1 00:00:02,400 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:06,960 --> 00:00:09,959 Speaker 2: It's one of the coolest double majors out there with 3 00:00:10,440 --> 00:00:14,320 Speaker 2: massive colonial heritage. You go to William Mary, you show 4 00:00:14,400 --> 00:00:17,480 Speaker 2: up William and Mary. You show up and like you're 5 00:00:17,480 --> 00:00:19,360 Speaker 2: going to take economics. That's what you do if you're 6 00:00:19,400 --> 00:00:23,560 Speaker 2: Seth Carpenter, now Morgan Stanley, but you double barrow with 7 00:00:23,800 --> 00:00:27,680 Speaker 2: French in economics. Was this your mother's idea? 8 00:00:29,200 --> 00:00:32,400 Speaker 3: Good to see you too. In fact, I was a 9 00:00:32,440 --> 00:00:35,840 Speaker 3: French major before I was an economics major. I did 10 00:00:36,200 --> 00:00:38,680 Speaker 3: a bunch of advanced placement classes in high school and 11 00:00:38,720 --> 00:00:41,720 Speaker 3: sort of started right into the sort of advanced classes 12 00:00:42,040 --> 00:00:43,360 Speaker 3: you know, believe it or not. I thought I was 13 00:00:43,400 --> 00:00:48,159 Speaker 3: going to be a lawyer, and someone said sympathies. Somebody 14 00:00:48,200 --> 00:00:49,320 Speaker 3: said to me, you know, if you want to be 15 00:00:49,320 --> 00:00:52,280 Speaker 3: a really good lawyer, develop your analytical skills. Take a 16 00:00:52,280 --> 00:00:56,200 Speaker 3: few economics classes. Can't do you any harm, and you 17 00:00:56,400 --> 00:01:00,000 Speaker 3: just might learn something about analytics. And really a few classes. 18 00:01:00,080 --> 00:01:03,120 Speaker 3: Then I went straight for Eck and I went deep 19 00:01:03,160 --> 00:01:04,880 Speaker 3: into economics and it didn't look back. 20 00:01:05,120 --> 00:01:07,520 Speaker 2: Some of these right minds, which you've had a privilege 21 00:01:07,560 --> 00:01:10,360 Speaker 2: of being with and working with, is an equal. Is 22 00:01:10,360 --> 00:01:12,679 Speaker 2: someone like Richard Claret of Columbia or a guy named 23 00:01:12,680 --> 00:01:16,640 Speaker 2: Bernanki your Princeton, and they have a massive respect for 24 00:01:16,680 --> 00:01:20,720 Speaker 2: the X axis. The financial media is completely driven by 25 00:01:20,840 --> 00:01:24,759 Speaker 2: change in the yxis and all that Ethan Harris leading 26 00:01:24,800 --> 00:01:27,600 Speaker 2: to charge here X Bank of America that we don't 27 00:01:27,600 --> 00:01:29,440 Speaker 2: know where the x axis is and we're going to 28 00:01:29,480 --> 00:01:32,960 Speaker 2: have what mathiness is an as some tote effort a 29 00:01:33,040 --> 00:01:36,920 Speaker 2: glide path out somewhere. Do you have a clue at 30 00:01:36,959 --> 00:01:40,280 Speaker 2: Morgan Stanley where the X axis is for our FED? 31 00:01:41,319 --> 00:01:44,360 Speaker 3: I mean, if I can interpret the xxes here to 32 00:01:44,400 --> 00:01:46,400 Speaker 3: mean the time to mension and sort of how things 33 00:01:46,440 --> 00:01:48,680 Speaker 3: go out over time, I think that's going to be 34 00:01:48,720 --> 00:01:51,800 Speaker 3: the key. We have a pretty strongly held view that inflation, 35 00:01:51,920 --> 00:01:53,800 Speaker 3: for example, is coming down, and so as a result, 36 00:01:53,800 --> 00:01:56,280 Speaker 3: the Fed's going to come down in terms come off 37 00:01:56,280 --> 00:01:59,640 Speaker 3: the peak rate. Exactly when that happens. Getting that timing 38 00:01:59,680 --> 00:02:03,680 Speaker 3: exactly right is tricky. We were very hardened by last 39 00:02:03,680 --> 00:02:07,960 Speaker 3: week's CBI print because we've been telling people from exactly 40 00:02:08,240 --> 00:02:12,440 Speaker 3: inflation's coming down, and we've been getting tons of pushback, left, 41 00:02:12,480 --> 00:02:14,399 Speaker 3: right and center, and then the CPI print came out 42 00:02:14,400 --> 00:02:16,400 Speaker 3: and it made the story at least for a while 43 00:02:16,480 --> 00:02:18,760 Speaker 3: easier to tell. We think there's more to come there, 44 00:02:18,760 --> 00:02:22,120 Speaker 3: but exactly getting the timing right is super hard. 45 00:02:22,680 --> 00:02:27,120 Speaker 1: Tom, the oldest football rivalry in the South, it is 46 00:02:27,120 --> 00:02:30,040 Speaker 1: not Alabama Auburn or Mississippi Georgiana. It is Wayne and 47 00:02:30,120 --> 00:02:32,959 Speaker 1: Mary and the University of Richmond, like one hundred and 48 00:02:33,000 --> 00:02:34,720 Speaker 1: thirty years, so those are rare arrival. 49 00:02:34,840 --> 00:02:37,760 Speaker 2: George Washington was on the sideline exactly exactly. 50 00:02:37,960 --> 00:02:40,600 Speaker 1: He said, how concerned are you and your colleagues are 51 00:02:40,600 --> 00:02:43,080 Speaker 1: moreganctantly about the consumer here because we're hearing more and 52 00:02:43,120 --> 00:02:45,919 Speaker 1: more data that certain folks are doing well out there, 53 00:02:45,960 --> 00:02:48,120 Speaker 1: but a lot of folks aren't. If you don't own 54 00:02:48,160 --> 00:02:50,919 Speaker 1: stocks or bonds or real estate, this inflation thing's hitting 55 00:02:50,919 --> 00:02:52,760 Speaker 1: you really hard. How do you guys think about that? 56 00:02:53,320 --> 00:02:55,200 Speaker 3: No, I think that's exactly right. I think there's a 57 00:02:55,200 --> 00:02:57,400 Speaker 3: lot of heterogeneity. I don't think there's any two ways 58 00:02:57,400 --> 00:03:00,160 Speaker 3: about it. You can see some of the deterioration, and 59 00:03:00,160 --> 00:03:03,120 Speaker 3: in credit conditions, you can start to see credit card 60 00:03:03,160 --> 00:03:06,160 Speaker 3: balances starting to rise after people went through over you know, 61 00:03:06,160 --> 00:03:08,160 Speaker 3: a few years ago, all the excess savings from the 62 00:03:08,160 --> 00:03:11,440 Speaker 3: fiscal transfers. So I think there's no question whatsoever, that 63 00:03:11,480 --> 00:03:15,160 Speaker 3: there is heterogeneity across the consumer, but there's also a 64 00:03:15,160 --> 00:03:18,000 Speaker 3: heterogeneity across what consumers are spending on. So if you 65 00:03:18,040 --> 00:03:21,720 Speaker 3: know we got retail sales, people made a lot about 66 00:03:21,760 --> 00:03:23,639 Speaker 3: that coming in soft. If you look at the first 67 00:03:23,720 --> 00:03:26,040 Speaker 3: quarter where we have all entire quarters worth of GDP 68 00:03:26,200 --> 00:03:31,000 Speaker 3: data for consumer spending, durable goods was negative quarter on quarter, 69 00:03:31,200 --> 00:03:33,600 Speaker 3: Non durables was about flat quarter on quarter. Services was 70 00:03:33,639 --> 00:03:37,000 Speaker 3: holding up. So again, more heterogeneity, and I think that's 71 00:03:37,040 --> 00:03:39,480 Speaker 3: the name of the game when we have what we 72 00:03:39,600 --> 00:03:41,240 Speaker 3: have said for a couple of years is going to 73 00:03:41,240 --> 00:03:43,120 Speaker 3: be a soft landing where we're going to have slowing 74 00:03:43,160 --> 00:03:46,480 Speaker 3: in the economy, We're going to have restraint from monetary policy, 75 00:03:46,520 --> 00:03:49,320 Speaker 3: inflation is going to eventually go away. That's not going 76 00:03:49,360 --> 00:03:53,000 Speaker 3: to be a recipe for everything happening smoothly, uniformly across 77 00:03:53,040 --> 00:03:53,400 Speaker 3: the board. 78 00:03:53,480 --> 00:03:58,160 Speaker 1: Well, then that argues it seems like for cutting rates, now, 79 00:03:58,440 --> 00:04:00,200 Speaker 1: do you think the FET should be cutting rates now 80 00:04:00,440 --> 00:04:02,600 Speaker 1: or is this wait and see approach maybe the best 81 00:04:02,640 --> 00:04:03,080 Speaker 1: way to go. 82 00:04:04,440 --> 00:04:07,560 Speaker 3: A bit of both. So I think they easily could 83 00:04:07,600 --> 00:04:10,440 Speaker 3: have cut rates already a little bit come off the peak. 84 00:04:10,440 --> 00:04:13,080 Speaker 3: I don't think there's any hurry for them to slash rates. 85 00:04:13,240 --> 00:04:15,480 Speaker 3: The economy is not dropping off of a cliff. 86 00:04:15,800 --> 00:04:16,000 Speaker 1: You know. 87 00:04:16,120 --> 00:04:19,360 Speaker 3: Our forecast is still more aggressive than the markets. We're 88 00:04:19,400 --> 00:04:23,320 Speaker 3: looking for three cuts this year starting in September. Again, 89 00:04:23,440 --> 00:04:26,800 Speaker 3: to get back to Tom's point about if the time 90 00:04:26,839 --> 00:04:29,200 Speaker 3: axis is if time is on the X axis, then 91 00:04:29,200 --> 00:04:31,240 Speaker 3: that's where a little bit of the uncertainty is. The 92 00:04:31,279 --> 00:04:35,239 Speaker 3: FED chair Powell his colleagues they saw this strong inflation 93 00:04:35,320 --> 00:04:37,760 Speaker 3: data in the first quarter. They were surprised the upside. 94 00:04:37,760 --> 00:04:40,760 Speaker 3: We were surprised at the upside. Understandably, they said, let's 95 00:04:40,880 --> 00:04:43,680 Speaker 3: make sure that the trend is still down. And so 96 00:04:43,720 --> 00:04:45,280 Speaker 3: I think that helps to explain a little bit of 97 00:04:45,320 --> 00:04:48,240 Speaker 3: the wait and see. But directionally, yea, I think they're 98 00:04:48,279 --> 00:04:50,160 Speaker 3: actually they're fine to come off of the peak. 99 00:04:50,440 --> 00:04:57,120 Speaker 2: The heterogeneity. Do we underestimate productivity, but it's efficacy to 100 00:04:57,160 --> 00:05:00,800 Speaker 2: the haves versus its efficacy to the not to me. 101 00:05:00,920 --> 00:05:04,360 Speaker 2: That's original territory out. We need to study that out 102 00:05:04,440 --> 00:05:05,000 Speaker 2: five years. 103 00:05:05,320 --> 00:05:08,039 Speaker 3: So I don't think I disagree. I think there's clearly 104 00:05:09,320 --> 00:05:11,960 Speaker 3: AI one of the key topics. People are talking about 105 00:05:12,000 --> 00:05:13,960 Speaker 3: it now, people will continue to talk about it for 106 00:05:14,000 --> 00:05:16,480 Speaker 3: a long time. At Morgan Stanley in research, we just 107 00:05:16,520 --> 00:05:18,920 Speaker 3: put out a piece recently. My colleague over in London 108 00:05:18,920 --> 00:05:22,320 Speaker 3: and Stanley pulled all of our equity analysts around the 109 00:05:22,360 --> 00:05:25,400 Speaker 3: globe and said, take each of your individual stocks that 110 00:05:25,480 --> 00:05:28,320 Speaker 3: you cover and let's classify them as enablers of AI, 111 00:05:28,520 --> 00:05:31,839 Speaker 3: as sort of beneficiaries, as maybe people getting disrupted by AI, 112 00:05:32,240 --> 00:05:35,080 Speaker 3: and see what's going on. I think this is categorically 113 00:05:35,400 --> 00:05:37,640 Speaker 3: a topic that's going to drive the narrative for a 114 00:05:37,680 --> 00:05:40,240 Speaker 3: long time, not just through in video, but in video 115 00:05:40,320 --> 00:05:42,800 Speaker 3: is clearly clearly part of it. And so then the 116 00:05:42,880 --> 00:05:45,599 Speaker 3: question becomes who wins and how do they win? And 117 00:05:45,640 --> 00:05:50,360 Speaker 3: I think returns to capital, returns to some companies are 118 00:05:50,400 --> 00:05:53,799 Speaker 3: going to stay very very strong, and to your point, Tom, 119 00:05:54,400 --> 00:05:56,440 Speaker 3: that's not those returns are not going to be shared 120 00:05:56,480 --> 00:05:58,400 Speaker 3: uniformly across the income distribution. 121 00:05:58,680 --> 00:06:03,600 Speaker 1: Do you think that makes the global economy more productive? 122 00:06:03,800 --> 00:06:05,599 Speaker 1: And is there a way to measure that? Is that 123 00:06:05,680 --> 00:06:08,479 Speaker 1: going to GDP forecasts or inflation forecasts? 124 00:06:08,560 --> 00:06:11,600 Speaker 3: I think great set of questions. I think it's hard 125 00:06:11,600 --> 00:06:14,720 Speaker 3: to believe that it will not make things more productive. 126 00:06:14,720 --> 00:06:16,320 Speaker 3: And the way I like to think about it is 127 00:06:16,960 --> 00:06:19,240 Speaker 3: I'm doing a forecast. There's a lot of uncertainty. I 128 00:06:19,240 --> 00:06:22,080 Speaker 3: can think of different possible outcomes, and you can put 129 00:06:22,080 --> 00:06:24,360 Speaker 3: different probabilities on those outcomes. But I kind of see 130 00:06:24,360 --> 00:06:27,640 Speaker 3: either AI is kind of not people make people more productive, 131 00:06:27,680 --> 00:06:29,640 Speaker 3: or it will make people more productive, and the average 132 00:06:29,640 --> 00:06:33,159 Speaker 3: of zero and something positive is positive. So I think directionally, 133 00:06:33,200 --> 00:06:36,880 Speaker 3: it's pretty clear. The time horizon is hard. The measurement 134 00:06:36,880 --> 00:06:38,960 Speaker 3: of it is very very hard. So one of the 135 00:06:39,200 --> 00:06:45,080 Speaker 3: favorite examples people love is about call centers. Right, So 136 00:06:45,160 --> 00:06:47,400 Speaker 3: I remember last summer, We're coming into the summer season. 137 00:06:47,400 --> 00:06:50,200 Speaker 3: This time last year, I was booking our family travel 138 00:06:50,279 --> 00:06:53,000 Speaker 3: to Europe and it was a disaster, and I was 139 00:06:53,000 --> 00:06:55,679 Speaker 3: on the phone on two different occasions for two hours straight. 140 00:06:56,839 --> 00:06:59,520 Speaker 3: You can imagine AI at its glory could take that 141 00:06:59,560 --> 00:07:02,800 Speaker 3: down to five minutes. And if everybody, every customer goes 142 00:07:02,839 --> 00:07:06,080 Speaker 3: from two hours to five minutes, every single person involved 143 00:07:06,120 --> 00:07:09,279 Speaker 3: will say that's higher productivity. But if they don't change 144 00:07:09,680 --> 00:07:11,440 Speaker 3: the number of workers, if they don't change the number 145 00:07:11,440 --> 00:07:13,720 Speaker 3: of flights that get sold, I'm really not clear that's 146 00:07:13,720 --> 00:07:15,760 Speaker 3: going to show up at all in the GDP data. 147 00:07:16,080 --> 00:07:17,600 Speaker 3: And yet it's clearly going to help things. 148 00:07:17,640 --> 00:07:20,120 Speaker 2: All right, we got to have you come back next time. 149 00:07:20,320 --> 00:07:23,040 Speaker 2: Drags Zettner along with you. You two are in speaking. 150 00:07:22,760 --> 00:07:25,440 Speaker 3: Terms, not just that we have our offices next to 151 00:07:25,480 --> 00:07:26,920 Speaker 3: each other and we talk every single time. 152 00:07:26,960 --> 00:07:29,120 Speaker 2: So you have to talk phishing with her. You have 153 00:07:29,160 --> 00:07:29,720 Speaker 2: to do drug. 154 00:07:29,920 --> 00:07:31,160 Speaker 3: I listen. That's why I listen. 155 00:07:31,240 --> 00:07:34,520 Speaker 2: We'll do a half hour or even three blocks. Brings 156 00:07:34,560 --> 00:07:36,640 Speaker 2: Zentner along with you next time. That's it gonna be 157 00:07:36,680 --> 00:07:39,680 Speaker 2: a great conversation. I got like ten more questions or 158 00:07:39,680 --> 00:07:43,360 Speaker 2: didn't even get to Seth Carpenter drives economics. It's the 159 00:07:43,400 --> 00:07:46,000 Speaker 2: new Morgan Stanley. Thank you so much.