1 00:00:05,800 --> 00:00:08,360 Speaker 1: Welcome to the Bloomberg P and L Podcast. I'm pim 2 00:00:08,400 --> 00:00:11,200 Speaker 1: Fox along with my co host Lisa A. Brahmowitz. Each 3 00:00:11,240 --> 00:00:14,440 Speaker 1: day we bring you the most important, noteworthy, and useful 4 00:00:14,480 --> 00:00:17,079 Speaker 1: interviews for you and your money, whether you're at the 5 00:00:17,120 --> 00:00:20,360 Speaker 1: grocery store or the trading floor. Find the Bloomberg P 6 00:00:20,520 --> 00:00:42,159 Speaker 1: M L Podcast on Apple Podcasts, SoundCloud and Bloomberg dot Com. 7 00:00:42,159 --> 00:00:44,000 Speaker 1: One of the issues having to do with trade and 8 00:00:44,200 --> 00:00:47,680 Speaker 1: the United States and China is technology. For example, Micron 9 00:00:47,680 --> 00:00:50,239 Speaker 1: Technology said a ban on the sale of some of 10 00:00:50,280 --> 00:00:55,680 Speaker 1: its products in China is unfair but won't hurt its earnings. 11 00:00:56,040 --> 00:00:58,680 Speaker 1: Here to tell us more about how chip makers are 12 00:00:58,760 --> 00:01:03,360 Speaker 1: trapped in the US China crossfire is our own Shira Oviday, 13 00:01:03,440 --> 00:01:07,000 Speaker 1: technology columnist for Bloomberg Opinion, and of course you can 14 00:01:07,040 --> 00:01:09,959 Speaker 1: follow Shira on Twitter at Shira over Day. All right, 15 00:01:10,000 --> 00:01:14,360 Speaker 1: Shara tell us about the chip companies and why this 16 00:01:14,400 --> 00:01:17,319 Speaker 1: has been a back and forth because it has to 17 00:01:17,400 --> 00:01:19,959 Speaker 1: do not just with tariffs, but then it has to 18 00:01:20,040 --> 00:01:24,560 Speaker 1: do with the imposition of bands about what kinds of 19 00:01:24,600 --> 00:01:27,840 Speaker 1: products can be sold between the two countries. Right, So 20 00:01:27,880 --> 00:01:31,720 Speaker 1: there's two issues at play here that involve computer chip makers. 21 00:01:31,800 --> 00:01:36,360 Speaker 1: US chip makers. So I think, much to the surprise 22 00:01:36,400 --> 00:01:40,319 Speaker 1: and chagrin of US chip makers, on the list of 23 00:01:40,319 --> 00:01:45,320 Speaker 1: the first wave of US tariffs of goods coming from 24 00:01:45,440 --> 00:01:52,880 Speaker 1: China are some products that impact US chip makers. So again, 25 00:01:53,440 --> 00:01:56,400 Speaker 1: they trade group for the chip company said, we're in 26 00:01:56,400 --> 00:01:59,720 Speaker 1: this weird position where some of the products that are 27 00:01:59,720 --> 00:02:03,160 Speaker 1: come from US chip companies that get sent to China 28 00:02:03,320 --> 00:02:07,040 Speaker 1: force sort of testing or some minor assembly, and then 29 00:02:07,320 --> 00:02:09,840 Speaker 1: sent back to the U S or other countries, they're 30 00:02:09,880 --> 00:02:13,000 Speaker 1: being subject to this tariff. Right, So you have US 31 00:02:13,080 --> 00:02:16,400 Speaker 1: tariffs that are trying to protect US companies that are 32 00:02:16,480 --> 00:02:20,280 Speaker 1: then being forced to absorb tariffs in some of these cases. Um, 33 00:02:20,320 --> 00:02:23,960 Speaker 1: which I think again was surprising to US chip companies. Now, 34 00:02:24,080 --> 00:02:27,080 Speaker 1: let's just take maybe just one example, because I know 35 00:02:27,160 --> 00:02:32,360 Speaker 1: that you know, not all chips are created equal, right, um, Micron, 36 00:02:32,600 --> 00:02:34,960 Speaker 1: which has been the sort of the post child for 37 00:02:35,000 --> 00:02:37,600 Speaker 1: this whole thing. It has to do that the issue 38 00:02:37,639 --> 00:02:42,560 Speaker 1: with Micron has to do with a Taiwanese chip maker 39 00:02:43,120 --> 00:02:49,280 Speaker 1: as well, United micro Electronics. They're based in Taiwan, correct, right, 40 00:02:49,320 --> 00:02:52,520 Speaker 1: So the the issue that Micron has is somewhat separate 41 00:02:52,560 --> 00:02:55,960 Speaker 1: from the tariff issues. So they have been sued Micron, 42 00:02:56,000 --> 00:02:58,840 Speaker 1: which is based in Boidi, Boise, Idaho, that makes these 43 00:02:58,919 --> 00:03:01,840 Speaker 1: kind of memory chips are essential and basically anything that 44 00:03:01,919 --> 00:03:04,880 Speaker 1: has a computer brain, so that includes smartphones, that includes 45 00:03:05,120 --> 00:03:09,280 Speaker 1: supercomputers and everything in between. So they've been sued for 46 00:03:09,400 --> 00:03:13,520 Speaker 1: patent infringement in China by both a Chinese company and 47 00:03:13,560 --> 00:03:17,400 Speaker 1: a Taiwanese company. And what Micron says is this lawsuit 48 00:03:17,639 --> 00:03:21,880 Speaker 1: which is basically accusing them of stealing um, you know, 49 00:03:22,000 --> 00:03:26,680 Speaker 1: proprietary technology from this Taiwanese and China for their graphics cards, 50 00:03:26,720 --> 00:03:30,280 Speaker 1: right computer graphics cards. So what Micron says is basically 51 00:03:30,320 --> 00:03:35,720 Speaker 1: this lawsuit is a ruse um too to cover up 52 00:03:35,840 --> 00:03:41,520 Speaker 1: for Chinese intellectual property theft of Micron's own technology. So 53 00:03:42,160 --> 00:03:44,600 Speaker 1: and Micron believes that this is politically motivated, that this 54 00:03:44,640 --> 00:03:47,640 Speaker 1: is part of China's kind of attempts to develop a 55 00:03:47,680 --> 00:03:51,600 Speaker 1: homegrown computer chip industry, and that part of that effort, 56 00:03:51,680 --> 00:03:55,440 Speaker 1: Micron says, is to kind of steal from American companies, 57 00:03:55,760 --> 00:03:58,600 Speaker 1: and they feel like Micron feels like they're caught in 58 00:03:58,640 --> 00:04:03,360 Speaker 1: this kind of US China battle over the future of technology. Okay, 59 00:04:03,360 --> 00:04:06,960 Speaker 1: so that's Microns case. Now let's go to another patient. 60 00:04:07,400 --> 00:04:10,240 Speaker 1: This has been to do with Qualcom. It wants to 61 00:04:10,320 --> 00:04:16,080 Speaker 1: acquire an XP semiconductor, but like in any situation, you 62 00:04:16,160 --> 00:04:19,279 Speaker 1: have to get government approval, right, Yeah, that's right. So 63 00:04:19,400 --> 00:04:21,800 Speaker 1: Qualcom again, like Micron, feels like it's kind of caught 64 00:04:21,800 --> 00:04:24,880 Speaker 1: in the crossfire between the U S and China trade 65 00:04:24,880 --> 00:04:27,840 Speaker 1: war that they have been trying to buy this Dutch 66 00:04:28,200 --> 00:04:32,159 Speaker 1: chip maker and XP for eighteen months I think, and 67 00:04:32,400 --> 00:04:36,599 Speaker 1: the last regulatory approval is the Chinese antitrust body, and 68 00:04:36,680 --> 00:04:40,960 Speaker 1: Qualcom has said with some justification that they believe that 69 00:04:41,080 --> 00:04:44,839 Speaker 1: regulatory approval in China is being held up because of 70 00:04:44,960 --> 00:04:51,680 Speaker 1: retaliation perhaps for the us UM essentially banning or imposing 71 00:04:51,720 --> 00:04:54,800 Speaker 1: a death sentence on z T, which is this um 72 00:04:54,880 --> 00:05:01,480 Speaker 1: Chinese telecom company that broke us UM us by selling 73 00:05:02,040 --> 00:05:04,760 Speaker 1: goods to Iran and other band countries and then lying 74 00:05:04,800 --> 00:05:07,360 Speaker 1: about it. It looks like z T s back in 75 00:05:07,400 --> 00:05:09,919 Speaker 1: the U S government's good graces after you know, a 76 00:05:09,920 --> 00:05:12,640 Speaker 1: big fine and some management changes. So we'll see if 77 00:05:12,680 --> 00:05:17,479 Speaker 1: that impacts the speed of regulatory approval for the Qualcom 78 00:05:17,560 --> 00:05:20,240 Speaker 1: n XP deal. Do you have a big whiteboard by 79 00:05:20,279 --> 00:05:23,719 Speaker 1: your desk in order to sort of diagram all of 80 00:05:23,760 --> 00:05:27,440 Speaker 1: the connections here because I'm gonna because I'm gonna go 81 00:05:27,520 --> 00:05:32,080 Speaker 1: even deeper here, which is that the chips that Micron 82 00:05:32,240 --> 00:05:38,920 Speaker 1: makes are very likely sold or shipped to China and 83 00:05:38,960 --> 00:05:45,680 Speaker 1: then put into products maybe let's say smartphones, right, that 84 00:05:45,760 --> 00:05:51,560 Speaker 1: are then sold to customers in the United States and Europe. Correct. Yeah, 85 00:05:51,600 --> 00:05:54,400 Speaker 1: it is very complicated. And I was asking folks in 86 00:05:54,440 --> 00:05:57,320 Speaker 1: the chip industry yesterday, is it possible that they could 87 00:05:57,360 --> 00:06:00,880 Speaker 1: be hit by tariffs on both side of this trade war? 88 00:06:01,200 --> 00:06:05,720 Speaker 1: Could they be subject to US tariffs on some products 89 00:06:05,760 --> 00:06:09,440 Speaker 1: and Chinese tariffs on some products? And the answer that 90 00:06:09,480 --> 00:06:12,520 Speaker 1: I got was, They're not really sure, but it's possible, 91 00:06:12,600 --> 00:06:16,320 Speaker 1: which would be mind blowing. And the companies that we've 92 00:06:16,360 --> 00:06:20,400 Speaker 1: just talked about, Micron, Qualcom, and XP, they're not the 93 00:06:20,440 --> 00:06:23,920 Speaker 1: only ones. We've got broad Calm, Texas Instruments, A m 94 00:06:24,040 --> 00:06:29,560 Speaker 1: D microchip technology, Intel, and video and analog devices. All 95 00:06:29,640 --> 00:06:35,680 Speaker 1: of these companies produce a decent amount of revenue in China. Yeah. 96 00:06:35,720 --> 00:06:39,040 Speaker 1: I mean, look, China is right now the world's biggest 97 00:06:39,440 --> 00:06:43,440 Speaker 1: buyer of computer chips. Um that if you look at 98 00:06:43,600 --> 00:06:47,920 Speaker 1: US exports by revenue, computer ships are number four, behind 99 00:06:48,000 --> 00:06:51,320 Speaker 1: things like airplanes and cars and oil. So you know, 100 00:06:51,360 --> 00:06:53,760 Speaker 1: this is a big U s export with a lot 101 00:06:53,760 --> 00:06:58,360 Speaker 1: of powerful and big US companies and computer ships are 102 00:06:58,360 --> 00:07:03,839 Speaker 1: also again the you know, the beating heart of China's 103 00:07:03,920 --> 00:07:09,040 Speaker 1: made made in China initiative to develop more homegrown technology. 104 00:07:09,320 --> 00:07:11,960 Speaker 1: So it's inevitable that these US chipmakers are getting kind 105 00:07:11,960 --> 00:07:15,200 Speaker 1: of caught in this power play between the US and China, 106 00:07:15,240 --> 00:07:19,000 Speaker 1: where China is both the their biggest customer in many 107 00:07:19,040 --> 00:07:23,120 Speaker 1: cases and also this kind of source of tension between 108 00:07:23,120 --> 00:07:26,360 Speaker 1: their home country, the United States, and their biggest market, China. 109 00:07:26,640 --> 00:07:30,680 Speaker 1: Is it worth noting that nobody forced these companies to 110 00:07:30,840 --> 00:07:33,600 Speaker 1: put their production Let's say, if they have production in 111 00:07:33,760 --> 00:07:38,400 Speaker 1: China in China, they went there because the scale and 112 00:07:38,440 --> 00:07:41,840 Speaker 1: the cost makes it possible to then buy a smartphone 113 00:07:42,680 --> 00:07:45,520 Speaker 1: that costs whatever it is but allows everybody to make 114 00:07:45,520 --> 00:07:47,320 Speaker 1: a decent profit on it. Yeah, and that's a that's 115 00:07:47,320 --> 00:07:50,120 Speaker 1: a totally fair point. That Look, the supply chain for 116 00:07:50,120 --> 00:07:53,640 Speaker 1: a lot of products, including computer chips, is very global. 117 00:07:54,080 --> 00:07:57,640 Speaker 1: That you do have these huge factories in China that 118 00:07:57,720 --> 00:08:01,240 Speaker 1: have developed expertise over the years in you know, certain 119 00:08:01,240 --> 00:08:05,160 Speaker 1: discrete elements of the computer chip manufacturing process. And the 120 00:08:05,160 --> 00:08:08,240 Speaker 1: same is true in Vietnam. And Malaysia and the United 121 00:08:08,240 --> 00:08:11,160 Speaker 1: States and other countries. You know, they have developed these 122 00:08:11,320 --> 00:08:17,200 Speaker 1: um specialties and certain aspects of smartphone manufacturing, testing and assembly. 123 00:08:17,680 --> 00:08:19,760 Speaker 1: And right now, I think what you're seeing in the 124 00:08:19,800 --> 00:08:22,640 Speaker 1: computer chip industry is some questioning about do we need 125 00:08:22,680 --> 00:08:26,040 Speaker 1: to adjust the supply chain as it has developed over 126 00:08:26,080 --> 00:08:32,400 Speaker 1: the last decades to kind of reflect this fear of 127 00:08:32,440 --> 00:08:35,920 Speaker 1: globalization being crimped in various corners of the world. So 128 00:08:36,000 --> 00:08:38,160 Speaker 1: it's it's really interesting right now, a little a little 129 00:08:38,160 --> 00:08:39,800 Speaker 1: bit of an irony when you think of all of 130 00:08:39,840 --> 00:08:45,280 Speaker 1: the sort of market driven decisions that are made and 131 00:08:45,600 --> 00:08:49,400 Speaker 1: yet they end up being political in terms. Everything is political. 132 00:08:49,480 --> 00:08:52,839 Speaker 1: Everything is political now. Thanks very much. Shira Oviday our 133 00:08:52,920 --> 00:08:55,839 Speaker 1: technology columns for Bloomberg Opinion. Check out all her stuff 134 00:08:55,880 --> 00:08:59,199 Speaker 1: on Bloomberg dot com, slash opinion, and follow her on 135 00:08:59,240 --> 00:09:27,280 Speaker 1: Twitter at your over Day. The unemployment rate moved to 136 00:09:27,400 --> 00:09:31,480 Speaker 1: hire in June from an eighteen year low. Steady hiring 137 00:09:31,640 --> 00:09:36,160 Speaker 1: and an increased number of job seekers continue to support 138 00:09:36,240 --> 00:09:40,199 Speaker 1: the labor market. US non farm payrolls rose a seasonally 139 00:09:40,240 --> 00:09:43,920 Speaker 1: adjusted two d and thirteen thousand in June. Here to 140 00:09:43,960 --> 00:09:46,839 Speaker 1: tell us more about the report and its implications is 141 00:09:46,920 --> 00:09:49,599 Speaker 1: Chris leu. He is a senior fellow at the University 142 00:09:49,679 --> 00:09:53,319 Speaker 1: of Virginia Miller Centers, a former Deputy Secretary of Labor 143 00:09:53,679 --> 00:09:56,840 Speaker 1: under President Barack Obama. He can be followed on Twitter 144 00:09:56,960 --> 00:10:01,360 Speaker 1: at Chris lout four All Chris lou forty four. I 145 00:10:01,360 --> 00:10:05,120 Speaker 1: want to focus first on wages and the increase that 146 00:10:05,200 --> 00:10:08,160 Speaker 1: we saw. I believe it was two point seven percent. 147 00:10:08,720 --> 00:10:12,320 Speaker 1: Do you believe that at that level we could get 148 00:10:12,360 --> 00:10:18,000 Speaker 1: to a four percent annual g d P rate? I don't, uh, 149 00:10:18,040 --> 00:10:21,440 Speaker 1: And I think that is really the concerning part of 150 00:10:21,520 --> 00:10:24,600 Speaker 1: an otherwise strong jobs numbers we have been in this 151 00:10:25,000 --> 00:10:26,920 Speaker 1: kind of two point five. I think we were up 152 00:10:26,920 --> 00:10:31,320 Speaker 1: to two point eight percent increased last month. Two point 153 00:10:31,360 --> 00:10:34,240 Speaker 1: seven is just not enough, and particularly when you consider 154 00:10:34,400 --> 00:10:37,440 Speaker 1: that inflation right now is running two point eight percent, 155 00:10:37,520 --> 00:10:40,880 Speaker 1: that effectively means that most workers aren't seeing any more 156 00:10:40,920 --> 00:10:43,760 Speaker 1: money than they did a year ago. And so we 157 00:10:43,920 --> 00:10:46,200 Speaker 1: we are in a very difficult situation right now where 158 00:10:46,200 --> 00:10:49,360 Speaker 1: the said um hasn't quite decided where they want to 159 00:10:49,400 --> 00:10:51,439 Speaker 1: go on rates, which will have an effect on wages. 160 00:10:51,760 --> 00:10:55,560 Speaker 1: We're starting to wonder whether this jobs market is different 161 00:10:55,559 --> 00:10:58,160 Speaker 1: than what we have always thought, which is if you're 162 00:10:58,160 --> 00:11:00,920 Speaker 1: down in this level of unemployment, you would expect ways 163 00:11:00,960 --> 00:11:03,760 Speaker 1: to be going up much much faster. So um, you know, 164 00:11:03,800 --> 00:11:05,560 Speaker 1: I think it's concerning, and I think many of us 165 00:11:05,559 --> 00:11:08,520 Speaker 1: are starting to wonder what this economy is fundamentally different 166 00:11:08,559 --> 00:11:10,880 Speaker 1: than what it used to be. Well, take that a 167 00:11:10,880 --> 00:11:13,160 Speaker 1: little bit further and tell us if you had to 168 00:11:13,200 --> 00:11:16,320 Speaker 1: explore that idea of a fundamentally different economy, what do 169 00:11:16,360 --> 00:11:19,040 Speaker 1: you mean by that. Well, Look, you would think when 170 00:11:19,040 --> 00:11:21,160 Speaker 1: you have normally a tightening labor market, a couple of 171 00:11:21,200 --> 00:11:23,480 Speaker 1: things happen. People come off the sidelines, which is what 172 00:11:23,520 --> 00:11:25,680 Speaker 1: happened this month, and it's one of the reasons why 173 00:11:25,720 --> 00:11:28,320 Speaker 1: the unemployment rates picked up from three point eight to 174 00:11:28,360 --> 00:11:30,560 Speaker 1: four percent. And that's a good thing. But you would 175 00:11:30,600 --> 00:11:33,800 Speaker 1: also think that in this tightening job market, employers would 176 00:11:33,800 --> 00:11:36,920 Speaker 1: have to pay more uh to entice workers to come there, 177 00:11:37,000 --> 00:11:39,520 Speaker 1: and it just doesn't happen. And you know, we know 178 00:11:39,600 --> 00:11:43,400 Speaker 1: that there are some solutions to this. Obviously, job training 179 00:11:43,440 --> 00:11:46,840 Speaker 1: is important in helping people advance the more skilled jobs. 180 00:11:47,600 --> 00:11:51,080 Speaker 1: High paying jobs like manufacturing and construction are another good answers, 181 00:11:51,120 --> 00:11:54,080 Speaker 1: and it's one of the reasons why infrastructure is always 182 00:11:54,120 --> 00:11:58,360 Speaker 1: a bipartisan policy idea raising the federal minimum wage and 183 00:11:58,400 --> 00:12:01,280 Speaker 1: state minimum wages would have an effec as well. But 184 00:12:01,480 --> 00:12:04,360 Speaker 1: we also may be trapped in a situation where we 185 00:12:04,480 --> 00:12:07,840 Speaker 1: now have a perpetual class of people who are doing 186 00:12:07,920 --> 00:12:12,280 Speaker 1: relatively unskilled labor at basically minimum wages who just can't 187 00:12:12,280 --> 00:12:14,840 Speaker 1: get out of that trap right now. And that's concerning 188 00:12:15,360 --> 00:12:18,480 Speaker 1: well to your point. In June, the share of American 189 00:12:18,520 --> 00:12:22,600 Speaker 1: adults working or looking for a job rose by two 190 00:12:22,640 --> 00:12:26,160 Speaker 1: tenths of a percentage point. That number now is sixty 191 00:12:26,200 --> 00:12:29,120 Speaker 1: two point nine percent, and it is up from that 192 00:12:29,280 --> 00:12:33,360 Speaker 1: low of sixty two point three that wasn't in But 193 00:12:33,960 --> 00:12:37,120 Speaker 1: it's like it's like the smallest share of adults participating 194 00:12:37,200 --> 00:12:40,400 Speaker 1: since the late nineteen seventies. This is not something that 195 00:12:40,559 --> 00:12:42,960 Speaker 1: is brand new, is it. No, that's exactly right. I mean, 196 00:12:43,040 --> 00:12:46,120 Speaker 1: throughout most of the Obama administration and now the Trump administration, 197 00:12:46,280 --> 00:12:50,400 Speaker 1: the figure you're sighting, the labor force participation has basically 198 00:12:50,440 --> 00:12:53,600 Speaker 1: been between about sixty two percent and sixty three percent, 199 00:12:53,960 --> 00:12:57,880 Speaker 1: and that's declined steadily since the mid nineteen seventies. Now, 200 00:12:57,920 --> 00:13:00,240 Speaker 1: in part it's because of changes in the Democrat six 201 00:13:00,320 --> 00:13:03,280 Speaker 1: of the workforce. We have a lot of people retiring earlier, 202 00:13:03,480 --> 00:13:05,839 Speaker 1: we have more people in school, so and that's a 203 00:13:05,880 --> 00:13:08,200 Speaker 1: good thing. We you know, we're looking at labor force 204 00:13:08,200 --> 00:13:11,080 Speaker 1: participation which goes all the way down to people aged sixteen, 205 00:13:11,160 --> 00:13:13,760 Speaker 1: so we don't necessarily want all of them in the workforce. 206 00:13:14,120 --> 00:13:16,600 Speaker 1: But it does suggest that we have far too many 207 00:13:16,640 --> 00:13:19,840 Speaker 1: people on the sidelines right now, either because they couldn't 208 00:13:19,880 --> 00:13:21,960 Speaker 1: find jobs, which was the case a couple of years ago, 209 00:13:22,480 --> 00:13:25,040 Speaker 1: or because the jobs weren't there, or because they're not 210 00:13:25,080 --> 00:13:28,120 Speaker 1: trained for the jobs. And that second part, if that's true, 211 00:13:28,280 --> 00:13:31,000 Speaker 1: is something that we really need to address as a country. Okay, 212 00:13:31,040 --> 00:13:35,120 Speaker 1: So would it be possible to address that more efficiently 213 00:13:35,320 --> 00:13:39,200 Speaker 1: if the Department of Labor and the Department of Education 214 00:13:39,280 --> 00:13:42,640 Speaker 1: work combined. Well, look, that's actually one of the theories 215 00:13:42,720 --> 00:13:46,000 Speaker 1: of the president's reorganization proposal that he came out with 216 00:13:46,040 --> 00:13:49,640 Speaker 1: a couple weeks ago. Um. Look, there there is certainly 217 00:13:49,640 --> 00:13:54,040 Speaker 1: a synergy between education and training UH in the in 218 00:13:54,440 --> 00:13:56,640 Speaker 1: the federal government, but there are also about nine different 219 00:13:56,640 --> 00:13:59,600 Speaker 1: federal agencies that deal with training UH, and the overlap 220 00:13:59,640 --> 00:14:03,000 Speaker 1: between the as agencies is actually relatively small. And having 221 00:14:03,040 --> 00:14:05,760 Speaker 1: been at one end of UM looking at that, we 222 00:14:05,960 --> 00:14:09,120 Speaker 1: function very Well, the bigger problem is we're not actually 223 00:14:09,160 --> 00:14:12,000 Speaker 1: investing enough money. The share of money that we put 224 00:14:12,000 --> 00:14:14,920 Speaker 1: in as the settled government into job training pales in 225 00:14:15,000 --> 00:14:17,800 Speaker 1: comparison to what Germany and other countries put in. We 226 00:14:17,920 --> 00:14:20,920 Speaker 1: don't really have a national job training strategy. It really 227 00:14:20,920 --> 00:14:24,760 Speaker 1: has done state by state, and we haven't invested sufficiently 228 00:14:24,840 --> 00:14:30,160 Speaker 1: improven job training methods like apprenticeships, which are wildly popular 229 00:14:30,200 --> 00:14:34,200 Speaker 1: and successful in Europe. Why haven't we been successful at that? 230 00:14:34,320 --> 00:14:37,120 Speaker 1: Is it just money? Well, it is money, but it's 231 00:14:37,120 --> 00:14:41,520 Speaker 1: also the way that employers operate. Employers tend to um 232 00:14:42,080 --> 00:14:45,200 Speaker 1: train their own workers, UH, and there's less incentive, frankly 233 00:14:45,320 --> 00:14:49,360 Speaker 1: to create a broader pipeline of workers. So what companies 234 00:14:49,400 --> 00:14:51,280 Speaker 1: will do in an industry is that they will fight 235 00:14:51,360 --> 00:14:54,840 Speaker 1: over a share of the pie instead of working collaboratively 236 00:14:54,920 --> 00:14:58,040 Speaker 1: to increase the pie, which is what UH companies do 237 00:14:58,120 --> 00:15:01,040 Speaker 1: in other countries. They invest in job training programs that 238 00:15:01,160 --> 00:15:04,880 Speaker 1: let's say, create more plumbers than the Chinas, understanding that 239 00:15:04,960 --> 00:15:06,800 Speaker 1: they may not be able to hire those people, but 240 00:15:06,880 --> 00:15:09,560 Speaker 1: that's good for the overall industry. So companies need to 241 00:15:09,560 --> 00:15:12,880 Speaker 1: start thinking about job training in a more collaborative way. 242 00:15:13,000 --> 00:15:16,520 Speaker 1: Do you believe that that may also be a result 243 00:15:16,720 --> 00:15:21,280 Speaker 1: of states, individual states competing with each other in order 244 00:15:21,360 --> 00:15:25,080 Speaker 1: to grab businesses because they think of it just as 245 00:15:25,120 --> 00:15:30,040 Speaker 1: a state's issue rather than of national issue. Well, that's 246 00:15:30,040 --> 00:15:32,840 Speaker 1: exactly that's a fantastic point. Far too often when states 247 00:15:32,840 --> 00:15:36,160 Speaker 1: are trying to lure companies there um, they just dropped 248 00:15:36,160 --> 00:15:38,680 Speaker 1: their tax rates. They provide tax and sentence to companies, 249 00:15:38,920 --> 00:15:41,560 Speaker 1: and far too often when you talk to companies, they'll say, look, 250 00:15:41,920 --> 00:15:44,480 Speaker 1: tax low, tax rates are fantastic, but it doesn't help 251 00:15:44,480 --> 00:15:47,000 Speaker 1: when we get there and we can't find the train 252 00:15:47,080 --> 00:15:49,840 Speaker 1: workers we need to fill our factories. And so far 253 00:15:49,920 --> 00:15:52,880 Speaker 1: more now come states are starting to understand if we 254 00:15:52,960 --> 00:15:56,240 Speaker 1: really want to attract companies, we need to have a 255 00:15:56,760 --> 00:15:59,280 Speaker 1: uh integrated job training program, and it's one of the 256 00:15:59,280 --> 00:16:02,120 Speaker 1: reasons why you continue to see more companies going to 257 00:16:02,200 --> 00:16:05,120 Speaker 1: more urban areas where they can find the train workers 258 00:16:05,200 --> 00:16:07,480 Speaker 1: for the work they need. Thank you very much. Chris 259 00:16:07,560 --> 00:16:11,520 Speaker 1: lou Senior Fellow, University of Virginia Miller Center. He's the 260 00:16:11,560 --> 00:16:15,200 Speaker 1: former Deputy Secretary of Labor under President Barack Obama. You 261 00:16:15,200 --> 00:16:43,680 Speaker 1: can follow him on Twitter at Chris lou Well. Turning 262 00:16:43,720 --> 00:16:45,960 Speaker 1: out of the shares of biogen they are up more 263 00:16:46,000 --> 00:16:49,280 Speaker 1: than fourteen and a half percent, as comes after Bargin 264 00:16:49,400 --> 00:16:53,360 Speaker 1: and its Japanese partner revealed results of a study of 265 00:16:53,400 --> 00:16:56,680 Speaker 1: a drug that is designed to raise hopes for the 266 00:16:56,720 --> 00:17:00,920 Speaker 1: treatment of Alzheimer's to battle this disease. Here to tell 267 00:17:00,960 --> 00:17:03,760 Speaker 1: us more about it is Drew Armstrong, or healthcare reporter 268 00:17:03,800 --> 00:17:06,840 Speaker 1: for a Bloomberg News and you can follow Drew on 269 00:17:07,080 --> 00:17:12,560 Speaker 1: Twitter at Armstrong Drew Okay Armstrong, Drew, what is the 270 00:17:12,640 --> 00:17:15,959 Speaker 1: breakthrough that we're seeing and learning about? Well, I wouldn't 271 00:17:15,960 --> 00:17:19,400 Speaker 1: describe what we saw today or I guess late last 272 00:17:19,480 --> 00:17:22,840 Speaker 1: night technically so much as a breakthrough, but a glimmer 273 00:17:22,880 --> 00:17:26,560 Speaker 1: of hope for a medical research field that has seen 274 00:17:27,320 --> 00:17:30,560 Speaker 1: a lot of glimmers of hope before followed by what 275 00:17:30,800 --> 00:17:35,920 Speaker 1: ultimately turned out to be disappointing failures. So late last 276 00:17:36,000 --> 00:17:39,040 Speaker 1: night we saw this data from biogen um n as 277 00:17:39,119 --> 00:17:42,679 Speaker 1: I basically saying, hey, we looked at this drug. It's 278 00:17:42,720 --> 00:17:46,919 Speaker 1: an experimental drug in mid stage testing, and it looks 279 00:17:46,920 --> 00:17:50,040 Speaker 1: like it helped people. There are a lot of caveats. 280 00:17:50,480 --> 00:17:53,439 Speaker 1: UM they're using a different measure of whether or not 281 00:17:53,480 --> 00:17:57,040 Speaker 1: it helped people than than other drug makers have before. 282 00:17:57,800 --> 00:18:01,919 Speaker 1: UM that the systems that appeared to give patients in 283 00:18:02,040 --> 00:18:04,800 Speaker 1: slowing the progression of Alzheimer's didn't show up when they 284 00:18:04,880 --> 00:18:07,800 Speaker 1: when they looked at this in at the twelve months 285 00:18:08,160 --> 00:18:10,600 Speaker 1: twelve months along in the study. This is just an 286 00:18:10,640 --> 00:18:12,920 Speaker 1: eighteen months, so they took a little bit longer than expected. 287 00:18:13,119 --> 00:18:15,199 Speaker 1: And they haven't announced yet. This is really important. One 288 00:18:15,200 --> 00:18:18,280 Speaker 1: of the things they're not saying so far that's really important. 289 00:18:18,359 --> 00:18:21,280 Speaker 1: They haven't announced that, Hey, this is great and we're 290 00:18:21,280 --> 00:18:23,399 Speaker 1: going to take this to the next stage. A lot 291 00:18:23,440 --> 00:18:25,120 Speaker 1: of times when you're a drug maker and you have 292 00:18:25,440 --> 00:18:29,399 Speaker 1: blockbuster good news, you say, great, phase two trial worked, 293 00:18:29,520 --> 00:18:32,159 Speaker 1: onto phase three, Let's get this in a bigger population 294 00:18:32,240 --> 00:18:34,040 Speaker 1: that we can use to get this drug approved by 295 00:18:34,040 --> 00:18:37,240 Speaker 1: the FDA. That is not in the statements that they 296 00:18:37,240 --> 00:18:39,399 Speaker 1: have given. And I think that should probably sound a 297 00:18:39,480 --> 00:18:43,240 Speaker 1: note of caution for people here. Okay, well put and 298 00:18:43,240 --> 00:18:49,359 Speaker 1: and really useful information through the target of this specific drug. 299 00:18:49,920 --> 00:18:55,000 Speaker 1: They're going after what are what is called beta amyloid. 300 00:18:55,680 --> 00:18:59,840 Speaker 1: And I know that there's another disease, there's hereditary amoloid 301 00:19:00,000 --> 00:19:02,359 Speaker 1: assists and so on, but this has to do with 302 00:19:02,400 --> 00:19:05,080 Speaker 1: the build up of a protein. Is that correct? Yeah, 303 00:19:05,160 --> 00:19:07,439 Speaker 1: that's exactly right, and and if I can kind of 304 00:19:07,480 --> 00:19:10,560 Speaker 1: explain the science here. One of the things that research 305 00:19:10,560 --> 00:19:12,840 Speaker 1: of notice researchers have noticed for a long time is 306 00:19:12,840 --> 00:19:15,840 Speaker 1: that if you take an image of an Alzheimer's patient's brain, 307 00:19:16,040 --> 00:19:18,080 Speaker 1: or if after they die you dissect it, you see 308 00:19:18,119 --> 00:19:21,439 Speaker 1: these little tangles of protein, essentially like plaque build up 309 00:19:21,440 --> 00:19:23,760 Speaker 1: in the brain that for a long time. It's it's 310 00:19:23,800 --> 00:19:26,080 Speaker 1: definitely known as a hallmark of the disease. You look 311 00:19:26,119 --> 00:19:29,000 Speaker 1: at people who have this disease and their brains all 312 00:19:29,040 --> 00:19:31,520 Speaker 1: have this. I think what hasn't been understood is is 313 00:19:31,560 --> 00:19:35,399 Speaker 1: it also the cause? You know, is this a is 314 00:19:35,440 --> 00:19:37,920 Speaker 1: this something that is causing the disease or just something 315 00:19:37,960 --> 00:19:40,920 Speaker 1: that happens to go along with it. And when if 316 00:19:41,000 --> 00:19:44,280 Speaker 1: it is, if this is what's damaging people's brains, when 317 00:19:44,280 --> 00:19:47,440 Speaker 1: does it start. Does it start building up silently when 318 00:19:47,440 --> 00:19:50,280 Speaker 1: we're forty or fifty years old, only kind of rearing 319 00:19:50,320 --> 00:19:54,280 Speaker 1: its head in actual Alzheimer's a decade or two decades later, 320 00:19:54,600 --> 00:19:57,640 Speaker 1: or is it something that you know, you are at 321 00:19:57,640 --> 00:19:59,560 Speaker 1: an elder age and you begin to show science and 322 00:19:59,600 --> 00:20:02,000 Speaker 1: that's when the damage begins. But the theory has been 323 00:20:02,080 --> 00:20:05,040 Speaker 1: that if you can do something to eliminate these plaques 324 00:20:05,480 --> 00:20:07,520 Speaker 1: or to even stop them from building up, that you 325 00:20:07,600 --> 00:20:13,439 Speaker 1: might somehow be able to slow Alzheimer's disease. That is 326 00:20:13,480 --> 00:20:15,840 Speaker 1: exactly so. And so if you can do that, you 327 00:20:16,119 --> 00:20:20,040 Speaker 1: this might be potentially a a drug that could you know, 328 00:20:20,080 --> 00:20:22,760 Speaker 1: actually alter the course of the disease. But so far, 329 00:20:23,400 --> 00:20:25,479 Speaker 1: even though a lot of drugs have shown success in 330 00:20:25,520 --> 00:20:28,800 Speaker 1: reducing the amount of plaque, you haven't actually seen the 331 00:20:28,840 --> 00:20:32,600 Speaker 1: kind of corresponding you know, decreases in the rate of 332 00:20:32,680 --> 00:20:36,360 Speaker 1: dementia or incognitive decline, those things that actually matter. I mean, 333 00:20:36,400 --> 00:20:38,280 Speaker 1: it's all, it's all well and good to treat a 334 00:20:38,400 --> 00:20:41,480 Speaker 1: biological thing, but if it doesn't help the patient, it 335 00:20:41,520 --> 00:20:44,360 Speaker 1: doesn't mean anything for these folks. So the question has 336 00:20:44,359 --> 00:20:47,639 Speaker 1: always been does this drug work on this thing, this plaque, 337 00:20:47,720 --> 00:20:50,720 Speaker 1: and does that also translate into a benefit. And so 338 00:20:50,880 --> 00:20:53,240 Speaker 1: there have been some signs in the studies that maybe 339 00:20:53,359 --> 00:20:55,879 Speaker 1: that's the case, But I think the big question is 340 00:20:55,880 --> 00:20:58,639 Speaker 1: going to be does it bear out in a wider study, 341 00:20:58,880 --> 00:21:01,760 Speaker 1: Does it really true, really alter the course of this disease, 342 00:21:01,880 --> 00:21:03,760 Speaker 1: or is there somewhere else the drug makers need to 343 00:21:03,800 --> 00:21:06,800 Speaker 1: be looking. Just quickly, a couple of the companies still 344 00:21:07,000 --> 00:21:11,280 Speaker 1: looking for drugs to combat Alzheimer's. Right. Yes, Roche is 345 00:21:11,320 --> 00:21:14,520 Speaker 1: in this space, um Eli, Lily and a number of 346 00:21:14,520 --> 00:21:17,159 Speaker 1: other folks have looked at some different approaches. You know, 347 00:21:17,320 --> 00:21:20,720 Speaker 1: drug makers look at this as probably the last great, 348 00:21:21,080 --> 00:21:24,359 Speaker 1: massive untreated disease in in the world. I mean, this 349 00:21:24,400 --> 00:21:28,360 Speaker 1: affects millions of people. It costs billions and billions of dollars. 350 00:21:28,520 --> 00:21:31,360 Speaker 1: It is a personal and tragedy for families when it's 351 00:21:31,359 --> 00:21:33,520 Speaker 1: struck by them. So this is a huge opportunity for 352 00:21:33,560 --> 00:21:35,159 Speaker 1: someone to try and do something about that has had 353 00:21:35,200 --> 00:21:38,520 Speaker 1: so many failures. Thank you very much. Drew Armstrong, healthcare 354 00:21:38,560 --> 00:21:42,440 Speaker 1: reporter from Bloomberg News. Follow him on Twitter at Armstrong 355 00:21:42,680 --> 00:21:47,000 Speaker 1: Drew for his continued insights and analysis and reporting about 356 00:21:47,000 --> 00:22:03,320 Speaker 1: the health care industry. Very interesting. My co host and 357 00:22:03,359 --> 00:22:08,240 Speaker 1: colleague Lisa Abramwitz on a well deserved holiday vacation. He's 358 00:22:08,240 --> 00:22:11,000 Speaker 1: not on vacation. He's Scott Wren. He's a senior global 359 00:22:11,040 --> 00:22:16,040 Speaker 1: equity strategist for Wells Fargo Investment Institute Assets Center Management 360 00:22:16,119 --> 00:22:20,159 Speaker 1: one point nine trillion dollars based in St. Louis. Scott 361 00:22:20,160 --> 00:22:23,720 Speaker 1: Rent always a pleasure, you know, looking at the performance 362 00:22:23,720 --> 00:22:27,240 Speaker 1: of the SMP five hundred. It's up three and three 363 00:22:27,240 --> 00:22:29,919 Speaker 1: and a quarter percent so far this year. Compare that 364 00:22:30,000 --> 00:22:35,320 Speaker 1: to the NASDAC up over eleven percent, the Dow basically unchanged. 365 00:22:35,960 --> 00:22:39,120 Speaker 1: What kind of market does this remind you of? Well, 366 00:22:39,200 --> 00:22:43,199 Speaker 1: you know, I tell you, Tim we Um, we have 367 00:22:43,240 --> 00:22:47,919 Speaker 1: been positive on the market, technology has done. We backed 368 00:22:47,920 --> 00:22:52,160 Speaker 1: off our overweight and technology last year, so we left 369 00:22:52,160 --> 00:22:54,200 Speaker 1: a little money on the table, no doubt about that. 370 00:22:54,800 --> 00:22:57,800 Speaker 1: UM small caps are doing a little bit better than 371 00:22:57,840 --> 00:23:00,240 Speaker 1: what we thought they would this year, and I think 372 00:23:00,240 --> 00:23:05,680 Speaker 1: that's almost solely due to the fears over a trade war. 373 00:23:06,240 --> 00:23:09,840 Speaker 1: But you know, really this this this market reminds me 374 00:23:10,359 --> 00:23:17,160 Speaker 1: of periods when it's it's fairly narrow and you're you're 375 00:23:17,440 --> 00:23:21,399 Speaker 1: toward the back end of certain cycles. But saying that 376 00:23:21,440 --> 00:23:26,879 Speaker 1: there are there are numerous other characteristics. One is overwhelming enthusiasm, 377 00:23:27,359 --> 00:23:31,240 Speaker 1: uh and chasing the market that I think are not um, 378 00:23:31,359 --> 00:23:33,760 Speaker 1: you know, they're not present right now, so it it 379 00:23:33,920 --> 00:23:37,280 Speaker 1: largely in narrowness, so to speak. It reminds me of 380 00:23:37,480 --> 00:23:40,520 Speaker 1: later stages of cycles. Well, when you talk about the 381 00:23:40,600 --> 00:23:43,280 Speaker 1: lack of enthusiasm, does that mean that you just can't 382 00:23:43,280 --> 00:23:46,720 Speaker 1: get people interested in stocks? Could that be a real 383 00:23:47,440 --> 00:23:51,560 Speaker 1: secular change because of the way that investments are made 384 00:23:51,680 --> 00:23:55,919 Speaker 1: using exchange traded funds. I think that that could be 385 00:23:56,080 --> 00:23:58,119 Speaker 1: part of it. But really, to be honest with you, 386 00:23:58,160 --> 00:24:00,520 Speaker 1: and if you look at at our science, and I 387 00:24:00,520 --> 00:24:04,800 Speaker 1: mean we cater to retail investors, um, most of them, 388 00:24:04,880 --> 00:24:08,320 Speaker 1: let's say you're north of sixty, Um, most of them, 389 00:24:08,359 --> 00:24:11,600 Speaker 1: at least on paper, they were burned in the tech bubble, 390 00:24:11,760 --> 00:24:15,320 Speaker 1: and then they were burned on when in the financial crisis. 391 00:24:15,359 --> 00:24:18,520 Speaker 1: And now they are older and they and they think 392 00:24:18,560 --> 00:24:21,040 Speaker 1: in terms of g I don't have the time to 393 00:24:21,200 --> 00:24:26,879 Speaker 1: make this money back there. They are concerned about, you know, 394 00:24:27,000 --> 00:24:31,560 Speaker 1: being down on their portfolio. They are concerned about outliving 395 00:24:31,600 --> 00:24:35,840 Speaker 1: their money. And so I think I think the secular change, really, 396 00:24:35,840 --> 00:24:37,959 Speaker 1: to be honest with you, is that with all this 397 00:24:38,040 --> 00:24:41,520 Speaker 1: money on the sidelines in past cycles, and I'm talking 398 00:24:42,119 --> 00:24:45,080 Speaker 1: you know, you look back over the last forty years, Um, 399 00:24:45,160 --> 00:24:47,639 Speaker 1: you know, if the market had moved this far over 400 00:24:47,680 --> 00:24:51,080 Speaker 1: this time by this time, there'd be a lot of chasing, 401 00:24:51,160 --> 00:24:55,040 Speaker 1: there'd be a lot of exuberance, um. Those types of things. 402 00:24:55,080 --> 00:24:57,480 Speaker 1: And so I think, really the secular change, at least 403 00:24:57,480 --> 00:25:02,720 Speaker 1: in my opinion, the stronger secular change is that you 404 00:25:02,800 --> 00:25:06,159 Speaker 1: have money on the sidelines that in no way, shape 405 00:25:06,240 --> 00:25:09,240 Speaker 1: or form is going to make it back into the market. 406 00:25:09,920 --> 00:25:12,119 Speaker 1: So if I go back all the way to January 407 00:25:12,119 --> 00:25:15,119 Speaker 1: of this year, January eight, for example, that seems like 408 00:25:15,160 --> 00:25:17,000 Speaker 1: a long time ago, doesn't it. Yeah, But I mean, 409 00:25:17,119 --> 00:25:19,240 Speaker 1: but where that's like ten points away from where we 410 00:25:19,280 --> 00:25:25,880 Speaker 1: are now on the SMP. That's where fifty nine. Yeah, 411 00:25:25,920 --> 00:25:29,000 Speaker 1: I just you know, and really for us, you know, 412 00:25:29,160 --> 00:25:32,760 Speaker 1: and you and I had talked, you know, in multiple times, 413 00:25:32,760 --> 00:25:34,080 Speaker 1: but you know, we thought we were going to see 414 00:25:34,080 --> 00:25:39,359 Speaker 1: a pullback, a reasonable pullback um the second half of seen. Uh. 415 00:25:39,359 --> 00:25:42,800 Speaker 1: It didn't come until the month of February, and it 416 00:25:42,920 --> 00:25:45,280 Speaker 1: happened very very fast. It happened for many of the 417 00:25:45,320 --> 00:25:48,359 Speaker 1: same reasons that we had been looking for. But you know, 418 00:25:48,440 --> 00:25:52,360 Speaker 1: really the market had not had, uh had a ten 419 00:25:52,359 --> 00:25:55,480 Speaker 1: percent pullback for for basically two years. And I think, 420 00:25:56,000 --> 00:25:59,400 Speaker 1: you know, we are over we you know, we were overdue. 421 00:25:59,800 --> 00:26:04,119 Speaker 1: And and I think the trigger um, which often happens 422 00:26:04,200 --> 00:26:08,879 Speaker 1: late in the cycle, is things about wage inflation, general inflation, 423 00:26:09,040 --> 00:26:12,840 Speaker 1: margin squeezes and what's the FED going to do about it? So, 424 00:26:13,119 --> 00:26:15,280 Speaker 1: you know, this cycle has been very different in a 425 00:26:15,320 --> 00:26:18,919 Speaker 1: lot of different ways. But as we move into what 426 00:26:19,119 --> 00:26:22,040 Speaker 1: is likely the later you know, third if you know, 427 00:26:22,320 --> 00:26:25,080 Speaker 1: third of the cycle or so. Uh, some of these 428 00:26:25,119 --> 00:26:28,639 Speaker 1: concerns that are causing the volatility outside of the trade 429 00:26:28,640 --> 00:26:32,720 Speaker 1: war um potential um are really things that you see 430 00:26:32,880 --> 00:26:36,040 Speaker 1: late in virtually every cycle. Okay, if that's the case, 431 00:26:36,080 --> 00:26:38,600 Speaker 1: where's the best place to put money late in the cycle. 432 00:26:39,080 --> 00:26:41,639 Speaker 1: I tell you, I think really, you know, industrials have 433 00:26:41,760 --> 00:26:44,840 Speaker 1: taken it on the chin here. As as as the 434 00:26:44,880 --> 00:26:48,879 Speaker 1: trade war rhetoric has has been pretty strong. I still 435 00:26:48,920 --> 00:26:53,439 Speaker 1: think that there's a relatively low probability that we're going 436 00:26:53,480 --> 00:26:55,840 Speaker 1: to have an all out trade war. Certainly the rhetorics 437 00:26:55,920 --> 00:26:58,720 Speaker 1: jumped up a little bit lately is probably the probability. 438 00:26:58,760 --> 00:27:00,960 Speaker 1: But you know, we want to take advantage of this 439 00:27:01,040 --> 00:27:04,320 Speaker 1: weakness and industrials. We've been overweighted industrials. We still want 440 00:27:04,320 --> 00:27:08,359 Speaker 1: to be overweight industrials. We want our clients on weakness 441 00:27:08,359 --> 00:27:12,920 Speaker 1: and industrials. Consumer discretionary financials. Clearly, if you look back 442 00:27:12,920 --> 00:27:15,640 Speaker 1: over the last three years, financials have done really well, 443 00:27:15,640 --> 00:27:19,720 Speaker 1: but obviously over the last six or twelve months they've stumbled. Um. 444 00:27:19,760 --> 00:27:22,560 Speaker 1: But you're looking forward, you know, we think that's still 445 00:27:22,600 --> 00:27:24,360 Speaker 1: going to be a good place to be. We think 446 00:27:24,359 --> 00:27:28,600 Speaker 1: it's too early to hide. So we've been underweight utilities, 447 00:27:28,640 --> 00:27:32,240 Speaker 1: we've been underweight staples. Now have those sectors done well 448 00:27:32,359 --> 00:27:37,040 Speaker 1: here since February second, early February when the markets started 449 00:27:37,040 --> 00:27:39,200 Speaker 1: to get the more chopping and we had to pull back, 450 00:27:39,240 --> 00:27:41,560 Speaker 1: Sure they have. But but I think when you look 451 00:27:41,600 --> 00:27:44,080 Speaker 1: ahead over the course of the next twelve months, you 452 00:27:44,080 --> 00:27:46,880 Speaker 1: want to be assertive. You want to lean towards those 453 00:27:46,880 --> 00:27:49,359 Speaker 1: sectors that are going to continue to benefit from a 454 00:27:49,400 --> 00:27:53,520 Speaker 1: continuation of this economy. You do not want to hide. Someday, 455 00:27:53,680 --> 00:27:55,439 Speaker 1: you know, somewhere out there on the horizon will be 456 00:27:55,480 --> 00:27:57,560 Speaker 1: time to hide. But I don't think it's now. When 457 00:27:57,560 --> 00:27:59,600 Speaker 1: you mentioned industrials, you just want to make sure we're 458 00:27:59,600 --> 00:28:01,679 Speaker 1: talking to about the companies such a and I'm not 459 00:28:01,720 --> 00:28:04,880 Speaker 1: saying that you're recommending them, just saying companies such as 460 00:28:05,440 --> 00:28:09,239 Speaker 1: Honeywell International shares down four and a half percent so 461 00:28:09,320 --> 00:28:13,639 Speaker 1: far this year. Shares of Eaton Corp. Also uh lower? 462 00:28:13,920 --> 00:28:16,600 Speaker 1: Uh this, you know my four percent this year. Those 463 00:28:16,600 --> 00:28:19,800 Speaker 1: are the kinds of companies, Yeah, machinery and you know, 464 00:28:19,880 --> 00:28:22,160 Speaker 1: those those kinds of things. I mean, you know, if 465 00:28:22,160 --> 00:28:24,720 Speaker 1: you look in a lot of these. Uh, if you 466 00:28:24,720 --> 00:28:26,920 Speaker 1: look at a lot of these these companies, I mean, 467 00:28:26,960 --> 00:28:30,400 Speaker 1: they are backlogged well into and now if you talk 468 00:28:30,440 --> 00:28:35,040 Speaker 1: to any industrials analysts, they will tell you that the 469 00:28:35,119 --> 00:28:39,040 Speaker 1: managements of the companies that they cover, they are nervous 470 00:28:39,080 --> 00:28:44,360 Speaker 1: about the potential for trade war, potential for acceleration in 471 00:28:44,440 --> 00:28:48,560 Speaker 1: this trade rhetoric which would negatively affect their businesses, you know. 472 00:28:48,640 --> 00:28:52,440 Speaker 1: But the fact is um through this year and into 473 00:28:53,760 --> 00:28:56,640 Speaker 1: um you know, they are booked up and and and 474 00:28:56,800 --> 00:28:59,240 Speaker 1: most industrial analysts, the guys who are in the in 475 00:28:59,280 --> 00:29:02,800 Speaker 1: the trenches covering the individual companies, they'll tell you that 476 00:29:02,920 --> 00:29:07,120 Speaker 1: you will not really be able to tell if the 477 00:29:07,200 --> 00:29:12,080 Speaker 1: tax code change was really helpful in terms of capex 478 00:29:12,440 --> 00:29:16,000 Speaker 1: until nineteen at least in the industrial sector. But you know, 479 00:29:16,080 --> 00:29:19,240 Speaker 1: certainly these capex numbers we saw in the fourth quarter 480 00:29:19,320 --> 00:29:22,080 Speaker 1: before the thing even kicked in, we're good. First quarter 481 00:29:22,200 --> 00:29:26,200 Speaker 1: was pretty darn good. And I suspect, based on these 482 00:29:26,240 --> 00:29:28,760 Speaker 1: I S M surveys and some other things that we're doing, 483 00:29:29,160 --> 00:29:31,520 Speaker 1: that that we're going to see some decent capex through 484 00:29:31,760 --> 00:29:33,640 Speaker 1: the balance of the year as well. I want to 485 00:29:33,640 --> 00:29:36,840 Speaker 1: thank you very much for joining me. Scott Wren senior 486 00:29:36,960 --> 00:29:41,040 Speaker 1: Global equity strategist for Wells Fargo Investment Institute. He's in 487 00:29:41,080 --> 00:29:44,960 Speaker 1: saying louis helping to manage one point nine trillion dollars 488 00:29:45,000 --> 00:29:51,800 Speaker 1: of customer assets. Thanks for listening to the Bloomberg P 489 00:29:51,920 --> 00:29:54,920 Speaker 1: and L podcast. You can subscribe and listen to interviews 490 00:29:54,920 --> 00:29:58,960 Speaker 1: at Apple Podcasts, SoundCloud, or whatever podcast platform you prefer. 491 00:29:59,400 --> 00:30:02,960 Speaker 1: I'm pimp box, I'm on Twitter at pim Fox. I'm 492 00:30:03,000 --> 00:30:06,280 Speaker 1: on Twitter at Lisa Abramo wits one. Before the podcast, 493 00:30:06,320 --> 00:30:08,920 Speaker 1: you can always catch us worldwide on Bloomberg Radio