 00:47:14,800 --> 00:47:18,200 Speaker 17: So I've said several times last year when when the 948 00:47:18,239 --> 00:47:20,839 Speaker 17: recession talk was really getting going, and it's like, we 949 00:47:20,920 --> 00:47:24,440 Speaker 17: need to we need to hope that that labor market 950 00:47:24,520 --> 00:47:28,120 Speaker 17: is as strong as the FED keeps complaining that it 951 00:47:28,160 --> 00:47:31,120 Speaker 17: is right, because if it's strong enough, it can buffer 952 00:47:31,640 --> 00:47:34,880 Speaker 17: and you know, slowly, there are other things related to 953 00:47:34,920 --> 00:47:38,759 Speaker 17: the pandemic, to the war in Ukraine that as those 954 00:47:38,800 --> 00:47:42,120 Speaker 17: work through, we could have inflation come down without the 955 00:47:42,120 --> 00:47:45,239 Speaker 17: FED doing more and more and more. But they're going 956 00:47:45,320 --> 00:47:48,080 Speaker 17: to keep pushing. So the labor market being strong is 957 00:47:48,080 --> 00:47:51,880 Speaker 17: good for people without a doubt, but it also can 958 00:47:53,000 --> 00:47:57,400 Speaker 17: just buffer us so that we slowly rebounce, we slowly 959 00:47:57,440 --> 00:48:00,400 Speaker 17: get inflation back down, as opposed to you know, bam, 960 00:48:00,440 --> 00:48:05,239 Speaker 17: there's a recession and everything falls, including inflation. So I 961 00:48:05,320 --> 00:48:08,320 Speaker 17: think it's the labor market is extremely important in that regard, 962 00:48:08,680 --> 00:48:14,040 Speaker 17: And in terms of my recession outlook, I really am 963 00:48:14,360 --> 00:48:16,920 Speaker 17: kind of on the fence right. For a long time, 964 00:48:16,960 --> 00:48:20,440 Speaker 17: I was optimistic that we could have of soft landing 965 00:48:21,160 --> 00:48:25,360 Speaker 17: in some maybe softish type landing. When we had the 966 00:48:25,440 --> 00:48:28,520 Speaker 17: disruptions in the banking sector, I think that caused more 967 00:48:28,600 --> 00:48:32,640 Speaker 17: concern that, you know, we may really not pull this 968 00:48:32,680 --> 00:48:35,120 Speaker 17: off because there's the FED has put a lot into 969 00:48:35,160 --> 00:48:37,520 Speaker 17: the system in terms of raid hikes, and they have 970 00:48:37,600 --> 00:48:39,560 Speaker 17: bank failures putting more in. 971 00:48:40,280 --> 00:48:41,600 Speaker 9: So it's kind but I agree with you. 972 00:48:41,640 --> 00:48:44,880 Speaker 17: As the latest data on the economy comes in, it 973 00:48:44,920 --> 00:48:45,920 Speaker 17: looks pretty good. 974 00:48:46,480 --> 00:48:48,719 Speaker 8: And especially on the back of that ADP data that 975 00:48:48,760 --> 00:48:51,680 Speaker 8: we got this morning Jolts, and then ahead of tomorrow's 976 00:48:51,800 --> 00:48:55,160 Speaker 8: jobs report, what's surview as far as the drink of 977 00:48:55,200 --> 00:48:56,719 Speaker 8: the labor marketing and what it can mean for the 978 00:48:56,719 --> 00:48:58,160 Speaker 8: Fed's decision later this month. 979 00:49:00,120 --> 00:49:02,359 Speaker 17: So I think we're going to continue to see an 980 00:49:02,400 --> 00:49:06,000 Speaker 17: expanding labor market. I mean no, not every month, right, 981 00:49:06,000 --> 00:49:08,640 Speaker 17: we could have a big downside surprise this time, because 982 00:49:08,680 --> 00:49:10,600 Speaker 17: you know we've had upside. But I think you know, 983 00:49:10,640 --> 00:49:13,240 Speaker 17: when you look broadbrushed and you look like recent months, 984 00:49:13,320 --> 00:49:17,080 Speaker 17: not just like today and you know tomorrow kind of picture, 985 00:49:17,160 --> 00:49:19,320 Speaker 17: I think we're seeing what the FED said it wanted 986 00:49:19,320 --> 00:49:22,360 Speaker 17: to see, which an economy slow it just like people 987 00:49:22,480 --> 00:49:25,319 Speaker 17: not spending so much, not you know, people coming back 988 00:49:25,360 --> 00:49:26,920 Speaker 17: to work so they don't have to pay the wages 989 00:49:27,000 --> 00:49:27,520 Speaker 17: quite so. 990 00:49:27,560 --> 00:49:30,040 Speaker 9: Much, so we'll know more. 991 00:49:30,520 --> 00:49:32,200 Speaker 17: We're going to know a lot more about the labor 992 00:49:32,239 --> 00:49:33,280 Speaker 17: market by Friday. 993 00:49:34,960 --> 00:49:36,160 Speaker 9: But at the end of the day, the Fed is 994 00:49:36,200 --> 00:49:37,440 Speaker 9: going to look at at inflation. 995 00:49:37,880 --> 00:49:40,000 Speaker 17: Are they get one more CPI before their meeting, and 996 00:49:40,040 --> 00:49:43,040 Speaker 17: that is going to take precedent over anything else that 997 00:49:43,080 --> 00:49:45,280 Speaker 17: they're learning because inflation is too high. 998 00:49:45,840 --> 00:49:48,279 Speaker 1: So, I mean a lot of folks will say. We 999 00:49:48,280 --> 00:49:51,319 Speaker 1: had Danielle Di Martino Booth from QI Research Consulting in 1000 00:49:51,360 --> 00:49:54,799 Speaker 1: here earlier today and she was saying she thinks the 1001 00:49:54,800 --> 00:49:57,960 Speaker 1: economy is much slower than the headline data is suggesting. 1002 00:49:57,960 --> 00:50:00,200 Speaker 1: Some of the data that she looks at. Is your 1003 00:50:00,239 --> 00:50:02,600 Speaker 1: sense at the economy is in fact slowing down and 1004 00:50:03,239 --> 00:50:03,920 Speaker 1: is it material? 1005 00:50:04,800 --> 00:50:07,799 Speaker 17: Well, if you think about the increase in perils this 1006 00:50:07,880 --> 00:50:10,960 Speaker 17: year compared to last year, they have slowed down. They're 1007 00:50:10,960 --> 00:50:14,480 Speaker 17: still really good, you know, in terms of relative to 1008 00:50:14,560 --> 00:50:18,560 Speaker 17: before the pandemic. So I mean getting two hundred thousand 1009 00:50:18,640 --> 00:50:21,480 Speaker 17: jobs a month, that was that was pretty standard before 1010 00:50:21,560 --> 00:50:22,239 Speaker 17: the pandemic. 1011 00:50:22,320 --> 00:50:24,360 Speaker 9: So we need to get and I. 1012 00:50:24,400 --> 00:50:27,640 Speaker 17: Think we're moving this way. There's enough rebalancing that we're 1013 00:50:27,680 --> 00:50:30,840 Speaker 17: starting to see things get kind. 1014 00:50:30,600 --> 00:50:32,719 Speaker 9: Of back to quote unquote normal. 1015 00:50:33,080 --> 00:50:37,040 Speaker 17: And that, and I think the labor market has behaved 1016 00:50:37,480 --> 00:50:40,000 Speaker 17: much more in that way than inflation has been a 1017 00:50:40,080 --> 00:50:43,280 Speaker 17: lot harder for people to square the data. 1018 00:50:44,440 --> 00:50:46,279 Speaker 1: All right, Claudia, thank you so much for joining a 1019 00:50:46,320 --> 00:50:51,440 Speaker 1: Claudia Salm founder and independent economists, some consulting, former sector 1020 00:50:51,480 --> 00:50:54,000 Speaker 1: chief at the Federal Reserve Board, former senior economists at 1021 00:50:54,040 --> 00:50:56,799 Speaker 1: the Council of Economic Advisors at the White House, so 1022 00:50:57,360 --> 00:50:58,879 Speaker 1: lots of experience. 1023 00:50:59,200 --> 00:51:03,400 Speaker 11: You're listening to catch a live program Bloomberg Markets weekdays 1024 00:51:03,400 --> 00:51:06,640 Speaker 11: at ten am Eastern on Bloomberg Radio, the tune in app, 1025 00:51:06,680 --> 00:51:09,560 Speaker 11: Bloomberg dot Com, and the Bloomberg Business App. You can 1026 00:51:09,560 --> 00:51:12,799 Speaker 11: also listen live on Amazon Alexa from our flagship New 1027 00:51:12,880 --> 00:51:17,160 Speaker 11: York station. Just say Alexa play Bloomberg eleven thirty. 1028 00:51:18,280 --> 00:51:20,680 Speaker 3: It's Thursday. Let's get to our good friend, Barry Ridholts. 1029 00:51:20,680 --> 00:51:23,920 Speaker 1: Always well dressed, always carries himself very well. He's a 1030 00:51:23,960 --> 00:51:26,440 Speaker 1: host of Masters in Business on Bloomberg Radio. Has also 1031 00:51:26,480 --> 00:51:29,080 Speaker 1: got a day job Chairman and chief investment Officer Reholts 1032 00:51:29,120 --> 00:51:31,359 Speaker 1: Wealth Management. Barry, I have no idea what to talk 1033 00:51:31,360 --> 00:51:32,879 Speaker 1: about today, so I'm gonna throw out a word and 1034 00:51:32,920 --> 00:51:36,040 Speaker 1: you just kind of react inflation? What's going on out there? 1035 00:51:36,200 --> 00:51:37,960 Speaker 1: How should we think about it? 1036 00:51:37,960 --> 00:51:40,880 Speaker 18: It peaked over a year ago, it's coming down, and 1037 00:51:41,360 --> 00:51:45,320 Speaker 18: the areas that are not coming down. You could blame 1038 00:51:45,360 --> 00:51:48,720 Speaker 18: the FED for causing a shortage of homes for sale 1039 00:51:48,840 --> 00:51:54,680 Speaker 18: and higher apartment rentals. Other than that, everywhere we look 1040 00:51:54,840 --> 00:51:58,799 Speaker 18: we see either falling prices. Look no further than the 1041 00:51:58,920 --> 00:52:02,879 Speaker 18: used car wholesale market, and use car price market has 1042 00:52:02,920 --> 00:52:07,480 Speaker 18: come down to luxury goods. The index that Bloomberg tracks 1043 00:52:07,520 --> 00:52:11,080 Speaker 18: of luxury watches have peaked and fallen twenty twenty five percent. 1044 00:52:11,440 --> 00:52:14,960 Speaker 18: So wherever we look, inflation is rolling over. The three 1045 00:52:15,560 --> 00:52:19,279 Speaker 18: sticking points are labor and I don't see how higher 1046 00:52:19,320 --> 00:52:21,560 Speaker 18: rates are magically going to make a million more workers 1047 00:52:21,960 --> 00:52:27,000 Speaker 18: uppear in the United States, semiconductors same and housing. And 1048 00:52:27,080 --> 00:52:31,600 Speaker 18: housing is where the Fed is actually making the situation worse. Perversely, 1049 00:52:31,960 --> 00:52:35,839 Speaker 18: the FED is causing higher inflation, and the sooner they 1050 00:52:35,840 --> 00:52:36,520 Speaker 18: realize that. 1051 00:52:36,600 --> 00:52:38,279 Speaker 3: How are they doing that, we'll all be what do 1052 00:52:38,320 --> 00:52:39,560 Speaker 3: you mean by that? How are they doing that? 1053 00:52:39,600 --> 00:52:39,920 Speaker 4: All? Right? 1054 00:52:40,520 --> 00:52:44,279 Speaker 18: Two major ways. The first is owner's equivalent rent is 1055 00:52:44,320 --> 00:52:48,839 Speaker 18: the largest part of CPI. What is it? It's effectively what 1056 00:52:48,920 --> 00:52:51,360 Speaker 18: it costs to rent your house if you wanted to 1057 00:52:51,400 --> 00:52:54,799 Speaker 18: rent it out. And when mortgage breaks go higher and 1058 00:52:54,840 --> 00:52:58,319 Speaker 18: there's an insufficient supply of single family homes and home 1059 00:52:58,360 --> 00:53:01,080 Speaker 18: prices go up, guess what happens to rental units. They 1060 00:53:01,080 --> 00:53:05,320 Speaker 18: go up also, second, there would be many more homes 1061 00:53:05,640 --> 00:53:09,719 Speaker 18: for sale. Perhaps he's in the price pressure we've seen 1062 00:53:09,800 --> 00:53:13,680 Speaker 18: both in purchase and rentals. If people didn't feel locked 1063 00:53:13,680 --> 00:53:15,799 Speaker 18: in to Hey, I have a three and a half 1064 00:53:15,880 --> 00:53:18,520 Speaker 18: four percent mortgage. If I go out and get a 1065 00:53:18,560 --> 00:53:21,399 Speaker 18: new mortgage at six and a half seven percent, it's 1066 00:53:21,440 --> 00:53:23,840 Speaker 18: going to cost me a whole lot more for not 1067 00:53:23,920 --> 00:53:27,120 Speaker 18: a whole lot more house. We're better off staying where 1068 00:53:27,120 --> 00:53:30,279 Speaker 18: we are, says so many homeowners. And Hey, we'll add 1069 00:53:30,320 --> 00:53:33,440 Speaker 18: a pool, we'll redo the kitchen, we'll we'll just do 1070 00:53:33,520 --> 00:53:37,839 Speaker 18: some renovation, which, by the way, indirectly contributes to all 1071 00:53:37,880 --> 00:53:41,560 Speaker 18: these rising prices for contractors. So many people have been 1072 00:53:41,560 --> 00:53:43,879 Speaker 18: doing that over the past couple of years. They're making 1073 00:53:43,920 --> 00:53:47,920 Speaker 18: that more expensive. If you want lower inflation, not only 1074 00:53:48,000 --> 00:53:50,719 Speaker 18: should the FED stop raising rates, they need to think 1075 00:53:50,719 --> 00:53:55,360 Speaker 18: about sliding back a cut or two in order to 1076 00:53:55,400 --> 00:53:59,880 Speaker 18: stabilize the rental market, which they are directly disrupting. 1077 00:54:00,640 --> 00:54:03,239 Speaker 8: And your latest column on the terminal is about how 1078 00:54:03,239 --> 00:54:08,160 Speaker 8: more inflation expectations silliness that you're writing about. So you're 1079 00:54:08,200 --> 00:54:12,319 Speaker 8: thinking that we aren't going to see higher inflation. But 1080 00:54:12,400 --> 00:54:13,960 Speaker 8: given what you were just talking about when it comes 1081 00:54:14,000 --> 00:54:16,600 Speaker 8: to especially shelter in housing, how you have different components 1082 00:54:16,640 --> 00:54:20,160 Speaker 8: when you're looking at inflation metrics, especially with CPI right, 1083 00:54:20,160 --> 00:54:22,960 Speaker 8: because shelter is more like around a third of the waiting, 1084 00:54:23,120 --> 00:54:25,879 Speaker 8: very different than say when you look at PCE right, 1085 00:54:25,920 --> 00:54:27,560 Speaker 8: which is a very different waiting there. 1086 00:54:28,280 --> 00:54:32,359 Speaker 18: That's exactly right. So first, forget expectations. When we look 1087 00:54:32,400 --> 00:54:36,160 Speaker 18: at goods prices, not only have they stopped going up, 1088 00:54:36,280 --> 00:54:39,280 Speaker 18: many of them have come down in price, and quite 1089 00:54:39,280 --> 00:54:43,000 Speaker 18: a few have fallen to levels that were pre pandemic. 1090 00:54:43,040 --> 00:54:45,360 Speaker 18: When we look at lumber, when we look at a 1091 00:54:45,440 --> 00:54:48,720 Speaker 18: number of industrial metals, when we look you know, pretty 1092 00:54:48,760 --> 00:54:51,600 Speaker 18: much across the board, even energy, where are we sixty 1093 00:54:51,640 --> 00:54:55,080 Speaker 18: eight seventy two a barrel? That's what it was in 1094 00:54:55,200 --> 00:54:59,080 Speaker 18: two thousand and six. So I'm okay with oil being 1095 00:54:59,120 --> 00:55:02,240 Speaker 18: the same price for twenty years. Yeah, it fell, it spiked, 1096 00:55:02,239 --> 00:55:05,319 Speaker 18: it collapsed again, but it's hard to say that we're 1097 00:55:05,360 --> 00:55:08,799 Speaker 18: really paying way too much for energy prices, natural gas 1098 00:55:08,840 --> 00:55:12,840 Speaker 18: prices can continue to drift lower despite the Russian invasion 1099 00:55:12,840 --> 00:55:17,280 Speaker 18: of Ukraine. So when we look at what's actually happening, 1100 00:55:17,400 --> 00:55:20,839 Speaker 18: prices are either no longer going up, or going up 1101 00:55:20,920 --> 00:55:24,520 Speaker 18: much more slowly, or actually coming down. But the Fed 1102 00:55:24,760 --> 00:55:28,880 Speaker 18: likes to do this thing called inflation expectations. They survey 1103 00:55:28,960 --> 00:55:32,000 Speaker 18: a few thousand people and they say, where do you 1104 00:55:32,120 --> 00:55:35,760 Speaker 18: think inflation will be in five years? And there really 1105 00:55:35,840 --> 00:55:39,239 Speaker 18: is one honest answer to that, How the hell do 1106 00:55:39,320 --> 00:55:43,200 Speaker 18: I know anything else besides that is a lie. So 1107 00:55:43,239 --> 00:55:45,640 Speaker 18: when people say we think inflation is going to be 1108 00:55:45,680 --> 00:55:49,400 Speaker 18: appreciably higher in five years, all they're really revealing is 1109 00:55:50,000 --> 00:55:53,960 Speaker 18: their experience the past three to six months, and human 1110 00:55:54,040 --> 00:55:56,360 Speaker 18: psychology is that's on a leg. It took people a 1111 00:55:56,360 --> 00:56:00,360 Speaker 18: little while to recognize while why inflation it's order to 1112 00:56:00,400 --> 00:56:03,959 Speaker 18: tick up, which is why inflation expectations throughout the first 1113 00:56:04,000 --> 00:56:07,440 Speaker 18: half of twenty twenty one were like, yeah, we're inflation's fine, 1114 00:56:07,760 --> 00:56:11,200 Speaker 18: just as it was spiking upwards, and then last summer, 1115 00:56:11,280 --> 00:56:14,759 Speaker 18: when it had peaked and reversed, people maintained their same, 1116 00:56:14,920 --> 00:56:18,239 Speaker 18: much higher inflation expectations for a few years. Humans are 1117 00:56:18,360 --> 00:56:22,640 Speaker 18: terrible at predicting and random people telling you what CPI 1118 00:56:22,760 --> 00:56:26,080 Speaker 18: will be five years from now. I know there's been 1119 00:56:26,080 --> 00:56:29,359 Speaker 18: a lot of medical experiment with psilocybin and magic mushrooms. 1120 00:56:29,480 --> 00:56:32,040 Speaker 18: I didn't know it had actually reached the FMC research 1121 00:56:32,080 --> 00:56:36,080 Speaker 18: department because that's the only explanation for this sort of survey. 1122 00:56:36,760 --> 00:56:39,600 Speaker 1: All right, Barry, we're getting to the dog days of summer. 1123 00:56:39,640 --> 00:56:41,800 Speaker 1: What are you driving these days? 1124 00:56:42,600 --> 00:56:46,839 Speaker 18: So in the last year, I picked up it's funny 1125 00:56:46,880 --> 00:56:48,240 Speaker 18: to talk about this without matter around. 1126 00:56:48,320 --> 00:56:48,480 Speaker 13: I know. 1127 00:56:48,640 --> 00:56:51,400 Speaker 3: I picked up an old. 1128 00:56:52,239 --> 00:56:56,040 Speaker 18: Nine to eleven or nineteen eighty eight Cabrio that the 1129 00:56:56,080 --> 00:56:58,640 Speaker 18: previous owner had just beaten the hell out of They 1130 00:56:58,680 --> 00:57:01,680 Speaker 18: had been racing it, and they had modified it. So 1131 00:57:01,719 --> 00:57:04,919 Speaker 18: I was able to pick it up for really deep 1132 00:57:04,960 --> 00:57:07,399 Speaker 18: down inside, I'm a value investor, so anytime I get 1133 00:57:07,440 --> 00:57:11,840 Speaker 18: a chance to pick up a Cabrio cheap, I did that, 1134 00:57:12,080 --> 00:57:14,839 Speaker 18: and I've slowly been bringing it back to stock. And 1135 00:57:15,239 --> 00:57:17,840 Speaker 18: as we're working on the car, by dumb luck, it 1136 00:57:17,880 --> 00:57:22,200 Speaker 18: turns out that it's the M four ninety one Special Edition, 1137 00:57:22,320 --> 00:57:25,600 Speaker 18: which is the nine to eleven Turbo. It has everything 1138 00:57:25,640 --> 00:57:28,880 Speaker 18: the turbo has minus the turbo, so the whale tail, 1139 00:57:28,960 --> 00:57:33,720 Speaker 18: the fat fenders, the big tires, beefed up, suspension and breaks. 1140 00:57:33,720 --> 00:57:36,440 Speaker 18: It's just the turbos were known as widow makers. They 1141 00:57:36,440 --> 00:57:41,000 Speaker 18: were notoriously dangerous. So this is everything minus that, and 1142 00:57:41,160 --> 00:57:45,439 Speaker 18: I actually just brought it in. The last things I'm 1143 00:57:45,480 --> 00:57:50,120 Speaker 18: having done is the suspension return to normal. And that's 1144 00:57:50,200 --> 00:57:52,960 Speaker 18: kind of my fun summer driver. You could pick up. 1145 00:57:52,960 --> 00:57:56,240 Speaker 18: Everybody looks at these expensive cars if. 1146 00:57:55,560 --> 00:57:57,320 Speaker 3: You do get them at a decent price. 1147 00:57:57,360 --> 00:58:00,280 Speaker 1: All right, Barry, thanks so much, Barry Ridults there getting 1148 00:58:00,320 --> 00:58:01,000 Speaker 1: us the car talk. 1149 00:58:01,280 --> 00:58:04,400 Speaker 11: You're listening to the tape. Can's are live program Bloomberg 1150 00:58:04,440 --> 00:58:08,040 Speaker 11: Markets weekdays at ten am Eastern on Bloomberg Radio, the 1151 00:58:08,120 --> 00:58:10,200 Speaker 11: tune in app, Bloomberg dot Com. 1152 00:58:09,880 --> 00:58:11,320 Speaker 13: And the Bloomberg Business App. 1153 00:58:11,360 --> 00:58:14,200 Speaker 11: You can also listen live on Amazon Alexa from our 1154 00:58:14,200 --> 00:58:19,240 Speaker 11: flagship New York station. Just say Alexa play Bloomberg eleven thirty. 1155 00:58:19,400 --> 00:58:22,320 Speaker 1: All right, here is a story that I've been sending 1156 00:58:22,360 --> 00:58:26,240 Speaker 1: to all of my Harvard buddies. They're not happy for 1157 00:58:26,280 --> 00:58:29,120 Speaker 1: a variety of reasons, and I'm blaming our next guest, 1158 00:58:29,200 --> 00:58:32,960 Speaker 1: Janet Lauren. Janet Lauren, higher education financi reporter for Bloomberg News. 1159 00:58:33,120 --> 00:58:37,840 Speaker 1: Harvard targeted by Massachusetts Bill on legacy admissions. Janet, give 1160 00:58:37,920 --> 00:58:40,000 Speaker 1: us a back story here, what's going on. 1161 00:58:40,480 --> 00:58:41,520 Speaker 9: So this bill. 1162 00:58:41,880 --> 00:58:45,080 Speaker 10: Has been introduced, it's been there was a committee last week. 1163 00:58:45,400 --> 00:58:47,880 Speaker 10: But the question is is it going to have an impact? 1164 00:58:48,080 --> 00:58:51,880 Speaker 10: So the question is does the state the state would 1165 00:58:51,920 --> 00:58:55,160 Speaker 10: like to tax schools based on their endowment pur student, 1166 00:58:55,200 --> 00:58:56,880 Speaker 10: and we know that there's a school with a quite 1167 00:58:56,960 --> 00:59:01,520 Speaker 10: large endowment in Massachusetts. It's a big target. And this 1168 00:59:01,760 --> 00:59:07,800 Speaker 10: would give schools, community colleges money based on formula foreign 1169 00:59:07,840 --> 00:59:10,640 Speaker 10: Downman per student if they have legacy admissions. And that 1170 00:59:10,720 --> 00:59:13,040 Speaker 10: means if your parent went to school there, do you 1171 00:59:13,080 --> 00:59:15,880 Speaker 10: get a preference? And also early decision and why does 1172 00:59:15,920 --> 00:59:19,560 Speaker 10: early decision make a difference. Typically students who apply earlier 1173 00:59:19,800 --> 00:59:23,320 Speaker 10: tend to be wealthier. They're not necessarily waiting to compare 1174 00:59:23,360 --> 00:59:26,800 Speaker 10: financial aid packages when they get them in March. So 1175 00:59:26,840 --> 00:59:30,360 Speaker 10: the question is Harvard again is always a big target. 1176 00:59:30,640 --> 00:59:33,840 Speaker 10: There's been legislation in Massachusetts before to try to TAXI 1177 00:59:33,920 --> 00:59:36,000 Speaker 10: ing down and also at Yale to tech and they 1178 00:59:36,000 --> 00:59:40,520 Speaker 10: have not been successful. There are huge drivers of money 1179 00:59:40,800 --> 00:59:44,680 Speaker 10: universities and the Higher Ed Association in Massachusetts said, look, 1180 00:59:44,680 --> 00:59:48,800 Speaker 10: if this goes through our students, our citizens are unfairly 1181 00:59:49,120 --> 00:59:52,760 Speaker 10: targeted because these policies potentially could go away. 1182 00:59:52,920 --> 00:59:55,640 Speaker 8: What historically has been the catalyst to prevent those types 1183 00:59:55,680 --> 00:59:57,960 Speaker 8: of policies from actually going through. 1184 00:59:58,560 --> 01:00:02,800 Speaker 10: Well, you know, firmative action in the Supreme Court decision 1185 01:00:02,960 --> 01:00:07,000 Speaker 10: has really prompted this. If the Supreme Court says you 1186 01:00:07,040 --> 01:00:09,960 Speaker 10: can't give a preference for race, why should you have 1187 01:00:10,000 --> 01:00:13,680 Speaker 10: a preference for wealthier applications? Is what is what this 1188 01:00:13,840 --> 01:00:14,919 Speaker 10: is is bringing. 1189 01:00:14,560 --> 01:00:19,080 Speaker 1: Out interesting I noticed in your reporting that the Massachusetts 1190 01:00:19,120 --> 01:00:22,600 Speaker 1: bill or the second richest college in the state, Massachusetts 1191 01:00:22,640 --> 01:00:26,200 Speaker 1: Institute of Technology MIT, wouldn't pay anything because it doesn't 1192 01:00:26,280 --> 01:00:29,040 Speaker 1: use binding early decision policies or legacy preferences. 1193 01:00:29,080 --> 01:00:31,680 Speaker 10: Yeah, I didn't know that. Yes, that is true. MIT 1194 01:00:31,880 --> 01:00:35,400 Speaker 10: has long had a policy not having legacies. But you know, 1195 01:00:35,520 --> 01:00:38,040 Speaker 10: MIT was one of the first schools to actually bring 1196 01:00:38,120 --> 01:00:41,360 Speaker 10: back the SAT and MIT is a Yes, they're pretty 1197 01:00:41,400 --> 01:00:43,400 Speaker 10: different because you kind of have to do the work, 1198 01:00:45,280 --> 01:00:47,720 Speaker 10: so it doesn't really matter if your parent went there. 1199 01:00:47,960 --> 01:00:50,680 Speaker 10: They're looking for kids who can excel in math and 1200 01:00:50,720 --> 01:00:53,680 Speaker 10: science and that's not going to be just anybody. And 1201 01:00:53,920 --> 01:00:56,920 Speaker 10: they also many of the schools do not have binding 1202 01:00:56,960 --> 01:01:01,040 Speaker 10: early decision policies. Harvard Yale, Princeton stand at MIT. You 1203 01:01:01,080 --> 01:01:04,000 Speaker 10: know that was done more than a decade ago to 1204 01:01:04,040 --> 01:01:07,400 Speaker 10: take out that advantage. In fact, several years ago schools 1205 01:01:07,440 --> 01:01:10,600 Speaker 10: actually abolished early decision like Princeton and a few schools 1206 01:01:11,160 --> 01:01:13,840 Speaker 10: followed that, and they said that they were actually losing 1207 01:01:13,920 --> 01:01:16,640 Speaker 10: kids because they do like to shore up where they're 1208 01:01:16,680 --> 01:01:18,200 Speaker 10: going to school as early as possible. 1209 01:01:18,680 --> 01:01:21,280 Speaker 8: How have these poor community colleges been impacted in the 1210 01:01:21,320 --> 01:01:23,080 Speaker 8: past when these policies haven't gone through. 1211 01:01:23,880 --> 01:01:28,160 Speaker 10: Well, community colleges are really quite underfunded. You know, I 1212 01:01:28,240 --> 01:01:31,640 Speaker 10: was talking to one bunker Hill Community College in Massachusetts 1213 01:01:31,640 --> 01:01:34,960 Speaker 10: where they have more than ten thousand students, and you know, 1214 01:01:35,280 --> 01:01:38,760 Speaker 10: their goal is to get kids to graduate associate's degree, 1215 01:01:39,280 --> 01:01:42,080 Speaker 10: ideally transfer to a four year college. And you know, 1216 01:01:42,120 --> 01:01:45,240 Speaker 10: the worst scenario is when you have some college you've 1217 01:01:45,280 --> 01:01:48,080 Speaker 10: taken on some loans and then you don't finish and 1218 01:01:48,120 --> 01:01:50,480 Speaker 10: they are, you know, traditionally quite underfunded. 1219 01:01:50,920 --> 01:01:53,040 Speaker 3: It's interesting because we're just talking to John Talker about this. 1220 01:01:53,320 --> 01:01:55,360 Speaker 1: You know, going to a community college for a couple 1221 01:01:55,400 --> 01:01:57,360 Speaker 1: of years and you can transfer all your credits to 1222 01:01:57,360 --> 01:01:59,200 Speaker 1: stay in the state of New Jersey to Rutgers, which 1223 01:01:59,240 --> 01:02:03,440 Speaker 1: is a state universe of New Jersey Sunday. And then 1224 01:02:03,440 --> 01:02:05,520 Speaker 1: you can graduate with a Rutgers degree with only really 1225 01:02:05,560 --> 01:02:06,800 Speaker 1: two years of a Rutgers tuition. 1226 01:02:07,240 --> 01:02:07,520 Speaker 9: Yes. 1227 01:02:07,640 --> 01:02:11,240 Speaker 10: Well, and really the biggest issue when you're talking about 1228 01:02:11,320 --> 01:02:14,800 Speaker 10: student loans is when you have some college you and 1229 01:02:14,880 --> 01:02:16,960 Speaker 10: you don't have the degree, but you're carrying this loan 1230 01:02:17,000 --> 01:02:19,680 Speaker 10: burden for a long time. And certainly people think about 1231 01:02:19,680 --> 01:02:22,240 Speaker 10: community college is an alternative to having a couple of 1232 01:02:22,320 --> 01:02:24,720 Speaker 10: years of less expensive school, and as you said, transfering, 1233 01:02:24,720 --> 01:02:27,360 Speaker 10: you're still having the Rutgers degree. And plus you know, 1234 01:02:27,440 --> 01:02:29,080 Speaker 10: real experience. 1235 01:02:29,160 --> 01:02:32,240 Speaker 8: As far as putting into perspective just how challenging is 1236 01:02:32,280 --> 01:02:35,080 Speaker 8: it and how many students end up not actually being 1237 01:02:35,080 --> 01:02:37,960 Speaker 8: able to accept and go to a university like Harvard 1238 01:02:38,040 --> 01:02:40,840 Speaker 8: just because of the increasing cost, Like say, if you 1239 01:02:40,880 --> 01:02:43,240 Speaker 8: don't have that kind of connection there where you're part 1240 01:02:43,240 --> 01:02:45,240 Speaker 8: of a family and an alumni group like that. 1241 01:02:45,760 --> 01:02:48,160 Speaker 10: Well, Harvard for a long time has been trying to 1242 01:02:48,200 --> 01:02:51,880 Speaker 10: increase its financial aid and targeted to lower income students. 1243 01:02:52,000 --> 01:02:54,920 Speaker 10: So our story last week talked about the incoming class 1244 01:02:55,840 --> 01:02:59,200 Speaker 10: twenty five percent have incomes of eighty five thousand or less, 1245 01:03:00,040 --> 01:03:03,320 Speaker 10: and that's something that they've been particularly trying to target 1246 01:03:03,360 --> 01:03:04,240 Speaker 10: in the last several years. 1247 01:03:04,280 --> 01:03:07,920 Speaker 1: How important are the legacy programs to the universities. I mean, 1248 01:03:07,920 --> 01:03:12,960 Speaker 1: it's a broad discussion point, but it seems like they're 1249 01:03:13,040 --> 01:03:16,200 Speaker 1: quite important for just I don't know, support and all 1250 01:03:16,240 --> 01:03:16,760 Speaker 1: that type of thing. 1251 01:03:17,360 --> 01:03:20,080 Speaker 10: Well, the University of Pennsylvania used to say, look, if 1252 01:03:20,120 --> 01:03:22,720 Speaker 10: your kid wants to go here, you went here. You 1253 01:03:22,800 --> 01:03:25,439 Speaker 10: have to apply early, and that that's the only place 1254 01:03:25,480 --> 01:03:27,400 Speaker 10: where you're going to have an advantage in the early 1255 01:03:27,480 --> 01:03:31,600 Speaker 10: decision process. But colleges like to you know, preserve their communities, 1256 01:03:31,640 --> 01:03:34,320 Speaker 10: They like to encourage alumni to donate, and you know, 1257 01:03:34,360 --> 01:03:36,040 Speaker 10: you may we had a comment in one of the 1258 01:03:36,040 --> 01:03:40,800 Speaker 10: stories earlier this week that legacy programs do encourage people 1259 01:03:40,880 --> 01:03:43,040 Speaker 10: to donate. You know, you're giving to your college for 1260 01:03:43,080 --> 01:03:45,200 Speaker 10: thirty years with the hopes that your kid might get in. 1261 01:03:45,280 --> 01:03:48,880 Speaker 10: That's you know, that is some revenue that schools don't 1262 01:03:48,920 --> 01:03:52,200 Speaker 10: want to curtail. And certainly we're also talking about wealthy 1263 01:03:52,200 --> 01:03:53,080 Speaker 10: donors too. 1264 01:03:53,600 --> 01:03:57,040 Speaker 8: Right, And what's the likelihood that when we're talking about 1265 01:03:57,040 --> 01:03:59,560 Speaker 8: these admission policies that they would actually. 1266 01:03:59,280 --> 01:04:02,680 Speaker 10: Likely go through time around? I mean, that's that's a 1267 01:04:02,720 --> 01:04:05,200 Speaker 10: good question. You talk to the higher ed lobby, you 1268 01:04:05,240 --> 01:04:07,960 Speaker 10: talk to observers, and they say, well, it's not that 1269 01:04:07,960 --> 01:04:10,720 Speaker 10: they have zero chance. Maybe they're you know, but before 1270 01:04:10,760 --> 01:04:12,720 Speaker 10: they had zero chance. Maybe it sounds a little bit 1271 01:04:12,720 --> 01:04:14,920 Speaker 10: more interesting with the Supreme Court. But you have to 1272 01:04:15,000 --> 01:04:18,560 Speaker 10: understand that colleges in massachuse there's a lot of rich 1273 01:04:18,600 --> 01:04:22,680 Speaker 10: colleges in Massachusetts, and you cannot undermine the power of lobbyists. 1274 01:04:23,360 --> 01:04:27,760 Speaker 10: Colleges for a long time resisted the federal tax on endowments. 1275 01:04:27,800 --> 01:04:30,720 Speaker 10: It's something that a lot of Congressmen were interested because 1276 01:04:30,760 --> 01:04:33,920 Speaker 10: you know, Harvard has fifty billion dollars, Yelle has forty 1277 01:04:33,960 --> 01:04:37,920 Speaker 10: one billion dollars. You know, these are these are massive 1278 01:04:38,280 --> 01:04:42,440 Speaker 10: asset allocations and they're a rich target. But ultimately, you know, 1279 01:04:42,480 --> 01:04:44,640 Speaker 10: except for the federal endowment tax that went through in 1280 01:04:44,680 --> 01:04:48,200 Speaker 10: the Trump tax cuts of twenty seventeen, they've never been successful. 1281 01:04:49,000 --> 01:04:50,680 Speaker 1: Talk to those about another topic that I know you're 1282 01:04:50,720 --> 01:04:54,120 Speaker 1: familiar with, which is we're seeing here the rich get richer, 1283 01:04:54,560 --> 01:04:57,760 Speaker 1: whether it's endowment or students or and maybe you know, 1284 01:04:57,800 --> 01:04:59,440 Speaker 1: the poor get poor in terms of some of these 1285 01:04:59,480 --> 01:05:04,080 Speaker 1: underfunded schools, under endowed schools literally going out of business. 1286 01:05:04,560 --> 01:05:07,200 Speaker 1: How's the playing field these days? What's happening out there 1287 01:05:07,880 --> 01:05:09,960 Speaker 1: what a higher education folks think is going to be 1288 01:05:10,160 --> 01:05:10,600 Speaker 1: the trend. 1289 01:05:10,960 --> 01:05:13,720 Speaker 10: Well, there are a couple of trends. The first one 1290 01:05:13,760 --> 01:05:17,680 Speaker 10: is you had a pandemic money that certainly helped gave 1291 01:05:17,720 --> 01:05:21,760 Speaker 10: a huge lifeline to colleges for several years, and that's 1292 01:05:21,760 --> 01:05:24,800 Speaker 10: going away. You have what we've been writing about for 1293 01:05:24,800 --> 01:05:28,480 Speaker 10: a decade, demographic shifts. There are just fewer eighteen year 1294 01:05:28,520 --> 01:05:31,040 Speaker 10: olds out there, there's fewer kids to go to college, 1295 01:05:31,520 --> 01:05:35,000 Speaker 10: and kids tend to go two hundred miles away from 1296 01:05:35,040 --> 01:05:37,360 Speaker 10: their homes, and there's a lot of colleges and areas 1297 01:05:37,400 --> 01:05:39,880 Speaker 10: that are constrained, such as the Midwest and the Northeast. 1298 01:05:40,320 --> 01:05:43,600 Speaker 10: So you have all these issues converging at the same time. 1299 01:05:43,640 --> 01:05:48,320 Speaker 10: With the prices expensive, our people making different decisions not 1300 01:05:48,400 --> 01:05:51,160 Speaker 10: to go to college. So you know when the price 1301 01:05:51,240 --> 01:05:53,880 Speaker 10: tag could be seventy eighty thousand dollars. Now, keep in 1302 01:05:53,880 --> 01:05:57,320 Speaker 10: mind that's not actually what most families pay because most 1303 01:05:57,320 --> 01:06:01,080 Speaker 10: of the smaller liberal arts colleges they do they do 1304 01:06:01,160 --> 01:06:03,800 Speaker 10: offer aid, so the sticker price is really not what 1305 01:06:03,840 --> 01:06:06,800 Speaker 10: they're paying. But it's a good question. We're starting to see. 1306 01:06:07,600 --> 01:06:10,880 Speaker 10: There was a college in New Jersey that has now 1307 01:06:11,040 --> 01:06:15,400 Speaker 10: since merged with Montclair State. Bloommen was Bloomfield College, Right, 1308 01:06:15,600 --> 01:06:17,560 Speaker 10: So I think you're starting to see more of that, 1309 01:06:17,720 --> 01:06:22,120 Speaker 10: and you know, as you see schools looking for debt 1310 01:06:22,400 --> 01:06:24,720 Speaker 10: and their ratings are constrained. 1311 01:06:25,000 --> 01:06:27,400 Speaker 8: Yeah, right, especially when you think of just in the 1312 01:06:27,440 --> 01:06:30,240 Speaker 8: context of COVID as well, what you were mentioning the 1313 01:06:30,320 --> 01:06:33,240 Speaker 8: haves and the have nots and how that can exacerbate that. 1314 01:06:35,080 --> 01:06:35,240 Speaker 15: Well. 1315 01:06:35,280 --> 01:06:37,640 Speaker 8: Great, Well, thanks so much for taking the time to 1316 01:06:37,880 --> 01:06:41,280 Speaker 8: speak with us. Janet Lauren, higher education finance reporter at 1317 01:06:41,280 --> 01:06:44,040 Speaker 8: Bloomberg News, talking to us about obviously this was a 1318 01:06:44,040 --> 01:06:46,439 Speaker 8: big topic you were looking forward to speaking to Paul 1319 01:06:46,440 --> 01:06:49,560 Speaker 8: as far as how Harvard is targeting this Massachusetts bill 1320 01:06:49,640 --> 01:06:52,800 Speaker 8: on legacy admissions and what that could mean obviously for endowments, 1321 01:06:52,800 --> 01:06:55,080 Speaker 8: but then also on the poor side of things, we 1322 01:06:55,080 --> 01:06:56,560 Speaker 8: were talking about community colleges. 1323 01:06:56,840 --> 01:06:58,280 Speaker 1: Yeah, and I just I kind of feel like the 1324 01:06:58,640 --> 01:07:03,480 Speaker 1: well resourced families will find a way around whatever blockades 1325 01:07:03,600 --> 01:07:05,480 Speaker 1: or you know, kind of challenge to put up by colleges. 1326 01:07:05,520 --> 01:07:06,920 Speaker 3: And clearly some of these things. 1327 01:07:06,800 --> 01:07:09,720 Speaker 8: Right, they have historically done in the lobbying efforts. 1328 01:07:09,920 --> 01:07:12,720 Speaker 3: Yeah, but you know, we thought about the Supreme Court 1329 01:07:12,720 --> 01:07:16,400 Speaker 3: case coming down people somebody said wrote in being a 1330 01:07:16,680 --> 01:07:19,560 Speaker 3: really good essay writer is not going to become even 1331 01:07:19,560 --> 01:07:21,120 Speaker 3: more important because you want to say, you know, as 1332 01:07:21,120 --> 01:07:24,080 Speaker 3: a you know, as an underprivileged blah blah blah blah, 1333 01:07:24,120 --> 01:07:26,640 Speaker 3: I overcame these and that's kind of the way to But. 1334 01:07:26,600 --> 01:07:28,360 Speaker 8: Then you also have to kind of think about the 1335 01:07:28,400 --> 01:07:28,800 Speaker 8: haves and. 1336 01:07:28,720 --> 01:07:29,160 Speaker 10: The have notz. 1337 01:07:29,240 --> 01:07:31,720 Speaker 3: Yep, Absolutely, it's been a big, big issue. 1338 01:07:32,120 --> 01:07:34,640 Speaker 1: But again, the community college schools have been such a 1339 01:07:34,640 --> 01:07:36,439 Speaker 1: great route for so many people over so many years. 1340 01:07:36,440 --> 01:07:39,520 Speaker 3: You'd like to see that continue. 1341 01:07:40,800 --> 01:07:43,920 Speaker 2: Thanks for listening to the Bloomberg Markets podcast. You can 1342 01:07:43,920 --> 01:07:47,720 Speaker 2: subscribe and listen to interviews at Apple Podcasts or whatever 1343 01:07:47,800 --> 01:07:49,280 Speaker 2: podcast platform you prefer. 1344 01:07:49,680 --> 01:07:50,480 Speaker 3: I'm Matt Miller. 1345 01:07:50,760 --> 01:07:54,200 Speaker 2: I'm on Twitter at Matt Miller nineteen seventy three and 1346 01:07:54,280 --> 01:07:54,760 Speaker 2: on Fall. 1347 01:07:54,640 --> 01:07:57,520 Speaker 1: Sweeney I'm on Twitter at pt Sweeney. Before the podcast, 1348 01:07:57,560 --> 01:07:59,959 Speaker 1: you can always catch us worldwide at Bloomberg Radio.