WEBVTT - Tariffs, The Fed, and Macro Focus with Morgan Stanley’s Ellen Zentner 0:00:02.520 --> 0:00:11.879 Bloomberg Audio Studios, podcasts, radio news. This is Masters in 0:00:11.960 --> 0:00:15.480 Business with Barry Ritholts on Bloomberg Radio. 0:00:16.440 --> 0:00:19.319 This week on the podcast what Can I Say? Tour 0:00:19.400 --> 0:00:24.200 de forced conversation about all things economic with Ellen Zettner. 0:00:24.880 --> 0:00:28.760 She's been at Morgan Stanley for just about a decade 0:00:28.840 --> 0:00:30.200 now better part of a decade. 0:00:31.640 --> 0:00:33.320 She was chief Economist. 0:00:33.960 --> 0:00:39.080 She has morphed into the Chief Economic Strategist and global 0:00:39.080 --> 0:00:43.400 head of thematic and macro investing for Morgan Stanley Wealth Management. 0:00:43.880 --> 0:00:47.320 The firm runs something crazy number like seven trillion dollars. 0:00:47.640 --> 0:00:50.840 She's also a member of the firm's Global Investment Committee. 0:00:51.080 --> 0:00:56.319 She's won every accolade and economic award you can as 0:00:56.320 --> 0:01:00.800 a Wall Street economist, and her interest just rangers far 0:01:00.840 --> 0:01:05.200 and wide. We talk about everything from tariffs to fit 0:01:05.319 --> 0:01:10.560 independence to data integrity at the BLS. She's just a 0:01:10.840 --> 0:01:16.880 very thoughtful, insightful economist who spends a lot of time 0:01:17.080 --> 0:01:20.600 thinking about how can I fashion this information in a 0:01:20.640 --> 0:01:25.160 way that will be useful for my clients, many of 0:01:25.200 --> 0:01:30.240 whom are investors, And now in her new role at 0:01:30.280 --> 0:01:35.000 Morgan Stanley Wealth Management, she becomes the client she's helping 0:01:35.040 --> 0:01:37.840 to run that big pile of money. I thought this 0:01:37.880 --> 0:01:41.720 conversation was absolutely fascinating, and I think you will also 0:01:41.920 --> 0:01:47.120 with no further ado my discussion with Morgan Stanley's Allen Zettner. 0:01:47.360 --> 0:01:49.800 Hi, Barry, thanks for having me. I'm really glad that 0:01:49.840 --> 0:01:53.800 you got my title correct and without losing your breath 0:01:53.800 --> 0:01:54.840 because it's a long one. 0:01:54.920 --> 0:01:57.840 Well, you know, AI helped me assemble that, and I 0:01:57.920 --> 0:02:00.440 know that's a theme of yours, so well, we'll get 0:02:00.440 --> 0:02:03.560 that to that a little later. It's been it's been 0:02:03.880 --> 0:02:06.480 a while since we had you on the last time 0:02:06.480 --> 0:02:09.920 you hear it was the first Trump administration. We're going 0:02:10.000 --> 0:02:13.519 to talk about a lot of policy issues, but before 0:02:13.520 --> 0:02:15.239 we get there, I just want to talk a little 0:02:15.280 --> 0:02:19.000 bit about your background because it's so interesting and not 0:02:19.160 --> 0:02:22.320 what we think of as the typical path to Wall Street. 0:02:22.639 --> 0:02:26.000 You get a bachelor's and an MBA from the University 0:02:26.080 --> 0:02:28.919 of Colorado. What was the original career planning. 0:02:28.960 --> 0:02:33.600 Yeah, bachelor's and masters from Denver, University of Colorado at Denver, 0:02:33.960 --> 0:02:37.679 which I think surprises people even more. Yeah, so I 0:02:39.080 --> 0:02:42.440 had gotten a late start, as I would put it, 0:02:42.480 --> 0:02:47.919 with the university. After high school, I was partying, having 0:02:47.960 --> 0:02:51.000 a great time gap year it was well, it turned 0:02:51.000 --> 0:02:52.560 out to be an unplanned gap year. 0:02:53.040 --> 0:02:54.280 And you know, in. 0:02:54.280 --> 0:02:56.560 The state of Texas, there's a lot of room. You 0:02:56.600 --> 0:02:58.880 don't need to live at home, and at least back 0:02:58.919 --> 0:03:00.520 then you didn't need to live at home in order 0:03:00.560 --> 0:03:03.280 to afford you know, you could afford to live. 0:03:03.160 --> 0:03:03.680 On your own. 0:03:04.120 --> 0:03:06.160 So I remember turning eighteen and my mother looked at 0:03:06.160 --> 0:03:08.440 her watch and basically said, why are you still here? 0:03:09.320 --> 0:03:11.480 And so I moved out with my friends. Was just 0:03:11.520 --> 0:03:14.240 having a great time. And so by the time I 0:03:14.320 --> 0:03:16.640 decided to get serious and said, hey, you know I 0:03:16.680 --> 0:03:20.720 want to I want to go somewhere else for university. 0:03:22.000 --> 0:03:26.080 I was starting university when my friends were graduating, and 0:03:26.160 --> 0:03:28.919 so I wanted a commuter campus, and University of Colorado 0:03:28.919 --> 0:03:32.120 Denver was just a phenomenal place to be with an 0:03:32.160 --> 0:03:33.880 amazing economics department. 0:03:34.400 --> 0:03:38.520 So Texas girl up in Denver. How to be a 0:03:38.520 --> 0:03:40.000 climate shock to you? 0:03:40.280 --> 0:03:40.600 It was? 0:03:40.680 --> 0:03:41.720 It was a little strange. 0:03:41.760 --> 0:03:45.600 So we had registered side unseen my parents and I 0:03:45.680 --> 0:03:49.480 we drove up the fifteen hour drive from Austin, Texas 0:03:49.560 --> 0:03:52.640 to Denver. The first twelve hours are in the state 0:03:52.680 --> 0:03:55.080 of Texas and then you finally get out of the state. 0:03:55.440 --> 0:03:57.560 That's that's starting in the middle. 0:03:57.680 --> 0:04:02.520 That wait, so New York to cut Texas to Colorado, 0:04:02.640 --> 0:04:07.000 Austin to Denver, Boston to Denver, fifteen hours, eighty percent 0:04:07.040 --> 0:04:08.840 of which are still in the stot are still in. 0:04:08.880 --> 0:04:09.520 The state of Texas. 0:04:09.680 --> 0:04:12.960 So you go through one tiny corner called Ratone Pass. 0:04:13.240 --> 0:04:17.160 That's where my Texas comes out. Rattone Pass right there 0:04:17.200 --> 0:04:20.000 where Colorado and New Mexico and Texas come together, and 0:04:20.040 --> 0:04:23.479 you just slip right through into Colorado. And so we 0:04:23.600 --> 0:04:28.080 registered side unseen. My mother woke me up. I was 0:04:28.080 --> 0:04:31.159 sleeping in the backseat of the car, and she said, Ellen, 0:04:31.279 --> 0:04:33.320 look and I woke up and I looked out of 0:04:33.360 --> 0:04:36.240 the window and I saw the mountains, and I was like, Mama, 0:04:36.360 --> 0:04:37.000 I'm home. 0:04:37.480 --> 0:04:39.120 I had never seen mountains before. 0:04:39.240 --> 0:04:40.680 Had you seen snow before? 0:04:41.400 --> 0:04:43.800 I had seen snow in Austin once every six years 0:04:43.800 --> 0:04:46.760 on average, it snowed. And so we made a snowman 0:04:46.839 --> 0:04:50.239 with a lot of rocks and sticks in it and leaves, 0:04:50.880 --> 0:04:53.599 but it was a snowman. But my mother had spent 0:04:53.720 --> 0:04:58.000 summers in Boulder. So my grandfather taught. Both my grandparents 0:04:58.080 --> 0:05:01.039 taught at University of Texas. My grandmother got her PhD 0:05:01.120 --> 0:05:04.599 from Cornell in the early thirties. My grandfather got his 0:05:04.640 --> 0:05:07.599 PhD from Columbia here in New York. They were both 0:05:07.640 --> 0:05:10.239 teaching at the University of Texas. He founded the physical 0:05:10.360 --> 0:05:15.360 education department at the University of Texas, and so here 0:05:15.400 --> 0:05:18.720 was a legacy. My mother grew up spending summers living 0:05:18.760 --> 0:05:21.920 in the dorm in Boulder because he would teach summers 0:05:22.080 --> 0:05:25.800 at University of Colorado and Boulder, and so she always 0:05:25.800 --> 0:05:28.640 talked about the mountains. And just when I decided to 0:05:29.160 --> 0:05:33.040 leave Texas for school, I said, that's where I want 0:05:33.080 --> 0:05:34.760 to go, is the mountains, even though I had no 0:05:34.800 --> 0:05:36.159 idea exactly what I was saying. 0:05:36.440 --> 0:05:40.039 But you ended up not leaving Texas permanently. After you 0:05:40.040 --> 0:05:44.960 get your MBA Revenu Estimating Division at the Texas State 0:05:45.120 --> 0:05:48.840 Controller's Office, working with some guy named George W. 0:05:49.000 --> 0:05:51.240 Bush, tell ye, tell us a little bit about this 0:05:51.320 --> 0:05:52.880 guy that used to be the governor of the state 0:05:52.920 --> 0:05:54.120 of Texas, you know. 0:05:55.360 --> 0:05:56.359 But no, that was great. 0:05:56.440 --> 0:06:00.960 So I got my master's degree in economic and said, well, 0:06:01.080 --> 0:06:03.479 what do I do now? And so made sense to 0:06:03.520 --> 0:06:06.360 go back home to Austin. Now, at that time, for economists, 0:06:06.760 --> 0:06:08.760 your option was to work for the state, or you 0:06:08.760 --> 0:06:10.960 could work for a u TEMCO, which is University of 0:06:10.960 --> 0:06:13.280 Texas Investment arm Like there's not a lot of areas 0:06:13.279 --> 0:06:18.799 for economists. Then now there's a thriving investment community, hedge funds, 0:06:18.839 --> 0:06:21.359 you name it. But then you worked for the state, 0:06:21.880 --> 0:06:26.480 and so it was a great way to start. Texas 0:06:26.600 --> 0:06:29.080 legislature is a binding a legislature. It's only in session 0:06:29.160 --> 0:06:33.359 in odd years. So I think I worked really really 0:06:33.400 --> 0:06:36.760 hard for five months every other year, and it was 0:06:36.800 --> 0:06:38.080 a wonderful, wonderful way. 0:06:38.960 --> 0:06:41.760 The rest of the time. Let's see, in the. 0:06:41.760 --> 0:06:45.680 Late nineties, there was this thing called day trading with 0:06:45.720 --> 0:06:48.240 no restrictions in a firm. You just sort of like 0:06:48.320 --> 0:06:50.360 have fun and be like, oh, I made a few 0:06:50.400 --> 0:06:53.640 thousand dollars today day trading. No, it was it was 0:06:53.640 --> 0:06:56.760 sort of a let's let's put it this way. It 0:06:56.800 --> 0:06:59.120 was a wonderful way to start where I could really 0:06:59.200 --> 0:07:02.520 dive deep into topics such as studying the fairness of 0:07:02.560 --> 0:07:06.640 the tax system in the state of Texas, doing economic 0:07:06.720 --> 0:07:09.600 development studies. We were a part of the study that 0:07:09.640 --> 0:07:13.040 helped attract the first Toyota tundra plant to the state 0:07:13.080 --> 0:07:17.120 of Texas in San Antonio and working for Tamra Ploute, 0:07:17.120 --> 0:07:23.720 who was just so important in steering my career. 0:07:23.880 --> 0:07:24.760 She was the chief. 0:07:24.520 --> 0:07:27.200 Economist for the State of Texas at the time PhD 0:07:27.240 --> 0:07:30.960 from University of Pennsylvania. You mentioned the Lawrence Arkline Award. 0:07:31.320 --> 0:07:34.960 It was such an honor to receive that twice because 0:07:36.320 --> 0:07:39.960 Tamar had studied under Lawrence Klin at University of Pennsylvania, 0:07:40.360 --> 0:07:43.560 and so it was just being thrown into a macro 0:07:43.800 --> 0:07:50.000 role was such a huge determinant of my entire career 0:07:50.160 --> 0:07:53.320 and studying things like household behavior in the state of Texas, 0:07:53.480 --> 0:07:57.000 which gave me my love for the consumer and household behavior, 0:07:57.040 --> 0:07:59.680 which has lasted my whole career. So I lasted there 0:07:59.680 --> 0:08:01.920 for about five years and then started looking for something 0:08:01.920 --> 0:08:02.200 in New. 0:08:02.200 --> 0:08:05.760 York, and consumer and household behavior lasted your whole career 0:08:06.280 --> 0:08:09.720 to good effect and good result, because as we've seen 0:08:09.800 --> 0:08:13.760 over the past fifty years, the US consumers what drives 0:08:13.760 --> 0:08:16.720 the entire economy. So being an expert in that space, 0:08:17.160 --> 0:08:20.160 I can't imagine that hurt your either your career hasn't hurt, 0:08:20.320 --> 0:08:21.520 or your economic forecast. 0:08:21.560 --> 0:08:25.560 And I've propelled many an economist off of the back 0:08:25.680 --> 0:08:28.320 of bringing them onto my team and saying, here you go, 0:08:28.440 --> 0:08:31.440 here's a huge consumer platform, learn it and run it. 0:08:31.840 --> 0:08:34.640 And they have gone on to do amazing things. One 0:08:34.679 --> 0:08:38.200 of them still with me at Morgan Stanley. Paula Campbell Roberts. 0:08:38.320 --> 0:08:42.080 One of my shining, shining achievements in my career is 0:08:42.120 --> 0:08:45.360 seeing her career at KKR flourish. 0:08:45.400 --> 0:08:49.280 That's really interesting. So how do you go from the 0:08:49.280 --> 0:08:53.000 Revenue Estimating Division in the Texas government to Bank of 0:08:53.080 --> 0:08:57.120 Tokyo Mitsubishi on Wall Street. That seems like a big jump. 0:08:57.240 --> 0:08:58.120 It is a big jump. 0:08:58.600 --> 0:09:05.160 So part of it was that I felt State government 0:09:05.240 --> 0:09:07.079 was not where I wanted to be for the long run. 0:09:07.559 --> 0:09:11.200 There's something about uh something in my DNA, as it 0:09:11.240 --> 0:09:13.440 is with many people in finance, that attracts me to 0:09:13.720 --> 0:09:17.880 just a fast moving environment. I needed something that was 0:09:18.040 --> 0:09:18.840 much more. 0:09:18.960 --> 0:09:21.440 Dynamic and not closed every other year. 0:09:21.679 --> 0:09:26.040 Yeah, not closed every other year, although I do sometimes 0:09:26.080 --> 0:09:29.199 long for the boring days of working at the State. 0:09:29.960 --> 0:09:32.920 Uh So, I knew that I needed. 0:09:32.679 --> 0:09:36.920 To go to either a d C or Chicago or 0:09:36.960 --> 0:09:41.600 in New York. I wasn't quite sure where. And so 0:09:41.640 --> 0:09:45.240 while I was job searching, which back then involved looking 0:09:45.280 --> 0:09:48.800 in the newspapers or which is going to sound I mean, 0:09:48.840 --> 0:09:49.880 people are just being like. 0:09:52.080 --> 0:09:54.120 Mailing them, so many of them. 0:09:55.120 --> 0:09:58.960 But also, you know, I have a long, rich history 0:09:59.000 --> 0:10:03.520 now with the National Association for Business Economics and their 0:10:03.600 --> 0:10:07.600 jobs Board, which was extremely antiquated then. Well didn't seem 0:10:07.640 --> 0:10:10.000 antiquated back then. People would be appalled at that job's 0:10:10.040 --> 0:10:12.960 board now. But I actually found my job at. 0:10:12.920 --> 0:10:14.679 Bank of Tokyo Mitsubishi. 0:10:15.760 --> 0:10:19.439 Through the NABE Jobs Board, which is still econjobs dot org. 0:10:20.040 --> 0:10:24.560 And so I think of Nabe as being my partner 0:10:24.600 --> 0:10:27.760 in my career since I joined Nabe in the late nineties. 0:10:28.640 --> 0:10:32.280 Long story short, I get this great job at Bank 0:10:32.320 --> 0:10:39.600 of Tokyo Mitsubishi. The as the senior economists there, I 0:10:39.720 --> 0:10:45.680 basically was a one man band, which was great because 0:10:45.720 --> 0:10:49.679 I had to wear every hat as economists for smaller 0:10:49.679 --> 0:10:53.680 institutions or with smaller research arms have to do. And 0:10:53.880 --> 0:10:55.760 what's so interesting about my time there, and I was 0:10:55.800 --> 0:11:00.640 there for eight years, is that during that time the 0:11:00.679 --> 0:11:04.320 financial crisis hit and I felt so lucky to be 0:11:04.320 --> 0:11:06.199 at a Japanese firm at that time because we had 0:11:06.240 --> 0:11:11.679 not taken part in mortgage backed security investing. We had 0:11:11.679 --> 0:11:15.400 already gone through a financial crisis of our own that 0:11:15.440 --> 0:11:18.560 had lasted a long time. Japanese firms were sitting on 0:11:18.600 --> 0:11:21.240 a pile of cash, and it was at that time 0:11:21.760 --> 0:11:27.160 that the ceremonial check was walked across Broadway to purchase 0:11:27.440 --> 0:11:31.040 twenty percent of Morgan Stanley to keep Morgan Stanley. 0:11:30.720 --> 0:11:36.600 Afloat from banks from from MUFG, which the check is 0:11:36.600 --> 0:11:38.800 written from Bank of Tokyo Mitsubishi. 0:11:39.400 --> 0:11:41.040 So that happened. 0:11:41.800 --> 0:11:45.960 And what was interesting was when I eventually ended up 0:11:45.960 --> 0:11:48.000 at Morgan Stanley to hear what it was like from 0:11:48.000 --> 0:11:52.040 my colleagues from the other side on a Friday, being told, 0:11:52.280 --> 0:11:53.800 you know, go home and we'll let you know on 0:11:53.840 --> 0:11:56.000 Sunday if you still have a job, if the doors 0:11:56.000 --> 0:11:58.200 are going to be open, and then being told on 0:11:58.240 --> 0:12:00.959 Sunday that you can go back to work, and the 0:12:01.040 --> 0:12:05.880 fear that they felt versus I didn't feel total job 0:12:05.920 --> 0:12:08.040 security because I for the first time I was seeing 0:12:08.080 --> 0:12:12.200 economics teams just on the whole, just being cut and 0:12:12.240 --> 0:12:14.360 you had never seen that poor. The economists are sort of, 0:12:14.720 --> 0:12:18.680 you know, we're kind of we've got decent job security 0:12:18.720 --> 0:12:20.200 compared to the rest in finance. 0:12:21.160 --> 0:12:23.640 But sorry. 0:12:23.679 --> 0:12:25.400 This is when I could make a joke about certain 0:12:25.440 --> 0:12:26.800 news that came out after. 0:12:27.960 --> 0:12:32.040 Free but no I didn't. But anyhow, what I. 0:12:32.040 --> 0:12:37.680 Really so vividly remember, similar to you, I was in 0:12:37.720 --> 0:12:41.920 an institution that, through a combination of dumb luck and 0:12:41.960 --> 0:12:44.280 what have you, was on the right side of that. 0:12:44.679 --> 0:12:47.800 So while the street was freaking out, I didn't feel 0:12:47.840 --> 0:12:51.480 personally the same job in security of pressure that everybody 0:12:51.520 --> 0:12:55.440 else did. But I had maintained an email list of 0:12:56.160 --> 0:13:02.400 ten or fifteen thousand readers, and most of the addresses 0:13:02.440 --> 0:13:07.720 were you know, MS dot com, mL dot com, whatever, 0:13:07.760 --> 0:13:13.400 the various institutional and you know, you would occasionally have 0:13:13.559 --> 0:13:16.680 somebody leave a position and you would have a bounce 0:13:16.760 --> 0:13:21.640 back rate each week of two three emails, but eight 0:13:21.760 --> 0:13:24.880 or nine I was seeing like three hundred, four hundred, 0:13:25.040 --> 0:13:28.360 five hundred emails a week come back. This is no 0:13:28.440 --> 0:13:31.679 longer a valid email address at GS dot com or 0:13:31.760 --> 0:13:32.640 whatever it happened it was. 0:13:32.760 --> 0:13:33.800 It was really alarming. 0:13:34.160 --> 0:13:37.800 It very like that was nothing I've ever experienced. Even 0:13:37.920 --> 0:13:42.439 two thousand, which seemed like it was a disaster, didn't 0:13:42.480 --> 0:13:43.040 compare to this. 0:13:43.200 --> 0:13:46.440 Yeah, yeah, so never experienced anything like it, And so, 0:13:48.559 --> 0:13:52.040 and you know, I really think that that's when LinkedIn 0:13:52.120 --> 0:13:54.840 took off because I had signed up for LinkedIn at 0:13:54.840 --> 0:13:57.880 the time but didn't use it. I'm still not a 0:13:57.920 --> 0:14:00.160 huge fan of social media. I know that's terrible to say. 0:14:00.160 --> 0:14:01.880 How can anybody be successful today with that? 0:14:02.320 --> 0:14:03.080 Using social media? 0:14:03.160 --> 0:14:05.719 I'm going to tell you I think that was a 0:14:05.920 --> 0:14:12.120 formally minority position, like an outlier position, And now I 0:14:12.160 --> 0:14:16.800 think the consensus has built that the algorithm is awful. 0:14:17.120 --> 0:14:22.880 It manipulates us towards outrage. You look at the rising 0:14:22.960 --> 0:14:27.680 levels of depression amongst teenagers. It's really tracks the rise 0:14:27.720 --> 0:14:31.600 of smartphones and social media. So I don't think it's 0:14:31.640 --> 0:14:34.200 as bad a thing to say in twenty twenty five 0:14:34.360 --> 0:14:37.080 more Yeah, But in twenty fifteen people would have looked 0:14:37.080 --> 0:14:38.040 at you like, what do you mean? 0:14:38.080 --> 0:14:39.080 You don't like, what do you mean? 0:14:39.200 --> 0:14:39.360 Yeah? 0:14:39.480 --> 0:14:42.040 And now I think the verdict is in or yeah. 0:14:42.040 --> 0:14:44.160 Well, I think for two thousand and eight. You know, 0:14:44.200 --> 0:14:47.840 in finance, oftentimes the jobs we have, when your time 0:14:47.960 --> 0:14:51.000 is up, you're ripped out of your seat and. 0:14:51.040 --> 0:14:53.240 With the box and a security guard escorting you to 0:14:53.280 --> 0:14:53.760 the time. 0:14:53.800 --> 0:14:57.800 Because you have access to sensitive information like that's how 0:14:57.840 --> 0:15:00.440 for most of us in finance, that's how you're is 0:15:00.440 --> 0:15:05.520 going to look one day, and so if you had 0:15:06.000 --> 0:15:08.760 joined LinkedIn, it was the way that you didn't lose 0:15:08.800 --> 0:15:11.760 all those contacts. And so I really think that's where 0:15:11.760 --> 0:15:14.120 and certainly that's where I was like, Okay, maybe I 0:15:14.120 --> 0:15:17.760 should keep up with people through LinkedIn, but I'll tell 0:15:17.760 --> 0:15:20.560 you that I have learned how to train those algorithms. 0:15:20.920 --> 0:15:24.320 So with Instagram, which I have since dropped all together. 0:15:24.480 --> 0:15:28.400 But when I was on Instagram, I got so tired 0:15:28.960 --> 0:15:33.600 of being marketed to as a fifty plus year old woman. 0:15:34.040 --> 0:15:37.280 It was every single ad was the best mascarra for 0:15:38.400 --> 0:15:41.600 insert you know, or it was the best insert you 0:15:41.640 --> 0:15:44.520 know blank for women over fifty. So it's the best 0:15:44.520 --> 0:15:47.480 mass scare for women over fifty, the best shampoo for 0:15:47.520 --> 0:15:50.240 women over fifty, the best whatever. And it would always 0:15:50.280 --> 0:15:53.400 somehow show this beautiful woman that happened to be over fifty. 0:15:53.680 --> 0:15:56.800 Wait till you're over sixty and just go through your 0:15:56.880 --> 0:15:59.720 spam folder and see you the sort of stuff that 0:15:59.760 --> 0:16:00.440 they marketing. 0:16:00.520 --> 0:16:01.520 Yeah, it's a little insulting. 0:16:01.560 --> 0:16:06.280 But what I did was I saw an ad one 0:16:06.320 --> 0:16:09.120 time for dog food. Now I don't have any pets, 0:16:09.640 --> 0:16:12.320 so I clicked on that ad and it started showing 0:16:12.320 --> 0:16:16.200 me dog food adds. So I stopped purchasing things because 0:16:16.240 --> 0:16:18.800 this was the problem. I'm an impulse buyer, so I 0:16:18.840 --> 0:16:24.480 would purchase things on Instagram and so, but then Instagram started, 0:16:24.520 --> 0:16:26.120 It got my number, It knew what I was doing, 0:16:26.200 --> 0:16:27.560 and so that I thought, okay, I need to click 0:16:27.600 --> 0:16:29.520 on the dog food ad and now poke around in 0:16:29.520 --> 0:16:32.440 that site a little bit, and then okay, I need 0:16:32.440 --> 0:16:33.760 to poke around the side of it and then add 0:16:33.800 --> 0:16:36.400 something to my cart, and then just abandoned it. And 0:16:36.480 --> 0:16:37.840 so for a while I was able to train. If 0:16:37.880 --> 0:16:40.760 I just did that a couple times, then for thirty days, 0:16:40.760 --> 0:16:43.000 I would get dog ads and I easily could continue 0:16:43.040 --> 0:16:44.880 to enjoy Instagram without buying a thing. 0:16:45.760 --> 0:16:48.720 One of the things that has made Facebook so valuable 0:16:49.560 --> 0:16:53.920 is its ability to create not just targeted ads to 0:16:54.080 --> 0:16:57.480 you and your demographics. All right, you're a woman over fifty, 0:16:58.200 --> 0:17:02.560 that's two blunts. They can also track your browsing history. 0:17:02.960 --> 0:17:05.119 They can link it to your zip code. They know 0:17:05.240 --> 0:17:09.560 how your town and county voted in the last election. 0:17:10.560 --> 0:17:14.159 They know your credit score and your purchase history, so 0:17:14.640 --> 0:17:16.920 you could really find you know, the old joke in 0:17:17.000 --> 0:17:21.200 advertising is half of advertising dollars are wasted. We just 0:17:21.280 --> 0:17:24.199 don't know which half. As you bring in more and 0:17:24.240 --> 0:17:28.040 more technology to this, we're starting to figure out exactly 0:17:28.400 --> 0:17:31.040 how to not waste any dollars, which is why some 0:17:31.080 --> 0:17:36.160 of the ads you get are kind of spooky and creepy, like, hey, 0:17:36.480 --> 0:17:39.320 is my phone listening to me? No, Well, whether it 0:17:39.359 --> 0:17:43.879 is or not, your browsing just is so revealing of THEIA. 0:17:43.960 --> 0:17:44.440 And it's true. 0:17:44.480 --> 0:17:46.280 But if you think about it, if we tie that 0:17:46.359 --> 0:17:48.560 back to the old days of just having to send 0:17:48.640 --> 0:17:52.920 out surveys for data and such, you know, as an economist, 0:17:53.640 --> 0:17:57.040 I want as much data as possible. I want it 0:17:57.119 --> 0:18:02.600 to measure everything you could possibly you know, look at sideways, 0:18:03.440 --> 0:18:07.080 and I appreciate having that detailed data. My husband used 0:18:07.119 --> 0:18:09.880 to get irritated because, again, back in the old days, 0:18:09.920 --> 0:18:12.960 when someone might actually call to do a survey, I 0:18:13.040 --> 0:18:14.640 would be the one that would give them the time 0:18:14.640 --> 0:18:17.480 of day and answer the survey because I knew that 0:18:17.760 --> 0:18:22.480 as a practicing economist, I would really appreciate having that detail. 0:18:22.920 --> 0:18:23.400 Instead. 0:18:23.520 --> 0:18:27.560 Now, because it's being done by algorithms and machines and 0:18:27.560 --> 0:18:29.720 there's not a personal call behind it, we're sort of 0:18:29.760 --> 0:18:32.320 alarmed that someone is getting that much information, But it's 0:18:32.359 --> 0:18:35.119 also because a good deal of it's not used to 0:18:35.200 --> 0:18:38.280 make the government more data more accurate, right, It's used 0:18:38.280 --> 0:18:41.879 to make a company more profitable by selling to you. 0:18:42.280 --> 0:18:44.040 So it is a bit different. 0:18:44.119 --> 0:18:47.119 But you know, if the government could employ those techniques 0:18:47.160 --> 0:18:50.840 and give me that kind of detailed data on our population, 0:18:51.600 --> 0:18:53.080 I would use it all day long. 0:18:53.840 --> 0:18:57.840 Coming up, we continue our conversation with Allen Zenner, chief 0:18:57.880 --> 0:19:01.320 economic strategist and global head of Madick and Macro Investing 0:19:01.359 --> 0:19:06.760 at Morgan Stanley, discussing the Mattic Investing and her macro 0:19:06.960 --> 0:19:19.199 work at Morgan Stanley. I'm Barry Dults. You're listening to 0:19:19.359 --> 0:19:23.080 Masters in Business on Bloomberg Radio. Allan Zantner is my 0:19:23.320 --> 0:19:27.600 extra special guest. She's chief economic strategist and global head 0:19:27.960 --> 0:19:32.240 of Thematic and macro Investing from Morgan Stanley Wealth Management. Overall, 0:19:32.280 --> 0:19:36.879 the firm manages over seven trillion dollars. Let's talk a 0:19:36.880 --> 0:19:41.720 little bit about your role at Morgan Stanley. What brought 0:19:41.720 --> 0:19:45.679 you there from? Previously you were at Nomura and Banka 0:19:45.760 --> 0:19:48.600 Tokyo Mitsubishi. What brought you to Morgan Stanley? 0:19:48.880 --> 0:19:52.720 Vincent Reinhardt, Oh really, yeah. 0:19:51.440 --> 0:19:51.520 Of. 0:19:53.480 --> 0:19:56.960 Rein Hart and Rogoff fame well, rhin Hart rein Harten Roguoff. 0:19:57.000 --> 0:19:59.960 So the rhin Harten rogue offf mostly is Carmen Reinhardt. 0:20:01.160 --> 0:20:04.520 And but yeah, Vincent called me up one day and said, 0:20:04.600 --> 0:20:07.520 would you like to come work for me? And I 0:20:08.600 --> 0:20:11.760 us of course I knew him previously. I was an economist, 0:20:12.000 --> 0:20:12.199 you know. 0:20:12.320 --> 0:20:14.240 I mean I knew of him. But did you know 0:20:14.480 --> 0:20:15.440 I knew of him? 0:20:15.680 --> 0:20:18.120 I did not know him on a personal basis, right, 0:20:18.280 --> 0:20:23.119 And it was an absolute surprise to get that call. 0:20:24.680 --> 0:20:27.080 And I couldn't go there fast enough. 0:20:27.200 --> 0:20:27.680 Huh. 0:20:27.720 --> 0:20:30.560 So it wasn't just the Morgan Stanley name, which is 0:20:30.800 --> 0:20:33.800 wonderful to go to a place where just the name 0:20:33.840 --> 0:20:37.000 alone gives you a certain amount of gravitas. I was 0:20:37.040 --> 0:20:40.320 the same economist I was previously doing the same work 0:20:40.320 --> 0:20:44.080 and the same methodologies, employing the same tools. But suddenly 0:20:44.119 --> 0:20:47.439 it was like, oh, she's at Morgan Stanley. So just 0:20:47.600 --> 0:20:54.280 changing the name to such a well respected firm meant 0:20:54.320 --> 0:20:56.119 all the difference in my career. 0:20:56.240 --> 0:20:57.800 But to specifically be able to. 0:20:57.760 --> 0:21:01.280 Go and learn from an economist who sat at the 0:21:01.560 --> 0:21:05.440 at the right hand of Alan Greenspan for so many years, 0:21:06.680 --> 0:21:09.199 you know, being a fed watcher and being able to 0:21:09.240 --> 0:21:13.920 then work for the quintessential fed watcher and sort of 0:21:13.960 --> 0:21:16.800 plug the holes. In my knowledge, it was just an 0:21:16.840 --> 0:21:18.639 opportunity I couldn't pass up. 0:21:18.680 --> 0:21:22.240 What was the role? You obviously didn't start as chief economy. 0:21:21.920 --> 0:21:23.600 I started as his senior economist. 0:21:23.720 --> 0:21:26.159 Oh really? And then how much longer was it before 0:21:26.280 --> 0:21:28.119 you were elevated as a chief economist? 0:21:28.200 --> 0:21:31.560 Oh gosh, about a year and a half. So Vincent 0:21:31.560 --> 0:21:33.280 and I were able to overlap for about a year 0:21:33.280 --> 0:21:35.400 and a half before I took the chief economist role. 0:21:36.400 --> 0:21:38.280 You may or may not know that that he and 0:21:38.359 --> 0:21:42.960 Carmen reside in Boston, and so being able to work 0:21:43.000 --> 0:21:46.679 full time from Boston continue to support Carmen in her 0:21:46.800 --> 0:21:51.679 role at Harvard, and also a role that fits him 0:21:51.720 --> 0:21:55.000 so perfectly well as the chief economist, the financial chief 0:21:55.040 --> 0:21:59.439 economist at Bnymellon is just the perfect place to be. 0:21:59.640 --> 0:22:03.320 So I am very thankful for the time that we 0:22:03.320 --> 0:22:06.520 were able to spend together overlapping there at Morgan Stanley, 0:22:06.920 --> 0:22:10.200 And so in twenty fifteen I then became the chief 0:22:10.320 --> 0:22:11.080 US economist. 0:22:12.040 --> 0:22:15.000 So on the Morgan Stanley website is a little bio 0:22:15.080 --> 0:22:19.000 of you, and in it you described twenty sixteen as 0:22:19.080 --> 0:22:24.120 a very significant and for you personally career defining year. 0:22:24.320 --> 0:22:24.960 Why is that. 0:22:25.760 --> 0:22:28.760 I like to think back of periods in my career 0:22:28.920 --> 0:22:34.119 when my limits were tested, and it might be the 0:22:34.160 --> 0:22:38.200 financial crisis, it might be some other recession, it might 0:22:38.200 --> 0:22:42.000 have been COVID, But certainly twenty sixteen we had a 0:22:42.000 --> 0:22:46.920 presidential election year and my limits were absolutely tested, both 0:22:46.960 --> 0:22:52.159 physically and mentally. So I had gone to DC the 0:22:52.200 --> 0:22:56.439 morning of the election. I had already voted in early voting. 0:22:57.560 --> 0:23:01.119 I had left on a sixth flight, which means I 0:23:01.119 --> 0:23:03.440 had to get up at four in the morning, and 0:23:03.960 --> 0:23:07.320 went to DC for meetings. Then I flew on to 0:23:08.040 --> 0:23:13.679 New Orleans to prep for a conference and decided that 0:23:14.000 --> 0:23:17.000 I would go to the gym, as I love to 0:23:17.000 --> 0:23:20.000 do when I'm at the hotel, and then you know, 0:23:20.200 --> 0:23:22.960 buckle down and get ready to watch the fun electional 0:23:23.440 --> 0:23:27.680 results come in, and watching the election results come in, 0:23:27.840 --> 0:23:31.639 and then answering client questions at the same time, and 0:23:31.680 --> 0:23:33.520 then seeing all of that unfold in a way that 0:23:33.920 --> 0:23:35.960 was surprising to many people. 0:23:37.560 --> 0:23:43.120 Where this cycle kicked off. Where okay, wait, I thought 0:23:43.119 --> 0:23:44.120 I was going to go to the gym. 0:23:44.160 --> 0:23:45.919 Okay, not going to the gym, Wait, I need to 0:23:46.000 --> 0:23:47.280 order some sort of dinner to the room. 0:23:47.320 --> 0:23:48.080 Okay, I can't beat. 0:23:49.119 --> 0:23:52.119 Then it was then it was oh gosh, Asia is awake. 0:23:52.480 --> 0:23:54.840 Got to get on calls with Asia. Then it was 0:23:55.040 --> 0:23:57.879 oh boy, Europe's waking up. Got to get on calls 0:23:57.920 --> 0:24:03.480 with Europe. Calls with my coll calls with these clients, calls, calls, calls, calls, calls. 0:24:03.640 --> 0:24:06.600 At eleven am in the morning, which was now more 0:24:06.640 --> 0:24:10.120 than twenty four hours later, after I had gotten up, 0:24:11.680 --> 0:24:13.800 I decided that maybe I should at least try to 0:24:13.800 --> 0:24:16.320 close my eyes for a little bit. I closed my eyes, 0:24:16.320 --> 0:24:20.760 couldn't fall asleep. I had to go down stairs at 0:24:20.760 --> 0:24:25.640 the hotel to deliver an economic outlook to what had 0:24:25.680 --> 0:24:29.120 then become a standing room only event, because look what's 0:24:29.200 --> 0:24:32.680 just happened. Let's hear from the economist. And we had 0:24:32.760 --> 0:24:35.280 just putten out put out. We had just put out 0:24:35.320 --> 0:24:37.320 our year ahead outlooks because those come. 0:24:37.240 --> 0:24:37.960 Out in November. 0:24:38.880 --> 0:24:42.080 And so I was there standing at the front of 0:24:42.119 --> 0:24:46.040 the room and I just left my PowerPoint presentation on 0:24:46.320 --> 0:24:49.480 the front page the holding screen as a holding screen, 0:24:49.520 --> 0:24:53.520 and said, let's go ask me whatever questions you have. 0:24:54.240 --> 0:24:56.800 I'm not going to have all the answers, but let's talk, 0:24:57.960 --> 0:25:00.760 and I don't even remember what I said. The time 0:25:00.800 --> 0:25:06.400 flew by. I then went back to the airport, tried 0:25:06.400 --> 0:25:08.960 to get on an earlier flight to go back, was 0:25:09.000 --> 0:25:12.720 still delayed. Finally got back at eleven pm at night 0:25:13.280 --> 0:25:16.760 to New York. I could not fall asleep still either 0:25:16.800 --> 0:25:20.080 on the flight or when I got home, and ultimately, 0:25:20.119 --> 0:25:23.040 finally I just gave up sleeping, went into the office, 0:25:23.200 --> 0:25:27.120 and forty two hours I went without sleeping. 0:25:27.520 --> 0:25:30.400 At a certain point, your cognitive functioning just starts to 0:25:30.480 --> 0:25:34.160 fall off a cliff. But that was real. I similarly 0:25:34.200 --> 0:25:38.920 have a vivid recollection of just shock from so many 0:25:38.960 --> 0:25:41.800 people questions that had to be really exciting. 0:25:42.040 --> 0:25:43.880 Yeah, so was it? And see you say exciting. 0:25:43.960 --> 0:25:48.720 Now I live off of that stuff because oh you're adrenaline. Jumpee, adrenaline. 0:25:48.960 --> 0:25:52.159 You're tested, your limits are tested. And what a great 0:25:52.200 --> 0:25:55.200 story to tell. I was also on the trading floor 0:25:55.200 --> 0:25:59.280 at one am when Brexit happened. I had gone to 0:25:59.320 --> 0:26:02.800 sleep at eleven and set the alarm for midnight. The 0:26:02.840 --> 0:26:05.960 alarm went off, I know that my husband immediately checked 0:26:05.960 --> 0:26:09.080 the phone. I heard him say, oh, sh and I 0:26:09.359 --> 0:26:12.399 was like, what what? And I was like, oh my god, 0:26:12.520 --> 0:26:13.840 I had to get in the shower and get to 0:26:13.880 --> 0:26:15.040 the trading floor by one am. 0:26:15.280 --> 0:26:19.480 I just read this morning. Nobody talks about Brexit anymore. 0:26:19.640 --> 0:26:23.000 I just read a data point that shocked me, which 0:26:23.200 --> 0:26:27.720 was the GDP of Italy just pasted the GDP of 0:26:27.840 --> 0:26:33.520 the UK. Mind blown. And there are a lot of reasons, 0:26:33.520 --> 0:26:37.080 but clearly Brexit has to be a significant part of that. Yeah, yeah, 0:26:37.160 --> 0:26:37.879 giant part of that. 0:26:37.920 --> 0:26:40.760 It's like, thank you UK for bringing some business back 0:26:40.800 --> 0:26:43.720 to us, because here's a country that is dying. Their 0:26:43.760 --> 0:26:48.120 birth rates are non existent, their population has been shrinking, 0:26:48.480 --> 0:26:52.679 So how can GDP be growing. There's no fundamental basis 0:26:52.720 --> 0:26:55.040 for it, so it must be some sort of tectonic 0:26:55.080 --> 0:26:56.480 shift like Brexit. 0:26:56.880 --> 0:27:00.359 Pretty pretty fascinating. There's so much stuff. I don't want 0:27:00.400 --> 0:27:05.240 to just get stuck in twenty sixteen. Let's go forward. 0:27:05.320 --> 0:27:07.920 Let's look forward. One of the things you wrote about 0:27:08.320 --> 0:27:12.080 was the coming youth boom economy. And when we look 0:27:12.119 --> 0:27:15.280 at gen z born between ninety seven and twenty twelve, 0:27:16.560 --> 0:27:20.960 they and gen y are going to dominate the US 0:27:21.000 --> 0:27:26.000 economy really in the next ten years or so. They'll 0:27:26.040 --> 0:27:30.240 yield higher consumption. You wrote wages and housing demand, stimulating 0:27:30.280 --> 0:27:33.679 GDP growth. This was a few years ago, do you. 0:27:33.600 --> 0:27:36.160 Still hold to that was in twenty nineteen. 0:27:35.880 --> 0:27:38.119 Yeah, So the youth boom is this still coming? 0:27:38.280 --> 0:27:41.399 Yeah? So we're here, we're in it, and we were 0:27:41.400 --> 0:27:43.960 at the cusp of it. Then Millennials were already starting 0:27:43.960 --> 0:27:46.840 to outnumber baby boomers, and then you've got Gen Z 0:27:47.040 --> 0:27:49.679 coming up behind them at that time that were just 0:27:49.720 --> 0:27:52.080 as large. So when you combine the two, and that's 0:27:52.080 --> 0:27:54.720 what we mean by the youth boom, you've got a 0:27:54.800 --> 0:27:58.680 demographic that is larger than any in our country's past 0:27:58.800 --> 0:28:01.640 and sets us apart on the globe stage. Because our 0:28:01.680 --> 0:28:06.000 major trading partners are across G ten, nobody has those demographics. Now, 0:28:06.000 --> 0:28:09.040 our birth rates have been falling, and that is a problem, 0:28:09.359 --> 0:28:11.600 and that's a problem that by the way, lights of 0:28:11.640 --> 0:28:16.280 Fire under the need for AI as well. But our 0:28:16.320 --> 0:28:19.280 birth rates are higher than our major trading partners, and 0:28:19.320 --> 0:28:24.879 so comparatively speaking, that is something that's very important that 0:28:24.960 --> 0:28:28.800 drives the back drop. Now, economists love demographics. Demographics make 0:28:28.840 --> 0:28:33.520 the world go round, and demographics, you know, it's when 0:28:33.560 --> 0:28:36.240 you look at any point in time, how well did 0:28:36.280 --> 0:28:40.720 the Census Bureau get demographic projections pretty well because it 0:28:40.760 --> 0:28:43.320 turns out we sort of all age kind of along 0:28:43.360 --> 0:28:48.040 the same track. And what we know from detailed government 0:28:48.120 --> 0:28:51.200 data is we know how we tend to move through 0:28:51.200 --> 0:28:54.520 the world and spend and behave at certain age ranges. 0:28:55.000 --> 0:28:57.960 So you, as an economist, you can just let your 0:28:58.120 --> 0:29:04.800 demographic cohorts age through those buckets and know kind of 0:29:04.840 --> 0:29:07.800 how the spending shifts are going to take place. When 0:29:07.840 --> 0:29:10.720 are participation rates in the labor force going to peak, 0:29:11.120 --> 0:29:14.240 When do we hit peak earning years, in peak working years, 0:29:14.240 --> 0:29:18.120 and therefore first time home buying years, et cetera, et cetera. 0:29:18.560 --> 0:29:20.560 So you mentioned housing as being one of our key 0:29:20.560 --> 0:29:25.160 calls in twenty nineteen, Well, that was only accelerated during COVID, 0:29:25.360 --> 0:29:30.600 for sure, it wasn't. There were many themes that were 0:29:30.640 --> 0:29:34.600 accelerated during COVID, and housing is one of those. In 0:29:34.680 --> 0:29:39.040 terms of of the incredible demand. I mean, we are 0:29:39.040 --> 0:29:41.760 going to be underbuilding housing for a decade. 0:29:42.560 --> 0:29:45.000 We have been under building housing really since the we 0:29:45.600 --> 0:29:46.400 estimate we. 0:29:46.360 --> 0:29:51.240 Will have an eighteen million unit shortfall that. 0:29:51.240 --> 0:29:53.880 We need to make up. That's a giant number. Chrise, 0:29:53.920 --> 0:29:55.960 It's a giant of course, we've been talking about four 0:29:55.960 --> 0:29:59.240 to five million currently and that comes from the National 0:29:59.280 --> 0:30:03.080 Association Realtors and the Association home Builders. So there's a 0:30:03.120 --> 0:30:05.080 little asterisk. Is this same and think. 0:30:04.960 --> 0:30:08.640 About that that's currently and then you grow that over time. 0:30:09.080 --> 0:30:12.080 You pair it with affordability, You pair it with the 0:30:12.560 --> 0:30:16.040 fact that our surveys do show that millennials and Gen 0:30:16.160 --> 0:30:20.320 Z by far still want to live in single family homes. 0:30:20.400 --> 0:30:22.720 They may not all be able to afford single family 0:30:23.240 --> 0:30:26.800 and so single family renting will be in high demand. 0:30:26.960 --> 0:30:30.320 We're going to need to build those units. Home builders 0:30:30.360 --> 0:30:33.200 are going to have to respond by building smaller, less 0:30:33.200 --> 0:30:37.360 expensive homes. We think modular housing will have a big 0:30:37.480 --> 0:30:40.280 role to play as well. And then you start to 0:30:40.320 --> 0:30:42.600 think about all the different ways we need to build 0:30:42.600 --> 0:30:45.920 homes as well that shortfall. In order to ensure all 0:30:45.920 --> 0:30:48.800 those homes, we're going to have to think about climate 0:30:48.840 --> 0:30:53.960 friendly building materials, more resist climate resistance building materials, all 0:30:54.000 --> 0:30:57.120 the different ways that we can appease the insurance companies 0:30:57.160 --> 0:30:59.040 so that we can actually build in the in the 0:30:59.120 --> 0:31:01.920 areas and make up for those shortfalls. So I think 0:31:02.280 --> 0:31:05.880 housing is certainly from a thematic perspective, something that can 0:31:06.480 --> 0:31:08.520 It's a great example to me because it's something where 0:31:08.880 --> 0:31:12.760 this is a longer run structural theme, but it can 0:31:12.800 --> 0:31:15.400 fall out of favorite time cyclically because it is very 0:31:15.440 --> 0:31:18.960 interstrate sensitive. Right now, housing is not in a great 0:31:19.000 --> 0:31:23.239 place in the US. Affordability is terrible, and it's not 0:31:23.280 --> 0:31:26.320 just an interest rate problem. More of the home price 0:31:26.520 --> 0:31:31.400 is made up from regulatory impacts than anything else. 0:31:32.040 --> 0:31:35.040 How much of this is a lack of supply I know, 0:31:34.720 --> 0:31:37.960 I've Jonathan Miller and folks like that have been writing 0:31:38.000 --> 0:31:41.080 supply is running twenty to thirty percent of what it 0:31:41.160 --> 0:31:44.280 normally is. And how much of it is a little 0:31:44.320 --> 0:31:47.320 bit of nimby. Once people buy a home, they don't 0:31:47.320 --> 0:31:50.680 want to see all the pretty scenery get knocked over 0:31:50.720 --> 0:31:53.840 and new houses put up over there. What's the solution 0:31:53.960 --> 0:31:54.200 to this? 0:31:54.400 --> 0:31:59.520 Well, I think the nimby really is a symptom of, or. 0:31:59.520 --> 0:32:05.600 A side of effect of the regulation or sorry that 0:32:06.320 --> 0:32:09.240 the nimbi not in my backyard leads to is part 0:32:09.240 --> 0:32:12.200 of what leads to the heavy handed regulation right and 0:32:12.280 --> 0:32:19.280 heavy handed regulation by far is a key contributor to 0:32:19.800 --> 0:32:22.840 the cost of overall housing. Then you add the cost 0:32:22.880 --> 0:32:26.840 of labor in a sector which has had a shortage 0:32:26.880 --> 0:32:30.120 of labor since two thousand and eight, and we only 0:32:30.160 --> 0:32:34.280 started to make up for that shortfall during the what 0:32:34.320 --> 0:32:36.920 I call the immigration period where we were bringing in 0:32:37.000 --> 0:32:39.440 millions of immigrants a year in twenty twenty two to 0:32:39.520 --> 0:32:42.920 twenty twenty three and part of twenty twenty four, only 0:32:42.960 --> 0:32:45.800 to see that reversal now put labor pressures on that 0:32:45.880 --> 0:32:49.360 sector again and then tear us on materials that go 0:32:49.480 --> 0:32:53.560 into construction. So it's just it's cost upon cost upon 0:32:53.720 --> 0:32:56.520 cost that home builders are having to deal with that 0:32:56.760 --> 0:33:01.920 help drive the affordability issues for the home buyers as well. 0:33:02.200 --> 0:33:06.600 Huh. Really intriguing. So obviously thematic investing is a big 0:33:06.640 --> 0:33:12.120 part of your job. Is there any other theme bigger 0:33:12.160 --> 0:33:14.280 than artificial intelligence today? 0:33:15.040 --> 0:33:18.600 I'm going to say a probably not, But artificial intelligence 0:33:18.600 --> 0:33:23.240 it's a very broad it's very broad, and so I 0:33:23.280 --> 0:33:28.440 would gear it more towards AI tech and diffusion, which 0:33:28.480 --> 0:33:32.240 has been a key pillar, thematic pillar for Morgan Stanley. 0:33:33.200 --> 0:33:36.480 But here's why. It seems like my answer is just 0:33:36.520 --> 0:33:40.520 so easy and almost like not well thought out, almost 0:33:40.520 --> 0:33:44.480 flippant in a way. AI is a generalized technology, so 0:33:44.560 --> 0:33:47.880 it flows through everything. So whether you're thinking about a 0:33:47.960 --> 0:33:53.840 multipolar world, theme, which importantly includes defense. We had gone 0:33:53.880 --> 0:33:57.960 long global defense back in January, and it was based 0:33:58.000 --> 0:34:02.120 on the fact that you've got your pallenteers of the 0:34:02.160 --> 0:34:05.840 world and open aiyes of the world of you know, 0:34:06.000 --> 0:34:13.200 working with the US government to modernize defense for tech 0:34:13.280 --> 0:34:16.799 and AI. And so if you think about you know, 0:34:17.000 --> 0:34:22.000 four themes, say longevity, AI, tech and diffusion, multipolar world, 0:34:22.200 --> 0:34:26.799 and the energy of everything. AI threads through all of that. 0:34:27.280 --> 0:34:28.240 It threads through. 0:34:28.080 --> 0:34:28.560 All of it. 0:34:29.400 --> 0:34:34.080 So when I think about, say conviction weighting those themes, 0:34:34.920 --> 0:34:36.919 your highest conviction weight is going to be on the AI, 0:34:37.000 --> 0:34:38.280 tech and diffusion. 0:34:38.400 --> 0:34:39.840 Because it does thread through everything. 0:34:39.880 --> 0:34:43.839 So what's more important the Magnificent seven or the magnificent 0:34:44.000 --> 0:34:47.240 four ninety three that are going to benefit from AI. 0:34:47.640 --> 0:34:50.520 Well, I think there it's very difficult to not have 0:34:50.920 --> 0:34:54.600 those big, big tech names, let's say, in a multi 0:34:54.600 --> 0:34:57.719 thematic portfolio, or if you're trying to take advantage of 0:34:58.120 --> 0:35:02.440 an AI theme, because they are big players in the space. 0:35:02.840 --> 0:35:05.240 I mean, as soon as someone in this country moves 0:35:05.239 --> 0:35:08.759 into contracts with the US government, you've got an incredible 0:35:08.760 --> 0:35:11.600 amount of funding. Look at someone like an Elon Musk, 0:35:11.640 --> 0:35:13.680 who is a creature of the government. Sure I mean, 0:35:13.680 --> 0:35:18.440 how much of his wealth comes from government contracts exactly. 0:35:18.760 --> 0:35:23.319 And so when these other players are wrapped up in 0:35:23.360 --> 0:35:27.839 government contracts and the government has put its priority in 0:35:27.960 --> 0:35:33.040 winning this seeming two horse race on AI against China, 0:35:33.680 --> 0:35:35.879 you would probably be ill advised to bet against that. 0:35:36.280 --> 0:35:39.279 It doesn't mean that AI tech infusion is just the 0:35:39.360 --> 0:35:42.719 mag seven. So of course, in my role, I can't 0:35:42.760 --> 0:35:45.200 talk about specific companies, and you don't want to ever 0:35:45.200 --> 0:35:47.240 take specific company advice from an economist. 0:35:47.320 --> 0:35:48.360 I'll just say, but. 0:35:49.840 --> 0:35:53.680 You've got very interesting players all the way down to 0:35:53.760 --> 0:35:55.759 mid cap and small cap all the way down to 0:35:55.800 --> 0:36:00.000 rustle three thousand that are important in an AI tech 0:36:00.120 --> 0:36:01.279 and diffusion space. 0:36:01.160 --> 0:36:05.839 Meaning they become more efficient, productive, profitable by deployment, sort 0:36:05.880 --> 0:36:08.960 of like what we saw post Internet end. 0:36:08.800 --> 0:36:11.960 Boss they and they become part of the fabric of 0:36:11.960 --> 0:36:16.320 that generalized technology that all companies end up using as 0:36:16.400 --> 0:36:18.600 AI diffuses across the economy. 0:36:19.120 --> 0:36:21.600 It makes plenty of sense to me, what other big 0:36:21.640 --> 0:36:24.080 themes are you paying close attention to. 0:36:25.320 --> 0:36:26.000 Some big themes? 0:36:26.000 --> 0:36:27.840 And again it's hard for me to get away of 0:36:27.920 --> 0:36:31.800 some sort of flavor of AI. So as an economist, 0:36:31.840 --> 0:36:35.360 I'm going to go back to demographics every time. What 0:36:35.440 --> 0:36:40.280 are the incentives for adopting AI? Right incentives or adopting 0:36:40.320 --> 0:36:45.360 are You've got to replace labor shortfalls. That's a huge incentive. 0:36:45.920 --> 0:36:48.879 And so if you are a country with falling birth 0:36:48.960 --> 0:36:53.160 rates and you can make up for that in several 0:36:53.200 --> 0:36:57.799 different ways. One is your existing population. You can put 0:36:57.800 --> 0:37:01.239 in policies to boost labor force participation so have a 0:37:01.280 --> 0:37:05.000 more full participation from your current population. You can be 0:37:05.120 --> 0:37:08.960 sure that you are not just have an open immigration system, 0:37:09.920 --> 0:37:13.440 and I don't mean just opening your borders to indiscriminate flows, 0:37:13.480 --> 0:37:17.240 but an open immigration system, a traditional open immigration system 0:37:17.239 --> 0:37:22.400 where you have a sound process for integrating immigrants into 0:37:22.440 --> 0:37:24.920 the labor market, something in the US has been very 0:37:24.960 --> 0:37:29.160 good at, something Europe is not very good at. Or 0:37:29.920 --> 0:37:35.560 you can replace that labor with AI and robotics. There's 0:37:35.600 --> 0:37:40.280 your incentive. There's your incentive for countries like China, like Japan. 0:37:41.040 --> 0:37:44.040 Maybe not like India right now, but India's demographics are 0:37:44.239 --> 0:37:47.240 not good. Really when you look further out a decade 0:37:47.280 --> 0:37:49.600 from now, fifteen twenty years from now. 0:37:49.520 --> 0:37:53.160 You know, it's funny you keep talking about demographics. Isn't 0:37:53.200 --> 0:37:57.680 the trend throughout history that as a country becomes first 0:37:58.120 --> 0:38:02.000 less poor and then wealthier, the birth rates just drop. 0:38:02.040 --> 0:38:06.399 People absolutely more affluent countries. It is a natural way 0:38:06.440 --> 0:38:10.000 of things. Countries that are able to, let me just say, 0:38:10.120 --> 0:38:14.880 roll with that right and boost productivity by making fuller 0:38:15.000 --> 0:38:19.320 use of your existing labor pool are those that still 0:38:19.360 --> 0:38:24.399 continue along that path of affluency. The US has not 0:38:24.520 --> 0:38:28.279 just higher birth rates than our major trading partners, we've 0:38:28.320 --> 0:38:31.040 got higher rates of productivity. It's part of what US 0:38:31.120 --> 0:38:34.560 exceptionalism is built upon, is that not only have we 0:38:34.640 --> 0:38:38.439 kept birth rates higher, which population growth and specifically growth 0:38:38.480 --> 0:38:42.600 in your labor force goes into the potential growth in 0:38:42.640 --> 0:38:47.680 your economy those calculations, but we're also making those more productive, 0:38:48.160 --> 0:38:51.480 and it's part of our secret sauce of success. You know, 0:38:51.560 --> 0:38:54.400 when I talk about US exceptionalism, I'm not even referring 0:38:54.400 --> 0:38:59.040 to markets financial markets. I'm talking about the US having 0:39:00.080 --> 0:39:03.799 more flexible labor market where we have higher rates of productivity. 0:39:04.480 --> 0:39:07.120 Very important that we continue to hang on to independent 0:39:07.160 --> 0:39:11.440 monetary policy, that we have stable currency, but that comparative 0:39:11.480 --> 0:39:15.759 advantage lies in your labor force and how far you 0:39:15.800 --> 0:39:17.839 can push it, and the US is just really good 0:39:17.840 --> 0:39:18.080 at that. 0:39:18.480 --> 0:39:21.560 So let me ask you a thematic question, only it's 0:39:21.600 --> 0:39:25.640 going to be a negative. What's the one economic myth 0:39:25.719 --> 0:39:29.480 you hear more than others? What question bubbles up from clients, 0:39:29.520 --> 0:39:34.200 from brokers and advisors, from people within that you wish 0:39:34.239 --> 0:39:35.160 would just go away? 0:39:36.080 --> 0:39:40.040 Maybe this gets too nuanced, because economists love nothing more 0:39:40.080 --> 0:39:45.040 than getting nuanced. But it's like you got the chicken 0:39:45.080 --> 0:39:49.160 and the egg backwards, right, right. So it's that the 0:39:49.160 --> 0:39:52.200 markets are pricing in that the FED is going to 0:39:52.239 --> 0:39:54.879 do something at its next meeting, and therefore the Fed 0:39:55.000 --> 0:39:56.160 has to do that. 0:39:56.360 --> 0:39:59.320 The markets have been so wrong about that for so long. 0:40:00.080 --> 0:40:01.879 I think the market's over time it had a very 0:40:01.920 --> 0:40:04.760 difficult So there's another one. Don't fight the Fed? Right, 0:40:04.920 --> 0:40:06.719 how many times do we say don't fight the Fed? 0:40:06.719 --> 0:40:10.120 And markets fight the Fed and they lose. But that 0:40:10.160 --> 0:40:14.239 the markets lead the Fed. Now, the FED makes low 0:40:14.320 --> 0:40:16.920 frequency decisions in a high frequency world. The market is 0:40:17.000 --> 0:40:17.880 very high frequency. 0:40:18.200 --> 0:40:19.840 That's a great way to describe that. 0:40:20.000 --> 0:40:22.319 Yeah, And so the fact of the matter is the 0:40:22.360 --> 0:40:25.600 market can respond on a dime when the data comes 0:40:25.600 --> 0:40:29.479 out when financial conditions change. The Fed can't. The Fed 0:40:29.560 --> 0:40:31.879 has to look at it, it has to deliberate it. 0:40:31.880 --> 0:40:34.200 It has to gain a consensus and then it moves. 0:40:34.920 --> 0:40:37.280 Much of the time, the market doesn't have it wrong. 0:40:37.800 --> 0:40:40.399 The market read the labor report of the most recent 0:40:40.440 --> 0:40:42.640 labor report and said that's not good. And guess what, 0:40:42.880 --> 0:40:45.520 the FED also thinks that's not good. Great, you're on 0:40:45.560 --> 0:40:47.439 the same page. But the market was able to price 0:40:47.440 --> 0:40:51.000 it in well ahead of the FED actually delivering in September. 0:40:51.320 --> 0:40:53.400 So I do believe that the FED is going to 0:40:53.400 --> 0:40:56.640 cut twenty five bases points in September. Now this is 0:40:56.680 --> 0:41:00.319 with my hat on as the chief economic strategist Morgan 0:41:00.400 --> 0:41:03.040 Stanley Wealth Management. There are others in the firm that 0:41:03.160 --> 0:41:06.000 also have FEWS views on the FED, but you've asked me, 0:41:06.520 --> 0:41:08.920 and the beauty of this podcast that I get to 0:41:08.920 --> 0:41:11.560 give my views and you're only talking to me here. 0:41:12.040 --> 0:41:15.680 So I do think though that our focus on September 0:41:16.320 --> 0:41:20.279 it can probably be best spent elsewhere in that the 0:41:20.280 --> 0:41:23.440 first cut is going to be the easiest, because, as 0:41:23.520 --> 0:41:27.160 Chairpell said, modestly restrictive. Do you need to be monstly 0:41:27.200 --> 0:41:31.320 restrictive when job growth has slowed? This sharply If you 0:41:31.320 --> 0:41:34.000 don't need to be mondstly restrictive, just make an adjustment 0:41:34.160 --> 0:41:36.480 they're not making any decisions about what happens after that. 0:41:36.840 --> 0:41:39.399 So the fact that you know, do they or don't 0:41:39.440 --> 0:41:42.160 they cut in September and by the way, fifty basis points. 0:41:42.239 --> 0:41:44.840 That's a hard no from me because I knew I 0:41:44.880 --> 0:41:47.040 could tell, I could tell the question was on your 0:41:47.040 --> 0:41:47.920 lips it was about. 0:41:47.719 --> 0:41:50.719 One hundred points. Someone now that's definitely. 0:41:50.239 --> 0:41:50.960 Even harder no. 0:41:52.520 --> 0:41:55.040 But I do believe that once you have made that cut, 0:41:55.120 --> 0:41:57.640 it's a little harder to justify if the data don't 0:41:57.719 --> 0:42:00.680 keep coming in in the same fashion to say why 0:42:00.760 --> 0:42:04.120 that one adjustment was perfect but not another. So I 0:42:04.520 --> 0:42:07.000 think where I would rather debate is how far do 0:42:07.080 --> 0:42:09.319 they need to go? And this is where I do 0:42:09.440 --> 0:42:14.480 disagree with some powers that be that the FED is 0:42:14.520 --> 0:42:17.560 going to need to cut a lot. I think we're 0:42:17.600 --> 0:42:19.640 going to have a good economy next year. I think 0:42:19.680 --> 0:42:22.080 productivity is going to be picking up even more. I 0:42:22.080 --> 0:42:24.080 think there are parts of the One Big Beautiful Bill 0:42:24.400 --> 0:42:27.440 with the investment incentives that are in it, which are 0:42:27.440 --> 0:42:29.480 going to help put a floor into the economy. And 0:42:30.880 --> 0:42:32.640 we're not going to have an environment where the Fed's 0:42:32.680 --> 0:42:34.360 going to need to cut one hundred and fifty tw 0:42:34.400 --> 0:42:35.120 hundred paces. 0:42:35.160 --> 0:42:38.359 To be fair. Stocks are at all time highs, real 0:42:38.440 --> 0:42:41.680 estates at all time highs, revenue and profits are at 0:42:41.800 --> 0:42:44.560 or near all time highs. It doesn't seem to be 0:42:44.640 --> 0:42:48.720 an economy begging for rate cuts, even as we're starting 0:42:48.760 --> 0:42:52.200 to see a slow down in some consumer spending and 0:42:52.280 --> 0:42:55.400 some hiring. But how much of that. 0:42:55.160 --> 0:42:56.640 That justifies lower rates? 0:42:57.120 --> 0:42:59.640 Doesn't tell you need to cut drastically, right, So do 0:42:59.680 --> 0:43:01.200 you want to good economy or do you want the 0:43:01.239 --> 0:43:02.280 Fed to cut drastically? 0:43:02.760 --> 0:43:05.840 Well, we know what the president wants, Yeah, what the 0:43:05.880 --> 0:43:08.880 economy needs and what the market wants. They may be 0:43:09.080 --> 0:43:10.640 something slightly different. 0:43:10.800 --> 0:43:14.279 Yeah, And if the Fed is watching it and objectively 0:43:14.320 --> 0:43:16.520 doing its job, then we will end up in the 0:43:16.560 --> 0:43:17.080 right place. 0:43:17.360 --> 0:43:20.880 Coming up, we continue our conversation with Allen Zenner, chief 0:43:20.920 --> 0:43:25.440 economic strategist for Morgan Stanley, discussing the state of today's 0:43:25.480 --> 0:43:30.120 economy in light of tariffs and trade policy. I'm Barry Ridults. 0:43:30.160 --> 0:43:42.040 You're listening to Masters in Business on Bloomberg Radio. I'm 0:43:42.040 --> 0:43:45.600 Barry Redults. You're listening to Masters in Business on Bloomberg Radio. 0:43:46.080 --> 0:43:49.440 My extra special guest is Alan Zenner. She is chief 0:43:49.520 --> 0:43:53.600 economic strategist and global head of thematic and macroinvesting for 0:43:53.760 --> 0:43:58.080 Morgan Stanley. The firm runs over seven trillion dollars. So 0:43:58.200 --> 0:44:02.239 you've written about tariff and trade policy. My question for 0:44:02.280 --> 0:44:07.279 you is how disruptive or destabilizing is this to either 0:44:07.320 --> 0:44:09.040 the US or global economy. 0:44:09.360 --> 0:44:15.480 So we've certainly seen disruption in confidence. Markets don't like opaqueness, 0:44:15.560 --> 0:44:18.799 they like certainty, and we could see that early on 0:44:18.920 --> 0:44:24.160 in the volatility of Wow. January hit and it was 0:44:24.400 --> 0:44:27.400 tariff's tarifs, tariffs, and the market clearly was caught off sides. 0:44:27.719 --> 0:44:31.480 Policymakers were caught off sides, economists were caught off sides. 0:44:31.880 --> 0:44:34.520 And so then you kick off the flory of activity. 0:44:34.520 --> 0:44:38.520 What does this mean when the world order is being reset? 0:44:38.800 --> 0:44:40.879 And it can mean a whole host of things. It's 0:44:40.880 --> 0:44:45.160 one reason why all economists, all forecasters have to take 0:44:46.120 --> 0:44:50.319 a very big slice of humble pie and take a 0:44:50.320 --> 0:44:53.759 big bite out of that because the uncertainty bands of 0:44:53.800 --> 0:44:55.560 any kind of forecast you put out are going to 0:44:55.600 --> 0:44:59.840 be highly uncertain. There's no way to know the impacts 0:44:59.840 --> 0:45:03.399 of tariffs truly until well after the fact. And that's 0:45:03.440 --> 0:45:07.440 because tariffs fall here, there, and everywhere. You're going to 0:45:07.520 --> 0:45:10.600 have some degree of manufacturers and the countries that we 0:45:10.680 --> 0:45:14.280 import from eating the cost. You're going to have importers 0:45:14.320 --> 0:45:17.080 along the way eating the cost, wholesalers eating the cost, 0:45:17.640 --> 0:45:21.160 businesses that sell final goods eating the cost, and consumers 0:45:21.480 --> 0:45:24.759 having to eat some of that as well. The forecasting 0:45:24.800 --> 0:45:29.440 comes in where okay, how much of each? What percentage 0:45:29.480 --> 0:45:32.200 of each? I think one thing that I've observed is 0:45:32.840 --> 0:45:36.280 businesses have been sitting on a good deal more cushion 0:45:37.000 --> 0:45:39.680 in terms of cash and free cash flow than I 0:45:39.680 --> 0:45:42.320 think anybody had suspected that they would. 0:45:42.120 --> 0:45:44.240 Be, Meaning they have the ability to eat. 0:45:44.040 --> 0:45:45.759 Some of the ability to eat some of it. 0:45:45.920 --> 0:45:49.640 I do think that even after Chinese manufacturers surprised us 0:45:49.680 --> 0:45:52.560 in twenty nineteen to the degree that they were willing 0:45:52.600 --> 0:45:56.080 to eat the costs, I think they've been able to 0:45:56.160 --> 0:46:03.840 continue to absorb it. I think ultimately for economists, because 0:46:04.080 --> 0:46:06.919 economists by and large are wearing a lot of egg 0:46:06.960 --> 0:46:09.920 on our face for getting it wrong, for sounding the alarm. 0:46:10.360 --> 0:46:12.480 The companies were sounding the alarm too. We're taking our 0:46:12.520 --> 0:46:15.120 cues from what the surveys are saying, what we're hearing 0:46:15.120 --> 0:46:17.799 directly from companies that I'm going to pass on these 0:46:17.840 --> 0:46:20.400 prices to consumers. I am not going to eat this, 0:46:20.760 --> 0:46:22.440 But then how much of that are companies talking their 0:46:22.440 --> 0:46:23.080 own book as well? 0:46:23.480 --> 0:46:26.680 To be fair, it's the middle of August. Liberation Day 0:46:26.800 --> 0:46:30.279 was early April, we had a ninety day pause. We 0:46:30.440 --> 0:46:34.239 really haven't felt the full impact on tariffs, and we 0:46:34.520 --> 0:46:38.680 probably won't until the fourth quarter or first quarter next year. 0:46:38.800 --> 0:46:42.560 So is it a little early to say, hey, no harm, 0:46:42.600 --> 0:46:43.239 no foul. No. 0:46:43.360 --> 0:46:45.680 I think it's definitely to early say no harm, no foul. 0:46:46.719 --> 0:46:49.439 And I don't think anyone, even the administration, is saying 0:46:49.440 --> 0:46:52.279 there won't be some bit of bearing the brunt of 0:46:52.320 --> 0:46:55.480 that among consumers, among businesses. 0:46:55.200 --> 0:46:56.000 In the US. 0:46:56.239 --> 0:46:59.560 I think it's just that you've got one faction saying 0:46:59.840 --> 0:47:01.319 that it's going to be a lot less of an 0:47:01.320 --> 0:47:05.479 impact than some other factions. And no one really knows, 0:47:05.680 --> 0:47:06.600 so let's all. 0:47:06.400 --> 0:47:07.279 Be humble about it. 0:47:07.360 --> 0:47:10.359 No one knows. But there seems to be a bit 0:47:10.480 --> 0:47:14.919 of a consensus that tariffs are a consumption tax. It's 0:47:14.960 --> 0:47:19.600 like a vat tax on US households and businesses. Is 0:47:19.640 --> 0:47:22.440 that overstating the threat or is that is that accurty? 0:47:22.480 --> 0:47:25.279 No, that's exactly how it works, to the extent that 0:47:25.360 --> 0:47:28.839 they that companies eat it on the margin or pass 0:47:28.880 --> 0:47:32.200 it onto households, and households eat it and paying higher prices. 0:47:32.400 --> 0:47:34.920 That is exactly how it works. I mean, that is 0:47:34.960 --> 0:47:37.960 the economic theory of it. That is sound. It's the 0:47:38.160 --> 0:47:41.239 degree to which the costs are absorbed and by what 0:47:41.320 --> 0:47:46.279 players along the import channel. That is the That is 0:47:46.320 --> 0:47:49.560 the unknown factor. And I can tell you that you know, 0:47:49.840 --> 0:47:53.040 what the President is doing or has been doing, is 0:47:53.840 --> 0:47:57.160 changing global trade in a way that typically would play 0:47:57.200 --> 0:48:01.160 out over a decade or so in a very short 0:48:01.200 --> 0:48:04.600 period of time, and so that's led to a tremendous 0:48:04.640 --> 0:48:08.880 amount of uncertainty. And like you said, this may be 0:48:08.920 --> 0:48:12.200 something where the full tariff impacts aren't felt until the 0:48:12.239 --> 0:48:16.080 fourth quarter or first quarter of next year. And if 0:48:16.080 --> 0:48:18.560 that is the case, we'll deal with it when it 0:48:18.600 --> 0:48:21.480 comes and Chair Pal and the Fed will be there 0:48:21.520 --> 0:48:24.440 to act very nimbly around that. I am confident of. 0:48:24.960 --> 0:48:30.239 But has there been unfair trade practices? Absolutely? Do we 0:48:30.320 --> 0:48:34.880 need to renegotiate trade contracts? Absolutely. I was at the 0:48:34.880 --> 0:48:39.960 State of Texas during NAFTA. NAFTA was not renegotiated until 0:48:39.960 --> 0:48:44.400 it became the USMCA under Trump's first term. Why the 0:48:44.400 --> 0:48:47.760 global economy is so dynamic. How could a trade agreement 0:48:48.040 --> 0:48:52.880 put together in the nineties still be relevant in twenty seventeen, 0:48:53.360 --> 0:48:54.600 twenty eighteen, twenty nineteen. 0:48:54.640 --> 0:48:55.520 It makes no sense. 0:48:56.400 --> 0:49:02.160 So absolutely we need to be revisiting, like alongside a 0:49:02.239 --> 0:49:03.319 dynamic global. 0:49:03.000 --> 0:49:05.080 Economy on a more regular basis, on. 0:49:05.000 --> 0:49:06.040 A more regular basis. 0:49:06.040 --> 0:49:08.200 We're just doing this over a short period of time, 0:49:08.239 --> 0:49:12.160 and that's created a good deal of disruption and uncertainty 0:49:12.200 --> 0:49:17.000 and volatility and guesswork, if you will, among the economics community. 0:49:17.239 --> 0:49:19.440 So let's talk about that guess work. There's going to 0:49:19.520 --> 0:49:24.200 be some of these tariffs showing up as on the 0:49:24.239 --> 0:49:28.080 household level. Is that a head wind for consumption? Same 0:49:28.160 --> 0:49:31.040 question about businesses If they have to eat some of 0:49:31.080 --> 0:49:35.520 the tariffs, that's going to affect profitability. There's no free lunch. 0:49:35.320 --> 0:49:35.720 Is there. 0:49:35.880 --> 0:49:38.600 No, There's never a free lunch. So we are seeing 0:49:38.640 --> 0:49:43.160 consumer spending slow now. It's slowing for several reasons. One, 0:49:43.840 --> 0:49:49.440 we've had a reversal of immigration in the US. That is, 0:49:49.920 --> 0:49:53.759 no small number of people bodies consume and so if 0:49:53.800 --> 0:49:55.920 you've got fewer bodies, they're consuming less. 0:49:56.400 --> 0:49:59.239 And I want to say we have had a negative 0:50:00.280 --> 0:50:03.960 net new population this year for the first time I 0:50:04.000 --> 0:50:06.480 think in US history. Is that is that accurate? 0:50:06.600 --> 0:50:08.840 Yeah, it's I mean we've slowed to a trickle in 0:50:08.920 --> 0:50:15.360 population growth at times, but it is highly unusual, highly unusual. 0:50:15.920 --> 0:50:20.680 You've got less bodies in the US, so you're consuming less. 0:50:21.280 --> 0:50:26.480 Now those bodies contributed to low income consumption. You've also 0:50:26.600 --> 0:50:30.120 got low income consumers in general in the US that 0:50:30.239 --> 0:50:33.600 when prices for goods go up from tariffs or for 0:50:33.640 --> 0:50:38.920 whatever reason, they're going to consume less. So consumer spending 0:50:38.960 --> 0:50:43.080 has been slowing. Now why hasn't it slowed even more 0:50:43.160 --> 0:50:46.600 so than it has when population growth has been negative 0:50:46.600 --> 0:50:50.400 from a reversal in immigration, Because the top end consumers 0:50:50.400 --> 0:50:54.920 are still spending. So the top income quintile in the 0:50:55.080 --> 0:50:59.000 US represents forty five percent of all consumer spending. If 0:50:59.040 --> 0:51:01.160 you take just the top two income quintels, that's more 0:51:01.200 --> 0:51:04.279 than sixty percent of all consumer spending. And so we 0:51:04.320 --> 0:51:07.000 want what we want. And whether you say maybe that's 0:51:07.000 --> 0:51:09.359 still an artifact of COVID, we were all taught we're 0:51:09.360 --> 0:51:12.960 going to die tomorrow, So spending it's God or it's 0:51:13.120 --> 0:51:18.400 just this tremendous, tremendous increase in real estate wealth and 0:51:18.480 --> 0:51:22.360 tremendous increase in financial wealth. And even though our marginal 0:51:22.360 --> 0:51:25.200 propensity to consume out of that wealth is smaller for 0:51:25.280 --> 0:51:28.960 upper income households, the growth in wealth is just enormous, 0:51:29.520 --> 0:51:32.600 and so when they're spending, it tends to mask weakness 0:51:33.040 --> 0:51:35.440 at the low end. But there are some risks along 0:51:35.520 --> 0:51:37.719 the horizon. Student borrows have to. 0:51:37.640 --> 0:51:38.800 Start paying that back. 0:51:39.160 --> 0:51:42.160 I don't think that we're out of the woods and 0:51:42.200 --> 0:51:45.319 that because the economy is growing at half the pace 0:51:45.360 --> 0:51:47.400 it was last year, we're just fine. I think we 0:51:47.440 --> 0:51:49.719 can grow even more slowly before it gets better. 0:51:49.960 --> 0:51:53.520 So let's talk about two issues that are policy concerns 0:51:53.560 --> 0:52:00.520 that you've raised. One is economic data integrity. Durding this 0:52:00.719 --> 0:52:03.640 a few days after Trump fired the head of the BLS. 0:52:04.360 --> 0:52:07.200 What sort of concerns does this raise in terms of 0:52:08.360 --> 0:52:10.239 protection of data integrity? 0:52:10.560 --> 0:52:14.640 So data integrity cuts both ways. So prior to that 0:52:14.880 --> 0:52:19.640 very high profile firing of the BLS commissioner, the concern 0:52:19.880 --> 0:52:23.279 among the economics community for quite some time has been 0:52:23.360 --> 0:52:28.399 that data integrity has been slipping. And the way we 0:52:28.440 --> 0:52:31.560 look measure that is we look at survey response rates, 0:52:32.080 --> 0:52:36.520 and especially because the Labor Market report is the end 0:52:36.600 --> 0:52:39.080 all be all number one data. 0:52:39.200 --> 0:52:41.080 Point in the US that we follow. 0:52:41.520 --> 0:52:46.319 The response rates had been slipping and now why is that, Well, 0:52:46.400 --> 0:52:52.960 they're myriad reasons. One is that we have frequent government shutdowns, 0:52:53.320 --> 0:52:55.640 and so when the lights aren't on and no one's 0:52:55.680 --> 0:52:58.080 there to police the survey and call you the business 0:52:58.080 --> 0:53:00.680 and say hey, it's really important that you respond, and 0:53:00.760 --> 0:53:03.640 you don't get that call as of business, it starts 0:53:03.719 --> 0:53:06.480 to instill in you the sense of maybe this survey 0:53:06.680 --> 0:53:10.440 isn't so important, maybe I don't need to answer that. 0:53:10.719 --> 0:53:13.040 And so what we've seen is after those episodes, you 0:53:13.120 --> 0:53:15.840 tend to have a slippage and response rates that you 0:53:15.920 --> 0:53:19.959 never quite get back. Another issue is we talked about 0:53:20.040 --> 0:53:22.600 the youth boom. I don't see a lot of youthful 0:53:22.640 --> 0:53:25.600 people jumping up and down to work for the government. 0:53:26.560 --> 0:53:31.720 Maybe that's because the systems are antiquated. I wonder, because 0:53:31.760 --> 0:53:34.680 you've got older generations at the government that are having 0:53:34.719 --> 0:53:39.240 to teach an antiquated programming language to younger generations coming 0:53:39.280 --> 0:53:44.279 in programming languages that don't exist anywhere else, And so 0:53:44.880 --> 0:53:49.520 how does that instill excitement among young people to come 0:53:49.560 --> 0:53:53.200 in and work for the government. We have also had 0:53:53.280 --> 0:53:57.799 a systematic underfunding of data agencies for quite some time 0:53:57.880 --> 0:54:02.840 as well. How can you you overhaul your systems without 0:54:02.920 --> 0:54:08.359 the proper funding, and so it's something that the NAY 0:54:08.360 --> 0:54:10.920 of the National Associate for Business Economics has really followed 0:54:10.920 --> 0:54:14.680 this closely. We have a Statistics Committee that meets with 0:54:14.719 --> 0:54:17.640 all the heads of the statistical agencies, and the statistical 0:54:17.719 --> 0:54:23.279 agencies have a very strong outreach program to economists in academia, 0:54:23.719 --> 0:54:27.799 in government, and in the private sector to say, here 0:54:27.800 --> 0:54:29.240 are methodologies, how. 0:54:29.080 --> 0:54:30.120 Can we do it better? 0:54:30.440 --> 0:54:33.880 And so we're constantly searching for ways to improve and honestly, 0:54:33.920 --> 0:54:36.360 to their credit, half the time, the private sector economists 0:54:36.400 --> 0:54:39.719 are like crickets, how can we do it better? Oh, 0:54:39.719 --> 0:54:41.759 you don't like the way we measure housing, tell us 0:54:41.800 --> 0:54:44.880 how we can do it better. Cricket, cricket. No, I 0:54:45.000 --> 0:54:46.319 just like to say I don't like the way you 0:54:46.360 --> 0:54:49.200 do it. I mean, but we're not really offering a 0:54:49.200 --> 0:54:53.040 lot of sound solutions. We're a massive economy. It's not 0:54:53.120 --> 0:54:55.480 easy to measure the data. But one thing that we 0:54:55.560 --> 0:55:00.160 do well historically is we measure data well, and we 0:55:00.239 --> 0:55:03.600 have the best most robust data sets out of any 0:55:03.640 --> 0:55:06.560 other country. We compare ourselves to, but it has been 0:55:06.920 --> 0:55:10.279 slipping so very fun. What I will advocate for is 0:55:10.440 --> 0:55:13.920 funding the data agencies and encouraging them to overhaul their systems. 0:55:14.400 --> 0:55:17.800 So let's talk a little bit about the Federal Reserve independence. 0:55:18.520 --> 0:55:22.800 How much risk is there that the FED could get politicized. 0:55:22.520 --> 0:55:24.440 So we have to take the risk seriously. 0:55:24.840 --> 0:55:29.480 And I understand why folks might be concerned that we 0:55:29.520 --> 0:55:33.600 could be headed for a time when there's collusion between 0:55:34.160 --> 0:55:36.520 the White House and the FED, because we've been there before, 0:55:36.560 --> 0:55:40.560 so you could understand the concern. And that was a 0:55:40.680 --> 0:55:45.759 very different time between Arthur Burns and the Nixon White House. 0:55:45.760 --> 0:55:47.080 But it was a very real time. 0:55:47.120 --> 0:55:50.120 And then it led to the hyperinflation, and those of 0:55:50.200 --> 0:55:52.600 us of a certain age, we don't want to live through. 0:55:52.640 --> 0:55:55.800 Nineteen seventies inflation. That was an ugly decade. 0:55:55.960 --> 0:55:57.600 Economics, that was an ugly decade. 0:55:57.600 --> 0:56:01.680 And I tell those harrowing tales to my team of 0:56:01.760 --> 0:56:05.880 waiting in line for gasoline with my mother, you know, 0:56:05.920 --> 0:56:08.560 because it was rationed or we couldn't get gasoline on 0:56:09.000 --> 0:56:09.680 a Sunday. 0:56:10.080 --> 0:56:13.000 I remember I had a lawn mowing business and I 0:56:13.040 --> 0:56:16.239 would show up with my little red gas can and 0:56:16.280 --> 0:56:18.440 they would say do you have an odd number license 0:56:18.520 --> 0:56:21.440 plate or an even number license plate? And my answer 0:56:21.480 --> 0:56:24.800 was always, I'm twelve. I don't have a license plate. 0:56:25.000 --> 0:56:26.640 I just need a gallon of gas so I can 0:56:27.160 --> 0:56:29.680 mow missus McCarthy's lawn down the street. 0:56:29.840 --> 0:56:30.040 Yeah. 0:56:30.280 --> 0:56:30.600 Always. 0:56:30.600 --> 0:56:31.960 I can't believe they had the nerve to ask a 0:56:31.960 --> 0:56:33.960 twelve year old, Oh, no, you show up, But it 0:56:34.040 --> 0:56:36.359 shows you why should you a twelve year old get 0:56:36.480 --> 0:56:38.160 priority or someone that needs. 0:56:37.920 --> 0:56:38.840 To commute to work. 0:56:38.960 --> 0:56:39.920 But apparently, but. 0:56:39.920 --> 0:56:43.080 My parents bought a house at eighteen percent mortgage interest 0:56:43.120 --> 0:56:43.879 in nineteen. 0:56:43.600 --> 0:56:44.600 Eighty eighteen percent. 0:56:44.920 --> 0:56:47.600 That was normal because if you didn't buy it that day, 0:56:47.760 --> 0:56:51.040 it was more expensive the next day. That's what strikes 0:56:51.080 --> 0:56:54.239 fear in the hearts of monetary policy makers because that 0:56:54.400 --> 0:56:57.120 is inflation expectations. The price was going to be more 0:56:57.160 --> 0:56:59.680 expensive tomorrow, so you better buy it today. 0:57:00.840 --> 0:57:05.800 Inflation expectations lead to consumer and behavior that helps the drive. 0:57:05.600 --> 0:57:08.800 Prices, yes, and it starts off that sort of vicious cycle. 0:57:09.040 --> 0:57:12.080 And so this is at the heart of why you 0:57:12.120 --> 0:57:15.799 need independent monetary policy making, because if the market believes 0:57:16.520 --> 0:57:21.160 that the FED might keep rates easier than the economy 0:57:21.200 --> 0:57:26.240 would otherwise dictate, then is that going to again lead 0:57:26.320 --> 0:57:30.040 to something like runaway inflation is going to lead to stagnation. 0:57:30.600 --> 0:57:34.920 And that's why every time there's some headline where the 0:57:35.880 --> 0:57:40.800 FEDS and dependence may be threatened, you see term premium 0:57:40.840 --> 0:57:43.360 increase at the long end of the yield curve. You 0:57:43.480 --> 0:57:48.520 see the stagnation playbook go go into effect among investors, 0:57:49.080 --> 0:57:53.600 and you know, going back to US exceptionalism. Independent monetary 0:57:53.600 --> 0:57:58.120 policy making is a pillar of US exceptionalism. 0:57:58.160 --> 0:58:02.160 Really interesting in a bunch of names floated for FED 0:58:02.280 --> 0:58:06.480 chair other than Scott Besson, who has said he's not 0:58:06.640 --> 0:58:11.120 interested and I think is probably the most thoughtful person 0:58:11.160 --> 0:58:14.320 that I've heard names I've heard thrown out. Any of 0:58:14.360 --> 0:58:19.160 those names make you remotely comfortable? Or what do you 0:58:19.280 --> 0:58:22.320 think about some of these trial balloons that keep getting 0:58:22.440 --> 0:58:23.120 tossed around? 0:58:23.320 --> 0:58:26.000 Yeah, so I think I agree with you. 0:58:26.720 --> 0:58:31.800 I like the steady hand and careful thinking that comes 0:58:31.840 --> 0:58:35.960 from Treasury Secretary Besson. It would actually, in policy circles, 0:58:36.000 --> 0:58:40.800 be a demotion to send the Treasury secretary to become 0:58:41.880 --> 0:58:42.480 a chair. 0:58:42.320 --> 0:58:45.240 Of the FMC. That's the emotion we think of it. 0:58:45.320 --> 0:58:49.560 So in markets, I often hear this from investors is wait, 0:58:49.720 --> 0:58:51.720 but the chair of the FED is the most powerful 0:58:51.760 --> 0:58:56.200 person in the world, but from in policy circles, it 0:58:56.280 --> 0:58:58.960 is a lesser position than Treasury secretary. 0:58:59.280 --> 0:59:04.280 Very interesting, it's a longer tenure, especially if we look 0:59:04.320 --> 0:59:09.600 at recent administrations. It's not like someone becomes treasure secretary 0:59:09.640 --> 0:59:11.480 and they're there for all four years. They seem to 0:59:11.520 --> 0:59:12.880 turn over pretty rapidly. 0:59:13.040 --> 0:59:16.120 It can be the case, right, but we've had not always. 0:59:16.200 --> 0:59:19.880 We've had back to back six year terms for pal. 0:59:20.080 --> 0:59:23.040 That's a pretty yeah, yeah for. 0:59:23.160 --> 0:59:26.600 Your terms, but yeah, and there tends to be a 0:59:26.600 --> 0:59:30.400 lot of longevity with FED chairs because they also don't 0:59:30.520 --> 0:59:36.000 change typically with administrations. Uh, and so in political parties, 0:59:36.280 --> 0:59:38.000 they tend to span political parties. 0:59:38.400 --> 0:59:40.080 So, look, there are a lot. 0:59:39.920 --> 0:59:43.040 Of you know, I obviously am going to have some 0:59:43.120 --> 0:59:45.640 personal favorites of mine that have been thrown out there. 0:59:45.640 --> 0:59:49.080 But unfortunately I'm not going to give you those names. 0:59:49.000 --> 0:59:51.280 But they will just tell me who you really don't like. 0:59:51.400 --> 0:59:54.520 There is yes, yes, I'll do the opposite. No, but 0:59:54.560 --> 0:59:57.120 there there there are plenty of names in there that 0:59:57.160 --> 1:00:01.560 have been tossed around as possibilities that would make fine 1:00:02.240 --> 1:00:05.160 FMC chairs. I think what you're going to see is 1:00:05.200 --> 1:00:07.720 with each of those names of a float to the top. 1:00:08.120 --> 1:00:11.840 The markets will have their say on whether that is 1:00:12.080 --> 1:00:15.040 a candidate that would be believed to be a mouthpiece 1:00:15.200 --> 1:00:17.200 of President Trump or not. 1:00:17.760 --> 1:00:25.120 When I look at various cabinet members Defense, Intelligence, Health 1:00:25.560 --> 1:00:32.080 and Welfare and most recently now BLS, can't say these 1:00:32.120 --> 1:00:35.640 are the best and the brightest. It's not camelot under Kennedy, 1:00:36.200 --> 1:00:40.280 and you could kind of under John F. Kennedy in 1:00:40.400 --> 1:00:43.280 nineteen sixty you could kind of get away with that 1:00:44.280 --> 1:00:50.960 in certain cabinet positions. Am I wrong in saying markets 1:00:51.040 --> 1:00:56.560 won't tolerate someone like an RFK junior and all of 1:00:56.600 --> 1:01:01.280 his anti vaccination attitudes at a place like NIH or 1:01:01.400 --> 1:01:06.520 CDC with a FED chair. Is the bar higher for 1:01:06.640 --> 1:01:12.440 the chairman of the Federal Reserve than other specific cabinet positions. 1:01:12.000 --> 1:01:14.439 Well, I think piggybacking on, you know, sort of your 1:01:14.520 --> 1:01:21.080 exact examples there, Who directly has a hand in influencing 1:01:21.200 --> 1:01:26.000 financial markets. That is the FED chair, That is the 1:01:26.120 --> 1:01:29.680 FOMC collectively, not just the FED chair, but the FOMC 1:01:29.800 --> 1:01:32.560 is a collective body, and that's why the markets will 1:01:32.560 --> 1:01:35.320 always be most sensitive to who is the chair of 1:01:35.320 --> 1:01:35.720 the FED. 1:01:36.240 --> 1:01:40.040 So I want to ask a question about policy, not politics. 1:01:40.440 --> 1:01:43.640 But very often when we talk about you know, anytime 1:01:43.680 --> 1:01:47.760 something comes up, like taco whatever, it seems to get 1:01:47.800 --> 1:01:52.680 overly politicized. But the one descriptor I heard that's kind 1:01:52.680 --> 1:01:56.520 of fascinating is that there isn't a Trump put, there's 1:01:56.600 --> 1:02:00.360 a Trump collar. And what that means is when markets 1:02:00.360 --> 1:02:03.360 are near all time highs, he's someone in bolden and 1:02:03.440 --> 1:02:06.840 can be very aggressive in doing things like firing the 1:02:06.920 --> 1:02:11.880 BLS commissioner when the market sells off and suddenly we're ten, fifteen, 1:02:12.040 --> 1:02:15.000 almost twenty percent off the highs. Hey, we're going to 1:02:15.040 --> 1:02:18.320 put a pause on taris for ninety days. There's a 1:02:18.360 --> 1:02:21.240 little bit of a floor there, and hence the phrase 1:02:21.320 --> 1:02:25.080 Trump collar. I know, we only have six or eight 1:02:25.120 --> 1:02:30.480 months worth of recent data. How important do you believe 1:02:31.480 --> 1:02:35.360 market prices are to this president and this administration? 1:02:35.800 --> 1:02:39.400 So in the first administration, you know, we we were like, okay, 1:02:39.440 --> 1:02:42.400 we've got his number. We've got his number. He takes 1:02:42.440 --> 1:02:45.280 the stock market as the single best indicator of his 1:02:45.320 --> 1:02:48.960 approval rating, right, and so if the stock market pukes, 1:02:49.000 --> 1:02:52.400 if it's a huge sell off, he's going to listen. 1:02:52.880 --> 1:02:57.640 And so we went into this second Trump term with 1:02:57.720 --> 1:03:01.480 the markets assuming Aha, Yes, all we have to do 1:03:01.800 --> 1:03:05.200 is speak and will speak volumes with a sell off 1:03:05.320 --> 1:03:08.000 and he will change his tune. Well, that is not 1:03:08.200 --> 1:03:11.240 what happened. That's not what happened, because the markets did 1:03:11.320 --> 1:03:14.040 puke when it became apparent that he was going to 1:03:14.080 --> 1:03:18.240 be very aggressive on a trade policy in his second term. 1:03:18.560 --> 1:03:21.520 The market puked and the President stayed the course. 1:03:21.960 --> 1:03:25.720 So someone asked me my opinion as to what I 1:03:25.760 --> 1:03:28.480 think trade policy is going to look like going forward, 1:03:29.280 --> 1:03:32.440 given how frequently we've seen flip flops and back and 1:03:32.480 --> 1:03:37.400 forth and extensions, and what I answered, And I'm curious 1:03:37.440 --> 1:03:40.600 as to your perspective on this. Tell me the last 1:03:40.600 --> 1:03:44.960 person who whispers and President Trump's year before a decision 1:03:45.240 --> 1:03:49.120 is made, and that'll tell me where the market will go. 1:03:49.680 --> 1:03:53.000 If it's Treasury Secretary Scott Bessen is the last person 1:03:53.040 --> 1:03:55.480 to speak to him. I think the markets would be 1:03:55.560 --> 1:03:59.640 pretty steady and on a gradual move higher if it 1:03:59.800 --> 1:04:03.000 had happens to be someone like Pena Navara will buckle 1:04:03.120 --> 1:04:07.160 up wearing for a bumpy ride. Fair way to describe 1:04:07.200 --> 1:04:10.520 the policy making in DC, I think. 1:04:10.440 --> 1:04:12.800 So, I mean basically what you're getting at in a 1:04:12.880 --> 1:04:16.960 roundabout way is just who do the markets trust? Who 1:04:16.960 --> 1:04:20.320 do the markets trust? And I think you've had Treasure 1:04:20.360 --> 1:04:23.640 Secretary Bessant that had an active role in that hair 1:04:23.720 --> 1:04:28.040 raising time between April second and April ninth, meeting with 1:04:28.280 --> 1:04:33.800 Chair Pal, helping to persuade the President to sort of 1:04:33.800 --> 1:04:37.600 back off at that time, adding to that hair raising 1:04:37.600 --> 1:04:40.640 moment by threatening to fire Pal like the markets have 1:04:40.720 --> 1:04:43.600 come to know Bessn't as a calm and steady voice. 1:04:43.720 --> 1:04:46.600 And steady is the word that always seems to pop 1:04:46.640 --> 1:04:47.280 into my head. 1:04:47.360 --> 1:04:51.520 Any equals certainty, equals your tea equals the opposite of volatility, 1:04:51.760 --> 1:04:55.560 and so you know the markets will speak volumes as 1:04:55.560 --> 1:04:58.280 to who they believe they can trust. 1:04:58.560 --> 1:05:02.040 Coming up, we continue our comversation with Ellen Zenner, chief 1:05:02.080 --> 1:05:06.520 economic strategist from Morgan Stanley. I'm Barry Riddults. You're listening 1:05:06.520 --> 1:05:17.400 to Masters in Business on Bloomberg Radio. All right, so 1:05:17.520 --> 1:05:19.480 I only have you for a limited amount of time. 1:05:19.560 --> 1:05:23.880 Let's jump to our favorite questions, starting with who are 1:05:23.920 --> 1:05:27.440 your mentors who helped shape your career? Well? 1:05:27.480 --> 1:05:30.720 Tamer Plout, so I have mentioned I worked for her 1:05:30.760 --> 1:05:33.840 at the State of Texas. She was a very influential 1:05:34.000 --> 1:05:36.960 chief economist at the State of Texas, and that was 1:05:37.040 --> 1:05:38.560 my She was my first. 1:05:38.600 --> 1:05:38.920 Barry. 1:05:38.920 --> 1:05:41.320 You always remember your first, So she was the first 1:05:41.360 --> 1:05:45.320 chief economist that I worked for, and he has followed 1:05:45.360 --> 1:05:49.400 my career for the next twenty five years. She's followed 1:05:49.440 --> 1:05:54.720 my career. I think my first foura fora into investment banking, 1:05:55.600 --> 1:06:00.080 my chief economist was David Wrestler at Numerous Security. He 1:06:00.360 --> 1:06:04.520 was a twenty six year veteran chief economist at twenty 1:06:04.560 --> 1:06:10.560 six year veteran of Numerous Securities and he's now playing 1:06:10.600 --> 1:06:15.320 golf twenty four to seven in the South. But he 1:06:15.480 --> 1:06:20.240 because it was my first foray into investment banking, into 1:06:20.280 --> 1:06:24.680 the high frequency world trading as a trading desk economist. 1:06:24.960 --> 1:06:29.000 He was very influential there and I still hear from 1:06:29.080 --> 1:06:32.280 him all the time when he sees me in the 1:06:32.360 --> 1:06:36.880 media or he hears of some forecasting award or something 1:06:37.000 --> 1:06:40.640 like that, like he's still the proud Papa today. And 1:06:40.680 --> 1:06:43.480 so those were two big early mentors of mine that 1:06:43.560 --> 1:06:44.400 helped shape my career. 1:06:44.520 --> 1:06:47.120 That's great. Before we get to books, and you actually 1:06:47.240 --> 1:06:51.520 brought a few books, I want to ask you about streaming. 1:06:51.560 --> 1:06:54.680 What are you listening to or watching What's What's keeping 1:06:54.760 --> 1:06:55.480 you entertained? 1:06:55.960 --> 1:06:58.600 I really developed a love for streaming. 1:06:58.680 --> 1:07:03.080 I've watched TV before very similar cod the TV was. 1:07:03.080 --> 1:07:06.760 Never on in our apartment, and so with COVID, I 1:07:06.920 --> 1:07:14.120 really my eyes were open. And so I really love documentaries. 1:07:14.120 --> 1:07:16.640 The one that I'm watching right now is on Billy Joel. 1:07:16.960 --> 1:07:21.280 I'm literally just wrapping up the first we stopped just 1:07:21.520 --> 1:07:22.880 before the Stranger. 1:07:23.160 --> 1:07:23.400 Yeah. 1:07:23.440 --> 1:07:25.800 So they must have made it for fifty somethings in 1:07:25.840 --> 1:07:28.360 this world, right, So well, if. 1:07:28.280 --> 1:07:32.560 You grew up in the sixties, seventies, eighties Bill, especially 1:07:32.600 --> 1:07:35.920 in New York or Long Island, Billy Joel was everywhere. 1:07:35.960 --> 1:07:39.360 Yeah, which I'm of an age that I know him 1:07:39.400 --> 1:07:42.280 in real time. But I'm from the South, so I 1:07:42.440 --> 1:07:47.160 didn't know all of these things. So my streaming habits 1:07:47.600 --> 1:07:52.840 are extremely polarized and polarizing probably so it's anywhere from 1:07:52.840 --> 1:07:57.000 documentary so I can expand my knowledge and expand my 1:07:57.120 --> 1:08:04.960 mind to the most streaming reality shows like Love Island 1:08:05.720 --> 1:08:08.880 and I Am not kidding you if anyone wants to say, wow, 1:08:08.960 --> 1:08:10.920 she really is a real person. 1:08:11.280 --> 1:08:12.560 It's the fact that I can. 1:08:12.480 --> 1:08:15.960 Enjoy Love Island and then in the next hour, I 1:08:15.960 --> 1:08:18.519 can enjoy a documentary on Billy Joel. 1:08:18.880 --> 1:08:20.880 So you have a couple of books here, let's talk 1:08:20.880 --> 1:08:23.360 about books are what are you reading now? What are 1:08:23.400 --> 1:08:24.240 some of your favorites? 1:08:24.320 --> 1:08:25.400 Yeah, I have a couple of books. 1:08:25.400 --> 1:08:27.920 So when I first as you mentioned, I was on 1:08:27.960 --> 1:08:30.559 almost exactly eight years ago, and I talked about Jonah 1:08:30.600 --> 1:08:33.040 Sarah's book A Piece of the Action, How the Middle 1:08:33.080 --> 1:08:36.160 Class Became the Money Class, still one of my favorite 1:08:36.240 --> 1:08:39.360 books on the rise of consumer credit in the US 1:08:39.360 --> 1:08:41.360 and our love hate relationship with it. 1:08:41.439 --> 1:08:45.719 But it's been that analysis of how the middle class 1:08:46.080 --> 1:08:51.599 suddenly gained entry to homes, mortgages, cars, and lots of 1:08:51.920 --> 1:08:57.559 consumer discretionary goods. Huge boom for middle class America, right. 1:08:57.800 --> 1:08:58.400 Incredible. 1:08:59.479 --> 1:09:02.480 It really is still an incredible book. And every economist 1:09:02.560 --> 1:09:04.840 of mine that I have covered the consumer and study 1:09:04.880 --> 1:09:09.000 household behavior, they have to read it. So I brought 1:09:09.040 --> 1:09:11.320 in today Kurt Vonnegutz player piano. 1:09:11.600 --> 1:09:13.719 Can't go wrong with Vonni and so I. 1:09:13.680 --> 1:09:16.200 Have not read this book, but I'll tell you that 1:09:16.439 --> 1:09:19.120 what I'm showing you, if the listeners could see, is 1:09:19.280 --> 1:09:23.639 a handwritten note from a colleague after watching a webcast 1:09:23.680 --> 1:09:25.920 of my how many people get handwritten notes. 1:09:25.960 --> 1:09:28.920 Still not many, right, but they catch your attention. 1:09:29.200 --> 1:09:34.719 And the webcast was me and Adam Jonas and Adam 1:09:34.800 --> 1:09:39.320 Jonas is he was always referred to as the Tesla guy. 1:09:39.439 --> 1:09:45.280 He's probably the quintessential thought leader at Morgan Stanley. He's 1:09:45.280 --> 1:09:49.120 just got a celebrity following, and he is leading the 1:09:49.200 --> 1:09:54.560 charge on robotics and humanoids. And so after that webcast, 1:09:55.000 --> 1:09:59.120 I was sent this because this book, written in the 1:09:59.200 --> 1:10:03.040 nineteen fifty covered rise of the corporation and replacement of 1:10:03.040 --> 1:10:07.360 the state, the ruthless efficiency of capitalism in dealing with labor, 1:10:07.960 --> 1:10:10.520 the overpowering of the worker. 1:10:10.280 --> 1:10:11.800 By AI and automation. 1:10:12.320 --> 1:10:14.400 That's all in this book from the nineteen seventy five 1:10:14.439 --> 1:10:15.040 years ago. 1:10:15.000 --> 1:10:16.000 Maybe five years ago. 1:10:16.160 --> 1:10:18.160 The other book I brought in so again, just like 1:10:18.240 --> 1:10:23.760 my streaming habits a cleft, is called The Bluegrass Conspiracy, 1:10:24.560 --> 1:10:27.920 An inside story of power, greed, drugs and murder. This 1:10:28.000 --> 1:10:31.000 is the backstory to Cocaine Bear, the movie Oh, which 1:10:31.040 --> 1:10:32.519 is one of my favorite movies. 1:10:32.840 --> 1:10:37.040 I haven't seen it because it sounds so bare crazy. 1:10:37.400 --> 1:10:40.000 Come on, yeah, I mean, it just sounds like a 1:10:40.120 --> 1:10:44.839 wildly fictionalized account of a highly unlikely event. 1:10:45.240 --> 1:10:46.360 Yeah, how's the book? 1:10:46.760 --> 1:10:49.880 The book, I am just starting and I cannot wait 1:10:49.920 --> 1:10:53.200 to get through it because the movie, the only thing 1:10:53.680 --> 1:10:56.200 that the movie that really happened that was in the 1:10:56.200 --> 1:10:59.000 movie was that there was a dead bear found in 1:10:59.080 --> 1:11:01.519 a national park with a belly full of cocaine. 1:11:01.520 --> 1:11:02.200 That is the. 1:11:02.040 --> 1:11:06.000 Only thing in the movie that was accurate. It was accurate. 1:11:07.360 --> 1:11:10.479 That actually is in the book. But there's a whole 1:11:10.560 --> 1:11:13.280 backstory here and I cannot wait to read it. It comes 1:11:13.360 --> 1:11:15.720 highly recommended, So you can see that my taste in 1:11:15.800 --> 1:11:19.640 books runs the gambit as well, just like my streaming. 1:11:19.880 --> 1:11:21.760 So if you haven't. 1:11:21.479 --> 1:11:25.080 Read Player Piano yet, have you read other Vonnugut? Have 1:11:25.160 --> 1:11:29.800 you read Kat's Cradle or Swaterhouse Vonnagut? All right, so 1:11:30.680 --> 1:11:34.519 everybody should read Slaughterhouse five, And if you're at all 1:11:34.560 --> 1:11:40.839 remotely interested in science and technology, run a mock Cat's 1:11:40.880 --> 1:11:44.479 Cradle is his version of that. What makes him so 1:11:44.680 --> 1:11:49.760 fascinating is he finds these incredible concepts and just so 1:11:50.000 --> 1:11:55.040 simply explains them in such an compelling and entertaining fashion. 1:11:55.880 --> 1:11:58.280 But isn't it also scary how books can be written 1:11:58.280 --> 1:12:01.200 that long ago? And then here we are talking about 1:12:01.280 --> 1:12:05.560 humanoids and robotics because another I have to say piggybacking 1:12:05.600 --> 1:12:09.320 off of this idea of robotics and humanoids. Twenty thirteen. 1:12:10.280 --> 1:12:14.120 Have you seen the movie Robot and Frank. No, Robot 1:12:14.160 --> 1:12:17.920 and Frank, Frank Langella was in it. Susan Sarandon, Peter 1:12:18.000 --> 1:12:22.839 sars Guard, James Marsden, Live Tyler Grow. 1:12:23.000 --> 1:12:23.839 That's some cavy. 1:12:24.280 --> 1:12:25.599 It is so. 1:12:25.560 --> 1:12:29.040 Talk about when we think about thematics, longevity is a 1:12:29.080 --> 1:12:33.200 thematic AI tech and diffusion is a thematic in terms 1:12:33.280 --> 1:12:40.040 of thematic investing. Robot and Frank is about a senior 1:12:40.240 --> 1:12:43.479 gentleman that he wants to age in place, and to 1:12:43.520 --> 1:12:46.559 help him do that, his family buys him a home 1:12:46.640 --> 1:12:48.200 companion robot. 1:12:48.040 --> 1:12:51.840 To which him, which is really not decades away. 1:12:51.920 --> 1:12:53.960 No, we're not that far off from that. In Japan, 1:12:54.000 --> 1:12:57.280 they're already testing it. So this was in twenty thirteen. 1:12:57.880 --> 1:13:01.479 The kicker, though, is that it just so happens that 1:13:01.960 --> 1:13:05.639 Frank was a petty thief in his prior life. He's 1:13:05.680 --> 1:13:08.800 now going through early dementia. He was a petty thief 1:13:08.800 --> 1:13:11.000 and he co opts the robot to help him. That's 1:13:11.000 --> 1:13:14.519 the fun part of the movie. But Robot and Frank 1:13:14.560 --> 1:13:14.960 twenty three. 1:13:15.000 --> 1:13:18.680 I'm check absolutely check that out. Our last two questions, 1:13:18.720 --> 1:13:21.240 what sort of advice would you give a recent college 1:13:21.240 --> 1:13:26.280 grad interest in the career in economics, finance, investing. What 1:13:26.320 --> 1:13:27.519 would your advice you to that. 1:13:27.960 --> 1:13:30.439 I would say for them to find any and everyone 1:13:30.479 --> 1:13:33.800 they can think of that works in that field already. 1:13:34.040 --> 1:13:35.680 The best is to if you. 1:13:35.720 --> 1:13:38.360 Can, not to cold call, but to try to find 1:13:38.400 --> 1:13:41.599 some sort of connection, whether it's your wealth advisor, and 1:13:41.680 --> 1:13:44.040 see who your wealth advice. I get contacted by our 1:13:44.080 --> 1:13:47.880 wealth advisors that say, hey, my client has a son 1:13:48.160 --> 1:13:50.400 who this Do you mind if I put you in 1:13:50.439 --> 1:13:53.360 touch with him? Find some way, And when you start 1:13:53.400 --> 1:13:56.599 to have conversations with people that are already working in 1:13:56.720 --> 1:13:59.519 areas where you think you want to work, never leave 1:13:59.560 --> 1:14:02.680 that converse without getting two more names from them of 1:14:02.760 --> 1:14:06.840 people they think you should contact, and can they make 1:14:06.880 --> 1:14:09.439 that opening for you so that you always have another 1:14:09.479 --> 1:14:10.639 conversation to be had. 1:14:10.960 --> 1:14:13.880 Each call always asks for two more names. That's great 1:14:13.880 --> 1:14:16.960 advice for someone right out of college. And our final question, 1:14:17.200 --> 1:14:21.040 what do you know about the world of economics, investing, 1:14:21.200 --> 1:14:25.839 thematic investing, macro economy today that might have been helpful 1:14:25.960 --> 1:14:28.680 twenty five or so years ago, really, when you were 1:14:28.680 --> 1:14:29.599 first starting out. 1:14:30.920 --> 1:14:33.160 I think if I were to know that. 1:14:35.280 --> 1:14:39.599 Models are not the end all be all, I would 1:14:39.600 --> 1:14:44.439 have started using anecdotal evidence a lot earlier. I am 1:14:44.479 --> 1:14:47.519 a very big believer in anecdotal evidence, and I've been 1:14:47.520 --> 1:14:51.799 criticized for that in my career. It's not statistically sound. 1:14:52.080 --> 1:14:55.719 I like to use my one man data sample, which 1:14:55.800 --> 1:15:00.880 is my husband when I studied behavior, and and I 1:15:01.000 --> 1:15:03.519 just it's a great way to connect to people, connect 1:15:03.520 --> 1:15:05.680 to your audience, get a message across. And I'm a 1:15:05.720 --> 1:15:09.920 big believer in using anecdotal evidence when thinking about how 1:15:09.960 --> 1:15:13.920 to adjust your forecast subjectively, and so I wish I 1:15:13.920 --> 1:15:16.280 had started using that my career even earlier. 1:15:16.439 --> 1:15:19.280 Ellen, this has been absolutely a pleasure. It's been way 1:15:19.280 --> 1:15:21.880 too long since we had you in here. We have 1:15:22.080 --> 1:15:26.040 been speaking with Alan Zenner. She's chief economic strategist and 1:15:26.160 --> 1:15:29.879 global head of thematic and macro investing for Morgan Stanley 1:15:29.920 --> 1:15:36.040 Wealth Management. They manage over seven trillion dollars in total assets. 1:15:36.800 --> 1:15:39.680 If you enjoy this conversation, well, be sure and check 1:15:39.680 --> 1:15:42.679 out any of the five hundred and forty seven we've 1:15:42.760 --> 1:15:46.400 done over the past twelve years. You can find those 1:15:46.560 --> 1:15:52.640 at iTunes, Spotify, Bloomberg YouTube, wherever you find your favorite podcast, 1:15:53.120 --> 1:15:55.639 and be sure and check out my new book, How 1:15:55.720 --> 1:15:59.960 Not to Invest The ideas, numbers and behaviors that they're 1:16:00.160 --> 1:16:03.160 joy wealth and how to avoid them, How Not to 1:16:03.280 --> 1:16:05.160 Invest at your favorite bookstore. 1:16:05.680 --> 1:16:07.040 I would be remiss. 1:16:06.640 --> 1:16:08.559 If I didn't thank the Crack team that helps with 1:16:08.600 --> 1:16:13.800 these conversations together each week. Peter Nicolino is my audio engineer. 1:16:14.360 --> 1:16:18.440 Anna Luke is my producer. Sean Russo is my researcher. 1:16:18.920 --> 1:16:23.560 Sage Bauman is the Heavy podcast at Bloomberg. I'm Barry Rutolts. 1:16:23.760 --> 1:16:28.080 You've been listening to Masters in Business on Bloomberg Radio