1 00:00:00,080 --> 00:00:13,040 Speaker 1: Yea. Welcome to the Bloomberg Surveillance Podcast. I'm Tom Keane. 2 00:00:13,480 --> 00:00:17,560 Speaker 1: Daily we bring you insight from the best in economics, finance, investment, 3 00:00:18,000 --> 00:00:23,480 Speaker 1: and international relations. Find Bloomberg Surveillance on Apple Podcasts, SoundCloud, 4 00:00:23,600 --> 00:00:33,199 Speaker 1: Bloomberg dot Com, and of course on the Bloomberg I 5 00:00:33,200 --> 00:00:35,240 Speaker 1: want to go to John Faroll with Nora Rabini because 6 00:00:35,280 --> 00:00:37,599 Speaker 1: John's got a great insight here to get their bitcoin 7 00:00:38,200 --> 00:00:40,600 Speaker 1: discussion started. I did want to mention that the President 8 00:00:40,680 --> 00:00:43,320 Speaker 1: is tweeted twice this morning, forty five minutes ago and 9 00:00:43,360 --> 00:00:45,519 Speaker 1: thirty minutes ago. In one of them, he makes a 10 00:00:45,560 --> 00:00:49,640 Speaker 1: clear distinction between the leadership and investigators of the Federal 11 00:00:49,680 --> 00:00:54,120 Speaker 1: Bureau of Investigation and the Justice Department versus later on 12 00:00:54,280 --> 00:00:58,040 Speaker 1: in a lengthy tweet, rank and file are great people. 13 00:00:58,160 --> 00:00:59,840 Speaker 1: So that seems to be the tone of the President 14 00:01:00,000 --> 00:01:02,440 Speaker 1: this morning. And you've got a great insight with Dr 15 00:01:02,560 --> 00:01:04,400 Speaker 1: Roubini and bitcoin. Yeah. I think it's gonna be a 16 00:01:04,400 --> 00:01:06,720 Speaker 1: lot of conversation today about the price action. Of course 17 00:01:06,720 --> 00:01:08,559 Speaker 1: there should be be down thirteen and a half percent 18 00:01:08,640 --> 00:01:11,160 Speaker 1: to seven eight sixty, But I think the conversation on 19 00:01:11,200 --> 00:01:13,920 Speaker 1: Wall Street is whether we institutionalize this stuff too quickly 20 00:01:14,160 --> 00:01:17,440 Speaker 1: put on the exchanges too quickly without enough thought. Professor, 21 00:01:17,560 --> 00:01:20,199 Speaker 1: do you think that is the case. It is. First 22 00:01:20,200 --> 00:01:22,640 Speaker 1: of all, for a long time the regulators were asleep 23 00:01:22,640 --> 00:01:25,280 Speaker 1: as they will where all this come was occurring. I mean, 24 00:01:25,280 --> 00:01:27,360 Speaker 1: think about the I c o s. These are just 25 00:01:27,600 --> 00:01:31,000 Speaker 1: things that are created to scare it completely security these laws. 26 00:01:31,040 --> 00:01:33,039 Speaker 1: You know, you invest in a company, you get debt 27 00:01:33,160 --> 00:01:35,120 Speaker 1: or equity. In this case is what you get a 28 00:01:35,200 --> 00:01:38,360 Speaker 1: plastic token that gives the rights or nothing. This should 29 00:01:38,360 --> 00:01:41,200 Speaker 1: be illegal, but thousands of I c you have occurred. 30 00:01:41,520 --> 00:01:43,560 Speaker 1: So for many many months they were asleep at they 31 00:01:43,560 --> 00:01:49,480 Speaker 1: will and then even allowed these derivatives futures being created. Luckily, 32 00:01:49,560 --> 00:01:52,400 Speaker 1: now the God religion they have said that these e 33 00:01:52,520 --> 00:01:54,880 Speaker 1: T F that they wanted to create, that we're essentially 34 00:01:54,880 --> 00:01:57,880 Speaker 1: going investing into liquid creato currency would not be allowed. 35 00:01:58,120 --> 00:02:00,200 Speaker 1: But there's been too little, too late, so fur they 36 00:02:00,200 --> 00:02:04,440 Speaker 1: put massive marching requirements on them to try futures north oft. 37 00:02:04,960 --> 00:02:06,840 Speaker 1: But given the price action of the last month, you 38 00:02:06,880 --> 00:02:09,480 Speaker 1: wonder whether north of forty percent was enough, Professor, it 39 00:02:09,600 --> 00:02:12,480 Speaker 1: was not enough. You know Bitcoin has fallen value by 40 00:02:12,520 --> 00:02:16,320 Speaker 1: sixty percent. You know in six weeks there is volatility 41 00:02:16,320 --> 00:02:19,799 Speaker 1: of twenty percent per day has fallen thirty percent and 42 00:02:19,960 --> 00:02:24,480 Speaker 1: last month percent overnight. You need much higher Marjory climates. 43 00:02:24,480 --> 00:02:27,960 Speaker 1: I mean they're typical situation which a bunch of insiders 44 00:02:28,400 --> 00:02:31,919 Speaker 1: pump it higher and higher. It was outright path manipulation, 45 00:02:32,200 --> 00:02:35,760 Speaker 1: and every sucker was a retaining investor bought the peak 46 00:02:35,880 --> 00:02:39,560 Speaker 1: between Thanksgiving and Christmas and New Year at twenty thousand 47 00:02:39,840 --> 00:02:42,400 Speaker 1: and they lost their shirt. This was really a scandal. 48 00:02:42,520 --> 00:02:46,560 Speaker 1: This is outright criminal manipulation. So it's strong evidence that 49 00:02:46,639 --> 00:02:48,960 Speaker 1: the price of bitcoin has been manipulated. So what is 50 00:02:49,000 --> 00:02:51,359 Speaker 1: that evidence that the price of bitcoin has been manipulates it? 51 00:02:51,680 --> 00:02:54,320 Speaker 1: What are you looking at specifically, Well, there are several things. 52 00:02:54,320 --> 00:02:57,360 Speaker 1: There have been some econometric studies that suggests that these 53 00:02:57,400 --> 00:03:01,560 Speaker 1: alternative currency titter the is a fiat currency is printing 54 00:03:01,919 --> 00:03:06,160 Speaker 1: two billion dollars of money out of nobere fiat is 55 00:03:06,200 --> 00:03:10,000 Speaker 1: not mind teter USTD has been used to prop up 56 00:03:10,320 --> 00:03:12,840 Speaker 1: the value of bitcoin in the last few months. These 57 00:03:12,840 --> 00:03:17,320 Speaker 1: econometric studies suggested without the manipulation, the price of bitcoin 58 00:03:17,400 --> 00:03:21,240 Speaker 1: will be done up to There's another study published on 59 00:03:21,280 --> 00:03:24,280 Speaker 1: the Journal of Monetary Economic that suggests that when the 60 00:03:24,320 --> 00:03:29,200 Speaker 1: price went one from one fifty there was outright again pumping, 61 00:03:29,280 --> 00:03:34,160 Speaker 1: damp and manipulation. There's clear evidence of manipulation. What's so 62 00:03:34,240 --> 00:03:37,920 Speaker 1: important here is is sacred is the bid and the 63 00:03:38,160 --> 00:03:42,480 Speaker 1: asked and whether it's Drew Foulinburg or Elvin Roth, the 64 00:03:42,520 --> 00:03:47,200 Speaker 1: Nobel laureate. In every advanced economics textbook, there's a thing 65 00:03:47,280 --> 00:03:51,800 Speaker 1: called auction theory. Dr Rubini. I'm not editorializing, I'm simply 66 00:03:51,840 --> 00:03:57,000 Speaker 1: staying in fact, I don't see transparent bid esque processes 67 00:03:57,720 --> 00:04:02,320 Speaker 1: in bitcoin. Do you know there is no transparency of 68 00:04:02,400 --> 00:04:06,600 Speaker 1: any sort that lots of exchanges that are Officer Financial Center, 69 00:04:07,120 --> 00:04:09,320 Speaker 1: many of them have not been audited. There is this 70 00:04:09,480 --> 00:04:13,400 Speaker 1: bit Phinex that ons Teeter Theater has been creating money 71 00:04:13,480 --> 00:04:16,400 Speaker 1: literally out of what you say, what is this? Is 72 00:04:16,440 --> 00:04:20,960 Speaker 1: this Kurkish teacher? No, No, it's a currency Teather Teter 73 00:04:21,080 --> 00:04:30,360 Speaker 1: each other. It's not. Honestly, is the biggest come ever 74 00:04:30,640 --> 00:04:34,040 Speaker 1: because they claim that they have about two billion dollars 75 00:04:34,040 --> 00:04:37,840 Speaker 1: of money backing. They want one fixed exchanges between the 76 00:04:38,680 --> 00:04:42,040 Speaker 1: theater and the US dollar. There is absolutely no events 77 00:04:42,040 --> 00:04:46,200 Speaker 1: of it. Bit Phoinex that is this criminal exchange is 78 00:04:46,240 --> 00:04:50,280 Speaker 1: controlling this other company, theater that is creating money out 79 00:04:50,320 --> 00:04:53,800 Speaker 1: of nowhere pretending that is backed by real dollars. They 80 00:04:53,800 --> 00:04:56,440 Speaker 1: cannot convert them back into real dollars, and they've been 81 00:04:56,560 --> 00:04:58,800 Speaker 1: using it for the last few months to push up 82 00:04:58,839 --> 00:05:02,120 Speaker 1: the price a bit point. It's really a criminal activity. 83 00:05:02,240 --> 00:05:05,400 Speaker 1: If your principer's pronounced teether, that's okay. I'm trying to 84 00:05:05,480 --> 00:05:09,480 Speaker 1: learn to tell you about Professor honestly. Honestly, Tom Keine 85 00:05:09,520 --> 00:05:12,000 Speaker 1: leaves us foreign a such a hard time. L I 86 00:05:13,560 --> 00:05:21,520 Speaker 1: G l I Lee Lee can wait do this and 87 00:05:21,560 --> 00:05:26,440 Speaker 1: not hasn't changed like Eric Kissinger is German accent even 88 00:05:26,440 --> 00:05:30,359 Speaker 1: after and we love it. I actually changed the accent 89 00:05:30,440 --> 00:05:32,160 Speaker 1: and I can't give it my accent. I don't want 90 00:05:32,160 --> 00:05:33,960 Speaker 1: to lose it. No, Rabeni is al We've read to 91 00:05:34,000 --> 00:05:37,240 Speaker 1: catch up with you, Rebilli Macro Associates chairman and m 92 00:05:37,440 --> 00:05:39,920 Speaker 1: y u Stern School of Business. Professor. I can tell 93 00:05:39,960 --> 00:05:42,520 Speaker 1: you in the commercial break, Professor Rabini is going to 94 00:05:42,600 --> 00:06:00,159 Speaker 1: give Mr Tom Keane a very very hard time with 95 00:06:00,279 --> 00:06:03,640 Speaker 1: your academic Seriously, Alan Krueger, As we look to this 96 00:06:03,880 --> 00:06:07,960 Speaker 1: job's day, the number one conundrum I see it's where 97 00:06:08,000 --> 00:06:12,800 Speaker 1: are traditional jobs for a traditional America. It's not technologically 98 00:06:12,880 --> 00:06:17,840 Speaker 1: savvy that doesn't have elite service sector multi language abilities 99 00:06:17,880 --> 00:06:20,599 Speaker 1: like young John Faroh, what do we do with a 100 00:06:20,720 --> 00:06:24,440 Speaker 1: part of America that just wants an old line job? 101 00:06:25,560 --> 00:06:28,080 Speaker 1: You know, I think we should take an historical perspective. 102 00:06:28,520 --> 00:06:32,360 Speaker 1: The manufacturing jobs were not great jobs before they were union, 103 00:06:32,400 --> 00:06:36,640 Speaker 1: but they kept a certain kind of American employed. They did, 104 00:06:36,960 --> 00:06:39,760 Speaker 1: They certainly did. And the service sector jobs could do 105 00:06:39,800 --> 00:06:43,880 Speaker 1: that too, if we work to make them higher paying jobs. 106 00:06:43,960 --> 00:06:47,800 Speaker 1: If we work to make them jobs that uh, where 107 00:06:47,839 --> 00:06:50,880 Speaker 1: where workers had more representation, where workers could bargain for 108 00:06:50,960 --> 00:06:55,240 Speaker 1: higher wages. Uh. It didn't just happen automatically in manufacturing. 109 00:06:55,240 --> 00:06:59,039 Speaker 1: It happened because the workers organized, because public policy supported it. 110 00:06:59,400 --> 00:07:01,800 Speaker 1: And yet we have the minimum wage today stuck where 111 00:07:01,800 --> 00:07:04,760 Speaker 1: it was in two thousand nine. So I think it's 112 00:07:04,760 --> 00:07:07,440 Speaker 1: a matter of choices, and and and and John Pharaoh. 113 00:07:07,560 --> 00:07:10,080 Speaker 1: This was is Alan Krueger mentioned earlier. This was the 114 00:07:10,160 --> 00:07:15,080 Speaker 1: lead idea of Angus Deaton and Davos, the laureate from Princeton, 115 00:07:15,200 --> 00:07:19,440 Speaker 1: that we just don't know except the available evidence, which 116 00:07:19,480 --> 00:07:22,560 Speaker 1: is the de unionization of the nation. Is there a 117 00:07:22,640 --> 00:07:26,080 Speaker 1: solution here, professor? And what is it? You've talked before 118 00:07:26,200 --> 00:07:28,880 Speaker 1: about the idea that say just quite simply, if you 119 00:07:28,920 --> 00:07:31,280 Speaker 1: worked for one fast food company, you should be able 120 00:07:31,320 --> 00:07:33,400 Speaker 1: to go to the next fast food company without a 121 00:07:33,440 --> 00:07:35,600 Speaker 1: barrier to entry, without a contract that says you can't 122 00:07:35,640 --> 00:07:38,240 Speaker 1: do that. That seems like one small solution to one 123 00:07:38,280 --> 00:07:41,000 Speaker 1: part of the country. What are the other solutions, Well, 124 00:07:41,040 --> 00:07:43,480 Speaker 1: there should be some things that are really non controversial, 125 00:07:44,160 --> 00:07:47,280 Speaker 1: to the extent that employers have been using practices to 126 00:07:47,360 --> 00:07:51,320 Speaker 1: prevent competition in the labor market, the suppress wages and mobility. 127 00:07:51,520 --> 00:07:55,160 Speaker 1: We should use our tools to prevent that, and we 128 00:07:55,280 --> 00:07:58,679 Speaker 1: have the tools anti trust for example. Anti trust typically 129 00:07:58,680 --> 00:08:01,080 Speaker 1: doesn't take into account act on the labor market, but 130 00:08:01,120 --> 00:08:03,240 Speaker 1: when we have more and more mergers and there's less 131 00:08:03,240 --> 00:08:08,240 Speaker 1: competition for workers that suppress his wages non compete agreements 132 00:08:08,280 --> 00:08:11,800 Speaker 1: of the workforce is currently covered by a noncompete agreement, 133 00:08:12,000 --> 00:08:13,840 Speaker 1: which makes it hard for them to find a better 134 00:08:13,880 --> 00:08:17,520 Speaker 1: paying job. Uh, they have really run a mark. They're 135 00:08:17,600 --> 00:08:22,560 Speaker 1: unnecessary in many of those cases, workers UH don't know 136 00:08:22,720 --> 00:08:25,800 Speaker 1: what they're signing on to. UM. So there are some 137 00:08:25,840 --> 00:08:29,040 Speaker 1: easy solutions, and some states have been have been pursuing them. Now. 138 00:08:29,120 --> 00:08:31,160 Speaker 1: I don't know if they're sufficient, but there's certainly a 139 00:08:31,160 --> 00:08:33,439 Speaker 1: step in the right direction. Listening to you, that professor, 140 00:08:33,480 --> 00:08:35,840 Speaker 1: it seems like the solutions both in terms of government 141 00:08:35,840 --> 00:08:40,280 Speaker 1: intervention and actually just liberalizing labor markets properly, enabling the 142 00:08:40,320 --> 00:08:43,880 Speaker 1: mobility of labor to actually function efficiently, because that's not 143 00:08:43,920 --> 00:08:46,200 Speaker 1: happening right now, is a mix of both ideas, the 144 00:08:46,240 --> 00:08:50,640 Speaker 1: intervention and the liberalism as well. Yes, yeah, I think 145 00:08:51,040 --> 00:08:52,840 Speaker 1: you know, if we can look at what some other 146 00:08:52,880 --> 00:08:56,080 Speaker 1: countries have done which haven't had nearly a severe problem, 147 00:08:56,120 --> 00:08:58,920 Speaker 1: and as Angest, Deaton and and Case have shown, the 148 00:08:59,080 --> 00:09:03,320 Speaker 1: US is really un nique in terms of uh middle 149 00:09:03,440 --> 00:09:09,360 Speaker 1: income people seeing their life expectancy decline. Um. So we 150 00:09:09,520 --> 00:09:12,360 Speaker 1: we know that other countries have managed to prevent the 151 00:09:12,360 --> 00:09:14,960 Speaker 1: worst of these problems. We mentioned Germany often when we 152 00:09:15,000 --> 00:09:18,199 Speaker 1: do that. I want you to speak and the Conservatives 153 00:09:18,200 --> 00:09:21,520 Speaker 1: and the Republicans think you're a died in the world democrat, 154 00:09:22,160 --> 00:09:25,440 Speaker 1: flaming liberal from Princeton, et cetera. I want you to 155 00:09:25,480 --> 00:09:29,120 Speaker 1: speak to the people that feel there's an individualistic power, 156 00:09:29,240 --> 00:09:32,640 Speaker 1: a lockey and power in this nation of the individual 157 00:09:32,760 --> 00:09:35,720 Speaker 1: to do better in too good and yet the pendulum, 158 00:09:35,800 --> 00:09:39,160 Speaker 1: some would say, has swung too far. How do you 159 00:09:39,200 --> 00:09:43,320 Speaker 1: address the historical pendulum of labor because we can all 160 00:09:43,360 --> 00:09:46,480 Speaker 1: agree we don't want gunfire in the streets of Detroit 161 00:09:46,559 --> 00:09:51,000 Speaker 1: or Chicago or wherever there was labor unrest seventy years ago. Well, 162 00:09:51,000 --> 00:09:53,400 Speaker 1: I think there are many benefits to society when workers 163 00:09:53,440 --> 00:09:56,600 Speaker 1: have a voice at work. A lot of people disagree 164 00:09:56,640 --> 00:09:59,680 Speaker 1: with that statement. That's I guess my point. Well, I 165 00:09:59,720 --> 00:10:01,520 Speaker 1: think the labor unions have not done a very good 166 00:10:01,640 --> 00:10:05,360 Speaker 1: job marketing themselves. Um. I think there's a bowling alone 167 00:10:05,360 --> 00:10:09,240 Speaker 1: phenomenon where people are not joining groups the way that 168 00:10:09,280 --> 00:10:12,280 Speaker 1: they used to, perhaps because of time pressures. I don't 169 00:10:12,280 --> 00:10:16,280 Speaker 1: think the union movement has done such a great job attracting, uh, 170 00:10:16,440 --> 00:10:19,920 Speaker 1: the growth in the workforce among women. Just as Mr Bezos, 171 00:10:19,960 --> 00:10:22,760 Speaker 1: we know you listen every morning. What would happen if 172 00:10:22,800 --> 00:10:29,320 Speaker 1: we unionized people filling cardboard boxes at Amazon speak? I 173 00:10:29,360 --> 00:10:32,520 Speaker 1: think the net benefits would be positive, you know, I 174 00:10:32,520 --> 00:10:34,280 Speaker 1: think that's what we've seen history. That would be a 175 00:10:34,320 --> 00:10:37,920 Speaker 1: positive for Jeff Bezos. No, not necessarily for Jeff Bezos, 176 00:10:37,920 --> 00:10:40,400 Speaker 1: but Jeff Bezos is doing just five You'd be unionizing 177 00:10:40,440 --> 00:10:44,800 Speaker 1: a lot of robots, wouldn't. It's humb king those box Well, 178 00:10:44,840 --> 00:10:47,160 Speaker 1: but but come on, this is important. Let me get 179 00:10:47,160 --> 00:10:48,720 Speaker 1: this up here. I can do this on the Bloomberg 180 00:10:48,760 --> 00:10:53,600 Speaker 1: folks instantly. I'm sorry, they got five sixty six thousand bodies. 181 00:10:53,640 --> 00:10:57,440 Speaker 1: Some of those are filling cardboard boxes. Yeah. Absolutely, And 182 00:10:57,640 --> 00:10:59,600 Speaker 1: you know, I think if they were unionized, they would 183 00:10:59,640 --> 00:11:02,000 Speaker 1: be paid better. I think they would feel better about 184 00:11:02,000 --> 00:11:05,120 Speaker 1: their jobs, they'd have more fair treatment, they'd have a 185 00:11:05,160 --> 00:11:08,240 Speaker 1: system of arbitration if they felt harassed or they felt 186 00:11:08,240 --> 00:11:11,160 Speaker 1: that the law had been violated. And take the company's side, 187 00:11:11,160 --> 00:11:14,480 Speaker 1: take the Basos side. He goes, no, we're not doing that. Well, 188 00:11:14,720 --> 00:11:17,839 Speaker 1: a lot of companies have been saying that, and that's 189 00:11:17,880 --> 00:11:20,320 Speaker 1: one of the reasons why we see profits at historically 190 00:11:20,360 --> 00:11:22,240 Speaker 1: high levels. That's one of the reasons why we see 191 00:11:22,240 --> 00:11:24,600 Speaker 1: private share of national inc I'm at historically higher. Well, 192 00:11:24,640 --> 00:11:26,760 Speaker 1: let's let's think of some economies that have a really 193 00:11:26,800 --> 00:11:29,280 Speaker 1: strong union presence and then think about how bad the 194 00:11:29,360 --> 00:11:32,839 Speaker 1: labor market has performed over the last decade. I can 195 00:11:32,880 --> 00:11:35,000 Speaker 1: think of many, and most of them reside in Europe. 196 00:11:35,080 --> 00:11:37,400 Speaker 1: And guess what, there are so many European politicians that 197 00:11:37,480 --> 00:11:40,200 Speaker 1: want to break up that mix. When we use this 198 00:11:40,240 --> 00:11:43,360 Speaker 1: word union, I think it just scares so many people. Professor, 199 00:11:43,440 --> 00:11:46,840 Speaker 1: They think of France they think of Italy, they think 200 00:11:46,880 --> 00:11:50,000 Speaker 1: of things not functioning properly, they think of things shutting down, 201 00:11:50,000 --> 00:11:54,280 Speaker 1: they think of strikes, they think of How do you 202 00:11:54,360 --> 00:11:58,959 Speaker 1: reintroduce the idea that actually unions are positive for the 203 00:11:59,000 --> 00:12:02,760 Speaker 1: American economy. Well, you could also think of Germany, which 204 00:12:02,760 --> 00:12:06,400 Speaker 1: has done quite well. You can think of Canada. Uh. 205 00:12:06,480 --> 00:12:08,960 Speaker 1: You know, I think that we need a new form 206 00:12:09,000 --> 00:12:10,960 Speaker 1: of organization in the labor market. I think we need 207 00:12:10,960 --> 00:12:14,160 Speaker 1: new institutions. When when unions eroded and only seven percent 208 00:12:14,200 --> 00:12:17,040 Speaker 1: of private sector workers are now in labor unions, the 209 00:12:17,120 --> 00:12:21,680 Speaker 1: institutions that filled the void were more inefficient occupational licensing 210 00:12:22,640 --> 00:12:24,560 Speaker 1: of workers are required to have a license to do 211 00:12:24,640 --> 00:12:27,880 Speaker 1: things like wash someone's hair at a beauty parlor, and 212 00:12:28,120 --> 00:12:30,920 Speaker 1: that is restricting competition and hurting our economy. So I 213 00:12:30,920 --> 00:12:34,600 Speaker 1: think we need to rethink, fundamentally, rethink the way workers 214 00:12:34,640 --> 00:12:36,800 Speaker 1: are represented at work. And it may be that the 215 00:12:36,840 --> 00:12:38,839 Speaker 1: old form of unions is not the optimal, but I 216 00:12:38,880 --> 00:12:42,600 Speaker 1: think some form of representation would be beneficial. John Ferroll 217 00:12:42,640 --> 00:12:44,840 Speaker 1: continue the conversation here. But you know, we've had a 218 00:12:44,960 --> 00:12:47,720 Speaker 1: huge response to today's show. Thank you to Dr Rubini 219 00:12:47,800 --> 00:12:50,760 Speaker 1: for that, and also thank you to doctor Krueger Roubini 220 00:12:50,880 --> 00:12:53,440 Speaker 1: didn't get this email. We thank this for coming in 221 00:12:53,480 --> 00:12:57,400 Speaker 1: over the transom. Krueger is a socialist who believes each 222 00:12:57,440 --> 00:13:01,000 Speaker 1: individual in the US should get helicopter your money. So 223 00:13:01,040 --> 00:13:03,680 Speaker 1: why don't you continue with their John, So I don't 224 00:13:03,720 --> 00:13:06,120 Speaker 1: pass the buck to May. The professor announces from South. 225 00:13:07,440 --> 00:13:10,040 Speaker 1: But that's the zeit geist that's out there that gets 226 00:13:10,080 --> 00:13:13,360 Speaker 1: you to seven union employment. Well, I think we just 227 00:13:13,400 --> 00:13:15,400 Speaker 1: have to look at results. Are we happy with an 228 00:13:15,400 --> 00:13:17,800 Speaker 1: economy whereas Angus dat and showed, the US is now 229 00:13:17,880 --> 00:13:20,320 Speaker 1: responsible for a tremendous amount of the poverty in the world. 230 00:13:20,800 --> 00:13:22,120 Speaker 1: You know, it is that the kind of country that 231 00:13:22,200 --> 00:13:25,760 Speaker 1: we want. I think we create more opportunity if we 232 00:13:25,880 --> 00:13:28,320 Speaker 1: have a more level playing field. And what I'm worried about, 233 00:13:28,400 --> 00:13:30,920 Speaker 1: John asked earlier about is it gonna get worse before 234 00:13:30,960 --> 00:13:34,920 Speaker 1: it gets better. The tremendous rise and inequality that we've 235 00:13:35,000 --> 00:13:38,960 Speaker 1: seen is feeding on itself. The gap and opportunities between children, 236 00:13:39,280 --> 00:13:43,359 Speaker 1: just by happenstance, are born to disadvantaged families is tremendous 237 00:13:43,400 --> 00:13:46,360 Speaker 1: compared to those who are born in the top. And 238 00:13:46,600 --> 00:13:48,280 Speaker 1: that's not good for our country in the long run. 239 00:13:48,320 --> 00:13:51,199 Speaker 1: We're not training the people the way we should and 240 00:13:51,240 --> 00:13:53,040 Speaker 1: I think in the long run that's gonna really hurt us. 241 00:13:53,240 --> 00:13:57,199 Speaker 1: Professor Kruger really appreciate sign Princeton University. He can almost 242 00:13:57,240 --> 00:14:13,640 Speaker 1: profess it. And now we welcome on Bloomberg Radio all 243 00:14:13,720 --> 00:14:16,760 Speaker 1: of you worldwide, coast to coast across all of America, 244 00:14:16,920 --> 00:14:21,200 Speaker 1: and I'm Bloomberg Television. William gross of Janice Henderson joins us. 245 00:14:21,360 --> 00:14:24,880 Speaker 1: Right now, Bill, we finally see good wage growth, and 246 00:14:25,040 --> 00:14:28,720 Speaker 1: critically we see a revision upward to wage wage growth 247 00:14:29,120 --> 00:14:32,200 Speaker 1: as well. Will that be the breakout condition that gets 248 00:14:32,280 --> 00:14:35,360 Speaker 1: us to the three percent yield you've talked about? Is 249 00:14:35,440 --> 00:14:39,760 Speaker 1: a critical point for the tenure? Oh? Yeah, I think 250 00:14:39,800 --> 00:14:42,320 Speaker 1: it is. Tom. You know, if you factor in two 251 00:14:42,360 --> 00:14:45,720 Speaker 1: point nine percent to y o Y wage growth and 252 00:14:45,840 --> 00:14:50,560 Speaker 1: you throw in a one in which I think is 253 00:14:50,840 --> 00:14:53,840 Speaker 1: probably normal to expect going forward, you know, you've got 254 00:14:54,680 --> 00:14:58,720 Speaker 1: two percent unit labor costs and hopefully two percent inflation 255 00:14:58,760 --> 00:15:01,560 Speaker 1: doesn't even factor in the you know, the week dollar 256 00:15:01,640 --> 00:15:04,320 Speaker 1: over the past twelve months. And so yes, I think 257 00:15:04,440 --> 00:15:07,840 Speaker 1: it basically means that we're approaching that magical to which 258 00:15:07,960 --> 00:15:11,360 Speaker 1: the Fed will continue, let's put it this way, will 259 00:15:11,400 --> 00:15:14,440 Speaker 1: continue to raise rates, well said, and I know they're 260 00:15:14,480 --> 00:15:17,800 Speaker 1: continue we know, and you know we were altra accommodative 261 00:15:17,840 --> 00:15:20,800 Speaker 1: with Vice Chairman Fisher. We've moved up, but we can't 262 00:15:20,840 --> 00:15:25,200 Speaker 1: even get an inflation targeted, inflation reduced FED funds target 263 00:15:25,360 --> 00:15:28,640 Speaker 1: rate to get to zero. Our real rates too low, 264 00:15:28,880 --> 00:15:33,800 Speaker 1: and is the Fed behind well, it depends, I guess 265 00:15:33,840 --> 00:15:36,040 Speaker 1: on which real rate you're talking about. You know, the 266 00:15:36,440 --> 00:15:40,560 Speaker 1: tenure real rate is about fifty plus basis points um. 267 00:15:41,120 --> 00:15:44,240 Speaker 1: You know what hasn't been normally well before Layman and 268 00:15:44,320 --> 00:15:46,800 Speaker 1: before the crisis, it was close to two percent. And 269 00:15:47,200 --> 00:15:49,800 Speaker 1: therein lies the robe and the question I suppose for 270 00:15:50,360 --> 00:15:53,840 Speaker 1: Chairman Powell, what's the new real interest rate, not only 271 00:15:53,920 --> 00:15:57,600 Speaker 1: for a tenure but for Fed funds. I think they're 272 00:15:57,800 --> 00:16:01,680 Speaker 1: targeting a zero percent real rate for Fed funds, which 273 00:16:01,800 --> 00:16:05,200 Speaker 1: might mean if we had two percent inflation two percent 274 00:16:05,360 --> 00:16:08,360 Speaker 1: Fed funds rate, that's you know, perhaps six months away 275 00:16:08,440 --> 00:16:13,240 Speaker 1: with two hikes up to two. But nonetheless it goes 276 00:16:13,320 --> 00:16:16,880 Speaker 1: along with what the market was expecting. And now perhaps 277 00:16:16,960 --> 00:16:20,080 Speaker 1: with these wedge games a little bit more. But I 278 00:16:20,120 --> 00:16:21,440 Speaker 1: want to talk to you about some of the price 279 00:16:21,520 --> 00:16:23,800 Speaker 1: action in the treasury market this morning off the back 280 00:16:23,840 --> 00:16:28,040 Speaker 1: of these numbers coming into big consensus positioning around a 281 00:16:28,280 --> 00:16:31,080 Speaker 1: flatter yield curve. I'm seeing a steeper curve on a 282 00:16:31,160 --> 00:16:33,360 Speaker 1: session so far. How do you think about that steeper 283 00:16:33,400 --> 00:16:35,320 Speaker 1: curve at the moment, Billy? Is that just the consensus 284 00:16:35,440 --> 00:16:38,440 Speaker 1: unwind of a big crowded trade for a flatter curve 285 00:16:38,800 --> 00:16:41,080 Speaker 1: or is that a fundamental rethink about the shape of 286 00:16:41,160 --> 00:16:46,480 Speaker 1: this curve through eighteen through nineteen. Well, I've never been 287 00:16:46,480 --> 00:16:49,120 Speaker 1: an advocate of a flatter curve from this point forward. 288 00:16:49,160 --> 00:16:52,480 Speaker 1: Admittedly the curve is flattened substantially over the past few years, 289 00:16:52,600 --> 00:16:55,160 Speaker 1: but you know, many are expecting the tenure in the 290 00:16:55,240 --> 00:16:57,920 Speaker 1: third year to flatten and maybe for the tenure to 291 00:16:58,000 --> 00:17:00,560 Speaker 1: go higher, because it always has, don't think in this 292 00:17:00,680 --> 00:17:04,159 Speaker 1: particular case, because we see inflation moving higher, which is 293 00:17:04,200 --> 00:17:06,800 Speaker 1: what the Fed wants, and you know, the longer dated 294 00:17:06,880 --> 00:17:11,399 Speaker 1: treasuries are inflation sensitive compared to short term rates, and 295 00:17:11,520 --> 00:17:14,760 Speaker 1: so um. You know, I think we go through this cycle, 296 00:17:14,880 --> 00:17:17,240 Speaker 1: this mini cycle, like it's a bare cycle, like I 297 00:17:17,359 --> 00:17:19,959 Speaker 1: talked about, you know, several months ago. But I think 298 00:17:20,000 --> 00:17:23,200 Speaker 1: we go through this cycle in a relatively mild fashion, 299 00:17:23,280 --> 00:17:26,600 Speaker 1: notwithstanding today's action, but in a relatively mild fashion in 300 00:17:26,680 --> 00:17:31,720 Speaker 1: which the curve you know, stays not steep, but stays positive. 301 00:17:31,760 --> 00:17:35,200 Speaker 1: And that would be for me to ten spread of 302 00:17:35,240 --> 00:17:38,720 Speaker 1: about forty to fifty basis points, so not a not 303 00:17:38,840 --> 00:17:41,160 Speaker 1: a flattening bill. Last time we spoke, we talked about 304 00:17:41,200 --> 00:17:43,240 Speaker 1: what higher rates could eventually mean for credit, and you 305 00:17:43,320 --> 00:17:46,360 Speaker 1: expressed where you were positioned around high yield. You expressed 306 00:17:46,400 --> 00:17:48,840 Speaker 1: the short position there. I'm just wondering what your thoughts 307 00:17:48,840 --> 00:17:51,399 Speaker 1: at the moment because we've had a significant repricing in 308 00:17:51,480 --> 00:17:54,159 Speaker 1: treasuries and in burns, yet I don't see credit stress 309 00:17:54,359 --> 00:17:56,879 Speaker 1: in high yield and investment grades. I still see spreads 310 00:17:56,960 --> 00:17:59,760 Speaker 1: really tight. Are you surprised by how resilient credit as 311 00:17:59,800 --> 00:18:05,000 Speaker 1: bay despite the pick up in treasury yads? Yeah, they're 312 00:18:05,080 --> 00:18:08,320 Speaker 1: they're really tight, Jonathan. But they have widen to be fair. 313 00:18:08,480 --> 00:18:11,080 Speaker 1: I I look at the h y C d X 314 00:18:11,200 --> 00:18:14,640 Speaker 1: and uh, you know, they've they've spread out by about 315 00:18:16,320 --> 00:18:19,520 Speaker 1: ten fifteen basis points. And the logic there is is 316 00:18:19,600 --> 00:18:22,160 Speaker 1: that the high old companies will have to pay more 317 00:18:22,240 --> 00:18:24,720 Speaker 1: for their money, and they have a substantial amount of 318 00:18:24,800 --> 00:18:28,720 Speaker 1: bonds to roll or to uh you know, replace when 319 00:18:28,800 --> 00:18:31,960 Speaker 1: others mature. Typically high old companies issue at the five 320 00:18:32,040 --> 00:18:35,000 Speaker 1: year area, and so in two thousand and eighteen, nineteen, 321 00:18:35,000 --> 00:18:37,840 Speaker 1: and twenty, they're going to be faced with narrowing spreads 322 00:18:37,920 --> 00:18:41,080 Speaker 1: in terms of margins and higher yields. And so that's 323 00:18:41,160 --> 00:18:45,000 Speaker 1: why it affects high old bonds. I think they're going 324 00:18:45,080 --> 00:18:47,040 Speaker 1: to continue to widen, and they just want everybody to 325 00:18:47,160 --> 00:18:50,040 Speaker 1: notice this. On Bloomberg Radio and Bloomberg Television worldwide that 326 00:18:50,160 --> 00:18:53,320 Speaker 1: John Farrell there was asking a sophisticated question for his 327 00:18:53,400 --> 00:18:58,000 Speaker 1: wonderful show The Real Yield a twelve noon today. I 328 00:18:58,040 --> 00:19:00,359 Speaker 1: know John Farrell was doing that. I'm sorry, Bill Grows, 329 00:19:00,600 --> 00:19:03,000 Speaker 1: that was way too bond like. But what we're gonna have, 330 00:19:03,160 --> 00:19:06,880 Speaker 1: Bill Gross is every month, every month, Bill Gross, we're 331 00:19:06,920 --> 00:19:11,080 Speaker 1: gonna have bond prices go down. At what point does 332 00:19:11,160 --> 00:19:16,320 Speaker 1: the retail investor or the smaller institutional account panic. They 333 00:19:16,359 --> 00:19:19,080 Speaker 1: don't listen to you, they don't listen to your good competitors, 334 00:19:19,400 --> 00:19:22,560 Speaker 1: and they're gonna say, wait, bond price down, I'm getting out. 335 00:19:22,840 --> 00:19:26,840 Speaker 1: How close are we to that? Well, I think we're 336 00:19:26,880 --> 00:19:29,399 Speaker 1: getting there. Tom. You know, on a month to month basis, 337 00:19:29,440 --> 00:19:32,040 Speaker 1: they're losing money and probably have for the last two 338 00:19:32,200 --> 00:19:35,560 Speaker 1: or three months, and investors don't like to lose money. 339 00:19:35,680 --> 00:19:39,000 Speaker 1: They prefer cash, right, or even cash and a mattress, 340 00:19:39,040 --> 00:19:41,760 Speaker 1: I suppose, but um, you know, it's a short period 341 00:19:41,840 --> 00:19:45,040 Speaker 1: of time. I would say that investors, bond investors should 342 00:19:45,080 --> 00:19:48,040 Speaker 1: expect to earn nothing in two thousand and eighteen and 343 00:19:48,160 --> 00:19:50,359 Speaker 1: maybe you know, with a minus sign in front of it. 344 00:19:50,480 --> 00:19:54,600 Speaker 1: Typically that doesn't happen because you know, with higher yields. 345 00:19:54,640 --> 00:19:57,480 Speaker 1: In the past, it's been the yields that have compensated 346 00:19:57,600 --> 00:20:00,639 Speaker 1: for the price declines. But now, um, you know, in 347 00:20:01,240 --> 00:20:03,840 Speaker 1: terms of going up by twenty or thirty basis points 348 00:20:03,880 --> 00:20:06,639 Speaker 1: in the last month, you know, for the tenure, that 349 00:20:06,800 --> 00:20:11,000 Speaker 1: basically implies a two percent price decline, and that's an 350 00:20:11,480 --> 00:20:14,679 Speaker 1: that requires an annual income of uh you know, uh 351 00:20:14,880 --> 00:20:17,680 Speaker 1: hope on clipping in order to compensate. So I think 352 00:20:17,800 --> 00:20:21,320 Speaker 1: retail is going to be sensitive now from this point forward, 353 00:20:21,359 --> 00:20:24,760 Speaker 1: certainly after this report. Okay, that's a really important statement. 354 00:20:24,840 --> 00:20:28,680 Speaker 1: Will you suggest, as being unconstrained at Janice, the dividend 355 00:20:28,800 --> 00:20:32,679 Speaker 1: growth is an alternative to bond clipping to a flat 356 00:20:32,840 --> 00:20:37,240 Speaker 1: or negative return this year for bond investors. Oh sure, 357 00:20:37,359 --> 00:20:41,760 Speaker 1: unconstrained and certainly Janice unconstrained. Uh, you know, can can 358 00:20:41,840 --> 00:20:45,240 Speaker 1: be unconstrained, and we've been because I've been forecasting higher 359 00:20:45,320 --> 00:20:47,760 Speaker 1: interest rates and lower bond prices. You know, we've been 360 00:20:47,880 --> 00:20:52,360 Speaker 1: short duration as opposed to positive duration. Typically total return funds, 361 00:20:52,720 --> 00:20:56,440 Speaker 1: you know, are forced to monitor what's called the Barkley's 362 00:20:56,480 --> 00:20:59,280 Speaker 1: aggregant index, which has a duration of five or an 363 00:20:59,320 --> 00:21:02,680 Speaker 1: average mature already of about seven or eight years. Unconstrained 364 00:21:02,760 --> 00:21:05,400 Speaker 1: can go the other way. And so we've been basically 365 00:21:05,520 --> 00:21:08,640 Speaker 1: a minus two years of duration for the last month 366 00:21:08,760 --> 00:21:10,280 Speaker 1: or two and I think you can see that in 367 00:21:10,359 --> 00:21:13,240 Speaker 1: the performance. So yeah, when you have a bear market, 368 00:21:13,359 --> 00:21:15,399 Speaker 1: you want to go unconstrained because it gives you the 369 00:21:15,440 --> 00:21:18,960 Speaker 1: flexibility to go minus as opposed to plus. Bill Gross 370 00:21:19,000 --> 00:21:21,920 Speaker 1: is always thank you for your attendance today. We greatly 371 00:21:22,000 --> 00:21:25,800 Speaker 1: appreciate on short notice your attendance with share Yellin's historic 372 00:21:26,359 --> 00:21:29,080 Speaker 1: final meeting. A few days ago on the FED day, 373 00:21:29,200 --> 00:21:44,720 Speaker 1: Mr Gross again with Janie Anderson, let's bringing Julia Coronado, 374 00:21:44,840 --> 00:21:48,119 Speaker 1: the president, founder of Macro Policy Perspectives. Julia, thank you 375 00:21:48,240 --> 00:21:50,399 Speaker 1: very much for being with us. Um all right, we 376 00:21:50,480 --> 00:21:52,680 Speaker 1: got the headline unders. I'm wondering, is there anything it's 377 00:21:52,920 --> 00:21:55,960 Speaker 1: specific that you want to point out because my question 378 00:21:56,040 --> 00:21:57,520 Speaker 1: to you is, I know you spent a lot of 379 00:21:57,560 --> 00:22:01,159 Speaker 1: time looking at the shadow labor force and particularly women 380 00:22:01,280 --> 00:22:03,920 Speaker 1: in the labor force. You can go with the big 381 00:22:04,440 --> 00:22:07,159 Speaker 1: you know, two hundred thousand print, or you can tell 382 00:22:07,240 --> 00:22:11,080 Speaker 1: us about shadow labor force. Well, look, I think actually 383 00:22:11,160 --> 00:22:14,000 Speaker 1: one of the most significant things of the report is 384 00:22:14,119 --> 00:22:17,399 Speaker 1: the wage growth that we're seeing. So it's you know, 385 00:22:17,560 --> 00:22:20,760 Speaker 1: not like it's skyrocketing, but it's picked up to two 386 00:22:20,840 --> 00:22:24,639 Speaker 1: point nine. We haven't really hit three percent yet this cycle. 387 00:22:24,800 --> 00:22:28,960 Speaker 1: So to me, the news today is that there's finally 388 00:22:29,280 --> 00:22:33,359 Speaker 1: some warming up in wage growth. It's not that broad base, 389 00:22:33,560 --> 00:22:37,200 Speaker 1: but it's there and um, and and that's good. And 390 00:22:37,320 --> 00:22:40,520 Speaker 1: I think on the shadow labor force front, the unemployment 391 00:22:40,640 --> 00:22:44,200 Speaker 1: rate held steady, the participation rate of the prime age 392 00:22:44,240 --> 00:22:48,960 Speaker 1: workers continues to improve. So um, you know it is 393 00:22:49,160 --> 00:22:52,080 Speaker 1: it's a good labor market. It's bringing people back, and 394 00:22:52,200 --> 00:22:55,840 Speaker 1: it's starting to finally deliver wage games for workers. All right, 395 00:22:55,920 --> 00:22:58,720 Speaker 1: And will that be enough to make it to a 396 00:22:58,800 --> 00:23:05,120 Speaker 1: three percent productivity radar? Is that still unrealistic? Well? Um, 397 00:23:05,760 --> 00:23:09,000 Speaker 1: that depends on the drivers of growth. I mean last 398 00:23:09,160 --> 00:23:12,000 Speaker 1: year and actually still in this report, we had some 399 00:23:12,160 --> 00:23:17,760 Speaker 1: of the productive sectors that is UM, manufacturing UH and 400 00:23:18,080 --> 00:23:24,040 Speaker 1: mining makes good solid contributions, so that bodes well for productivity. 401 00:23:24,160 --> 00:23:28,800 Speaker 1: But UM, it really doesn't change the overall trends that 402 00:23:28,880 --> 00:23:31,639 Speaker 1: we've come off the lows. But it's a pretty subdued 403 00:23:32,440 --> 00:23:37,520 Speaker 1: UH productivity UM picture for the US. When does this 404 00:23:37,680 --> 00:23:43,200 Speaker 1: translate into accelerated inflation? Well, you know, the Phillips curve 405 00:23:43,320 --> 00:23:46,960 Speaker 1: is flat, so the translation from wage growth to pricing 406 00:23:47,760 --> 00:23:52,879 Speaker 1: is tenuous at best. UH So I wouldn't draw the 407 00:23:53,040 --> 00:23:55,920 Speaker 1: line from the wage gains that we've seen to hire 408 00:23:55,960 --> 00:24:00,800 Speaker 1: core inflation. But at least it's supportive. You're you're less 409 00:24:00,840 --> 00:24:05,240 Speaker 1: worried about downward pressures from this given this report. Here's 410 00:24:05,240 --> 00:24:07,959 Speaker 1: a key question, and this locks into where potential GDP 411 00:24:08,200 --> 00:24:10,439 Speaker 1: is the run rate of the economy, or demographics are 412 00:24:10,480 --> 00:24:13,639 Speaker 1: product activity? Do you have a year over year wage 413 00:24:13,640 --> 00:24:17,480 Speaker 1: growth statistics where things unwind? I mean, we talked about 414 00:24:17,520 --> 00:24:21,560 Speaker 1: unemployment four point one, but does Julia Coronado at two 415 00:24:21,600 --> 00:24:24,400 Speaker 1: point nine percent year over a year say, wow, it's 416 00:24:24,520 --> 00:24:28,560 Speaker 1: three or three two or three four? Things change? Do 417 00:24:28,640 --> 00:24:32,560 Speaker 1: you have that number in your head? You know, it's 418 00:24:32,600 --> 00:24:36,200 Speaker 1: definitely whatever that number might be, it's it's both the 419 00:24:36,480 --> 00:24:40,400 Speaker 1: rate and the speed of acceleration. So if we look 420 00:24:40,440 --> 00:24:44,320 Speaker 1: at sort of the chart of this wage picture, it's 421 00:24:44,320 --> 00:24:48,520 Speaker 1: still a very gradual acceleration that makes you much less 422 00:24:48,600 --> 00:24:51,560 Speaker 1: worried than if it was a hockey stick. Uh. And 423 00:24:51,680 --> 00:24:54,160 Speaker 1: we have seen that the last expansion, we saw average 424 00:24:54,320 --> 00:24:57,919 Speaker 1: hourly earnings accelerate pretty sharply, and people always wonder are 425 00:24:57,960 --> 00:25:00,280 Speaker 1: we going to hit that non linear part of the 426 00:25:00,320 --> 00:25:04,560 Speaker 1: Phillips curve. This looks linear, So there's nothing worrisome here 427 00:25:04,640 --> 00:25:07,280 Speaker 1: that says, oh my gosh, that needs to lamb on 428 00:25:07,359 --> 00:25:10,200 Speaker 1: the brakes. This is more like, finally we're getting what 429 00:25:10,320 --> 00:25:12,680 Speaker 1: we wanted to see and expected to see. Do you 430 00:25:12,880 --> 00:25:16,040 Speaker 1: see how Julia goes quadratic on us? I noticed that 431 00:25:16,200 --> 00:25:20,399 Speaker 1: linear is linear and then she coming up folks, Julia 432 00:25:20,440 --> 00:25:24,240 Speaker 1: Cornado will go quadratic with Dr Cornado. We can even 433 00:25:24,280 --> 00:25:26,920 Speaker 1: go log quadratic with that cool boy. That means I 434 00:25:26,960 --> 00:25:31,240 Speaker 1: gotta get my GPL out. That's your GPL char GPL charts. Yeah, 435 00:25:31,320 --> 00:25:33,560 Speaker 1: that's what I use. Courtesy of Tom King. Michael barrs 436 00:25:33,600 --> 00:25:35,960 Speaker 1: here with his cool and as her slide ruble. To 437 00:25:36,040 --> 00:25:38,520 Speaker 1: be sure we get through the next section as well, 438 00:25:38,520 --> 00:25:41,040 Speaker 1: We'll continue with Dr Coronado, always good to have her, 439 00:25:41,080 --> 00:25:44,360 Speaker 1: wonderful to ever with Nora Robini this morning she survived 440 00:25:44,359 --> 00:26:02,080 Speaker 1: the bitcoin questions as well. We're speaking with Eric Brynjolfson. 441 00:26:02,119 --> 00:26:04,000 Speaker 1: He is a professor at the m I T. Sloan 442 00:26:04,080 --> 00:26:06,560 Speaker 1: School of Management and also director of the m I 443 00:26:06,680 --> 00:26:11,600 Speaker 1: T Initiative on the Digital Economy. Professor Brynson, what can 444 00:26:11,920 --> 00:26:18,960 Speaker 1: artificial intelligence or machine learning currently do better than human beings? Well, 445 00:26:19,000 --> 00:26:22,480 Speaker 1: it's very good at classifying and prediction, um, so things 446 00:26:22,520 --> 00:26:26,919 Speaker 1: like you mentioned earlier, reading X rays or recognizing our faces. Um. 447 00:26:27,119 --> 00:26:29,960 Speaker 1: They can do that at human or superhuman levels, and 448 00:26:30,080 --> 00:26:33,040 Speaker 1: that means that radiologists are going to have to focus 449 00:26:33,119 --> 00:26:35,919 Speaker 1: on other parts of their jobs. They can also recognize 450 00:26:36,240 --> 00:26:38,880 Speaker 1: speech and language at a level close to human levels, 451 00:26:39,160 --> 00:26:41,280 Speaker 1: and now they being able to make decisions about things 452 00:26:41,359 --> 00:26:45,639 Speaker 1: like hiring, parole decisions, credit decisions where to place ads 453 00:26:46,240 --> 00:26:48,960 Speaker 1: as well or better than humans. What are the kinds 454 00:26:49,040 --> 00:26:52,800 Speaker 1: of jobs that artificial intelligence will not be able to 455 00:26:52,960 --> 00:26:55,359 Speaker 1: do because of the very way that it is actually 456 00:26:55,440 --> 00:26:58,800 Speaker 1: put together and learns. So I think it's best to 457 00:26:58,800 --> 00:27:01,160 Speaker 1: think at the task level rather than the job level. 458 00:27:01,320 --> 00:27:04,360 Speaker 1: Almost every job will have some components that are affected 459 00:27:04,400 --> 00:27:07,640 Speaker 1: by machine learning, but almost every job will have significant 460 00:27:07,680 --> 00:27:10,119 Speaker 1: parts that are not affected. The parts that won't be 461 00:27:10,200 --> 00:27:15,040 Speaker 1: affected are those that involved creativity and large scale problem solving, 462 00:27:15,119 --> 00:27:17,760 Speaker 1: even just asking the right questions. Machines don't know how 463 00:27:17,800 --> 00:27:21,280 Speaker 1: to do that. Also interacting with other people, you know, 464 00:27:21,400 --> 00:27:26,639 Speaker 1: emotional intelligence, teamwork, motivating, caring for people. There's lots and 465 00:27:26,720 --> 00:27:29,280 Speaker 1: lots of jobs and tasks that that primarily do that 466 00:27:29,440 --> 00:27:33,359 Speaker 1: kind of work. Now, last point to you, Professor Robert 467 00:27:33,520 --> 00:27:38,480 Speaker 1: Gordon Uh, the noted economist and professor at Northwestern University. 468 00:27:39,200 --> 00:27:41,840 Speaker 1: He has spoken in the past about the era a 469 00:27:41,960 --> 00:27:45,400 Speaker 1: big innovation is over and that US economic growth could 470 00:27:45,480 --> 00:27:49,320 Speaker 1: slow as a result. What is your response to that. 471 00:27:50,600 --> 00:27:52,560 Speaker 1: Bob is a dear, dear friend. We've known each other 472 00:27:52,640 --> 00:27:54,840 Speaker 1: for twenty five three years. We often have dinner together. 473 00:27:55,160 --> 00:27:57,119 Speaker 1: I agree with him on so many things. This is 474 00:27:57,160 --> 00:28:01,000 Speaker 1: one we fundamentally disagree about. I think we are just 475 00:28:01,119 --> 00:28:04,840 Speaker 1: in the early stages of the biggest set of innovations 476 00:28:05,000 --> 00:28:09,879 Speaker 1: ever to hit humanity. Probably and Uh, it's going to 477 00:28:10,560 --> 00:28:13,640 Speaker 1: affect almost every industry. But it's hard to make those 478 00:28:13,720 --> 00:28:16,200 Speaker 1: kinds of predictions just by looking at economic data. The 479 00:28:16,280 --> 00:28:18,639 Speaker 1: recent data I've been I think kind of disappointing. When 480 00:28:18,680 --> 00:28:20,720 Speaker 1: it comes to productivity. You have to look at the 481 00:28:20,800 --> 00:28:23,840 Speaker 1: underlying technology, like the examples they just described to you, 482 00:28:24,200 --> 00:28:26,880 Speaker 1: and when I look at them, I see almost every 483 00:28:26,960 --> 00:28:30,320 Speaker 1: part of the economy being transformed. Eric Jolson, thank you 484 00:28:30,440 --> 00:28:45,440 Speaker 1: so much for the Massachusetts Institute of Technology. We now 485 00:28:45,560 --> 00:28:50,000 Speaker 1: turn to UH Professor Scott Sashnik. Uh not in Minnesota, 486 00:28:50,080 --> 00:28:52,040 Speaker 1: he's in New York, co host of Bloomberg Business of 487 00:28:52,080 --> 00:28:56,040 Speaker 1: Sports on Bloomberg Radio eight pm tonight eleven a m Saturday. 488 00:28:56,080 --> 00:28:59,880 Speaker 1: As we staggered a Sunday in the Super Bowl, Scott is, 489 00:29:00,000 --> 00:29:01,480 Speaker 1: we get to your guests and you know the way 490 00:29:01,520 --> 00:29:04,000 Speaker 1: you're taking it. This year, I was in London and 491 00:29:04,200 --> 00:29:06,080 Speaker 1: I didn't have the football game, so I watched the 492 00:29:06,160 --> 00:29:09,880 Speaker 1: highlights on YouTube, which is incredible, like twelve minutes of 493 00:29:10,160 --> 00:29:13,640 Speaker 1: both teams highlights. It wasn't like sappy highlights, and I 494 00:29:13,840 --> 00:29:17,880 Speaker 1: was blown away by the execution of the Patriots. Are 495 00:29:17,960 --> 00:29:21,840 Speaker 1: these patriots different than the old Patriots? Look at you 496 00:29:22,000 --> 00:29:24,080 Speaker 1: like a millennial, Like if I didn't know you, if 497 00:29:24,120 --> 00:29:26,000 Speaker 1: I wasn't looking at you right now, Like how old 498 00:29:26,120 --> 00:29:28,480 Speaker 1: is Tom? If you like twenty four? But but but 499 00:29:28,600 --> 00:29:32,920 Speaker 1: I watched I think they're great. YouTube highlights twelve minutes 500 00:29:33,000 --> 00:29:35,680 Speaker 1: long of every key playing. But now that this is 501 00:29:35,720 --> 00:29:41,120 Speaker 1: not a different Patriots team, this is really a testament 502 00:29:42,040 --> 00:29:45,080 Speaker 1: to what they do. If you think it's lucky, or 503 00:29:45,120 --> 00:29:48,160 Speaker 1: if you think precisely that this is just Tom Brady 504 00:29:48,240 --> 00:29:50,000 Speaker 1: that had the best quarterback in the NFL, So you 505 00:29:50,080 --> 00:29:52,720 Speaker 1: can do this great stat Michael Barr and I talked 506 00:29:52,720 --> 00:29:57,920 Speaker 1: about on the show, eighteen undrafted free agents are on 507 00:29:58,120 --> 00:30:00,600 Speaker 1: this team. Now, if you know about the NFL and 508 00:30:00,680 --> 00:30:03,520 Speaker 1: how tight you have to manage the salary cap, if 509 00:30:03,640 --> 00:30:07,440 Speaker 1: you can get eight teen players, which is an enormous 510 00:30:07,560 --> 00:30:10,600 Speaker 1: sum on your roster who are undrafted free agents, you 511 00:30:10,680 --> 00:30:13,560 Speaker 1: don't have to pay those guys the big bucks. Those 512 00:30:13,600 --> 00:30:17,080 Speaker 1: are guys who pay play for just a paltry amount, 513 00:30:17,120 --> 00:30:20,120 Speaker 1: so you can then do other things. But the execution 514 00:30:20,440 --> 00:30:23,120 Speaker 1: of it, if to a non football person like me, 515 00:30:23,880 --> 00:30:27,120 Speaker 1: is it unique to the Patriots? Is it the new profits? 516 00:30:27,160 --> 00:30:29,600 Speaker 1: What's unique? Which is what is unique to the Patriots 517 00:30:29,720 --> 00:30:32,800 Speaker 1: is the motto of do your job. They bring in 518 00:30:33,560 --> 00:30:36,959 Speaker 1: players who may not be the fastest, the biggest, the whatever, 519 00:30:37,240 --> 00:30:40,600 Speaker 1: but they had a unique skill set, one skill that 520 00:30:40,760 --> 00:30:43,240 Speaker 1: that team needs at that position and Michael Barr. This 521 00:30:43,440 --> 00:30:48,400 Speaker 1: is unlike the Detroit Lions. Oh yes, gosh, yes, the 522 00:30:48,640 --> 00:30:51,440 Speaker 1: New England Patriots. That's why they got guys like Mike 523 00:30:51,480 --> 00:30:54,480 Speaker 1: Gilliesslie where they can find the talent from other teams 524 00:30:54,680 --> 00:30:57,239 Speaker 1: and say, hey wait, they're not done yet, and they 525 00:30:57,360 --> 00:30:59,760 Speaker 1: find these running backs and they're very good at it. 526 00:31:00,240 --> 00:31:03,280 Speaker 1: So you want to jump in on this conversation, I 527 00:31:03,320 --> 00:31:06,840 Speaker 1: mean with experts like here, Like one of my pals 528 00:31:06,880 --> 00:31:09,200 Speaker 1: happens to be one of the best lacrosse players in 529 00:31:09,240 --> 00:31:12,320 Speaker 1: the world, Paul Rabel. He plays an MLL. He's on 530 00:31:12,440 --> 00:31:14,920 Speaker 1: Team USA, but he's a great lacrosse player. And we 531 00:31:15,000 --> 00:31:17,280 Speaker 1: all know Bill Belichick likes lacrosse. His daughter was a 532 00:31:17,320 --> 00:31:19,840 Speaker 1: coach in college. He played. You know what He's told Paul, 533 00:31:20,600 --> 00:31:23,720 Speaker 1: if you want you're smart, you're tough, you're fast. Paul 534 00:31:23,760 --> 00:31:26,240 Speaker 1: has never played football, so you'll be my starting safety 535 00:31:26,320 --> 00:31:28,920 Speaker 1: right now if you want to play football. He recognizes 536 00:31:29,000 --> 00:31:32,960 Speaker 1: the skill set transfers, and he recognizes the intelligence of 537 00:31:33,040 --> 00:31:37,720 Speaker 1: the athlete matters very quickly. As we get to your show, 538 00:31:37,840 --> 00:31:41,360 Speaker 1: one more general question next year is this Belichick's last 539 00:31:41,400 --> 00:31:44,040 Speaker 1: game coaching? Is this where Brady says, enough, boy, I 540 00:31:44,120 --> 00:31:48,680 Speaker 1: know they're downplaying this disagreement stuff. But the offensive coordinators gone, 541 00:31:48,840 --> 00:31:52,080 Speaker 1: the defensive coordinators gone. And perhaps the most telling thing 542 00:31:52,200 --> 00:31:54,440 Speaker 1: is that Bill has let them interview for those jobs 543 00:31:54,520 --> 00:31:57,200 Speaker 1: and has promoted them to those teams for those jobs. 544 00:31:57,480 --> 00:31:59,960 Speaker 1: That's something he's never done before. You have to wonder 545 00:32:00,000 --> 00:32:02,440 Speaker 1: if he wins. I'll do something. Michael Barr tell us 546 00:32:02,480 --> 00:32:04,840 Speaker 1: about the show very quickly. Here tell us about the show. 547 00:32:04,960 --> 00:32:08,640 Speaker 1: We got a guy that's on location experiences the CEO. 548 00:32:09,320 --> 00:32:11,520 Speaker 1: He will be on. He will talk about all the 549 00:32:11,680 --> 00:32:16,120 Speaker 1: behind the scenes stuff, John Collins and what's happening at Minneapolis. 550 00:32:16,320 --> 00:32:19,760 Speaker 1: Michael bar thank you so much. Scott Sashnick. Scott Sashnik, 551 00:32:20,160 --> 00:32:23,040 Speaker 1: co host of Bloomberg Businesses Sports on Bloomberg Radio eight 552 00:32:23,080 --> 00:32:26,840 Speaker 1: pm tonight eleven am Saturdays. Mr sash expends more time 553 00:32:27,320 --> 00:32:30,880 Speaker 1: and unnamed ice hockey rinks and anyone. I know. They 554 00:32:30,920 --> 00:32:32,600 Speaker 1: didn't even tell you who they think is gonna win. 555 00:32:32,960 --> 00:32:36,479 Speaker 1: Oh do excuse me? Come on, we we's gonna win. 556 00:32:37,560 --> 00:32:40,800 Speaker 1: I cannot and let see going against the Patriots. Okay, 557 00:32:40,960 --> 00:32:43,120 Speaker 1: Scott sas thank you so much. Michael Barr, thank you. 558 00:32:43,320 --> 00:32:46,560 Speaker 1: I know that Detroit Lions are gonna win. Scotch, Michael Barr, 559 00:32:46,640 --> 00:32:57,240 Speaker 1: Andrew stand it one of these years. Thanks for listening 560 00:32:57,360 --> 00:33:01,240 Speaker 1: to the Bloomberg Saveillance podcast. Subscribe right and listen to 561 00:33:01,440 --> 00:33:07,160 Speaker 1: interviews on Apple Podcasts, SoundCloud, or whichever podcast platform you prefer. 562 00:33:07,720 --> 00:33:11,040 Speaker 1: I'm on Twitter at Tom Keene before the podcast. You 563 00:33:11,080 --> 00:33:14,480 Speaker 1: can always catch us worldwide. I'm Bloomberg Radio